s4 ! i .AA.^53 fr:rSH U.S. Department of Commerce Volume 113 Number 3 July 2015 Fishery Bulletin U.S. Department of Commerce Penny S. Pritzker Secretary National Oceanic and Atmospheric Administration Kathryn D. Sullivan NOAA Administrator National Marine Fisheries Service Eileen Sobeck Assistant Administrator for Fisheries The Fishery Bulletin (ISSN 0090-0656) is published quarterly by the Scientific Publications Office, National Marine Fisheries Service, NOAA, 7600 Sand Point Way NE, Seattle, WA 98115-0070. Although the contents of this publica- tion have not been copyrighted and may be reprinted entirely, reference to source is appreciated. The Secretary of Commerce has deter- mined that the publication of this peri- odical is necessary according to law for the transaction of public business of this Department. Use of funds for printing of this periodical has been approved by the Director of the Office of Management and Budget. 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U.S. Department of Commerce Seattle, Washington Volume 113 Number 3 July 2015 Fishery Bulletin Contents Articles 231-241 Parrish, Frank A., Nicholas T. Hayman, Christopher Kelley, and Raymond C. Boland Acoustic tagging and monitoring of cultured and wild |uvemle crimson jobfish ( Pristipomoides Filamentosus) in a nursery habitat 242-255 Dahlheim, Marilyn E., Alexandre N. Zerbini, Janice M. Waite, and Amy S. Kennedy Temporal changes in abundance of harbor porpoise (Phocoena phocoena) inhabiting the inland waters of Southeast Alaska 256-269 Ryer, Clifford H., William C. Long, Mara L. Spencer, and Paul Iseri Depth distribution, habitat associations, and differential growth of newly settled southern Tanner crab ( Chionoecetes bairdi) in embayments around Kodiak Island, Alaska The National Marine Fisheries Service (NMFS) does not approve, recommend, or endorse any proprie- tary product or proprietary material mentioned in this publication. No reference shall be made to NMFS, or to this publication furnished by NMFS, in any advertising or sales promotion which would indicate or imply that NMFS approves, rec- ommends, or endorses any propri- etary product or proprietary mate- rial mentioned herein, or which has as its purpose an intent to cause directly or indirectly the advertised product to be used or purchased be- cause of this NMFS publication. 270-289 Edward A. Laman, Stan Kotwicki, and Christopher N. Rooper Correlating environmental and biogenic factors with abundance and dis- tribution of Pacific ocean perch ( Sebastes alutus) in the Aleutian Islands, Alaska 290-301 Willis, C. Michelle, Jonathan Richardson, Tracey Smart, Joseph Cowan, and Patrick Biondo Diet composition, feeding strategy, and diet overlap of 3 sciaenids along the southeastern United States 302-312 Lin, Yu-Jia, Chi-Lu Sun, Yi-Jay Chang, and Wann-Nian Tzeng The NMFS Scientific Publications Office is not responsible for the con- tents of the articles. Sensitivity of yield-per-recruit and spawning-biomass-per-recruit models to bias and imprecision in life history parameters: an example based on life history parameters of Japanese eel (Anguilla japonica) II Fishery Bulletin 113(3) 313-326 Nichol, Daniel G., and David A. Somerton Seasonal migrations of morphometrically mature male snow crab ( Chionoecetes opilio ) in the eastern Bering Sea in relation to mating dynamics 327-340 Beck, Steve, and Megan K. La Peyre Effects of oyster harvest activities on Louisiana reef habitat and resident nekton communities 341-351 O'Farrell, Michael R., and William H. Satterthwaite Inferred historical fishing mortality rates for an endangered population of Chinook salmon ( Onchorhynchus tshawytscha) 352-354 Guidelines for authors 231 NOAA National Marine Fisheries Service Fishery Bulletin ** established 1881 ■*?. Spencer F. Baird First U S. Commissioner of Fisheries and founder of Fishery Bulletin Acoustic tagging and monitoring of cultured and wild juvenile crimson jobfish {Pristipomoides filamentosus ) in a nursery habitat Email address for contact author: frank.parrish@noaa.gov 1 Pacific Islands Fisheries Science Center NOAA Daniel K. Inouye Regional Center 1845 Wasp Boulevard, Building 176 Honolulu, Hawaii 96818 2 School of Ocean and Earth Science and Technology University of Hawaii at Manoa 1000 Pope Road Honolulu, Hawaii 96822 Abstract—The movements of cul- tured (n = 18) and wild (n= 28) juve- nile crimson jobfish (Pristipomoides filamentosus ) are reported for a known nursery off windward Oahu, Hawaii. The 2 batches of fish were tagged with acoustic transmitters in separate years (2006, 2007) and monitored with a receiver array for up to 10 weeks. Of the cultured fish, 75% left the nursery within 3 days, more than twice the exit rate for wild fish tagged the following year. The number of wild fish detected peaked during daylight hours, indi- cating that the fish were diurnally active. Tidally driven changes in bot- tom temperature did not explain the behavioral patterns of the wild fish that remained in the nursery for multiple weeks. Additional receiv- ers deployed on the slope adjacent to the nursery detected that two- thirds of the wild fish departed from the nursery after a short period (mean: 1.2 days [SD 1.69]), by cross- ing areas with soft substrate similar to that of the nursery. In contrast, the fish that exited by rock ledges stayed near the rock ledges longer (mean: 13.3 days [SD 20.9]). These movement patterns provide insight into the early life history of this deepwater snapper and a glimpse at some of the challenges for future stock enhancement efforts. Manuscript submitted 18 December 2013. Manuscript accepted 13 March 2015. Fish. Bull. 113:231-241 (2015). doi: 10.7755/FB. 113.3.1 Online publication date: 7 April 2015. The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA. Frank A. Parrish (contact author)1 Nicholas T. Hayman1 Christopher Kelley2 Raymond C. Boland1 Eteline snappers compose an impor- tant, high-value component of tropi- cal insular fisheries throughout the Pacific and Indian Oceans, and catch of sizeable portions is exported from their country or archipelago of origin. The crimson jobfish ( Pristipomoides filamentosus), also known as the pink snapper, composes more than a quarter of the commercial landings by weight of the Hawaiian bottom- fish fishery (Brodziak et ah, 2011). In addition, this species is thought to account for roughly the same per- centage of bottomfish recreational landings, which, when added to com- mercial landings, would increase the overall catch of this snapper by a factor of 2-3 (Zeller et ah, 2008). Because of the high market value of crimson jobfish, scientists of the University of Hawaii spent a consid- erable effort during 1997-2006 at- tempting to breed this species in cap- tivity for potential use in aquaculture and stock enhancement. They were successful at maintaining broodstock, producing larvae, and rearing fish to 20-24 cm in fork length (FL) (C. Kel- ley, unpubl. data), which is similar to the size of juveniles that occur in nearshore nursery habitats. Culturing large numbers of juve- niles is not yet possible, but if it is achieved, they hypothetically could be grown for harvest in oceanic cages or used to enhance wild populations through releases to known nursery grounds as is done with other fish- eries species (Bell et ah, 2008). Al- though these types of enhancement activities have been undertaken for freshwater and anadromous species, their use in marine systems is more recent. Notable examples in Hawaii include hatchery releases of striped mullet ( Mugil cephalus) (Leber and Arce, 1996) and Pacific threadfin ( Polydactylus sexfilis) (Friedlander and Ziemann, 2003). In order to release cultured fish into the wild for the purposes of stock enhancement, researchers will need to know where to deploy the fish and how they will behave. Ide- ally, cultured juvenile fish would be released in a place suitable for that stage of its life history. Larvae of eteline lutjanid snappers are known to reside in the plankton until they 232 Fishery Bulletin 113(3) reach a length of 5-6 cm FL (Leis, 1987; Leis and Lee, 1994). Crimson jobfish settle and form loose schools over featureless soft-bottom habitat at depths of 80- 100 m (Parrish, 1989). While in their nursery they feed on benthic and, to a lesser extent, a mix of plank- tonic invertebrates and small nektonic fishes (DeMar- tini et ah, 1996; Schumacher, 2011). Survey results indicate that slope areas close to sources of coastal discharge (e.g., draining embayments or reef chan- nels) tend to support greater numbers of juveniles and serve as premium habitat or nursery grounds (Parrish et al., 1997). These nurseries are important gateways in the life history of the crimson jobfish and provide a window to understanding and predicting year-class fluctuations. The most studied nursery ground for crimson jobfish in Hawaii is the offshore area of Kaneohe Bay, Oahu. Monthly sampling of the juvenile population in this area has revealed seasonal patterns in the distribution of fish sizes consistent with an annual progression of a year class through its recruitment, growth, and emi- gration to adult habitats (Moffitt and Parrish, 1996). Fish at sizes of 7-10 cm FL appear in this nursery habitat in the fall and stay there for a period of 6-7 months until they reach 20-30 cm FL (Moffitt and Par- rish, 1996). Otolith features of juvenile crimson jobfish indicate ages of ~6 months for 10.5-cm-FL fish, about a year for 18.5-cm-FL fish, and 2 and 3 years, respec- tively, for 28.0- and 36.0-cm-FL fish (DeMartini et ah, 1994; Andrews et ah, 2012). At 2-3 years of age, fish begin to emigrate offshore to deeper habitats used by subadults (Okamoto1) and adults (Haight et al., 1993a). Because only 2 wild juvenile crimson jobfish had been tagged and tracked in the Kaneohe nursery (Moffitt and Parrish, 1996) before our study, there has been insufficient understanding of juvenile crimson jobfish movements and how they might compare with those of crimson jobfish raised in captivity. In this study, we report new observations of 2 batch- es of juvenile crimson jobfish that were implanted with acoustic tags and released in separate years to the nursery habitat off windward Oahu. In the first year (2006) of this study, a batch of cultured fish were tagged and released, followed by a second year (2007) in which wild fish were collected from the nursery, tagged, held for observation, and then released. We investigated the hypotheses that cultured juvenile fish released to a known nursery site would linger and make use of the nursery habitat or move directly off to other locations. Similarly, we investigated whether the wild fish taken from the site, tagged, and released back to the nursery would behave differently from the cultured fish. 1 Okamoto, H. Y. 1993. Project to develop opakapaka (pink snapper) tagging technique to assess movement behavior. Final Report of the Hawaii Department of Land and Natu- ral Resources to NOAA, 18 p. NOAA Award No. NA90AA- D-IJ466. [Available from Division of Aquatic Resources, Hawaii Department of Land and Natural Resources, 1151 Punchbowl Street, Room 330, Honolulu, HI 96813-3088.] Materials and methods Study area The Kaneohe Bay nursery (Fig. 1) is a submerged ter- race, 70-100 m deep, roughly 8 km2 in area, and is separated from the nearest known aggregation of adult crimson jobfish by more than 5 km. Video surveys (Parrish et ah, 1997), backscatter data collected with a multibeam sonar (Dartnell and Gardner2), and side- scan sonar data (C. Kelley, unpubl. data) indicate that the bottom at this nursery site is “soft” (unconsolidated sediment) and generally featureless. Two isolated, ex- posed rock ledges identified on the slope adjacent to the nursery were hypothesized to be potential transi- tion habitats for juveniles when they leave the nursery to emigrate to deeper, hardbottom adult habitat. Receivers We monitored the nursery ground with two VR23 pas- sive underwater receivers (VEMCO, Bedford, Canada), deployed in 2006 approximately 800 m apart at a depth of 75-80 m. Subsurface floats suspended the receivers 5 m above the bottom to maximize reception of signals from tagged fish. This configuration reduced acoustic effects on signal reception from the thermocline (Sid- erius et al., 2007). Weighted with a concrete anchor, the receivers were fitted with an ORE Offshore SWR acoustic release transponder (EdgeTech, West Ware- ham, MA) that detached and allowed the receivers to float to the surface when a coded acoustic signal was transmitted. In 2007, 4 additional receivers were de- ployed at a depth of 140 m at sites on the adjacent slope (2 north and 2 south of the nursery), and each pair was split between soft bottom (sites 2 and 4) and rock ledge (sites 1 and 3) habitats (Fig. 1). The receiv- ers on the slope were separated from other receivers by distances ranging from 1200 to 2500 m. Attached to the bottom of each receiver mooring, a temperature data logger recorded temperatures on an hourly basis to track tidal effects of a cold bottom layer that had been identified at the Kaneohe nursery in previous studies (Moffitt and Parrish, 1996). Tagging of juvenile fish Cultured juveniles were raised in captivity from eggs spawned from broodstock held at the Hawaii Institute of Marine Biology (HIMB), a marine research center of the University of Hawaii at Manoa located on Co- 2 Dartnell, P., and J. V. Gardner. 1999. Sea-floor images and data from multibeam surveys in San Francisco Bay, South- ern California, Hawaii, the Gulf of Mexico, and Lake Tahoe, California-Nevada. U.S. Geological Survey Digital Data Se- ries DDS-55, vers. 1.0. [Online version of interactive CD- ROM. Available at Website.] 3 Mention of trade names or commercial companies is for iden- tification purposes only and does not imply endorsement by the National Marine Fisheries Service, NOAA. Parrish et al.: Movements of cultured and wild juvenile Pristipomoides filamentosus in a nursery habitat 233 Map of the study area off windward Oahu, showing the deployment sites of 6 receivers with their 400-m radiuses of detection. The gray rectangle in the inset map indicates the position of the study area off the island of Oahu. Two receivers, the locations of which are indicated by the circles filled with diagonal lines, monitored movements of tagged juvenile crimson jobfish ( Pristipomoides filamentosus ) in the snapper nursery on a terrace outside of Kaneohe Bay where tagged cultured and wild crimson jobfish were released in 2006 and 2007, respectively. Open circles indicate the sites (numbered 1-4) where additional receivers were deployed in 2007 to monitor the use by the tagged wild fish of rock ledge (sites 1 and 4) and soft bottom (sites 2 and 4) habitats on the slope adjacent to the nursery. Lines indicate depth contours in meters. conut Island in Kaneohe Bay. Broodstock juveniles were originally captured from the Kaneohe nursery and raised through sexual maturity in floating pens. Spawned eggs were collected from the broodstock pens and transferred to tanks in a fish hatchery facility at HIMB. Larvae were raised in tanks for 4 months, then transferred to floating pens where rearing continued until they were 8 months of age and had grown to 20-24 cm FL, a considerably faster growth rate than those reported for wild fish and based on otolith analy- ses (DeMartini et ah, 1994; Andrews et ah, 2012). The acoustic tags were surgically implanted, and the fish were held in a floating pen for 4 days to verify that they continued to swim and feed actively. Wild juveniles (17-30 cm FL) were collected from the Kaneohe nursery by hook and line, verified as crim- son jobfish (Uchida and Uchiyama, 1986), implanted with acoustic tags, and observed in a floating holding pen for 10 days until ocean conditions permitted trans- port of fish to the nursery site for release. Two fish died, the first within an hour of surgery and the second that evening. All other fish schooled and fed normally during days of observation. The tags were V9 transmitters (VEMCO; 69 kHz, 9 by 21 mm), each of which had a unique code, was sterilized with alcohol, and inserted into the ventral abdominal cavity of a fish through a 1-cm incision while that fish was anesthetized in a bath of tricaine methanesulfonate (Finque! MS-222, Argent Chemical Laboratories, Redmond, WA). Iodine and binding tis- sue adhesive were applied to the wound, and it was closed with a square knot suture made with a 2.0 sur- gical needle. To minimize handling, the lengths of both cultured and wild fish were measured in the water and the percentage of tag weight to body weight was esti- mated by using a published length-weight relationship for juvenile crimson jobfish {n= 125) collected from the study area (Moffitt and Parrish, 1996). In the sample of fish tagged, the tags never exceeded 4% of the body weight (Brown et ah, 1999). On the day of release, we used a receiver to confirm that the tag in each fish was functioning and transmit- 234 Fishery Bulletin 1 13(3) ting a signal. At the Kaneohe nursery, the fish were split equally into 2 batches and released at the surface over each of the 2 receiver moorings. A snorkeler ob- served that all fish swam down (to a depth of ~30 m) and disappeared from sight within a minute. Tags had an expected life of 95 days and emitted a signal with a pseudorandom delay at an average of 100 s. Cultured fish were released on 23 June 2006 and monitored for 58 days; wild fish were released on 10 July 2007 and monitored for 76 days. Data analysis We assumed a detection radius of 400 m for the re- ceivers that was based on the results from the manu- facturer’s range calculator (Website) when we used the inputs of the tag power (151 db) and using the average windward Oahu wind speed (15-20 kt). Wind speed affects sea-surface conditions and introduces background noise that impacts the travel of trans- mitter signals underwater. Simultaneous detections were rare and only occurred between the 2 receivers deployed on the nursery site; they were the receivers closest to each other and monitored approximately half the area of the nursery habitat. The rest of the receivers allowed us to monitor habitat on the slope and were spaced far enough apart to avoid overlap- ping detections. It was necessary to discern signals from a tag on a resident, live fish from signals from a tag that was still transmitting but lost on the bot- tom for various reasons (e.g., tag expulsion or death of fish). For the purposes of this study, signals were as- sumed to be emitted from dead fish if 1) they had an inordinately high number of detections (e.g., >15,000) consistent with the detection of the continuous trans- mitting of a tag lost on the bottom for the full dura- tion of the surveillance period and 2) they were de- tected by only 1 receiver. Because prior tracking (Moffitt and Parrish, 1996) indicated that movement patterns of fish in the nurs- ery differed between day and night, the detections of the fish in our study were binned in 6-h intervals for analysis (2400-0559, 0600-1159, 1200-1759, and 1800-2359). Initially, the density of tagged fish (and the risk of signal collisions) was high; therefore, we re- quired 2 or more successive signals detected within 1 h to provide greater temporal resolution for the first 3 days. We defined a signal as “successive” if it was a repeat signal detected within 5 min of the previous signal — a time period adequate enough for 2 detections given the cycle of the tag’s delay between transmis- sions. After 3 days, when most of the fish had departed, the risk of signal collisions that create false detections was reduced; therefore, multiple (>2) isolated detec- tions (spaced more than 5 min apart) were accepted as long as they fell within the 6-h time interval. Combin- ing successive detections binned by time intervals in- creased confidence that the fish were actually present (94.5% confidence intervals binned by hour, 97.9% by 6 h) and rendered insignificant the effect on our analysis of erroneous detections from signal collisions of mul- tiple tags (see Pincock4). We used the data from the 2 nursery receivers to look at patterns of time spent in the nursery, of in- fluences of temperature, and of fish body length. Data recorded by the 4 slope receivers were used to exam- ine patterns of habitat use by wild fish as they trav- elled away from the nursery. The sample size of fish was suitable for detecting large effect sizes at a power of 0.80 with an alpha of 0.10 (Cohen, 1988). All sta- tistical analyses were performed in IBM SPSS, vers. 22 (IBM, Armonk, NY). Normalized data fitted to a negative exponential distribution showed how close the decline in fish detections was to a constant rate. In other comparisons, analysis of variance (ANOVA), correlation, and standard nonparametric tests (e.g., Mann-Whitney [MW] and Kruskal-Wallis [KW] ) were used to analyze patterns in fish movements over time and in relation to body size and habitat (Siegel and Castellan, 1988). Results Tag detections in the nursery Movements documented through tag detections indi- cated that 18 cultured fish and 28 wild fish were alive and suitable for inclusion in the analysis (Table 1). Seven other fish were excluded, including 2 wild fish that went undetected, 2 wild fish that were present only briefly (< 10 signals), and 2 cultured and 1 wild fish whose tags emitted continuous signals recorded by 1 receiver (an indication that the tags were immobile and lying on the bottom because of tag expulsion or the death of a fish). Detections of tags lost on the bot- tom were unaffected by daily tidal changes in the tem- perature cycle, indicating that there was little effect from the thermocline on the reception of the receivers. Almost all (97%) of the tagged fish (cultured and wild) used in the analysis moved back and forth between the 2 nursery receivers, indicating that the fish were active. The signals of both cultured and wild fish declined exponentially to a low and variable level of presence by the end of the surveillance period in each year. Within 3 days of release, the portion of released cul- tured fish that were detected in the nursery area dropped to less than 20% in a pattern that closely fit- ted an inverse exponential curve (adjusted coefficient of multiple determination, i?2=0.821). In contrast, 75% of wild fish persisted in the nursery for 3 days, reducing the fit to the curve (adjusted i?2=0.205) and, therefore, indicating that the decline was not as con- tinuous as the drop observed for cultured fish (Fig. 2). 4 Pincock, D. G. 2012. False detections: what they are and how to remove them from detection data. Application note. AMIRIX Systems Inc. DOC-004691-03, 11 p. [Available at Website.] Parrish et al.: Movements of cultured and wild juvenile Pristipomoides filamentosus in a nursery habitat 235 Table 1 Fish tag number, fish type, and fork length (FL) in centimeters of juvenile crimson jobfish (Pristipomoides filamentosus), as well as the number of days they were detected during this study off windward Oahu in 2006 and 2007, number of receivers in the nursery that detected them, and number of receivers on the adjacent slope that detected these fish. The right column lists the figure numbers in this article in which each fish is plotted. NA=not applicable. Fish tag Fish type FL (cm) Duration (days) Number of nursery receivers Number of slope receivers Figure number(s) 691 Cultured 23 1 2 NA 2 692 Cultured 23 52 2 NA 2 693 Cultured 23 2 2 NA 2 695 Cultured 23 2 2 NA 2 696 Cultured 24 1 2 NA 2 697 Cultured 22 1 2 NA 2 698 Cultured 20 1 2 NA 2 699 Cultured 24 2 2 NA 2 700 Cultured 21 1 1 NA 2 701 Cultured 23 50 2 NA 2 702 Cultured 23 1 2 NA 2 703 Cultured 24 49 2 NA 2 704 Cultured 24 1 2 NA 2 705 Cultured 23 2 2 NA 2 706 Cultured 24 2 2 NA 2 708 Cultured 23 3 2 NA 2 709 Cultured 22 53 2 NA 2 710 Cultured 23 3 2 NA 2 1830 Wild 27 48 2 2 2, 3 1831 Wild 30 75 2 2 2,3 1832 Wild 22 4 2 1 2,3 1833 Wild 22 28 2 2 2, 3 1834 Wild 22 29 2 1 2,3,5 1835 Wild 19 75 2 0 2,3,5 1838 Wild 30 4 2 1 2,3 1839 Wild 18 49 2 1 2,3 1840 Wild 19 61 2 2 2,3 1841 Wild 30 9 2 1 2,3 1842 Wild 23 75 1 1 2,3 1843 Wild 18 9 2 1 2,3 1844 Wild 22 44 2 0 2,3,5 1847 Wild 17 5 1 1 2,3 1848 Wild 26 5 2 1 2,3 1849 Wild 30 74 2 2 2,3 1850 Wild 18 60 2 2 2,3,5 1856 Wild 30 10 2 2 2,3 1857 Wild 28 9 2 3 2,3 1858 Wild 19 5 1 3 2,3 1859 Wild 20 65 2 1 2,3 1860 Wild 23 20 2 1 2,3 1862 Wild 20 9 2 0 2,3 1863 Wild 18 4 2 1 2,3 1864 Wild 23 24 2 1 2,3 1866 Wild 30 17 2 3 2,3 1867 Wild 20 12 0 1 2,3 1869 Wild 23 2 2 0 2,3 236 Fishery Bulletin 1 13(3) The mean fork lengths of the 2 groups were similar (cultured: 22.3 cm [SD 1.0]; wild: 23.1 cm [SD 4.5]), but the range was greater for wild fish. However, even in an analysis where the sample of wild fish was lim- ited in relation to fish in the narrower size range of cultured fish (20-24 cm FL), the wild fish still persisted in the nursery sig- nificantly longer than cultured fish (MW: Z=-2.6, P<0.01). Comparison of the body lengths of all wild fish according to time spent in the nursery showed that bigger fish left sooner (coefficient of correlation, r=-0.39, n= 28, P<0.05). Light and temperature The tidally driven cycle of bottom temperature in the nursery is an- other variable that potentially could influence fish behavior. Prior work has shown that high tides pushed a cooler, bottom-associated lens of water (~2°C colder) into the nursery (Moffitt and Parrish, 1996). Our data loggers on the bottom confirmed this tidal influx of cold water for both years with the temperature cycle ranging between 22.0°C and 25.5°C (Fig. 4). This prominent environmen- tal feature is present interannually, but the cyclical change in tempera- ture did not appear to control the behavior of the fish in our study. Tag detections indicate that 4 of the wild crimson jobfish (18-22 cm FL) stayed at the nursery for multiple weeks, and, during that time, they showed no behavioral change attrib- utable to the temperature cycle (Fig. 5). One of those wild fish (tag 1835) moved from the range of one receiver on the terrace to the other receiver and then adopted a pattern of being present during the day and absent at night. Movements of the other 3 fish (tags 1834, 1850, and 1844) showed that they remained continuously within the range of detection for large portions of the period regardless of changes in temperature. The wild fish lingered in the nursery for 3 days after release, and documented move- ments indicate a bimodal pattern of higher numbers of the wild fish in the nursery dur- ing the day than during the night, indicat- ing that the fish were diurnally active (Fig. 3). The inflection point in the pattern of data for high and low fish numbers was most ob- vious around dawn and dusk and the larger daytime numbers were statistically signifi- cant (ANOVA: F= 23.7, PcO.OOl). In the eve- ning, when detections in the nursery were lower, there was no corresponding increase in the number of fish detected at the re- ceivers on the slope adjacent to the nursery (t=- 0.57, P= 0.572) 0) -Q E Hours since release Figure 3 Bimodal pattern in the numbers of wild juvenile crimson jobfish (Pristipomoides filamentosus ) detected by hour for the first 3 days after release in 2007 of fish in the nursery offshore of Kaneohe Bay, windward Oahu. The gray bars represent hours of night. Parrish et al.: Movements of cultured and wild juvenile Pnstipomoides filamentosus in a nursery habitat 237 Wild fish movements on the slope One or more of the 4 slope receivers was visited by 85% of the wild fish. Some fish passed them briefly, as they emigrated away from the nursery into deeper wa- ters, and others chose to linger on the slope for a while before moving deeper. All the receivers were visited, but more than half the tagged fish visited the slope re- ceiver closest to the nursery (located at site 2 north of the nursery; Fig. 1) (Table 2). There was no significant difference in the number of fish visiting soft bottom versus rock ledge habitats (MW: Z=-1.3, P=0.21). The number of days the fish lin- gered at the slope sites varied widely be- cause of their habitat type and distance from the nursery; however, a mixed-effects model showed that the longest stays were at the sites with rock ledges (sites 1 and 3; Fig. 1) (F=4.99, P=G.012). The range of fish lengths (18-30 cm FL) did not signifi- cantly differ between substrate types (MW: Z=-0.172, P=0.88). Temperatures at the 4 slope receivers were on average 2°C cooler (Table 2) than the temperatures at the 2 receivers in the nursery. Only at slope site 3, located to the south of the nursery close to the head of a deep canyon, were average temperatures nearly 1°C cooler than the average temperatures at the locations of other slope receivers (KW: ^2=633, P<0.001). The receiver at site 3 recorded 3 of the 4 fish with the longest stays on the slope (28-61 days). The fourth fish had the maximum stay (8 days) near the receivers deployed in soft bottom habitats (sites 2 and 4), after it had spent 23 days at the northern rock ledge habitat (site 1). 25 5 24.5 O m ♦♦♦♦♦♦♦♦♦♦♦♦♦♦ ♦ ♦♦♦♦♦ ♦♦♦ ♦♦ ♦♦♦♦♦♦ ♦♦♦ ♦♦♦♦♦♦♦♦♦♦♦♦ ♦♦♦ 23 5 22.5 A A AAA A AA AA AA AA A A A A A A A A A A A A A A A A A XXXXXXXXXXXXXXXX XX XXXXXXX XX XX XX XXXXXXXXXXX XXX XXX ♦ Tag 1834 ■ Tag 1835 ♦ Tag 1844 x Tag 1850 21.5 7/22/2007 7/29/2007 Date 8/5/2007 Figure 5 The diverse set of presence and absence patterns for 4 individual juvenile crimson jobfish ( Pristipomoides filamentosus) . Detections of their tags were binned by peri- ods of 6 h, that persisted at the nursery offshore of Kaneohe Bay, windward Oahu, for a 15-day period in 2007. The gray bars represent hours of night, and the gray line is the bottom temperature in degrees Celsius. 238 Fishery Bulletin 113(3) Discussion Time in the nursery It is unknown why the signals of cultured fish released in the first year of this study disappeared faster than wild fish in the second year. This release is the first one of a deepwater fish species raised in captivity. There are many potential factors, such as depth, light levels, and temperature, that likely influenced the behavior of the released cultured fish. Cultured fish reared in the warm surface water of a bay cage had none of the familiarity with the nursery habitat that the wild fish had. The released wild fish lingered because they knew the site, they had not yet matured enough to emigrate, or there were significant environmental differences be- tween years that influenced fish behavior. Environmental effects, including freshwater dis- charge, have been reported to influence the behavior of tagged marine species in coastal estuaries during their early life history (Manderson et al., 2014). The Kaneohe nursery differs from nurseries in estuarine habitats, because it is located deep, at the edge of an oceanic slope, where the substrate, temperature (Mof- fitt and Parrish, 1996), and nutrients (Parrish et ah, 1997) have been found to be consistent between years in prior studies. The temperature records from both tagging years in this study were similar, and there is no clear association between temperature and be- havior of the crimson jobfish. The original plan was to conduct a simultaneous release of cultured and wild fish in 2007 to compare their behavior, but the funding for the culture program was unexpectedly cut. Future studies are needed to distinguish whether interannual environmental effects are indeed a concern or whether the observed fish behavior is due to the inability (or a lack of need) for cultured juvenile fish to integrate into an assemblage of wild juveniles. Potential tagging effects Surgical implantation of acoustic tags in small fish has the potential to add significant weight and affect the fish’s buoyancy and behavior. Prior studies (Mc- Cleave and Stred, 1975; Adams et al., 1998) recom- mended that tags should be no more than 2% of fish body weight. The V9 tags exceeded this percentage for 8 of our fish; 1 tag in 1 fish accounted for as high as 3.3% of estimated body weight. However, all the fish fell well within the percentage of tag weight identified by Brown et al. (1999), who showed success with the use of tags that were 6-12% of body mass of juvenile salmon (smolt). Our observations of fish actively swim- ming in the holding pen for days before release and documented movement between receivers after release indicate that there was little behavioral effect from the size of the tags used. Having endured the stress of tagging, release, and descent through the water column, most of the released fish successfully reached the bottom where they were repeatedly detected for a day or more by the nursery receivers. A single 20-cm fish (tag 1867) was not de- tected by either of the nursery receivers after it was released, but it appeared 9 days later at site 3 on the adjacent slope (Fig 1). It stayed there for 2 days be- fore disappearing from the study. The disappearance of tag signals is either the result of the fish emigrat- ing outside the receiver surveillance area or of it being consumed by a predator that leaves the area. The fea- tureless mud bottom of the nursery supports few other fish (DeMartini et al., 1996) that would be resident predators of the crimson jobfish; therefore, predation loss was likely from larger, transient fishes that passed through the nursery. Loss of tagged fish to predation is expected, although we have no way to evaluate the degree of this impact. Movement of wild fish There have been few studies of tagged deepwater snap- pers and most of them have been of adult fish. The most recent work (Weng, 2013) looked at movements of tagged adult eteline red snappers and found that ruby snapper ( Etelis carbunculus) showed more fidelity to the area of their release than did tagged flame snapper (Etelis coruscans ). A separate study of 18 tagged adult crimson jobfish (40-60 cm FL) showed that 75% of fish remained in the monitored release area (Ziemann and Kelley5). Because those mature fish had already immi- grated to their adult habitat, we might expect greater fidelity for them than for the juvenile fish in our study. In contrast, we examined the temporary use of nurs- ery habitat by juveniles before they moved to the next stage in their life history. The time spent in the nursery varied from a few days to multiple weeks. For many of the fish tagged in our study, diurnal movements were detected in and out of the range of receivers in the nursery. The study on tagged adult crimson jobfish found that they aggre- gated during the day and ranged over a wider area at night (Ziemann and Kelley5). The movements of the juveniles in our study were much more limited. The receivers deployed on the slope adjacent to the nurs- ery did not detect a greater number of juvenile crim- son jobfish during evening hours than during daytime hours; an increase would be expected if the fish were engaged in wide-ranging movements. It is possible that the juveniles could have moved inshore to shal- lower depths; however, data from a previous study that conducted boat-based tracking of 2 juveniles indicated that the fish would move deeper (Moffitt and Parrish, 1996). The individual tracks of both fish showed cre- puscular movements, the fish stayed in shallower wa- 5 Ziemann, D., and C. Kelley. 2004. Detection and documen- tation of bottomfish spillover from the Kaho'olawe Island Re- serve. Final report submitted to the Kaho'olawe Island Re- serve Commission for Study I. [Available from Kaho'olawe Island Reserve Commission, 811 Kolo St., Ste. 201, Wailuku, HI 96793.] Parrish et a!.: Movements of cultured and wild juvenile Pristipomoides filamentosus in a nursery habitat 239 Table 2 The identification number and substrate type of the 4 sites on the windward Oahu slope where receivers were deployed in 2007. Also shown is the distance in kilometers of each receiver from the nursery, num- ber of tagged juvenile crimson jobfish (Pristipomoides filamentosus) that were detected, mean number of days when those fish were present at each site, and mean bottom temperature at each site. For “Days present” the mean, standard deviation (SD), and range are given for each site. There were 2 substrate types: rock ledge and soft bottom. Days present Temp. (°C) Receiver Substrate Nursery (km) No. fish Mean (SD) Range Mean (SD) 1 Rock 4.0 5 6.0 (9.9) 0.25-23.5 21.8 (1.0) 2 Soft 1.5 17 1.5 (2.0) 0.25-8.3 21.8 (1.0) 3 Rock 1.8 8 17.8 (25.2) 0.25-61.0 21.0 (1.0) 4 Soft 3.3 8 0.6 (0.4) 0.25-2.0 21.8 (1.0) ter during the day and in deeper water at night, shift- ing between adjacent areas (<300 m separation) that differed slightly in depth ( ~ 10 m). For both tracks, the area of daytime activity was twice the size of the area of activity at night. This commuting behavior could explain the bimodal pattern seen for the tagged fish in our study before they left the nursery. If these fish also shifted deeper at night, some of them would be out of detection range until morning when they returned to the shallower portion of their home range and were more active. Looking at the patterns in the movements of the 4 wild fish that persisted in the nursery for multiple weeks, 2 fish (tags 1834 and 1850) appeared to have both their areas of activity during day and night mostly inside the detection area of the receivers in the nursery (Fig. 5). In contrast, the pattern of a third fish (tag 1835) indicates that the area of activity during the day was within the detection range of the receiver and the area of nighttime activity was outside that range. Some drift in the home range of individual fish can occur, as was observed for the fourth wild fish (tag 1844) that stayed at the nursery for multiple weeks, but the extent to which the size or location of home ranges are subject to change over time is unknown. As the wild fish departed the nursery and ranged farther out on the slope, they used both soft bottom and rock ledge habitats before emigrating away. Al- though the size of the fish at the sites on the slope did not statistically differ by habitat type of sites, a few of the larger fish (mean: 25.5 cm FL [SD 5.4]) clearly persisted for more than a month at sites with rock ledges. Crimson jobfish at this size are at the lower end of the size range of subadults documented to ag- gregate around relief features (Okamoto1). Presumably, this shift in habitat use occurs because the fish grow to a size where they need to change their diet or for- aging strategy. Studies of stomach contents of crimson jobfish have shown a transition from a juvenile diet of mostly benthic invertebrates (DeMartini et al., 1996) to an adult diet of mostly large plankton, including jellies and salps (Haight et al., 1993b). Maturing and adult fish use high-relief habitat more than juveniles do — they exploit the increased water flow around relief features to improve their level of success in encounter- ing and feeding on drifting plankton over their level of success at low-relief habitats. Future tagging work in the Kaneohe nursery should include receivers deployed in nearby locations with adult crimson jobfish assem- blages to see if some of the emigrating juveniles make a direct transition to adult habitat. Considerations for stock enhancement Although we have no explanation for the behavioral dif- ference seen between the 2 batches of tagged fish, the patterns observed for wild and cultured fish are similar to findings from other marine fish studies. Simultane- ous releases of tagged cultured and wild individuals generally have shown that cultured fish tend to move away sooner and farther than wild fish (D’Anna et al., 2004; Yokota et al., 2007; Fairchild et al., 2009; Lino et al., 2009). Future studies with releases of tagged juve- nile crimson jobfish might include a staged release pro- cess (Fairchild et al., 2010) that would give fish time to acclimate to the nursery and, therefore, make them more likely to use the habitat like wild fish. However, if cultured fish were to continue to leave the nursery directly, and there were no means to verify their sur- vivorship after they have left, the use of larger fish (>30 cm FL) that are old enough to skip the nursery stage and join subadults or adults should be considered for enhancement efforts. Stock enhancement studies on shallower Hawaiian species have shown that the size of release is an important variable in the success of stocking efforts (Leber, 1995; Leber et al., 1998; Leber et al., 2005). Finally, it is possible that being reared, or even just being held for a time in captivity and fed, can accelerate the ontogentic shift from the nursery stage to subadult phase in the life history of the crimson job- 240 Fishery Bulletin 1 13(3) fish. For example, the type or amount of food is likely to be better calorically in captivity than in the wild (Alasalvar et ah, 2002; Gregorakis et al., 2002; Hande- land et al., 2003; Periago et ah, 2005; Benetti et ah, 2010), and it could accelerate the development of the reserves a fish needs to graduate to the next habitat during its life history. Within 3 days of release, the majority of tagged fish in both years departed from the nursery, although cul- tured fish exited at twice the rate of wild fish. There were no obvious environmental differences seen be- tween years that could explain the different behavior patterns. For the batch of wild fish, higher numbers were detected during daylight hours than at night, and the movement of fish that stayed in the nursery for multiple weeks did not correspond with tidally driven changes in bottom temperature. Larger juveniles (>25 cm FL) emigrated away from the nursery earlier; two- thirds of these juveniles traveled across soft bottom habitats (mean: 1.2 days [SD 1.69]) and the rest lin- gered in areas with rock ledges (mean: 13.3 days [SD 20.9]). Our research indicates that juvenile crimson jobfish cultured in the laboratory or pulled from the wild will quickly emigrate even if released in a viable nursery habitat. This behavior prompts a number of ontogenetic, behavioral, and survivorship questions for future study that are particularly relevant for aqua- culture as a means to enhance the stock of deep-slope fish species. 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N., and J. H. Uchiyama. 1996. Fishery atlas of the Northwestern Hawaiian Is- lands. NOAA Tech. Rep. NMFS 38, 142 p. Weng, K. C. 2013. A pilot study of deepwater fish movement with re- spect to marine reserves. Anim. Biotelem. 1:17. Yokota T., R. Masuda, N. Arai, H. Mitamura, Y. Mitsunaga, H. Takeuchi, and T. Tsuzaki. 2007. Hatchery-reared fish have less consistent behavioral pattern compared to wild individuals, exemplified by red tilefish studied using video observation and acoustic telemetry tracking. Hydrobiologia 582:109-120. Zeller, D., M. Darcy, S. Booth, M. K. Lowe, and S. Martell. 2008. What about recreational catch? Potential impact on stock assessment for Hawaii’s bottomfish fisher- ies. Fish. Res. 91:88-97. 242 NOAA National Marine Fisheries Service Fishery Bulletin & established 1881 •3). In addition, a “ship” covariate was proposed for the period 2010-2012 to assess whether the use of ships with different height platforms had an effect on detection probability. This covariate had 4 levels, namely 1 level for each ship used during the summer surveys. For each year, covariates were tested singly or in additive combination. It was expected that P was posi- tively correlated with group size and platform height but negatively correlated with Beaufort sea state. If a proposed model was inconsistent with these expecta- tions, then that model was deleted from the analysis before model selection was performed (e.g., Zerbini et al., 2006). The model with the lowest Akaike’s informa- tion criterion (AIC) was used for statistical inference (Burnham and Anderson, 2002). In the estimates pro- vided here, the probability of detecting porpoise on the trackline was assumed to be unity (g(0)=l; see Discus- sion section). Estimation of group size Porpoise were considered to be in a group when ani- mals were within 10-15 body lengths of each other. Group size has the potential to affect estimates of P. If larger groups are easier to detect further away from the trackline, then use of average group size can bias estimates (Buckland et al., 2001). In our explor- atory analysis, regression of group size versus detec- tion probability (Buckland et al., 2001) indicated that detections were independent of group size. Therefore, stratum-specific simple means were used after trunca- Dahlheim et al.: Temporal changes in abundance of Phocoena phocoena inhabiting the inland waters of Southeast Alaska 247 Table 2 Regions identified within the study area with overall size of each stratum and the amount of survey effort realized during line-transect surveys for harbor porpoise (Phocoena phocoena) conducted in summer in South- east Alaska in 3 survey periods (1991-1993, 2008-2007, and 2010-2012). Survey effort (km) Region Region name Area (km2) 1991-1993 2006-2007 2010-2012 1 Cross Sound, Icy Strait, and Glacier Bay 2302 1210 522 1122 2 Lynn Canal and Stephens Passage 1985 740 345 526 3 Frederick Sound 2951 1059 579 1279 4 Upper and Lower Chatham Strait 4267 957 354 694 5 Sumner Strait, Wrangell, and Zarembo Island 2943 812 450 1136 6 Clarence Strait to Ketchikan 3218 533 159 599 Total 17,665 6228 2466 6172 tion to estimate the expected group size for analysis conducted with CDS models. For MCDS models, es- timates of the expected group size were obtained as proposed by Marques and Buckland (2003, Eq. 16 on p. 928). Estimation of abundance Stratum-specific abundance was estimated with the most supported detection probability model for each period. Total abundance in the survey regions was es- timated by summing across the estimates of each in- dividual stratum. Abundance and variance were esti- mated as in Innes et al. (2002) and Marques and Buck- land (2003). Lognormal 95% confidence intervals (CIs) (Buckland et al., 2001) were computed for abundance estimates for each period. Results Between 1991 and 2012, 8 line-transect surveys were completed during the summer in Southeast Alaska (Ta- ble 1). The regions (or strata) within the study area are depicted in Figure 1. Total and stratum-specific regions and realized survey effort are summarized in Table 2. In all regions combined, a total area of 17,665 km2 rep- resenting 14,865 km of survey trackline was surveyed. Figure 2 Sightings of harbor porpoise (Phocoena phocoena) and completed tracklines for line-transect surveys conducted in the inland waters of Southeast Alaska during summer in (A) 1991, (B) 1992, and (C) 1993. 248 Fishery Bulletin 113(3) Figure 3 Sightings of harbor porpoise (Phocoena phocoena) and completed tracklines for line- transect surveys conducted in the inland waters of Southeast Alaska during summer in (A) 2006 and (B) 2007. Completed tracklines and harbor porpoise sightings are depicted for each of the 3 periods in Figures 2-4. Estimation of detection probability Parameter estimates for the models most supported by AIC for each period are presented in Table 3, and their equivalent detection functions are illustrated in Fig- ure 5. Estimation of P varied between 0.47 (coefficient of variation [CV]=0.04) and 0.61 (CV=0.04). The half- normal model with a Beaufort category covariate was selected as the best fit for the periods 1991-1993 and 2010-2012, and the hazard rate model without covari- ates was the most supported model in 2006-2007. Encounter rates and estimation of group size Sightings and group encounter rates are presented in Table 4. The total number of harbor porpoise groups seen in inland waters in Southeast Alaska during the summer was 422, 137, and 434 for the periods 1991- 1993, 2006-2007, and 2010-2012, respectively. How- ever, because of truncation of perpendicular distance data, the number of sightings used in the estimation of density was 381, 130, and 412 for each period. The greatest average encounter rate was observed in the period 2010-2012 (0.07 groups/km, CV=0.17) and the lowest was recorded within the period 2006-2007 (0.05 groups/km, CV=0.20). Expected average group sizes (Table 5) ranged from 1.37 (CV=0.03, during 2010-2012) to 1.59 individuals/group (CV=0.05, during 1991-1993). Estimation of density and abundance Stratum-specific estimates of density and abundance of harbor porpoise in Southeast Alaska during the summer are summarized in Table 6. Overall, density was similarly high in the earliest (1991-1993, density (D)=0.06, CV=0.13) and the latest (2010-2012, D=0.06, CV=0.10) periods. In contrast, density declined by half during the period 2006-2007 (D=0.03, CV=0.20). Overall estimates of abundance indicated a significant decline in the numbers of Southeast Alaska harbor porpoise from the levels observed in the early 1990s (A=1076, 95% 01=910-1272) to the mid-2000s (A/=604, 95% 01=468-780) a drop that was followed by a signifi- cant increase in the early 2010s (N=975, 95% 01=857- 1109) when the population reached numbers similar to those observed 20 years earlier (Table 6, Fig. 6). Regions of higher density were consistently found near Glacier Bay and Icy Strait (region 1; the northern region of the study area) and around Zarembo Island and the town of Wrangell (region 5; the southern re- gion of the study area), with mean densities in these 2 regions nearly 2 and 4 times greater, respectively, than the mean overall density of harbor porpoise in South- east Alaska. Abundance in these 2 regions correspond- ed to 75-88% of the overall harbor porpoise abundance in the study area (Table 6), but trends in abundance differed between them. Although region 5, with Zarem- bo Island and Wrangell, showed a pattern similar to the one seen in the whole of Southeast Alaska, that is to say, they showed a significant decline from the early 1990s to the mid-20G0s followed by a significant in- Dahlheim et al.: Temporal changes in abundance of Phocoena phocoena inhabiting the inland waters of Southeast Alaska 249 Maps with locations of sightings of harbor porpoise ( Phocoena phocoena) and completed tracklines for line-transect surveys conducted in the inland waters of Southeast Alaska during summer in (A) 2010, (B) 2011, and (C) 2012. crease in the early 2010s, abundance in region 1, with Glacier Bay and Icy Strait, remained relatively stable during the 22-year period of this study (Table 6, Fig. 6). Discussion Estimation of abundance Overall abundance was found to vary among survey pe- riods in this 22-year study (1991-2012). The abundance UV=1076) in the early 1990s in the first survey period was relatively high, lower for the period 2006-2007 (1V=604) and higher again for the period 2010-2012 ( N=975 ). Because the surveys conducted in this study covered a long period of time, they were subject to some changes in methods that could affect the abundance es- timates. In addition, multiple factors could have affect- ed the sightability and identification of harbor porpoise groups, and these factors are discussed below. To the best of our ability, we kept survey effort com- parable throughout the years. With the exception of the 2007 survey, during which effort was reduced because of a 3-day mechanical breakdown and fog conditions encountered throughout various regions of the survey area, effort remained fairly consistent and only minor changes were made in trackline and coverage because of adverse weather conditions, ship mechanical break- downs, or cruise duration. However, the number of bi- ologists who participated in the survey varied over the 22-year study period from 4 to 6 due to either the lack of vessel accommodations or NOAA restrictions. Both experienced and inexperienced observers were used Table 3 Most supported models of detection probability and estimates of detection probability of harbor porpoise (Phocoena phocoena) in Southeast Alaska during the periods 1991-1993, 2006-2007, and 2010-2012. hn=half normal; hr=hazard rate; Beaufort=Beaufort sea state; CV=coefficient of variation; P=detection probability. Detection Year probability model P CV (P) 1991-1993 hn + Beaufort 0.51 0.04 2006-2007 hr 0.61 0.08 2010-2012 hn + Beaufort 0.47 0.04 and some individuals participated in several different surveys and one observer participated in all surveys. Laake et al. (1997) showed that observer experi- ence affects their ability to detect harbor porpoise in aerial surveys; inexperienced observers miss porpoise groups 2-3 times more than experienced observers. We assumed when comparing experienced with expe- rienced observers that the same pattern would occur during vessel surveys. However, inexperienced observ- ers can also have difficulty both with correctly estimat- ing group size and with accurately identifying a species (NMML, unpubl. data6). Average group sizes did not 6 NMML (National Marine Mammal Laboratory). 2010. Un- publ. data. Alaska Fish. Sci. Cent., Natl. Mar. Fish. Serv., NOAA, 7600 Sand Point Way NE, Seattle, WA. 98115-6349. 250 Fishery Bulletin 113(3) Table 4 Sightings (AO of harbor porpoise ( Phocoena phocoena) and group encounter rates (ER; groups/km) during surveys conducted in summer in Southeast Alaska inland waters during the periods 1991-1993, 2006-2007, and 2010-2012. CV=coefficient of variation. Region Region name 1991-1993 2006-2007 2010-2012 N ER CV N ER CV N ER CV 1 Cross Sound, Icy Strait, and Glacier Bay 177 0.15 0.12 71 0.14 0.29 160 0.14 0.13 2 Lynn Canal and Stephens Passage 22 0.03 0.25 7 0.02 0.39 12 0.02 0.42 3 Frederick Sound 25 0.02 0.28 10 0.02 0.38 11 0.01 0.51 4 Upper and Lower Chatham Strait 16 0.02 0.29 3 0.01 0.51 4 0.01 0.00 5 Sumner Strait, Wrangell and Zarembo Island 132 0.16 0.25 39 0.09 0.28 214 0.19 0.14 6 Clarence Strait to Ketchikan 9 0.02 0.42 - - - 5 0.01 0.51 Total 381 0.06 0.12 130 0.05 0.20 412 0.07 0.17 differ over the years, indicating that observer experi- ence was not an issue. Although experienced observers can readily discern the profile differences between a surfacing harbor por- poise and a slow rolling Dali’s porpoise (Phocoenoid.es dalli), accurate species identification can prove difficult for an inexperienced observer. Occasionally, a vertical spray of water, termed a “pop splash,” occurs as the porpoise breaks the water surface to breathe (Taylor and Dawson, 1984). This vertical spray of water gener- ated by a fast-moving harbor porpoise can, at times, be confused with the characteristic spray associated with a rooster-tailing Dali’s porpoise. Within the 2 ma- jor regions where harbor porpoise concentrated, Dali’s porpoise sightings were either rare or very limited in numbers (Dahlheim et ah, 2009). The percentage of un- identified porpoise varied across survey years from 0% to 16% of the total number of porpoise seen. Of particu- lar interest is that the percentages of unidentified por- poise were lowest (0-3%) during the mid-2000s, when the steepest abundance declines were noted. The experience level of observers varied during this multiyear study. However, on the basis of low varia- tion in group size, low overlap of harbor and Dali’s por- poise distribution, and the rate of unidentified porpoise sightings over the study period, the potential biases that result from observer variability are not a signifi- cant factor in the abundance estimates. Harbor porpoise are small, have no visible blow, and have a very low profile in the water. These features are well-known constraints in visual detection of this species (e.g., Hammond et al., 2002). Sighting cues can be very subtle, and observers can easily miss sighting an animal even in the best of conditions. The majority of the surveys in our study were conducted in Beau- fort sea states between 0 and 3 and that condition is reflected in the sighting data. Under these relatively good conditions, 99% of the sightings were collected. Nonetheless, models with a Beaufort category were se- lected in 2 out of the 3 periods, indicating that high- er sea states significantly reduced the sightability of porpoise. Over the 22-year period, 5 different vessels were used, but ship height did not influence detection of Table 5 Average expected group size, E(S), for harbor porpoise (Phocoena phocoena) during surveys conducted in inland waters of Southeast Alaska during the summer season of the periods 1991-1993, 2006-2007, and 2010-2012. CV=coefficient of variation 1991- -1993 2006-2007 2010- -2012 Region Region name E(S) CV E(S) CV E(S) CV 1 Cross Sound, Icy Strait, and Glacier Bay 1.6 0.06 1.73 0.06 1.41 0.06 2 Lynn Canal and Stephens Passage 1.49 0.10 1.57 0.17 1.24 0.07 3 Frederick Sound 1.74 0.10 2.30 0.19 1.73 0.14 4 Upper and Lower Chatham Strait 1.39 0.08 1.33 0.21 1.50 0.00 5 Sumner Strait, Wrangell, and Zarembo Island 1.53 0.04 1.31 0.05 1.36 0.03 6 Clarence Strait to Ketchikan 1.61 0.16 0.00 0.00 1.00 0.00 Total 1.56 0.03 1.59 0.05 1.37 0.03 Dahlheim et al.: Temporal changes in abundance of Phocoena phocoena inhabiting the inland waters of Southeast Alaska 251 Distance (km) Distance (km) Distance (km) Figure 5 Detection probability models that fit perpendicular distance data collected during surveys of harbor porpoise ( Phocoena phocoena) in Southeast Alaska for the following periods and models: (A) 1991-1993, half normal (hn)+Beaufort sea state; (B) 2006-2007, hazard rate; and (C) 2010-2012, hn+Beaufort sea state. harbor porpoise, possibly because most groups were ob- served well within the maximum detection range pro- vided by each ship. Animal responses may have varied on the basis of the noise profiles transmitted by these different platforms. If animals move toward or away from the survey platform during line-transect surveys, density estimates will be over- or underestimated, re- spectively. Palka and Hammond (2001) reported that North Atlantic harbor porpoise avoided the survey plat- form. However, Williams and Thomas (2007) reported that responsive movement toward or away from sur- vey platforms was not pronounced for harbor porpoise that occupied the coastal waters of British Columbia. During our investigations, we did not observe harbor porpoise responding to our survey platform; however, quantitative data that addressed porpoise avoidance or attraction were not collected. It is unlikely that we missed areas with high den- sities of harbor porpoise given the extent of our spa- tial coverage and the long-term nature of our study. In addition to the 8 summer surveys reported here (in 1991-1993, 2006-2007, 2010-2012), we also con- ducted 5 line-transect surveys each in the spring and fall (Table 1). Some areas typically not covered during our line-transect surveys (e.g., when we were off effort while entering bays and inlets to anchor for the night, finding shelter from storms, or conducting studies on killer whales; see Dahlheim and White, 2010) did not reveal any other regions of high porpoise densities. In addition, between 1994 and 2005, 24 more vessel sur- veys, during which line-transect methods were not car- ried out throughout this study area, found no other ar- eas of high porpoise densities (Dahlheim et al., 2009). An aerial study conducted in 1997 (Hobbs and Waite, 2010) included some additional survey areas in South- east Alaska but also did not reveal any other locations with high densities of harbor porpoise. Interviews with other researchers, local residents, and fishermen famil- Tahle 6 Summer density (D; individuals/km2) and abundance (TV; number of individuals) of harbor porpoise ( Phocoena phocoena ) from surveys conducted in the inland waters of Southeast Alaska during the periods 1991-1993, 2006-2007, and 2010-2012. CV=coefficient of variation. 1991-1993 2006-2007 2010-2012 Region Region name D N CV D N CV D N CV 1 Cross Sound, Icy Strait, and Glacier Bay 0.15 342 0.14 0.13 297 0.31 0.14 332 0.14 2 Lynn Canal and Stephens Passage 0.03 65 0.24 0.02 35 0.44 0.02 40 0.42 3 Frederick Sound 0.03 81 0.32 0.02 64 0.41 0.01 30 0.54 4 Upper and Lower Chatham Strait 0.02 68 0.31 0.01 26 0.56 0.01 25 0.04 5 Sumner Strait, Wrangell, and Zarembo Island 0.16 461 0.25 0.06 182 0.29 0.18 526 0.15 6 Clarence Strait to Ketchikan 0.02 60 0.45 0.00 0 0.00 0.01 21 0.49 Total 0.06 1076 0.13 0.03 604 0.20 0.06 975 0.10 252 Fishery Bulletin 1 13(3) a) o c M n c D n re re > O 1400 1200 1000 800 600 400 700 600 JO 500 JO re eg o' 400 re re c r c • Overall SE Alaska □ Glacier Bay and Icy Strait O Wrangell and Zarembo Island 300 200 100 o. re 1990 1995 2000 Year 2005 2010 Figure 6 Estimates for overall and regional abundance of harbor por- poise (Phocoena phocoena) from surveys conducted in South- east Alaska during the periods 1991-1993, 2006-2007, and 2010-2012. Note the significant declines (nonoverlapping confidence intervals) in the estimates provided for overall Southeast Alaska and for the region that included Wrangell and Zarembo Island in the mid-2000s and the relatively sta- ble trend over the 22-year study period (1991-2012) for the region that included Glacier Bay and Icy Strait. Error bars indicate 95% confidence intervals. iar with these waters also revealed no other areas of major porpoise concentrations. Because of the patterns of clumped distribution ob- served for harbor porpoise, if we did miss an entire re- gion where animals were concentrated both temporally and spatially, that omission would significantly affect our abundance estimate for that particular year. How- ever, by pooling data across sequential years, we re- duced the variance resulting from the naturally patchy distribution of harbor porpoise. The abundance estimates we derived for harbor por- poise in Southeast Alaska are likely biased low for 2 major reasons. We did not sample all areas used by harbor porpoise in inlands waters of Southeast Alaska. This region encompasses an area of 27,808 km2, but only 17,665 km2 were actually surveyed. Although there is limited evidence that any of the regions that were not surveyed corresponded with high-density por- poise habitats, the occurrence of a small number of animals in these regions would lead to an underesti- mated abundance. Another important source of nega- tive bias in results of harbor porpoise studies comes from animals that are missed along the trackline, that is from the violation of the assumption ofg(0)=l. Previ- ous studies have documented the importance of obtain- ing an estimation of the proportion of animals missed along the trackline (i.e. , the proportion derived from g[0] experiments) to compute absolute esti- mates of abundance (Barlow, 1988; Palka, 1995, 1996). These studies have shown that approxi- mately 20-50% of harbor porpoise groups are missed. If g(0) correction factors obtained from other vessel studies (Barlow, 1988; Palka, 1995) are used to adjust for animals missed by observers, the total number of harbor porpoise in South- east Alaska may be 1. 5-2.0 times greater than the numbers reported here. However, the actual value of the correction factor for our study is un- known and may vary considerably on the basis of many aspects and circumstances that affect porpoise sightability, including visual search pro- tocols of observers, weather and visibility condi- tions, survey platform, behavior of porpoise, and density of animals in different regions (Laake and Borchers, 2004; Laake et al., 1997; Palka, 1995). Clearly, g(0) experiments are needed to obtain absolute abundance of harbor porpoise in Southeast Alaska. Ideally, these estimates should be survey-specific in order to assess whether and how very different survey teams and conditions affect the estimation of animals missed along the tracklines. Before the surveys conducted in 2011 and 2012, a trend analysis, completed to include the 1991-1993, 2006-2007, and 2010 surveys, indi- cated a high probability of a decline in porpoise numbers ranging from 2% to 4% per year for the whole study area (Zerbini et al.7). However, when data from 2011 and 2012 were added to this anal- ysis, the rate of decline over the entire study period decreased substantially and was no longer significant. The increase in abundance observed for the waters sur- rounding Wrangell and Zarembo Island represented a three-fold increase that is not biologically plausible given the rate at which this species reproduces. There- fore, it is likely that this increase reflected a combina- tion of factors, including possible population growth, a shift in distribution, or the influx of porpoise from other regions (e.g., offshore waters). It is unclear why the decline in porpoise numbers oc- curred between the early 1990s and the mid-2000s (Fig. 6) or, in fact, if this decline is real. The low abundance in 2006 and 2007 cannot be explained by reduced sur- vey effort (i.e., 2 survey years versus 3 survey years for the periods 1991-1993 and 2010-2012) because similar effort per unit of area took place where high-densities of porpoise occur for all years. Given the clumped distribution of harbor porpoise in the study area, it 7 Zerbini, A., M. E. Dahlheim, J. Waite, A. Kennedy, P. R. Wade, and P. J. Clapham. 2011. Evaluation of population declines of harbor porpoise (Phocoena phocoena) in Southeast Alaska inland waters. In Book of abstracts: 19th biennial conference on the biology of marine mammals; Tampa, FL., 28 November-2 December. Society for Marine Mammalogy, Moss Landing, CA. Dahlheim et al.: Temporal changes in abundance of Phocoena phocoena inhabiting the inland waters of Southeast Alaska 253 is possible but unlikely, given the multiple years in- volved and the overall extent of the area coverage in our study, that a large grouping of animals was missed during a survey period. One explanation is that part of the population may have moved outside our study area (e.g., offshore waters) because of shifts in prey availability and abundance. Without knowing whether porpoise shift their distribution or what might drive it if they do (e.g., prey preferences or oceanographic con- ditions), we cannot determine whether porpoise move- ment patterns are a factor in the observed downward trend. In addition, a change in porpoise numbers may also be dependent upon year-to-year variations in habi- tat suitability, increased predation, increased mortality from bycatch, or a combination of all these factors. When examined on a regional scale, abundance was relatively consistent throughout the survey pe- riod in the northern region that included Glacier Bay. In contrast, a significant downward trend in abun- dance was estimated for the southern region that in- cluded the waters surrounding Wrangell and Zarembo Island between the early 1990s and the mid-2000s, and an increase was observed for that region as of 2010. Of particular interest is that porpoise numbers declined only in regions where salmon (Oncorhyn- chus spp.) and Pacific herring net fisheries operate. Certainly, bycatch has been shown to be a significant source of porpoise mortality in other geographic areas (Gaskin, 1984; Read and Gaskin, 1988; Woodley and Read, 1991; Read et al., 1993) and may, in fact, be responsible for the downward trend observed in our data for the mid-2000s. We are unable, however, to attribute the decline in the mid-2000s to incidental takes in the net fisheries given that interaction data are not available. Regardless of the reasons for that decline, further studies are necessary to understand the possible causes of the variability observed in our study in the abundance of harbor porpoise in inland waters off Southeast Alaska. Insights into population structure As currently defined (see Introduction), the Southeast Alaska stock of harbor porpoise occurs from Dixon En- trance to Cape Suckling, including all inland and coast- al waters within this region (total area= 106,087 km2). Studies that have addressed stock structure of harbor porpoise in Alaska are either not available or based on limited sampling from a particular area (Rosel et al., 1995; Chivers et al., 2002). Outside Alaska, research has shown that harbor porpoise stock structure is of a finer scale than that of the stock structure reflected in the Alaska stock assessment report for 2011 (Allen and Angliss, 2012). Stock discreteness in the eastern North Pacific was, for example, analyzed by using mitochon- drial DNA from samples collected in California, Wash- ington, and British Columbia but from only one sample from Alaska (Rosel, 1992). Results of our initial investi- gation indicated little interbreeding of harbor porpoise along the western coast of North America. Further genetic testing by Rosel et al. (1995, 1999) showed that harbor porpoise in both the eastern North Pacific and North Atlantic were not panmictic and that movement was sufficiently restricted resulting in ge- netic differences. Furthermore, Chivers et al. (2002), using both mitochondrial and nuclear (microsatellite) DNA, examined the intraspecific structure of harbor porpoise that inhabited the eastern North Pacific and reported similar findings. These studies revealed sta- tistically significant genetic differentiation, indicating demographic independence of fairly small subunits within the population. Additional evidence that harbor porpoise restrict their movements has been obtained from both contami- nant research and satellite tagging studies. Investiga- tions on the pollutant loads of harbor porpoise from California to the Canadian border (Calambokidis and Barlow, 1991) also suggest restricted movement pat- terns of harbor porpoise. Pollutant studies produced similar results in the North Atlantic (Westgate and Tolley, 1999). Satellite-tagging operations conducted in Puget Sound, Washington, have shown that porpoise movements were fairly localized and did not occur be- tween Neah Bay (at the entrance of the Strait of Juan de Fuca) and the San Juan Islands; these 2 regions are separated by approximately 150 km of continuous open waterways (Hanson8). During our study, harbor porpoise distribution was clumped in 2 major areas that were consistent through- out the 22-year period: the waters of Glacier Bay and Icy Strait and the waters surrounding Wrangell and Zarembo Island, including the adjacent waters of east- ern Sumner Strait (northern and southern regions, respectively; also see Dahlheim et al., 2009). These regions are separated by a distance of approximately 400 km. If harbor porpoise within the inland waters of Southeast Alaska behave in the same manner as har- bor porpoise elsewhere have been reported to behave (i.e., movements are locally restricted), then a low level of mixing would be expected, indicating the potential for reproductive isolation between the 2 regions. The physical character of this region (e.g., hundreds of is- lands and a complexity of waterways) may also limit frequent movements of harbor porpoise between the 2 regions. The difference in abundance trends between the northern and southern regions of the study area pro- vides additional evidence that these 2 regions, where consistent porpoise concentrations have occurred over 2 decades, represent regions of population structuring for this species within the inland waters of Southeast Alaska. Of utmost concern is that incidental takes within a small region (e.g., Wrangell and Zarembo Is- land) could severely affect undefined localized stocks of harbor porpoise that could easily go undetected unless stock structure is identified. On a larger scale, given the wide distribution of harbor porpoise throughout 8 Hanson, B. 2013. Personal commun. Northwest Fish. Sci. Cent., 2725 Montlake Blvd. East, Seattle, WA 98115-2097. 254 Fishery Bulletin 113(3) Alaska waters, it is likely that several other regional and subregional populations exist within the 3 current- ly designated stocks. In summary, the results of our analysis with data from surveys conducted between the years 1991 and 2010 led us to believe that numbers of harbor porpoise within the inland waters of Southeast Alaska declined significantly, highlighting a potentially important con- servation issue. With the inclusion of data from sur- veys conducted in 2011 and 2012, our analysis indi- cates that if a decline occurred, then the population may be recovering. It is not clear whether the observed decline and subsequent increase in abundance repre- sent a true decline in the population or a reflection of variable local abundance related to interannual differ- ences in prey availability, habitat suitability, or other factors. The overall changes in abundance of harbor porpoise observed in this study could have remained undetected were it not for the long time series of this research, clearly demonstrating both the value and need for multiyear studies on long-lived mammals, such as ce- taceans. Understanding the distribution, abundance, and population trends of a given species is essential for conservation efforts to be effective. On the basis of our study, we hypothesize that harbor porpoise populations within the inland waters of Southeast Alaska contain structure. Although this structure is currently unclear, we suggest that different stocks probably exist within this region. A proper assessment of the status of the harbor porpoise stock or stocks in Southeast Alaska re- quires a combination of research approaches, i.e., con- ducting coastal and inland surveys at the same time to evaluate stock abundance, exploring correction factors for this species (e.g., g[0] experiments), performing ge- netic studies (to fully define stock structure), and using satellite telemetry (to understand porpoise movements within or across current stock boundaries). Acknowledgments Our appreciation is extended to the various captains and crew of the John N. Cobb and of the FV Steller, FV Northwest Explorer, RV Medeia, and RV Aquila. We thank numerous observers for their many hours of sur- vey effort. This manuscript was improved by the criti- cal reviews of B. Taylor and J. Laake (Southwest Fish- eries Science Center, La Jolla, California). We thank H. Braham, D. 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Variability of the mitochondrial control region in populations of the harbour porpoise, Phocoena, on inter- oceanic and regional scales. Can. J. Fish. Aquat. Sci. 52:1210-1219. Rosel, P. E., S. C. France, J. Y. Wang, and T. D. Kocher. 1999. Genetic structure of harbour porpoise Phocoena phocoena populations in the northwest Atlantic based on mitochondrial and nuclear markers. Mol. Ecol. 8:S41-S54. Taylor, B. L., and P. K. Dawson. 1984. Seasonal changes in density and behavior of har- bor porpoise (Phocoena phocoena) affecting census meth- odology in Glacier Bay National Park, Alaska. Rep. Int. Whaling Comm. 34:479-483. Westgate, A. J., and K. A. Tolley. 1999. Geographical differences in organochlorine con- taminants in harbour porpoises Phocoena phocoena from the western North Atlantic. Mar. Ecol. Prog. Ser. 177:255-268. Williams, R., and L. Thomas. 2007. Distribution and abundance of marine mammals in the coastal waters of British Columbia, Canada. J. Cetacean Res. Manage. 9:15-28. Woodley, T. H., and A. J. Read. 1991. Potential rates of increase of a harbor porpoise, Phocoena phocoena, population subjected to incidental mortality in commercial fisheries. Can. J. Fish. Aquat. Sci. 48:2429-2435. Zerbini, A. N., J. M. Waite, J. L. Laake, and P. R. Wade. 2006. Abundance, trends and distribution of baleen whales off Western Alaska and the central Aleutian Is- lands. Deep-Sea Res. I 53:1772-1790. 256 NOAA National Marine Fisheries Service Abstract— We examined depth dis- tribution, habitat association, and growth of newly settled southern Tanner crab ( Chionoecetes bairdi) at 4 sites around the eastern end of Kodiak Island, Alaska, during 2010 and 2011. Settlement was from April through July, and crab den- sity peaked during May-July, at 10 crabs/m2 in 2010 and 2.3 crabs/m2 in 2011. By the end of August most crabs had progressed through 3-5 molt stages (instars). An associa- tion between crabs and tubes of the ampharetid polychaete Sabellides sibirica was observed in 2010, but it was not seen in 2011 when both crabs and worms were less abun- dant. Crabs in protected embay- ments were larger in August than crabs at open coastal sites. Crabs at protected sites were also found in shallower water than at open coast- al sites — a difference that may have exposed them to higher ambient wa- ter temperature and may have ac- celerated their growth. Accelerated growth may in turn result in earlier maturation. Southern Tanner crabs probably settle over a wide range of depths, but shallow embayments (depths <50 m) may play a dispro- portionately large role in providing recruits to the adult population, due to accelerated crab growth and survival. Manuscript submitted 19 August 2014. Manuscript accepted 6 April 2015. Fish. Bull. 113:256-269 (2015). doi: 10.7755/FB. 113.3.3 Online publication date: 30 April 2015. The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA. Fishery Bulletin .%» established 1881 ■, 1.5 c (D 13 1.0 c re ® 0.5 0.0 10 20 30 40 50 60 70 Depth (m) Figure S Mean densities of age-0 southern Tanner crabs ( Chionoecetes bairdi ) from beam trawl hauls, by depth, conducted at Pillar Creek Cove, Kodiak Island, Alaska, in July and August 2011. Error bars indicate standard error of the mean. July to August (Wald %2=23.4, df=l, P<0.001), the ef- fect of depth on density was consistent across months (monthxdepth: Wald %2=7.1, df=3, P=0.055). At Holiday and Pillar, the depth distribution of poly- chaete worms in 2011 (Fig. 6) was similar to that ob- served in 2010 (Fig. 3), albeit, overall worm abundance was lower. Worms at Kalsin displayed a distribution similar to that of worms at Pillar, in distinct contrast to Womens, where worms were most abundant at the 2.0 r 5 10 15 20 25 Depth (m) Figure 6 Mean worm index scores (averaged over months), which provide a measure of relative abundance of worm tubes on a 5-point scale (0-4), plotted against depth for each of the 4 sites surveyed in 2011 around Kodiak Island, Alaska, at Holiday Beach, Pillar Creek Cove, Womens Bay, and Kalsin Bay. Error bars indi- cate standard error of the mean. Figure 7 From quadrat surveys conducted by divers in 2010, mean densities (A) of age-0 southern Tanner crabs ( Chionoecetes bairdi) and (B) of worm tubes, plotted against depth for the study site at Pillar Creek Cove, Kodiak Island, Alaska (y-axis variables are averaged over months). Error bars indicate standard error of the mean shallowest depth and decreased in abundance as depth increased. On first examination, worm abundance might be construed as influencing the distribution of crabs at Womens because crabs also were more abun- dant in shallow water. However, worm abundance did not have a significant influence on crab abundance in the GLM (Wald *2=3.0, df=l, P=0.083). Diver estimation of crab density The quadrats used by divers to assess crab density during 2010 provided an examination of habitat asso- ciations on a micro scale (<1 m); the crab scrape, on the other hand, provided an examination at a larger scale (>10 m). Although there was a tendency for crab density from quadrats (Fig. 7A) to decline through the summer, this effect was not significant (Wald x2=5.3, Ryer et al: Depth distribution, habitat associations, and differential growth of Chionoecetes bairdi 263 200 r c 150 Carapace width (mm) Figure 8 Cumulative size-frequency distribution of southern Tanner crabs (Chionoecetes bairdi) from all sites, months, and depths surveyed in 2010 and 2011 around Kodiak Island, Alaska. A tabulation of median size, size range, and molt increment for each molt stage is provided in Table 1. df=2, P=0.070). As seen in the scrape data, crab den- sity estimated by divers in quadrat surveys increased with depth (Wald x2=12.8, df=3, P=0.005). This depth effect was consistent over months (monthxdepth: Wald X2=3.5, df=4, P=0.474). Although crab density appeared to mirror the observed depth distribution of worm tubes (Fig. 7B), worms tubes were not a significant covariate in the GLM analysis (Wald x2=0.9, df=l, P=0.354), in- dicating no association at this spatial scale. Table 1 Medians and ranges of carapace widths (mm) for pro- posed molt stages of southern Tanner crabs ( Chionoece- tes bairdi) collected during 2010 and 2011 from all 4 sites that were surveyed around Kodiak Island, Alaska. Increment percentages indicate the relative increase in carapace width from one molt stage to the next. Stage Median (mm) Range (mm) Increment (%) Cl 3.4 2.6-4. 1 _ C2 4.8 4. 2-5. 6 41 C3 6.8 5.7-8. 2 42 C4 9.7 8.3-11.3 43 C5 13.4 11.4-15.2 38 C6 17.8 15.3-20.1 32 C7 23.4 20.4-26.6 31 C8 31.8 28.5-35.6 36 C9 42.0 37.3-45.7 32 Age-0 crab molt intervals and size distributions Cumulative size-frequency distributions (all sites and months) were examined initially for each year (2010 and 2011). However, because patterns were identical, we combined both years into a single distribution (Fig. 8; Table 1). Break points between peaks in the size-frequency distribu- tion were taken to be boundaries between suc- cessive molt stages. Percent increase in size over the prior stage averaged 36.9%, within a range of 31-43% (Table 1). There was a trend for molt increments to decrease in later molt stages. Using this classification, we assigned individual crabs to stages, thereby allowing us to examine differ- ences in population composition between months and study sites. A comparison of the 4 study sites surveyed in August of 2010 revealed a significant differ- ence in molt-stage frequencies (x2=349.13, df=12, P<0.001). C4 instars were dominant at Womens and Kalsin, and C3 instars were dominant at Hol- iday and Pillar. Accordingly, the mean carapace widths of crabs at Womens (10.1 mm [SE 0.1]) and Kalsin (9.1 mm [SE 0.1]) were larger than those at Holiday (7.2 mm [SE 0.1]) and Pillar (7.0 mm [SE 0.1]; Kruskal-Wallis: P<0.001; multiple comparisons: P<0.05). Examination of data from surveys conducted in 2011 revealed that differences between study sites in fre- quency distribution of molt stages were established relatively early in the late summer (Fig. 9). Differences in molt-stage composition between sites were evident in May (x2=41.36, df=6, P<0.001). Cl instars dominated populations, although C2, C3, and even C4 instars were present at Kalsin and in lessening degrees at Pillar and Holiday (we did not include Womens in our analy- sis because only several Cl instars were encountered there). As a consequence, the mean carapace widths of crabs at Kalsin (4.5 mm [SE 0.2]) and Pillar (4.0 mm [SE 0.1]) were larger than the mean at Holiday (3.6 mm [SE 0.1]; Kruskal-Wallis: P<0.001; multiple com- parisons: P<0.05). By June, crabs were present at Wo- mens and were typically one stage further along than those at the other sites (x2=184.89, df=9, PcO.OOl). Ac- cordingly, the mean carapace width of crabs at Wom- ens (5.7 mm [SE 0.2]) was larger than the means for crabs at Kalsin (4.2 mm [SE 0.1]) and Pillar (3.8 mm [SE 0.1]), where crabs in turn were larger than crabs at Holiday (3.5 mm [SE 0.1]; Kruskal-Wallis: P<0.001; multiple comparisons: P<0.05). Similarly, in July, C3 instars were prevalent at Womens, whereas C2 instars dominated the other sites (x2=436.06, df=12, P<0.001). As a result, the order of mean carapace widths of crabs at the study sites was Womens > Kalsin > Holiday > Pillar, and all sites differed significantly from each other (Kruskal-Wallis: P<0.001; multiple comparisons: P<0.05). Lastly in August, C4 instars dominated at Womens, a mixture of C3 and C4 instars dominated at Kalsin, C3 instars were dominant at Holiday, and a 264 Fishery Bulletin 113(3) May June July 200 150 in 100 50 * * 150 125 100 75 50 25 0 0 1 2 3 4 5 6 7 150 125 100 75 50 f ] 25 0 ■111 0 1 2 3 4 5 6 7 300 250 200 150 100 50 0 100 80 60 40 20 0 August Holiday 200 150 100 50 0 0 1 2 3 4 5 6 7 ★ 0 1 2 3 4 5 6 7 300 250 200 150 100 50 0 01234567 01 100 80 60 , 2 3 4 5 6 7 Pillar ■ 40 20 0 01234567 01234567 150 200 300 100 125 * * 250 80 150 100 200 60 75 100 150 40 50 100 25 * 50 50 20 Q slilb c >1 2 3 4 5 6 7 C >1234567 01234567 0 150 200 300 100 Womens 125 100 75 50 25 0 0 1 2 3 4 5 6 7 150 100 50 0 HHMHB 250 200 150 100 50 0 0 1 2 3 4 5 6 7 0 12 3 80 60 40 * 20 5 6 7 0 1 §§gg 2 3 4 5 6 7 Kalsin 11111®^ 2 3 4 5 6 7 Molt stage (C1-C6) Figure 9 Frequency distribution of molt stages of southern Tanner crabs (Chionoecetes bairdi ) from each of the 4 sites around Ko- diak Island, Alaska, that were surveyed during May, June, July, and August 2011. An asterisk (*) indicates presumed age-1 crabs, which were excluded from statistical analysis. Columns are months (May-August). Rows are sites (Holiday Beach, Pillar Creek Cove, Womens Bay, Kalsin Bay). Note that the y-axes are different among months. mixture of C2 and C3 instars were dominant at Pillar (X2=291.00, df=12, P<0.001). As in July, the ranking of sites by mean carapace width was Womens > Kalsin > Holiday > Pillar, and all sites differed significantly from each other (Kruskal-Wallis: P<0.001; multiple comparisons: P<0.05). Molt-stage composition varied with the interaction of month, depth, and study site; however, there was no discernible pattern, and, there- fore, we did not explore this interactive effect further. Although the relative abundance of molt stages largely controlled differences in mean carapace width among sites, for crabs at given molt stages there were also small but significant differences between sites. Considering only Cl crabs, we found that there was no difference in mean carapace width between sites (F[3, 928] = l-34, P=0.261). However, among C2 crabs, mean carapace width was greater at Womens (4.93 mm [SE 0.03]) than at Kalsin (4.82 mm [SE 0.02]) and Holiday (4.78 mm [SE 0.02]), where the means in turn were larger than the mean at Pillar (4.70 mm [SE 0.02]); Kruskal-Wallis: P<0.001; multiple comparisons: P<0.05). Among C3 instars, those at Womens (7.13 mm [SE 0.04]) and Kalsin (6.98 mm [SE 0.03]) had greater mean carapace widths than those at Holiday (6.67 mm [SE 0.03]), where the mean in turn was larger than the mean at Pillar (6.55 mm [SE 0.03]); Kruskal-Wallis: P<0.001; multiple comparisons: P<0.05). Lastly, among C4 instars, those at Womens (9.77 mm [SE 0.03]) and Kalsin (9.82 mm [SE 0.05]) again had greater mean carapace widths than those at Holiday (9.51 mm [SE 0.08]), where the mean was in turn greater than that at Pillar (9.08 mm [SE 0.09]); P[3; 503]=26.6, PcO.001). Crabs in the C5 and C6 molt stages were too few in number to provide meaningful comparisons. Ryer et al. : Depth distribution, habitat associations, and differential growth of Chionoecetes bairdi 265 Mean daily seawater temperatures at 15 m (MLLW) for the period from 20 May through 22 August 2011, were 8.2°C, 8.1°C, 8.0°C and 7.7°C for Womens, Pil- lar, Holiday, and Kalsin, respectively. Mean daily sea- water temperature increased though the season (F[i 3Y5]=7475.2 1, P<0.001) and differed among sites (F^ 375]=31.95, P<0.001), with mean temperature at Wom- ens and Pillar higher than that at Holiday and with mean temperature at Holiday higher than at Kalsin (Tukey’s HSD: P<0.05). Discussion Our results illuminate several aspects of the early life history and habitat use of recently settled Tanner crab. First, data indicate that settlement and metamorpho- sis by Tanner megalopae in the northwestern Gulf of Alaska begins in April and continue into July. We did not sample before May; therefore, our inference that settlement begins in April is based on the observation that in May nearly all age-0 Tanner crabs at our study sites were in the Cl molt stage, indicating that they had been on bottom for a relatively short period. By July, Cl instars were infrequent in scrape tows and were completely absent in August. This recruitment schedule resulted in increasing crabs densities from May to a peak in July, and it is consistent with the pattern of egg hatching (April-May) that has been re- ported for both primiparous and multiparous females (Stevens, 2003b; Swiney, 2008). Because the timing of settlement at our various sites was comparable and the 4 sites are separated by only tens of kilometers, we posit that larval sources for these sites were the same. Stevens (2003b) speculated that hatching of Tanner eggs in Chiniak Bay is synchronized with spring tides, which act to break down dominant costal circulation patterns and potentially result in greater larval reten- tion within the Chiniak Bay system. Depth had a strong influence on crab density, al- though this effect varied between embayments. At Pillar and Holiday, recently settled crabs were absent or scarce from scrape tows at depths <8 m, but they became more abundant with increasing depth out to 23 m. Trawl tows conducted during July 2010 at Pillar revealed that crab density was highest at depths of 30- 35 m, decreasing farther offshore, at depths of 50-80 m. By August, densities had declined and there was no longer a maxima at intermediate depths. In contrast with densities at Pillar and Holiday, at Womens and Kalsin, crab density was generally highest at depths between 10 and 15 m, although there was variability among months. We did not conduct trawl sampling at either Womens or Kalsin and have no knowledge of what crab densities were at depths greater than those sampled by the scrape (25 m). We suspect that the difference in crab depth distri- bution between Pillar and Holiday, on one hand, and Womens and Kalsin, on the other, is primarily relat- ed to wave energy. Womens is the most protected of the study sites, with a narrow entrance and offshore islands that dissipate wave energy. Although not as protected as Womens, the Kalsin study site is located near the head of the Kalsin Bay and, as such, typi- cally experiences lower wave action than the sites at Pillar and Holiday. Pillar and particularly Holiday are more exposed and frequently experience strong wave action from the Gulf of Alaska. Although bottom surge associated with wave action may directly affect crabs, by interfering with settlement, impeding foraging, or dislodging crabs from the bottom, we suspect that the influence of wave energy on sediment characteristics is also a primary factor. Because of the inverse relationship between depth and wave-induced bottom scour, sites such as Pillar and Holiday are characterized by coarse sand in shal- low water (depths <10 m), by fine sands or silty sands at depths of 10-25 m, and finally by an increasing con- tribution of mud at depths >25 m (Stoner et ah, 2007). At Womens and Kalsin, as a result of lower wave en- ergy, compared with that at other sites, finer silts and muddy sediments occur at shallower depths (senior au- thor, personal observ. ). For juvenile Tanner crabs, the ability to bury themselves in silty or muddy sediments is their first line of defense against predators. Similar- ly, juvenile flatfish use burial as a predation deterrent and preferentially choose sediment in which they can easily bury themselves (Stoner and Ottmar, 2003). Fur- thermore, fine sediments around Kodiak typically have higher organic content than coarse sediment (Stoner et ah, 2007). Tanner crabs consume not only a variety of infaunal prey, including bivalves, polychaetes, and other crustaceans, but also detrital material (Jewett and Feder, 1983), which presumably occurs in higher concentrations in silty and muddy sediments than in coarser sediments. After the spring bloom, diatoms set- tle to the bottom and accumulate in low wave-energy areas. This flocculent material is readily observed on the surface of fine sediment in Womens Bay during late spring and summer months (Munk4). Juvenile crabs and fishes often seek physically struc- tured habitats. Juvenile red king crab and blue king crab ( Paralithodes platypus) prefer highly structured habitats, which consist of pebbles, cobble, hydroids, macroalgae, shell material, etc., where they are less vulnerable to predators (Stoner, 2009; Pirtle and Ston- er, 2010). Tanner crabs, like snow crabs, generally are thought to prefer sandy, silty, and muddy sediments — a preference that might be explained by their lack of spines that would, if present as in king crabs, inhibit them from rapidly burying themselves (senior author, personal observ.). However, in beam trawl hauls con- ducted during 2009, we observed that recently settled Tanner crabs were most common at depths of 15-30 m, the same depth range where S. sibirica is most abundant (Ryer et ah, 2013). On the basis of this re- 4 Munk, E. 2008. Personal commun. Kodiak Laboratory, Alaska Fisheries Science Center, 301 Research Ct., Kodiak, AK 99615. 266 Fishery Bulletin 113(3) lationship, we hypothesized that recently settled Tan- ner crabs were preferentially using the habitat created by S. sibirica. Juvenile flatfish, principally northern rock sole and Pacific halibut (Hippoglossus stenolepis ), are also attracted to this type of habitat (Ryer et ah, 2013). Although fish avoid areas where worms were so dense as to preclude burial, fish aggregate along the sparse and patchy edges of this habitat type (Ryer et ah, 2013). In 2010, when both worm tubes and crabs were relatively abundant, there was a significant posi- tive effect of worm abundance on crab density, after the effect of depth was factored out. However, during 2011, when both worms and crabs were less abundant, worm abundance had no effect on crab density. This differ- ence in effects indicates that the habitat created by S. sibirica tubes has only a modest influence on distribu- tion of age-0 Tanner crabs. In a manner analogous to the refuge function of eel- grass (Zostera marina L.) (Wilson et ah, 1987; Ryer, 1988), the physical structure of the worm tube habitat may provide age-0 Tanner crabs refuge from fish preda- tors. Predation by Pacific cod ( Gadus macrocephalus ) is thought to regulate Tanner crab recruitment in the Gulf of Alaska and Bering Sea (Livingston, 1989). Ju- venile Tanner crabs may also consume S. sibirica di- rectly or the associated invertebrate species supported by the worm tube habitat (senior author, personal ob- serv.). Alternatively, both species may be attracted to the same depth and sediment characteristics, possibly explaining their association. This interpretation is sup- ported by results from our quadrat surveys, which were conducted by divers at a finer scale than that of the scrape tows and which indicated there was no rela- tionship between crab density and worm tube density. Resolving the nature of this association could be ad- dressed though controlled laboratory experimentation that might reveal whether age-0 Tanner crabs show an attraction for the structure provided by S. sibirica and whether an association reduces predation on age-0 Tanner crabs. Growth in crustaceans is a function of molt incre- ments, typically expressed as percent increase in size, and a function of the frequency with which those molts occur. Knowledge of the age distribution of a popula- tion can be important information in stock assessment. In practice, aging commercially harvested North Pa- cific crabs species relies upon imprecise estimates of the number of molts that occur during each year. Our data indicate that age-0 Tanner crab, around Kodiak Island, pass through between 3 and 5 molts from settle- ment through August. By May of the next year, crabs have gone through 6 or more molt stages. Although no other studies have documented growth during the first year for this species, Donaldson et al. (1981) reported a strong size mode at 18 mm (C6 instars) during May- June in Prince William Sound, northern Gulf of Alaska. Therefore, it appears that crabs in the northern Gulf of Alaska, including near Kodiak, typically go through roughly 6 molt stages in their first year. On the basis of various samples from areas in the Gulf of Alaska, these authors concluded that Tanner crabs typically un- dergo 3 more molts in their second year and 2 molts in their third year, after which molting occurs annually. Donaldson et al. (1981) found that 50% of females were mature at 83 mm and 50% males were mature at 90 mm, indicating that age at maturity for this species is approximately 5 years for females and 7 years for males. Variance in this age-growth schedule will result from differential growth rates between localities and years. Temperature plays an important role in modu- lating growth in crustaceans (Hartnoll, 1982). After 60 days, red king crab and blue king crab reared at 1.5°C were mostly still Cl instars, whereas those reared at 8°C for 60 days were mostly C3 instars (Stoner et al., 2010, 2013). This finding indicates that crabs settling into habitats with differing ambient temperatures may experience vastly different growth rates. Using pub- lished, temperature-dependent growth rates, Stevens (1990) estimated growth and years to maturity for red king crabs from areas with varying temperature re- gimes in Bristol Bay, Alaska. He concluded that growth varies greatly between areas, such that crabs recruit- ing to the pot fishery in the eastern Bering Sea in any given year may be derived from up to 4 or 5 year class- es. This conclusion indicates that it would be advanta- geous for Tanner megalopae to preferentially settle in shallower water where temperatures are supportive of accelerated growth. Naturally, such an outcome would require that other factors, such as forage base and pre- dation risk, do not compromise the enhanced growth for crabs settling in shallower water. Data from out study indicate that growth rates dif- fer among sites. During both 2010 and 2011, crabs from Womens were generally 1 molt stage larger by the end of August than crabs from Pillar and Holiday. There are several possible explanations for this observed size difference. Crabs may simply recruit earlier at Womens than at the other sites. However, this notion is not con- sistent with results from our May 2011 sampling which indicated that crabs at Womens may actually have re- cruited slightly later. Temperature may play a role. We did document minor differences in mean ambient bot- tom temperature (at a depth of 15 m MLLW) between sites; temperature was greatest at Womens. However, the difference in mean temperature between sites was only 0.5°C, and we are skeptical that this difference would result in the greater size observed for crabs at Womens. Age-0 Tanner crabs molt approximately once every 873 degree days in the laboratory, and a temper- ature shift of 0.5°C would only marginally increase the frequency of molting (Long et al., 2013b). Furthermore, temperature was lowest at Kalsin, yet crabs at Kalsin were closest in size to those at Womens and generally were larger than those at Pillar and Holiday. It is per- haps more important to note that bottom temperature at 15 m may not be representative of temperatures for an entire embayment. For example, at both Womens and Kalsin where high growth was seen, crabs tended to be found at shallower depths, where temperatures are expected to be higher. Ryer et al.: Depth distribution, habitat associations, and differential growth of Chionoecetes bciirdi 267 The observed difference in molt-stage frequency be- tween sites may be a product of differential emigra- tion or mortality. If predation is size-dependent, and predators are largely consuming smaller crabs, the size-frequency distribution of crabs at Womens could be skewed toward larger crabs by heavy predation. If this size-selective postsettlement process was in fact occurring, we would expect crab numbers to decline rapidly as a result of predation. Settlement was large- ly complete by July, but Womens was the only site to experience no population decline from July to August, indicating that predation was low at that site. Alterna- tively, differential migration may offer an explanation, if it is a natural progression for Tanner crabs to settle in shallow water and then migrate to deeper water. Unlike the other sites, Womens has a narrow entrance with a sill that rises up to a depth of approximately 11 m. This narrow entrance could reduce offshore migra- tion of juveniles in Womens Bay. However, there is no structural hindrance to offshore migration at Kalsin, where crabs were also relatively large. If anything, we suspect that the shallow sill at Womens may block the offshore migration of larger crabs in the fall, winter, or spring because Womens was the only site that retained an appreciable number of age-1 crabs. Lastly, sites like Womens and Kalsin have finer sedi- ments, which are likely to accumulate organic carbon and support a denser infaunal community than the other sites. Therefore, crabs may have more or better food there. Results of preliminary lipid and essential fatty acid analysis that we performed on crabs from our study sites (Copeman and Ryer5) indicate that crabs from Womens and Kalsin had higher levels of storage lipids and of diatom fatty acid markers than crabs from Pillar and Holiday. Overall higher levels of storage lipids and diatom-derived fatty acids have been associated with accelerated growth in larval Pa- cific cod (Copeman and Laurel, 2010) and juvenile red king crabs (Copeman et ah, 2012). We also observed that, for individual molt stages, crabs were larger at Womens and Kalsin than at Holi- day and Pillar. In a review of crustacean growth, Hart- noil (1982) concluded that, for many species, increases in the quantity or quality of food not only decreased the intermolt period but also increased the molt increment. However, this effect of food availability on growth may vary ontogenetically. Among larger juvenile blue crabs, growth has been correlated with higher food density (Seitz et ah, 2005), whereas, for smaller juveniles, this link has not been made (Long et al., 2011). In contrast, increases in temperature typically decrease both the intermolt period the molt increment, although Stoner et al. (2010) reported an increase in red king crab molt increments with increased temperature. A further un- derstanding of the relative role of temperature ver- sus food on growth of the Tanner crab will await con- 5 Copeman, L. A., and C. H. Ryer. 2010. Unpubl. data. Alaska Fisheries Science Center, 2030 S. Marine Science Dr., Bldg. RSF951, Newport, OR 97365-5296. trolled laboratory experiments that manipulate these parameters. Whether juvenile Tanner crabs use habitats that are distinct from those occupied by adults remains unclear. The arguments presented here make the case that juveniles would fare better in shallow waters (depths <50 m). Further, we encountered few individ- uals larger than the C7 molt stage (carapace widths of 20-26 mm), indicating that crabs older than 2 or 3 years of age are found in different, perhaps, deep- er habitats. In Glacier Bay, Alaska, Tanner crabs are segregated by ontogenetic stage; smaller, or juvenile, crabs are located at the heads of fjords, near glaciers, and adult, or larger crabs are more centrally locat- ed in fjords and in inlet areas (Nielsen et al., 2007). However, this segregation did not appear to be depth related, and the authors speculated that cannibalism, competition, predation, or differences in substrate preferences might be responsible. In Cook Inlet, Alas- ka, large individuals were found throughout the inlet, whereas juveniles with carapace widths <20 mm were concentrated in the inlet mouth at generally greater depths (Paul, 1982). This diversity of results indicates that the factors that control the distribution of age-0 crabs can vary between areas. Although we do not yet know the full range of depths and habitats used by age-0 Tanner crabs, the settlement densities and patterns documented in this work indicate that relatively shallow waters ( <50 m) may constitute an important habitat for Tanner crabs around Kodiak Island, particularly because tempera- tures in these shallow waters can be expected to speed growth and shorten the number of years before crabs recruit to the fishable or reproductive population. Acknowledgments We thank M. Ottmar, S. Haines, and C. Sweitzer for as- sistance with logistics. R. Foy, E. Munk, P. Cummiski, and K. Swiney provided logistical support in Kodiak. We also wish to thank the captain of the FV Miss-O, T. Tripp, for valuable assistance on the water. Two anony- mous reviewers provided helpful comments on an early draft of this manuscript. This work was supported by 2010 and 2011 Essential Fish Habitat funds from the NOAA Alaska Fisheries Science Center. Literature cited Baker, R., and M. Sheaves. 2007. Shallow-water refuge paradigm: conflicting evi- dence from tethering experiments in a tropical estu- ary. Mar. Ecol. Prog. Ser. 349:13-22. Conover, W. J. 1971. Practical nonparametric statistics, 462 p. John Wiley & Sons, Inc., New York. Copeman, L. A., and B. J. Laurel. 2010. Experimental evidence of fatty acid limited growth 268 Fishery Bulletin 113(3) and survival in Pacific cod larvae. Mar. Ecol. Prog. Ser. 412:259-272. Copeman, L. A, A. W. Stoner, M. L. Ottmar, B. Daly, C. C. Par- rish, and G. L. Eckert. 2012. 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[Available at http:// www.adfg.alaska.gov/FedAidPDFs/sp05-09.pdf] Yamashita, Y., M. Tanaka, and J. M. Miller. 2001. Ecophysiology of juvenile flatfish in nursery grounds. J. Sea. Res. 45:205-218. 270 NOAA National Marine Fisheries Service Abstract— In the Aleutian Islands, patterns of distribution and abun- dance of Pacific ocean perch ( Se - bastes alutus ) are influenced by oceanographic processes and bio- genic structures. We used general- ized additive modeling (GAM) to ex- amine relationships between these predictors and patterns of settled juvenile and adult distribution and abundance from bottom trawl sur- veys conducted from 1997 through 2010. Depth, temperature, and loca- tion had the greatest influence, and biogenic structures co-occurring with this species improved predictions. Model results confirmed previously reported depth- and temperature- dependent patterns of Pacific ocean perch and revealed the elevated presence and abundance of this fish in proximity to Aleutian pass- es. Adults were more common and abundant in deeper (-225 m) water than were juveniles (-150 m), and the probability of encountering ei- ther life stage increased in the pres- ence of fan- and ball-shaped sponges over moderate slopes and decreased with increasing tidal velocities. The GAMs accounted for one-quarter of the deviance for juvenile presence- absence (24.9%) and conditional abundance (25.0%) and accounted for 38.7% and 42.5% of the deviance for the same adult response variables. Although depth, temperature, and location were the dominant predictor variables of both juvenile presence and abundance, our results indicate that biogenic structures that provide vertical structure in otherwise low- relief, trawlable habitats may repre- sent refugia for Pacific ocean perch juveniles and adults. Manuscript submitted 18 August 2014. Manuscript accepted 20 April 2015. Fish. Bull. 113:270-289 (2015). Online publication date: 7 May 2015. doi: 10.7755/FB. 113.3.4. The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA. Fishery Bulletin & established 1881 «100 kg/ha) could be af- filiated with zones of increased productivity and prey availability. Other researchers have confirmed that ju- venile and adult Pacific ocean perch occur over similar temperature ranges but present different depth distri- butions ( i.e. , adults inhabit >200 m waters) (Carlson and Haight, 1976; Rooper, 2008). Epibenthic invertebrates, such as sponges, corals, and bryozoans, are common in the Aleutian Islands (Malecha et al., 2005), where they are collected regu- larly as part of the AFSC RACE Division bottom trawl surveys (Heifetz et al., 2005). Their extent and diver- sity also have been noted from submersible and un- derwater camera studies of the region (Rooper et al., 2007; Stone et al., 2011). Despite their apparent ubiq- uity in the Aleutian Islands, we presume that these attached sessile invertebrates are patchily distributed in the trawlable areas where RACE bottom trawl sur- veys are conducted. Mounting evidence indicates that the presence of sponges and corals enhances structural heterogeneity in otherwise low-relief environments and can lead to increases in biodiversity and abundance of associated animals (e.g., Tissot et al., 2006; Beazley et al., 2013; Knudby et al., 2013). The morphological fea- tures of these biogenic structures may also serve as re- fugia for different life stages of commercially harvest- ed species of Sebastes (Freese and Wing, 2003; Rooper and Boldt, 2005; Baillon et al., 2012) and Atka mack- erel ( Pleurogrammus monopterygius) (Rand and Lowe, 2011) in Alaska waters. Previous studies have also shown putative asso- ciations of rockfishes with sponge, coral, and bryozo- an assemblages across a wide range of physical and oceanographic conditions (Love et al., 1991; Rooper and Martin, 2012). Other studies have shown that rock- fishes in low-relief, trawlable habitats (e.g., sand or gravel bottom with few boulders or obstructions) tend 1 Spencer, P. D., and J. N. Ianelli. 2010. Assessment of Pacif- ic ocean perch in the Bering Sea/Aleutian Islands. In Stock Assessment and Fishery Evaluation Report for the Ground- fish Resources of the Bering Sea/Aleutian Islands Regions, p. 1033-1083. [Available from North Pacific Fishery Manage- ment Council, 605 West 4th Ave., Suite 306, Anchorage, AK 99510.] 2 Reuter, R. 2015. Personal commun. Alaska Fish. Sci. Cent., Natl. Mar. Fish. Serv., 7600 Sand Point Way NE, Seattle, WA 98115. to concentrate near the few boulders or rocky outcrops with attached epibenthic invertebrate communities (e.g., Freese and Wing, 2003; Du Preez and Tunnicliffe, 2011). The Pacific ocean perch has been the focus of several previous studies in Alaska, and there is strong evidence that postsettlement juveniles and adults of Pacific ocean perch are found associated with sponges and corals (Krieger, 1993; Brodeur, 2001; Rooper and Boldt, 2005; Rooper et al., 2007). These studies have not distinguished species of sponges, corals, or bryo- zoans because of the difficulty in providing consis- tent identifications. Our study attempts to determine whether the presence or absence of biogenic structures across the broad spectrum of environmental conditions under which they occur affects Pacific ocean perch dis- tribution and abundance. Consistent field identification of sponges to specific or even generic levels of classification is difficult with the macroscopic techniques available in the field. Add- ing to the confusion, sponge morphological features, even within a single species, can vary dramatically with environmental conditions, such as current flow and sedimentation rate (Dayton et al., 1974; Bell and Barnes, 2001; Stone et al., 2011), and sponges quickly adapt their morphology to their environment (Palum- bi, 1984). Given these challenges, categorizing sponges into groups based on their gross morphology is an at- tractive alternative. The approach of lumping sponges into groups based on body form has the advantage of eliminating confusion caused by changing and differen- tially applied systematics and gives us an intuitive link to EFH. In this study, we consider sponge morphology from a functional perspective (the “fish-eye view”) of the structure it provides in the habitat. An added ben- efit of grouping the sponges by this functional morphol- ogy is to foster comparability of sponge assemblages among survey years by downplaying the differences in identification attributable to differing levels of exper- tise among the field biologists. Sponges and corals are vulnerable to removal or damage by fishing gear (Engel and Kvitek, 1998; Freese et al., 1999; Freese, 2001; Wassenberg et al., 2002; Stone et al., 2011). In addition, these sessile inverte- brates are long lived and have limited larval dispersal and reproductive potential (Andrews et al., 2002). As a result, a disturbance resulting in 67% mortality of sponges or corals would require 20-34 years for these organisms to recover 80% of their predisturbance bio- mass (Rooper et al., 2011). Their ecological importance, their vulnerability to damage or removal due to human activities, and their prolonged postdisturbance recov- ery times have led to the designation of some areas of notable coral and sponge diversity in the Aleutian Islands as “habitat areas of particular concern” under the Magnuson-Stevens Act and to their subsequent clo- sure to fishing (Hourigan, 2009). Gaining greater un- derstanding of the role that biogenic structures play in the distribution and abundance patterns of Pacific ocean perch in the broader context of the oceanograph- ic habitats where they co-occur could prove valuable to 272 Fishery Bulletin 1 13(3) the ecosystem-based management of this commercially harvested fish. The primary objective of this study was to describe the distribution and abundance of Pacific ocean perch in relation to physical and biological oceanographic factors across this species’ range, on the basis of data from bottom trawl surveys conducted periodically in the Aleutian Islands during the summer. We postulate that biogenic structures (sponges, corals, and bryozo- ans) can modify Pacific ocean perch distribution and abundance across gradients of environmental and physical conditions by providing additional structural heterogeneity in trawlable habitats where we sample. We used generalized additive modeling (GAM) to iden- tify the physical and biological oceanographic predictor variables that influence the relationships between Pa- cific ocean perch distribution and abundance. We used field observations and out-group comparisons to vali- date the resulting models. Materials and methods Trawling procedures A stratified-random sampling design was used for the AFSC RACE Division Aleutian Islands bottom trawl survey of trawlable areas shallower than the depth of 500 m across the Aleutian archipelago (Fig. 1). The survey area extends on the north side of the Aleutian island chain from Unimak Pass in the east (165°W) to Stalemate Bank in the west (170°E); on the south side of this archipelago, the survey extends from Samalga Pass (170°E) to Stalemate Bank in the west. Strata are based on 4 depth intervals (1-100 m, 101-200 m, 201- 300 m, and 301-500 m) over the continental shelf and upper slope. The depth strata are further segregated by the North Pacific Fisheries Management Council’s (NPFMC) Bering Sea Aleutian Islands regulatory area (NPFMC3) into survey districts that correspond to the NPFMC subdivisions of western, central, and eastern Aleutian districts and an additional southern Bering Sea survey district that roughly corresponds to the Bogoslof district. Trawl sample allocation in each stra- tum was achieved with a modified Neyman optimum allocation sampling strategy (Cochran, 1977) to provide representative samples of fishes and invertebrates oc- curring at each sampling location within each stratum. Bottom trawl surveys were conducted according to standard protocols established in Stauffer (2004). Our goal was to land each trawl net quickly on the bot- tom in fishing configuration at a towing velocity of 1.5 m/s (3 kn) and to maintain vessel speed, with the net retaining fishing configuration and proper bottom contact for 15 min (an area of approximately 2.25 ha 3 NPFMC (North Pacific Fishery Management Council). 2014. Fishery management plan for groundfish of the Bering Sea and Aleutian Islands Management Area, 144 p. NPFMC, Anchorage, AK [Available at website.] was swept on average during each tow). Tables of stan- dard scope ratios of trawl warp in relation to bottom depth were used to reduce potential fishing power dif- ferences between the vessels used in different surveys. Date, time, and GPS-generated position were recorded throughout each tow; depth, water temperature, and time of collection also were recorded during each tow with an SBE 394 microbathythermograph (Sea-Bird Electronics, Inc., Bellevue, WA). During each tow, the vertical and horizontal trawl openings were measured with Scanmar acoustic net mensuration sensors (Scan- mar International, Point Richmond, CA). A bottom con- tact sensor was attached to the midpoint of the roller gear and was used to measure the degree of contact between the ground gear and the bottom. Trawl hauls were performed during daylight hours (i.e., between 0.5 h after sunrise and 0.5 h before sunset), and all trawl performance data were judged after completion through the use of computer-generated graphics and data summaries. For our analyses, we included only catches obtained with satisfactory trawl net perfor- mance and bottom contact and only those for which distance fished, net width, bottom depth, and water temperature were recorded. Data used to parameterize and select the best-fitting GAMs were collected during the periodic bottom trawl surveys of the Aleutian Islands used to assess Pacific ocean perch distribution and abundance. The survey completed in 2000 was the last in a series of triennial surveys. Since 2000, Aleutian Islands bottom trawl sur- veys have been conducted biennially with the exception of 2008, when insufficient funds led to the cancellation of that year’s survey effort. For the surveys undertak- en between 1997 and 2010, an average of 394 stations that met our criteria to be included in this study were sampled per year. Total station counts ranged from 355 in 2006 to 413 in 2002. Physical variables An array of physical, environmental, and spatial pre- dictor variables was used to parameterize the GAMs. At each bottom trawl survey station, start and end po- sitions of the trawl were recorded and bottom depth and temperature were measured. Kriging, a geostatisti- cal procedure that estimates a spatial surface from an array of point values, was used to calculate an index of local bottom slope at each survey station from 100-m bathymetric contour increments between 0 and 2000 m derived from ETOP02 gridded elevation data by fol- lowing the method of Rooper and Martin (2009). Tide velocity (Vt) was predicted at each sampling station for the date and time of the bottom trawl survey by us- ing tidal prediction software developed at Oregon State University (Tidal Prediction Software [OTPS], website accessed January 2010) (Egbert et ah, 1994; Egbert 4 Mention of trade names or commercial companies is for iden- tification purposes only and does not imply endorsement by the National Marine Fisheries Service, NOAA. Laman et al Correlating environmental and biogenic factors with abundance and distribution of Sebastes alutus in Alaska 273 170"W I Akutan Par* Amukta Pass Seguam Pass Islands of Four Mountains 172°E i Stalemate Bank O Stations Aleutian islands bottom trawl survey grid Buldir Pass Figure ^ Map of the survey grid and trawl stations of the Alaska Fisheries Science Center Resource Assessment and Conservation Engineering Division Aleutian Islands bottom trawl survey sampled during 1997-2010 in the (A) eastern, (B) central, and (C) western Aleutian Islands. 274 Fishery Bulletin 1 13(3) and Erofeeva, 2002). To address current-dependent catchability of the bottom trawl, predicted tidal veloc- ity was decomposed into component vectors with veloci- ties parallel or perpendicular to the ship’s direction of travel. The difference between the ship’s bearing and the direction of tidal flow (Aq) was calculated as A o~if(GT - 9S + 360°) < 360°, then(0T-d s + 360°), (1) else ( — where dy = the direction of tidal flow; and 6>s = the direction of the ship’s travel during the trawl survey. Parallel current (Cp) was then calculated as Cp~if (90° < Ah<270°, then 1 + (tan(AH(r))) (2) else Vt ' l + (hxn(A0(r))) where Ae(r) = the angular difference between the direc- tion of tide flow and ship’s travel. Note that Cp carries a negative sign if it is opposite the ship’s direction of travel. Because the speed of water flowing through the mouth of the trawl is an impor- tant factor that could affect the catch efficiency of the bottom trawl, we estimated trawl velocity at the net mouth (iVg) as Ns~v$ - Cp, (3) where vq = the ship’s velocity. Finally, cross current (Cx) can be estimated as Cx~Cptan(Au(r)). (4) Its absolute value ( | Cx | ) was included in the model. Invertebrate data The precision of sponge identification by scientists during the Aleutian Islands bottom trawl surveys has varied over time and remains challenging (Stone et ah, 2011). We chose to examine the Aleutian Islands surveys between 1997 and 2010 because, with the advent of waterproof invertebrate field guides for use on deck in 1996 (Kessler5), 1997 (Clark6), 1999 (Clark7), and 2006 (Clark8), our ability to consis- tently identify sponges and other invertebrates to high- er taxonomic levels in the field was enhanced. As AFSC field biologists have become more familiar with these identification tools, the number of sponge taxa reported from the Aleutian Islands bottom trawl survey has also increased, rising from 7 in 1994 to around 70 in 2006 and 2010. Recently, Stone et al. (2011) recognized 125 unique sponge taxa from the Central Aleutian Islands and indicated that there were likely many more species yet to be described from this region. Sponges were identified on Aleutian Islands bottom trawl surveys to the lowest possible taxonomic level on the basis of the existing field guides, but identifica- tions depended on the identifier’s expertise as well as on the minimum level of identification required that year, both of which varied within and between survey years. The uncertainty in our taxonomic identifications of sponges coupled with our primary aim of considering their contribution to structural heterogeneity in the environment led us to employ Bell and Barnes’ (2000) method of grouping sponges by body form into morpho- logical groups (i.e., morphogroups). By combining this technique with a modified version of the list of macro- scopical features in Boury-Esnault and Rtitzler’s (1997) thesaurus of sponge morphology, we created 15 mor- phogroups representing local Aleutian sponge fauna (Fig. 2) and assigned field identified sponges to these groups ex post facto. A group composed of identifiable sponges that did not fit into 1 of the 15 morphogroups (e.g., Plakina tanaga ) and unidentifiable fragments of sponges were assigned to a general category entitled “Porifera unidentified.” Corals and bryozoans are epibenthic invertebrates that also provide biogenic structure, which may serve as habitat resources for Pacific ocean perch in this part of their range (Rooper and Boldt, 2005; Rooper et ah, 2007; Boldt and Rooper, 2009). To allow comparison with these and similar studies (e.g., Rooper and Mar- tin, 2012), we grouped the coral and bryozoan taxa into single presence-absence composite “corals” and “bryo- zoans” factors, respectively. Wing and Barnard (2004) included 105 coral species from Alaska waters in their revised field guide. Heifetz et al. (2005) documented 69 taxa of corals in the Aleutian Islands; 25 of them were endemic to the region. For this study, the composite corals factor was composed of members of the orders Alcyonacea, Anthoathecata, Antipatharia, and Sclerac- tinia. From these orders, 99 unique taxa were reported from our catches during the Aleutian Islands bottom trawl surveys conducted between 1997 and 2010. The 5 Kessler, D. W. 1996. Alaska’s saltwater fishes and other sea life. Unpubl. manuscript. Revision by staff of the Alas- ka Fish. Sci. Cent. Resource Assessment and Conservation Engineering (RACE) Division (for use at sea) of Kessler, D. W. 1985. Alaska’s saltwater fishes and other sea life, 358 p. Alaska Northwest Publishing Co., Anchorage, AK. 6 Clark, R. N. 1997. Invertebrates of the Aleutian Islands, 169 p. Unpubl. manuscript. Alaska Fish. Sci. Cent., Natl. Mar. Fish. Serv., 7600 Sand Point Way NE, Seattle WA 98115. 7 Clark , R. N. 1999. Gulf of Alaska invertebrates, 100-1000 m, 179 p. Unpubl. manuscript. Alaska Fish. Sci. Cent., Natl. Mar. Fish. Serv., 7600 Sand Point Way NE, Seattle WA 98115. 8 Clark, R. N. 2006. Field guide to the benthic marine inver- tebrates of Alaska’s shelf and upper slope taken by NOAA7 NMFS/AFSC/RACE Division trawl surveys, 305 p. Unpubl. manuscript. Alaska Fish. Sci. Cent., Natl. Mar. Fish. Serv., 7600 Sand Point Way NE, Seattle WA 98115. Laman et al . : Correlating environmental and biogenic factors with abundance and distribution of Sebastes alutus in Alaska 275 Figure 2 Nominal morphogroups assigned to field identified sponges on the basis of mor- photypes from Boury-Esnault and Rtitzler (1997) and Bell and Barnes (2000): (A) arborescent, (B) clavate, (C) encrusting, (D) flabellate, (E) flagelliform, (F) globular, (G) globular-papillate (e.g., Weberella bursa , an image of which rep- resents this morphogroup in this figure), (H) massive (e.g., Halichondria spp.), (I) ovate, (J) papillate, (K) pedunculate, (L) repent, (M) stipitate, (N) tubular, and (O) vase. (P) The Porifera unidentified group is represented by an identifi- able sponge (e.g., Plakina tanaga ) that did not fit in to the predetermined mor- phogroups. Globular-papillate and vase morphogroups are modified from those of Boury-Esnault and Rutzler (1997) to incorporate local faunal variants; for example, the vase morphogroup is a composite of the turbinate, caliculate, and infundibuliform morphotypes from Boury-Esnault and Rutzler (1997). majority of these taxa (85) are primnoids, gorgonians, stony cor- als, and octocorals, all of which provide vertical relief over the trawlable habitats we sampled, and a few are among the tall- est biogenic structures that oc- cur in the Aleutian Islands (e.g., Primnoa willeyi can reach 3 m in height). Similarly, we included all bryozoans reported from our Aleutian Islands bottom trawl catches (~25 taxa) as a compos- ite predictor variable because of the biogenic structure they may provide. Our standard trawl net with its rubber bobbin roller gear (Stauffer, 2004) is not optimized for collecting attached epiben- thic invertebrates. Therefore, all of the biogenic structures used to parameterize our models were coded as presence or absence be- fore analyses. We also considered that trawl nets sampled sponges differentially (see Wassenberg et al., 2002), integrating their ac- tual distribution over trawlable bottom for the duration of the trawl haul. Therefore, we consid- er the coding of biogenic struc- tures in our trawl catches as presence-absence factors to be a conservative measure of their occurrence. Fish data Catch per unit of effort (CPUE) was measured in kilograms per hectare and calculated for ju- venile and adult Pacific ocean perch with the area-swept meth- od (Wakabayashi et al., 1985). Length composition, estimated for each trawl by measuring a selected subset of up to 200 fork lengths (FL) of Pacific ocean perch from the catch, was used to proportionally allocate the catch of Pacific ocean perch on the basis of length at first matu- rity (Paraketsov, 1963; Chikuni, 1975) into juveniles (FL<250 mm) and adults (FL>250 mm) for each trawl tow. Nonzero CPUE values (conditional abun- dance) were log-transformed and then placed on a common propor- 276 Fishery Bulletin 1 13(3) Table 1 Independent variables that parameterized the general- ized additive models used to predict presence, absence, and abundance of Pacific ocean perch ( Sebastes alutus). Sponge morphogroups were coded as presence-absence factors (1 or 0, respectively), and the units for continu- ous variables are temperature (°C), depth (m), local slope (°), and for velocity measures (cm/s). Note that Sp is a composite term substituted for all sponge morpho- groups and U during model formulation. Factors Continuous variables A=arborescent T=temperature C=clavate D=depth E=encrusting Sl=local slope F=flabellate Long.=longitude Fl=flagelliform Cx=cross current G=globular /Vs=trawl velocity Gp =globular-papillate M=massive 0=ovate P=papillate Pe=pedunculate R=repent S=stipitate Tu=tubular V=vase U=Porifera unidentified Sp=all sponges, composite Co=all corals, composite Br=all bryozoans, composite Vr=tide velocity tional scale by dividing individual CPUE estimates by the sum of the annual CPUE within each cruise year; by design, this approach ignored interannual differenc- es in Pacific ocean perch abundance in favor of allow- ing interannual comparisons during model validation. Modeling Pacific ocean perch distribution and abundance were modeled with the nonparametric regression technique of GAMs (Hastie and Tibshirani, 1986) in R statistical software, vers. 2.13.1 (R Core Development Team, 2011) and the mgcv package (Wood, 2006). This fish species is patchily distributed across our survey area and, typi- cal of field collected data, presents a greater proportion of zero catches than would be expected from a Pois- son distribution, resulting in abundance data that are overdispersed (McCullagh and Nelder, 1989). To model these zero-inflated catch data, we followed the recom- mendation of Barry and Welsh (2002) and undertook independent GAM selection for the Pacific ocean perch presence-absence and conditional abundance data sets. The presence-absence GAMs used a binomial distribu- tion with a logit link function; the conditional abun- dance models employed a Gaussian distribution with an identity link function. Probability of presence and conditional abundance of Pacific ocean perch was predicted from GAMs pa- rameterized with a variety of physical, environmental, spatial, and biogenic variables (for a list of these vari- ables and their abbreviations, see Table 1). To reduce the tendency of GAMs to over-fit data, we constrained the degrees of freedom (dP for some of the smoothed continuous terms in the models (i.e., df=4 for local slope [SI], Up Cx, and Ns\ df=10 for depth and temperature combined [D,T]). To identify interdependencies amongst continuous predictor variables we examined Pearson’s correlation coefficient (r; Krebs, 1989) for all pairwise comparisons and determined that only depth and tem- perature were moderately correlated ( | ?' | =0.55). Con- sequently, we combined depth and temperature into a bivariate interaction term in the GAM. To determine interdependency of sponge morph, bryozoan, and coral presence-absence factors, we computed Pearson’s coef- ficient of mean square contingency (O; Zar, 1984), found that for all pairwise comparisons |0| was <0.50, and consequently included each biogenic presence-absence factor as an independent predictor in the GAM. Four candidate models for the prediction of presence or conditional abundance of juvenile and adult Pacific ocean perch underwent backward stepwise term selec- tion (Weinberg and Kotwicki, 2008; Zuur et al., 2009). The 4 initial model formulations for both of those re- sponse variables were -A + C + E + F + FI + G + Gp + M + 0 + Pe + R + S + Tu+V+U + Co + Br + (1) s(Long.) +s(Sl) + s(Nq) + s(C-g) + s(D,T), -A + C + E + F + FI + G + Gp+M + 0 + P + Pe + R + S + Tu + V + U + Co + Br + (2) s(Long.) + s(Sl) + s (Vy) + s(D,T), ~ Sp + Co + Br + s(Long.) + s(Sl) + s(N$) + s(CJ + s(D,T), ~ Sp + Co + Br + s(Long.) + s(Sl) + ^ s(V^) + s(D,T). Formulations 1 and 2 contained the full suite of 18 presence-absence factors for biogenic structures (15 sponge morphogroups [for abbreviations of these fac- tors, see Table 1] and 1 term each for Porifera uniden- tified [U], all corals, composite [Co], and all bryozoans, composite [Br]) as well as the smooth terms longitude (Long.), SI, and D,T. These model formulations differed by using either (1) the 2 smoothed vector components of Vt (Cx and Wg) or 2) simply smoothed Vt- Formu- lations 3 and 4 used a reduced predictor variable set by combining all sponges into a single presence-ab- sence term (Sp) and then testing both suites of smooth terms as applied in formulations 1 and 2. Backward stepwise term selection involved fitting each of the 4 formulations above independently with a GAM and then removing the least significant terms iteratively until only significant predictor terms remained. Signifi- cance for all models and statistical tests was inferred Laman et al.: Correlating environmental and biogenic factors with abundance and distribution of Sebastes alutus in Alaska 277 Table 2 Prevalence of biogenic structures, measured as percent frequency of occur- rence in trawl tows per annum, in catches of bottom trawl surveys conducted in the Aleutian Islands between 1997 and 2010. Substratum Survey year 1997 2000 2002 2004 2006 2010 Porifera unidentified 63 78 74 78 78 77 Corals 48 51 52 49 50 55 Globular-papillate 43 52 47 46 43 55 Globular 43 39 44 39 37 36 Flabellate 35 37 39 34 34 47 Arborescent 27 41 34 25 32 35 Massive 29 30 25 28 33 38 Papillate 21 30 24 24 37 28 Bryozoans 23 32 14 15 13 24 Vase 12 14 16 18 14 20 Ovate 10 4 10 13 6 14 Repent 0 0 0 4 7 10 Tubular 0 0 2 4 3 4 Encrusting 0 2 2 4 0 2 Clavate 1 2 1 0 2 0 Flagelliform 0 0 1 1 1 0 Stipitate 0 0 0 0 2 1 Pedunculate <1 0 <1 0 0 0 from P<0.05. The best-fitting GAMs among the 4 starting models that predicted juvenile or adult presence or abundance were selected on the basis of the lowest Akaike’s infor- mation criterion scores. Predicted presence of juvenile and adult Pacific ocean perch, based on the GAMs formulated with data from the period 1997-2010, was validated by comparison with ob- served presence of this species from the 2012 Aleutian Islands bottom trawl survey. Comparisons were made with Cohen’s kappa coeffi- cient ( k ; Manel et al., 2001), which measures the proportion of correct- ly predicted cases of presence or absence after accounting for chance effects. This coefficient ranges from 0 to 1, corresponding with poor to near perfect agreement (Landis and Koch, 1977). For conditional CPUE models, we used a form of jack-knifing, it- eratively leaving out a single year of data, to internally validate the GAM. Residual deviance from each iteration of this cross-validation was used to compute a pseudocoefficient of determi- nation (r2; O’Brien and Rago, 1996) that was used to measure model fit. The residual deviance (RD) is the deviance remaining in the data that is unexplained by the full model (i.e. , RD=l-r2). By iteratively dropping terms retained in the best-fitting GAM and recalculat- ing r2, we were able to assess the relative contribution of that term to the deviance explained by the model, thereby estimating its leverage in the GAM. Results Summary of biological collections Between 1997 and 2010, 6 summer bottom trawl sur- veys were conducted in the Aleutian Islands by AFSC, resulting in a total of 2364 stations included in this study. The Pacific ocean perch was consistently ranked amongst the most abundant fish species collected on these surveys and commonly occurred in the survey catches; they were caught in 58% of the standard sur- vey tows. Of the trawl catches, 23% contained juvenile Pacific ocean perch and 53% contained adults. Juve- niles co-occurred with adults in about one-third of the trawl catches (34%), and the majority of trawl catches with juveniles also contained adults (79%). Sponges and corals were common in hauls of the Aleutian Is- lands bottom trawl surveys as well; they occurred in about 87% of the trawl catches. Sponges were the most commonly occurring struc- ture-forming invertebrate collected in our surveys be- tween 1997 and 2010, followed by corals and bryozoans. The majority of the trawl tows selected for analyses contained sponges and corals, which were also present in most of the catches containing Pacific ocean perch (about 91%). The composite corals group occurred in just over half (51%) of the tows in all survey years. Of catches containing juvenile Pacific ocean perch, 96% also collected sponges or corals, but the rate of co-oc- currence for adults was lower (90%). Bryozoans were less common in our catches than were sponges or cor- als, occurring, on average, in about 20% of the trawl hauls. They were also less common in hauls that con- tained Pacific ocean perch juveniles or adults, occurring in about 20% of these hauls. “Porifera unidentified” was the most common sponge category occurring in our survey tows each year (Table 2). Globular (G) and globular-papillate (Gp) sponges oc- cur at similar or slightly elevated rates compared with some of the larger morphotypes (e.g., arborescent [A], flabellate [F], and massive [M] ). Clavate (C), encrusting (E), and tubular (Tu) sponges were less common, and pedunculate (Pe) sponges were the rarest morphotype collected. Summary of environmental and physical data Bottom trawl hauls included in this study were con- ducted over a wide variety of physical and oceanograph- ic conditions. The deepest trawl hauls during the study period were conducted at 488 m and the shallowest at 278 Fishery Bulletin 113(3) Table 3 Backward stepwise term selection used in identification of the best-fitting generalized additive models (GAM) for predicting distribution and abundance of Pacific ocean perch ( Sebastes alutus ) on the basis of data from bottom trawl surveys conducted in the Aleutian Islands during 1997-2010, including the percent contribution of each predictor variable to the deviance explained by the best-fitting model and Akaike’s information criterion score (AIC). An asterisk (*) indicates the best-fitting GAM formulation. See Materials and methods section for initial model formulations and Table 1 for definitions of variable abbreviations. CPUE=catch per unit of effort. Initial Contribution by Deviance Response model Independent each variable explained Life stage variable formulation variables retained (%) (%) AIC Juvenile Presence- 1 F+G+Gp+M+U+Co+Br+ absence factor 2 s(Log.n)+s(Sl)+s(D,T)+s( C '%) F+G+Gp+M+U+Co+Br 24.9 1971.77 +s(Long.)+s(Sl)+s(D, T)+s(V t) 2.7;3.1;0.9;0.6;3.0;1.0; 1.1; 12.3;2.1;40.9;1.7 25.0 1970.10* 3 Sp+Co+s(Long.)+s(Sl)+s(D,T)+s(Cx) 20.7 2070.22 4 Sp+Co+s(Long.)+s(Sl)+s(D,T)+s(V t/ 20.9 2068.65 Juvenile Conditional 1 and 2 C+0+V+s(Log.n)+s(D,T) 3.3;5.5;4.3;41.7;26.8 24.9 2358.05* CPUE 3 and 4 s(Long.)+s(D,T) 22.0 2372.99 Adult Presence- 1 F+G+U+Br+s(Long.)+s(Sl)+s(D,T)+ absence factor 2 s(Ng) F+G+U+B7'+s(Long.)+s(Sl)+ s(D,T)+s(Vr) 1.4;0.4;0.8;0.9;6.6;1.8; 38.6 2054.45 68.8;0.9 38.7 2050.85* 3 Sp+Co+Br+s(Long.)+s(Sl)+s(D,T) 37.7 2079.74 4 Sp+Co+Br+s(Long.)+s(Sl)+s(D,T)+ s(VT) 38.0 2073.70 Adult Conditional 1 and 2 G+Co+s(Long.)+s(Sl)+s(D,T) 1.4;0.7;14.2;1.4;84.0 42.5 5692.83* CPUE 3 and 4 Br+s(Lon)+s(Sl)+s(D,T) 42.0 5702.49 32 m. Many of the deeper stations are near passes be- tween islands in the Aleutian archipelago, but, in gen- eral, deeper stations occur more frequently in the east- ern part of the survey area (around Samalga, Amukta, and Seguam passes) than in the west. The values for SI from the kriged bathymetry at trawl stations ranged from 0° to 15°. Tidal currents predicted at each bottom trawl haul from the tidal prediction model ranged from <1 cm/s to ~ 300 cm/s (around 3 m/s or 6 kn). The high- est current velocities were predicted around Seguam and Amukta passes, and some additional areas of high current were predicted on the east side of Amchitka Pass. Bottom temperatures (T) measured in situ during trawl hauls ranged from 3°C to 7°C. Results of generalized additive modeling Prediction of presence and absence The best-fitting GAMs for predicting the probability of presence of ju- venile and adult Pacific ocean perch in the Aleutian Islands accounted for a quarter of the deviance in the juvenile model and 38.7% of the deviance in the adult model (Table 3). The depth distribution of adults, cen- tered around 225 m, was deeper than that of juveniles, found at depths around 150 m. Model effects showed very little dependence on temperature (Figs. 3 and 4). Model responses (GAM effects represented by the solid lines on graphs) indicate increased probability of encountering Pacific ocean perch life stages when >0 and decreased probability when <0. The standard error generally increases around the predictions for which sample size decreases, signifying areas of lower confi- dence in the model. Geographically, the predicted odds of collecting either life stage increased at Unimak Pass (165°W), in the passes near the Islands of Four Moun- tains (170°W), in Amukta and Buldir passes (173°W and 177°E), and in Near Strait (175°E; Figs. 5 and 6). Effects due to local slope were similar for both juve- niles and adults and the probabilities of encountering either life stage increased over moderate slopes up to around 5° of incline. Increasing tidal velocities initially led to increased probability of encountering adults, but the probability of encounter for juveniles steadily decreased with in- creasing velocities. The presence of biogenic structures accounted for more of the deviance explained in the juvenile presence-absence model than with the adult model (11.3% versus 2.6%; Table 3). The biogenic struc- Laman et al.: Correlating environmental and biogenic factors with abundance and distribution of Sebastes alutus in Alaska 279 Longitude Slope o CD it CD < 0 Figure 3 From the best-fitting generalized additive model (GAM), predictions of presence of juvenile Pacific ocean perch ( Sebastes alutus ) at trawl stations in the Aleutian Islands during 1997-2010 in relation to (A) longi- tude, (B) kriged bottom slope, (C) predicted tidal current velocity, and (D) the interaction between depth and temperature. A change in number orientation indicates that either a maximum or a minimum was reached for the GAM effect. tures retained in the models were either erect forms (e.g., F or Co) or have been reported to be epizoic on erect sponges (e.g., G and Gp sponges; Stone et ah, 2011). Although the presence of certain sponge morpho- groups and Co was associated with increasing probabil- ity of encountering juveniles and adults, the presence of Br was associated with decreasing probability of en- countering either life stage of Pacific ocean perch. This decrease may result from the shallower depth distribu- tion of Br (depths <110 m) compared with the depth distribution of Pacific ocean perch juveniles (depths -150 m) and adults (depths -225 m). More than half of the deviance explained in each presence-absence GAM was attributable to the D,T and Long, terms. Validation of presence-absence generalized additive mod- eling The success of the GAMs to predict Pacific ocean perch distribution (presence) varied with life stage (Figs. 5 and 6). Based on the scale proposed by Lan- dis and Koch (1977) for assessing model performance, the GAM predictions of presence of juvenile Pacific ocean perch from 2012 survey data displayed moder- ate agreement with trawl observations from the same year (£=0.52). GAM predictions of adult presence were more accurate, showing substantial agreement when predicted presence or absence of adults was compared with observed adult distribution for 2012 (£=0.70). Prediction of conditional abundance More deviance in the model was explained by the best-fitting condition- al abundance GAM for adults than by the best-fitting GAM for juveniles (Table 3). As with the presence-ab- sence GAMs, the D,T and Long, terms were the most influential predictors of conditional abundance. Unlike the results from the presence-absence GAMs, there were temperature-related optima in both the juvenile 280 Fishery Bulletin 113(3) o 0) 3= 0) < CD 2 1 0 -1 -2 -3 -4 ■jJU MUB HUB 1 1 III M— i Bill I 1 MB | 170 E 175 E 180 175W170W165W Longitude Slope o 0) 3= d) < CD Current (cm/s) Figure 4 From the best-fitting generalized additive model (GAM), predictions of presence of adult Pacific ocean perch ( Sebastes alutus) at trawl stations in the Aleutian Islands during 1997—2010 in relation to (A) lon- gitude, (B) kriged bottom slope, (C) predicted tidal current velocity, and (D) the interaction between depth and temperature. A change in number orientation indicates that either a maximum or a minimum was reached for the GAM effect. and adult conditional abundance GAMs (Figs. 7 and 8). Similar D,T-dependent optima were observed for ju- venile and adult Pacific ocean perch abundance where present, and predicted conditional abundance was highest over depths of 200-250 m and a temperature range of 4.5-5.0°C. As with the predictions of increased probability of occurrence from the presence-absence GAMs, some of the highest predicted conditional abun- dances for either life stage are associated with major Aleutian passes. Higher abundances were predicted around Buldir Pass (176°E) and Seguam Pass (173°W), and some decreased abundances were predicted around the Islands of Four Mountains (170°W). Predicted adult conditional abundance increased with increasing SI, up to an incline of around 5°, but SI was not a predictor retained in the juvenile conditional abundance GAM. Fewer biogenic structures were retained in the best- fitting conditional abundance GAMs, than in the pres- ence-absence GAMs, but the relative contribution of these predictors to the deviance explained in the model was similar within each life stage (Table 3). The com- bined deviance explained by the presence or absence of biogenic structures remained a more important propor- tional contributor to the total deviance explained in the juvenile conditional abundance GAM than in the adult GAM (13.1% versus 2.1%). When sponges of the C and V morphogroups were present, the predicted juvenile conditional abundance was higher, but the presence of sponges of the ovate [O] morphogroup was associated with a decrease in the abundance of juveniles where present. For adults, conditional abundance increased in the presence of Co and decreased in the presence of sponges of the G morphogroup. Validation of conditional abundance generalized additive modeling By cross-validating our GAM predictions it- Laman et al.: Correlating environmental and biogenic factors with abundance and distribution of Sebastes alutus in Alaska 281 Unimak Pass Islands of Four Mountains Akutan Pass B -r - 0Sk + - 176°W 174°W k Amchitka Pass f + - + + + 170‘E 172"E 174”E 176”E 178”E Figure 5 Observed (symbols) and predicted (shaded) presence or absence of juvenile Pacific ocean perch ( Sebastes alutus) over an inverse distance-weighted surface from a generalized additive model based on Aleutian Islands bottom trawl surveys con- ducted during 1997-2010 across the (A) eastern, (B) central, and (C) western Aleutian Islands. 282 Fishery Bulletin 1 13(3) 172°W L_ Seguam Pass 172°E i 174°E L™ 178°E L Stalemate Bank Probability o-o.i ] 0. 1-0.2 ] 0.2-0. 3 ] 0. 3-0.4 ] 0.4-0. 5 ] 0.5-0. 6 1 0.6-0. 7 0.7-0. 8 0.8-0. 9 0.9-1 % - Absent + Present Near Strait ' f4 f. Buidir Pass * j£+*i**> > Figure 6 Observed (symbols) and predicted (shaded) presence or absence of adult Pacific ocean perch ( Sebastes alutus ) over an inverse distance-weighted surface from a generalized additive model based on Aleutian Islands bottom trawl surveys conducted during 1997-2010 across the (A) eastern, (B) central, and (C) western Aleutian Islands. Laman et al Correlating environmental and biogenic factors with abundance and distribution of Sebastes alutus in Alaska 283 eratively against excluded years, we showed that the conditional abundance GAMs did a fair job of predicting juvenile Pacific ocean perch abundance and a better job for adults than for juveniles. The deviance explained in each of the jack-knifed cross-validations ranged from 23.2% to 28.5% for juveniles and from 41.4% to 44.8% for adults. Examination of diagnostic plots and residu- als indicated that model assumptions were met. Discussion Depth, temperature, and proximity to major Aleu- tian passes (D,T and Long., respectively) were domi- nant influences in our GAMs ( i.e. , accounted for the greatest proportion of the deviance explained) and op- erated over broad spatial scales. These effects compared favorably with similar findings of other researchers by confirming the depth distributions and temperature af- filiations of Pacific ocean perch life stages (Carlson and Haight, 1976; Brodeur, 2001; Love et al., 2002; Rooper and Boldt, 2005; Rooper 2008). The GAMs predicted in- creases of occurrence and abundance of Pacific ocean perch in proximity to most major Aleutian passes (e.g., Amukta, Seguam, and Buldir) that were similar to findings by Logerwell et al. (2005). We also determined that the inclusion of predictors that act over more local scales (e.g., biogenic structures and slope of the bottom at a sampling station) can improve the GAM fit and enhance our understanding of Pacific ocean perch dis- tribution and abundance patterns within the context of broader scale oceanographic processes. Logerwell et al. (2005) concluded that patterns of demersal fish distribution and abundance could reflect proximity to biological “hot spots,” where prey aggre- gations form and productivity increases because of the convergence of bathymetric and hydrographic pro- cesses, such as those observed near Aleutian passes. There is substantial tidal mixing in the passes (Ladd et al., 2005), and the dominant flow of water through them is from the south to the north (Stabeno et ah, 1999). The tidal mixing, the persistent northward wa- ter movement, and the interaction of mixed water with the euphotic zone near these passes often create local 284 Fishery Bulletin 1 13(3) Longitude Slope Figure 8 From the best-fitting generalized additive model (GAM), predictions of conditional abundance (scaled, normalized CPUE where present) of adult Pacific ocean perch ( Sebastes alutus ) at trawl stations in the Aleutian Islands during 1997-2010 in relation to (A) longitude, (B) kriged bottom slope, and (C) the inter- action between depth and temperature. A change in number orientation indicates that either a maximum or a minimum was reached for the GAM effect. regions of high production, especially to the north of the passes (Ladd et ah, 2005). In addition, upwelling can occur around passes and may enhance local pro- duction (Swift and Aagaard, 1976; Coyle, 2005), lead- ing to potentially greater abundance of the zooplankton prey of Pacific ocean perch (Carlson and Haight, 1976; Brodeur, 1983; Boldt and Rooper, 2009). Southward cur- rents that flow through Aleutian passes typically flow down the western side of the pass, whereas northward flow occurs on the eastern side (Stabeno et ah, 2005). Because the dominant current along the south side of the Aleutian chain is to the west and the dominant current along the north side is to the east, larval re- tention zones could exist near passes (Stockhausen and Hermann, 2007). Genetic studies of Pacific ocean perch in other areas have indicated that stock structure on a small scale (70-400 km) may occur and could be the result of limited dispersal of early life stages (Seeb and Gunderson, 1988; Withler et al., 2001; Palof et ah, 2011). The possibility for high productivity and larval retention around Aleutian passes, combined with the potential natural barriers to migration of Pacific ocean perch along the archipelago (e.g., predominant currents as well as deeper passes in the western Aleutian Is- lands), could further explain our results that indicate increases in presence and abundance near Aleutian passes. The structural heterogeneity created in trawlable habitats by the presence of sponges, corals, and bryo- zoans presumably provides refugia from predation and shelter from currents for juvenile Pacific ocean perch (Stoner, 1982; Ryer, 1988; Ryer et al., 2004) and re- cently has been shown to provide nursery habitat for redfish larvae ( Sebastes spp.) around sea pens (Baillon Laman et al.: Correlating environmental and biogenic factors with abundance and distribution of Sebastes alutus in Alaska 285 et al., 2013). Juvenile Pacific ocean perch have been observed in close association with sponges and corals on the bottom (Carlson and Straty, 1981; Rooper et al., 2007) and appear to favor more spatially heteroge- neous habitats (Du Preez and Tunnicliffe, 2011). Adult Pacific ocean perch are known to form schools on or near the seafloor (Krieger, 1993; Brodeur, 2001; Han- selman et al., 2012) where we typically collect them over areas of softer seafloor substrata, such as sand or gravel, during our surveys. Adults have been observed in association with sea whip forests (Brodeur, 2001), although they appear, on the basis of our model results, to be less benthically oriented than juveniles. The ap- parent affiliation of Pacific ocean perch with biogenic structures over trawlable habitats in the Aleutian Is- lands could potentially modify their distribution and abundance patterns on a local scale within the context of the broadly acting biological and oceanographic pro- cesses that determine larger scale patterns. All our models retained biogenic structures with morphological features capable of increasing struc- tural heterogeneity in the otherwise low-relief, traw- lable habitats, but none retained the Sp predictor, the presence-absence factor compositely representing all sponges. Most of the sponges and corals retained in our models are erect forms (e.g., V and F sponges and primnoid corals), but even the nonerect forms (e.g., G and Gp sponges) are known to be epizoic on larger, erect sponge forms (Stone et al., 2011). In pre- vious studies that showed associations of Sebastes spe- cies (Heifetz, 2002; Krieger and Wing, 2002; Du Preez and Tunnicliffe, 2011) and Pacific ocean perch (Rooper and Boldt, 2005; Rooper et al., 2007) with sponges and corals, the epibenthic invertebrates were considered composite categories. The results of our study refine our understanding of the relationship between Pacific ocean perch distribution and abundance and the struc- tural heterogeneity provided by biogenic structures from these larger composite groupings. Our results in- dicate that habitat heterogeneity, and vertical relief in particular, can affect Pacific ocean perch distribution and abundance. Although studies have indicated that the presence of structure-forming epibenthic invertebrates can lead to enhanced abundance and biodiversity of associated animals (e.g., Du Preez and Tunnicliffe, 2011; Beazley et al., 2013; Knudby et al., 2013), Tissot et al. (2006) concluded that associations of fishes with sponges and corals do not necessarily imply functional relationships between these groups of organisms. The co-occurrences between Pacific ocean perch and biogenic structures that we modeled in the Aleutian Islands may derive from facultative relationships (e.g., structural refugia and prey availability) or could simply result from a convergence of conditions that favor the presence of both the fish and epibenthic invertebrates. The under- lying mechanisms leading to the patterns observed in our study are an important area for future study. Generalized additive models relate response vari- ables to dependent model variables through additive and unrestrictive smooth functions, making them well suited for modeling typical interactions of species with environment (Hastie and Tibshirani, 1986; Maravelias, 2001; Guisan et al., 2002). The GAMs also provide a data-defined assessment of the shape of the response of a species to independent variables (Maravelias and Papaconstantinou, 2003). The anticipated nonlinear relationships of Pacific ocean perch distribution and abundance with their environment made GAMs well suited to provide a tool that was more informative than traditional regression techniques. One drawback to the use of GAMs is that they can over-fit the data, resulting in unrealistic models with limited predictive power (Kim and Gu, 2004; Wood, 2006). To minimize the risk of over-fitting, we con- strained the df available to smoothed continuous pre- dictor variables in the model and successfully validated our GAM predictions of juvenile and adult presence with a data set external to the modeling effort (i.e., the data from the 2012 Aleutian Islands trawl survey). We conclude that the GAMs parameterized in this study were fairly accurate predictors of juvenile occur- rence but were better at predicting adult occurrence. Furthermore, our validation results indicate that these models were robust predictors of the distribution and abundance of Pacific ocean perch juveniles and adults in the Aleutian Islands in subsequent years. Our approach of modeling presence and absence and conditional abundance independently is a technique intended to cope with zero-inflated and over-dispersed data and that is common to abundance surveys (Mc- Cullagh and Nelder, 1989; Barry and Welsh, 2002). Pro- cesses that influence distribution and those that affect abundance do not have to be the same. By modeling the 2 response variables independently, we were able to determine that the models for Pacific ocean perch distribution and conditional abundance shared more in common than not. For example, the best-fitting models for both life stages across both model classes all share the D,T and Long, terms in common, but for the pres- ence-absence GAMs adults and juveniles also share the SI and Vt terms. By comparison, there is no over- lap in the suite of biogenic structures retained in the juvenile presence-absence and conditional abundance GAMs, a result that may indicate that the local con- ditions leading to enhanced probability of encounter- ing juvenile Pacific ocean perch in our trawl tows are not the same as those leading to increased abundance when this species is present. There is ample evidence that rockfishes occur com- monly in areas that are untrawlable with our present net (Carlson and Haight, 1976; Zimmermann, 2003; Rooper et al., 2007; Rooper et al., 2011). Underwater camera and submersible observations indicate that some untrawlable areas are havens for biogenic struc- tures and fishes (Rooper et al., 2007; Stone et al., 2011). In some instances, catch rates for Pacific ocean perch varied with tidal velocity (i.e., juvenile and adult oc- currence). Changing catch rates could result from tidal current regimes that affect distribution and abundance 286 Fishery Bulletin 113(3) of Pacific ocean perch directly (e.g., currents that ex- ceed swimming speeds) or indirectly by impacting bio- genic structures that would otherwise provide refugia from currents (e.g., physical removal of structures in high current areas or their morphological adaptation to differing local current or sedimentation regimes). We hope to use in situ observation of current speeds and fish behavior (e.g., optical sampling) over trawlable and untrawlable bottom in the future, along with direct measurements of water velocity into the net mouth, to try and elucidate some of the potential mechanisms of this phenomenon and to improve the predictive power of these models. We were not able to account for all of the variables that may influence the distribution and abundance of Pacific ocean perch in the Aleutian Islands. Among these variables were the availability of prey and the substrate type at each bottom trawl survey station. Both of these factors are known to influence the dis- tribution and abundance of rockfishes (Carlson and Straty, 1981; Pearcy et al, 1989; Matthews, 1990; Love et al., 1991; Stein et al., 1992; Krieger and Ito, 1999; Yoklavich et al., 2000; Boldt and Rooper, 2009). Pacific ocean perch feed primarily on copepods and euphasiids both as juveniles and adults (Carlson and Haight, 1976; Brodeur, 1983; Boldt and Rooper 2009), and the success of these predator-prey interactions is concen- tration dependent and partly mediated by the avail- ability of light that enables a fish to locate its prey. Water column light (irradiance) profiles vary widely across the Aleutian Islands (senior author, unpubl. data). Fish species are known to change their behavior in response to changing ambient light levels (e.g., Ryer and Olla, 1999; Kotwicki et al., 2009). The amount and spectral range of the available light in the water col- umn may be another important component of EFH for fish with visually mediated behaviors (Sathyendranath and Platt, 1990). Incorporating irradiance and spectral quality of light as habitat parameters in future models will provide new insights into delineating fish habitats. Effective management of fish populations and fishing activities requires better knowledge of the functional relationships between fish species and their habitats. In the case of Pacific ocean perch, we have concluded from this study that the species occurs predictably within certain depth ranges, in certain areas, and that they can be associated with erect forms of sponges and corals. In the Aleutian Islands, fishing activities can af- fect benthic habitats by causing damage and mortality to sponges and corals. A number of studies have shown that recovery times for sponges and corals damaged by bottom trawling or natural phenomena could be on the order of decades to centuries (Freese et al., 1999; Andrews et al., 2002; Rooper et al., 2011). Diagnosing the relationships between commercially important fish species and biogenic structures vulnerable to damage from human activity will be useful for management decisions to balance habitat protection and commercial fishing opportunities. Acknowledgments The authors thank the captains, fishermen, and sci- entific staff who spent many hours at sea conducting these surveys. We thank D. Somerton, W. Palsson, K. Mier, J. Orr, and the anonymous reviewers for their time and effort that greatly improved this manuscript. In addition, we are indebted to M. Martin, L. Britt, and R. 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Bony fishes were the most frequently consumed prey of weakfish. Decapods, nonde- capod crustaceans, and polychaetes were the most commonly consumed prey of southern kingfish and Atlan- tic croaker. Some individuals of all species consumed specific prey types and others consumed varying prey types; however, specialization was a more common trait for weakfish than for the other 2 species. Weak- fish diets had minimal overlap with diets of the other 2 species; however, the Morisita-Horn index indicated considerable overlap between south- ern kingfish and Atlantic croaker. Potential for competition could oc- cur between these 2 species, but, because both are often opportunistic feeders, it is unlikely that competi- tion would occur unless shared re- sources become scarce. Descriptions of feeding strategies, prey resources, and the potential for competition among co-occurring species can pro- vide a framework for management of these species, particularly for ecosys- tem-based management. Manuscript submitted 3 September 2014. Manuscript accepted 1 May 2015. Fish. Bull. 113:290-301. Online publication date: 15 May 2015. doi: 10.7755/FB.113.3.5 The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA. Fishery Bulletin established 1881 Spencer F. Baird First U S. Commissioner of Fisheries and founder of Fishery Bulletin Diet composition, feeding strategy, and diet oweriap of 3 sciaenids along the southeastern United States C. Michelle Willis (contact author) Jonathan Richardson Tracey Smart Joseph Cowan Patrick Biondo Email address for contact author: willisc@dnr.sc.gov Southeast Area Monitoring and Assessment Program-South Atlantic Marine Resources Research Institute South Carolina Department of Natural Resources 217 Fort Johnson Road Charleston, South Carolina 29412 Ecosystem-based fisheries manage- ment is dependent on defining not only target species but the species and habitats with which they inter- act. Ecosystem-based management models ideally would account for the complexities of ecosystems, allowing managers to incorporate ecosystem relationships in management strat- egies and decisions (Brodziak and Link, 2002). The Magnuson-Stevens Fishery and Conservation Reau- thorization Act of 2006 (Magnuson- Stevens... Act, 2007) highlighted the need for research detailing interde- pendence among fisheries; trophic relationships can play a key role in understanding ecosystem composi- tion, status, and energy linkages within the system (Link, 2002; Mag- nuson-Stevens... Act, 2007; Ainsworth et ah, 2008). As a result, the South Atlantic Fishery Management Coun- cil (SAFMC) has prioritized efforts to characterize fish diets, define rela- tionships between predator and prey, and to better understand how these relationships affect economically im- portant species (SAFMC1). Therefore, 1 SAFMC (South Atlantic Fishery Man- the South Atlantic component of the Southeast Area Monitoring and As- sessment Program (SEAMAP-SA), as part of its Coastal Survey (a long- term, fishery-independent, shallow- water trawl survey from Cape Ca- naveral, Florida, to Cape Hatteras, North Carolina), began collecting stomachs from 3 common species of Sciaenidae: weakfish ( Cynoscion regalis ), southern kingfish ( Men- ticirrhus americanus), and Atlantic croaker ( Micropogonias undulatus). Weakfish, southern kingfish, and Atlantic croaker commonly occur along the eastern coast of the United States, residing in shallow waters over bottoms of sand or sandy mud. Distributions of these species greatly overlap, sharing a geographic range from Cape Cod, Massachusetts, to Florida and into the Gulf of Mexico (only occasionally in the Gulf of Mex- ico in the case of weakfish) (Goode, agement Council). 2009. Fishery Eco- system Plan of the South Atlantic Re- gion. Volume V: South Atlantic research programs and data needs, 177 p. South Atlantic Fishery Management Council, North Charleston, SC. [Available at website.] Willis et al.: Feeding behavior of 3 sciaemds along the southeastern United States 291 1884; Chao, 2002). In the southeastern United States, these species have a similar life history; they grow rap- idly and are capable of spawning as early as 1 year of age (Walton, 1996). Weakfish generally spawn from March through July in estuarine and nearshore waters, and juveniles use the estuary as nursery grounds. From 2008 through 2010, weakfish with an average age <1 year old and a mean of 21 cm in total length (TL) were captured in SEAMAP-SA trawl surveys, but this species reportedly lives to 8 years and can reach a length of 90 cm TL (Shepherd and Grimes, 1983; Chao, 2002). Adult weak- fish migrate seasonally between nearshore and offshore waters, and forage throughout the water column. Southern kingfish are bottom foragers that spawn on the continental shelf from April through August, live up to 6 years, and can grow to lengths of 60 cm TL (Bearden, 1963; Smith and Wenner, 1985; Chao, 2002). For southern kingfish captured by SEAMAP-SA from 2008 to 2010, the average age was 1 year and the average size was 18 cm TL. Atlantic croaker are shelf-spawners during October-January and can reach an age of 15 years and length of 46 cm TL (Hales and Reitz, 1992; Barbieri et al., 1994; Richardson and Boylan2). From 2008 to 2010, the mean age and length for specimens of Atlantic croaker collected by SEAMAP-SA were 1 year and 22 cm TL, respectively. Atlantic croaker are demersal and use their inferior- located mouth to suck prey from the substrate (Over- street and Heard, 1978). Juveniles of both southern kingfish and Atlantic croaker use estuaries as nurser- ies, a characteristic similar to weakfish (Musick and Wiley, 1972; Harding and Chittenden, 1987). Although the life history of these 3 species has been studied extensively, quantitative diet information from the southeastern United States is either lacking or was collected 2 or more decades ago. The potential for diet overlap among sciaenids with similar feeding strate- gies has not been addressed in this region to date. Mer- riner (1975) examined the diet of weakfish captured in North Carolina waters and found that penaeid and mysid shrimps, anchovies, and clupeid fishes were the most common food items. He noted a gradual onto- genetic shift from shrimp to clupeids, specifically the Atlantic thread herring (Opisthonema oglinum), begin- ning when weakfish were about 19 cm standard length (SL) and 1 year of age. McMichael and Ross (1987) analyzed the diets of southern kingfish, northern king- fish ( Menticirrhus saxatilis), and gulf kingfish ( M . lit- toralis) in the Gulf of Mexico and found that southern kingfish most frequently consume bivalve siphons and cumaceans, followed by mysids, polychaetes, brachy- urans, and gammarid amphipods. Although frequency 2 Richardson, J., and J. Boylan. 2013. Results of trawling efforts in the coastal habitat of the South Atlantic Bight, 2012. Report SEAMAP-SA-CS-2012-004, 101 p. [Available from Mar. Resour. Res. Inst., Mar. Resour. Div., South Caro- lina Dep. Natl. Resour. 217 Fort Johnson Rd., Charleston, SC 29422.] of prey items seemed to be dependent on season, prey item composition was not found to be significantly dif- ferent among species within a season in that study. A diet study of species of Menticirrhus, conducted near the Patos Lagoon in Brazil, has shown both low species diversity and seasonal differences in prey consumption, with polychaetes, amphipods, and various crustaceans being consumed most frequently (Rodrigues and Vieira, 2010). Overstreet and Heard (1978) studied Atlantic croaker diets in the Gulf of Mexico and found a high diversity of prey items, including polychaetes, mysids, blue crabs, amphipods, and penaeids, among other prey items. Each of these fish species is important both commer- cially and recreationally, and each commonly occurs as bycatch in the shrimp trawl fishery (Smith and Wenner, 1985; Murray et al., 1992; Diamond et al., 2000). In ad- dition, Atlantic croaker is harvested for use in the bait industry (Ross, 1988). Management of these species has become necessary as these industries evolve and catch levels increase. We investigated the diets of weakfish, southern king- fish, and Atlantic croaker off the southeastern United States to provide current regional information on their diets. We also assessed the overlap in prey among the 3 species and examined several factors that may influ- ence this assessment, including spatial and temporal variation in sampling. Materials and methods Field sampling Fishes were collected from 2008 to 2010 during shallow-water trawl hauls conducted as part of the SEAMAP-SA Coastal Survey by staff of the South Car- olina Department of Natural Resources. Paired 22.9- m mongoose-type Falcon3 trawl nets (Beaufort Marine Supply, Beaufort, SC), which had a net body of no. 15 twine with 4.8-cm stretch mesh and a cod end of no. 30 twine with 4.1-cm stretch mesh, were deployed from the RV Lady Lisa, a 23-m wooden-hulled, double-rigged St. Augustine Trawlers (St. Augustine Trawlers Inc., St. Augustine, FL) shrimp trawler. Trawl hauls were conducted during daylight hours at target speeds of 1.3 m/s (2.5 kn) for 20 min and at depths between 4 and 10 m (Hendrix and Boylan4). For the Coastal Survey, trawl hauls are conducted at randomly selected loca- tions within 6 regions from Cape Canaveral, Florida, to Cape Hatteras, North Carolina (Fig. 1). Regions are 3 Mention of trade names or commercial companies is for iden- tification purposes only and does not imply endorsement by the National Marine Fisheries Service, NOAA. 4 Hendrix, C., and J. Boylan. 2011. Results of trawling efforts in the coastal habitat of the South Atlantic Bight, 2010. Report SEAMAP-SA-CS-2010-004, 108 p. [Available from Mar. Resour. Res. Inst., Mar. Resour. Div., South Caro- lina Dep. Nat. Resour, 217 Fort Johnson Rd., Charleston, SC 29422.] 292 Fishery Bulletin 113(3) Map of the sampling area of the Coastal Survey of the Southeastern Monitoring and Assessment Program — South Atlantic off the south- eastern coastline of the United States, extending from Cape Canav- eral, Florida, to Cape Hatteras, North Carolina. The sampling area is divided into 6 regions: Florida (FL), Georgia (GA), South Carolina (SC), Long Bay (LB), Onslow Bay (OB), and Raleigh Bay (RB). Black circles indicate locations where 3 sciaenid fishes — weakfish (Cy- noscion regalis ), southern kingfish (Menticirrhus americanus), and At- lantic croaker (Micropogonias undulatus) — were collected from 2008 through 2010 for analysis of their stomach contents. divided further into strata based on latitude (-0.28° latitude; 2-5 strata per region). The Coastal Survey includes 3 cruises conducted each year during 3 sea- sons: spring (April-May), summer (July-August), and fall (September-November). Specimens retained for life history research (including diet analysis) were selected from the total catches at a rate of 2 repre- sentatives per size class (based on TL in centimeters) per stratum per season. Fish were kept on ice on deck until sample processing began. Total length (in milli- meters), SL (in millimeters) and total body weight (in grams) were measured, and otoliths and gonads were extracted. Stomachs, excluding the intes- tinal tract, were removed from selected specimens, wrapped in cheesecloth and labeled. Stomachs were stored in 10% neutral buffered formalin for a minimum of 14 days, after which they were rinsed with room temperature tap water several times and stored in 70% ethanol. Laboratory processing Extraneous tissue was removed from the stomach, the stomach was blotted to re- move excess liquid and emptied, and a wet weight of the contents was recorded to the nearest 0.001 g. Each prey item was identified to the lowest possible taxon that could be collapsed into 7 course prey categories: bony fishes, decapod crusta- ceans, echinoderms, mollusks, nondeca- pod crustaceans, polychaetes, and other (composed of unidentified animal tissue and rarely seen miscellaneous taxa). Identifications were made from voucher specimens, with staff assistance from the Southeastern Regional Taxonomic Center, and according to various references (e.g., Baremore and Bethea5). Small parts were sorted and counted to estimate numbers of individuals whenever possible. When prey were highly digested, key body parts, such as eyes, telsons, or otoliths, were used to make counts. When the number of individuals could not be determined (e.g., from unidentified animal tissue), a conservative count of one individual was assigned. Prey were collectively weighed by taxon to the nearest 0.001 g. Data analysis before any analyses, prey items that could not be identified and stomach contents that were incidentally ingested (e.g., sand and gravel) were removed from the data set. To provide the most conservative es- timate of overlap in diet, only stomachs from fish collected in trawl hauls that captured all 3 species were included in analyses. Co- occurrence provides the most likely possibility that shared resources were available to each species, re- gardless of whether they used them. Diet contents were grouped into the 7 prey categories, initially to reduce the number of zero observations in the data set. Data 5 Baremore, I. E., and D. M. Bethea. 2011. A guide to oto- liths from fishes of the Gulf of Mexico. Panama City Labo- ratory, NOAA Southeast Fisheries Science Center, Panama City, FL. Last modified 29 August 2011. [Available at web- site.] Willis et al.: Feeding behavior of 3 sciaenids along the southeastern United States 293 were fourth-root transformed, and cluster analysis and nonmetric multidimensional scaling were performed on the resulting Bray-Curtis dissimilarity matrix (Mc- Cune and Grace, 2002; Bozzetti and Schulz, 2004) with the packages labdsv and vegan in R software, vers. 2.15.2 (R Core Team, 2012). Predator species, region, year, and season were examined as categorical vari- ables and water depth (in meters), bottom temperature (in degrees Celsius), and salinity were examined as continuous variables by analysis of similarity. Three metrics of stomach content by prey category were calculated, as percentages, for each predator spe- cies, according to Hyslop (1980), where the total sample was defined as all prey within a given prey category: frequency of occurrence, composition by weight, and composition by number. An index of relative impor- tance (IRI) was determined by combining these met- rics to eliminate any biases created when each method is analyzed individually (Goldman and Sedberry, 2010; modified from Pinkas et ah, 1971): IRI = (N + W)xF, (1) where F = frequency of occurrence; N = composition by number; and W - composition by weight. IRI has been included only in tabular form as a meth- od of data comparison across diet studies because it is calculated by combining indices that may produce varying results and, therefore, is not necessarily the most robust representation of diet (Cortes, 1997; Hans- son, 1998). To provide a more complete picture of prey consumption by each predator, IRI is presented by year. In additional, mean percent weight and mean per- cent number were calculated for each predator accord- ing to Chipps and Garvey (2007). Prey were analyzed at the lowest possible taxon, and bootstrapping was used to generate bias-corrected 95% confidence inter- vals for both means with the package boot in R, (vers. 2.15.2). Prey were then grouped into higher prey cat- egories for the purpose of graphical presentation. Feeding strategy was determined with the method of Amundsen et al. (1996), modified from the method of Costello (1990), where prey-specific abundance (Pj) is plotted against frequency of occurrence. Expressed as a percentage, prey-specific abundance is a given prey taxon’s proportion in relation to all prey items ob- served in only those predator stomachs that contained the given prey taxon: Pi = £St x 100, (2) the feeding strategy of the predator population. Data points that cluster near the top of the y-axis indicate specialized feeding by individuals within the popula- tion. A cluster close to the origin describes infrequent consumption of a prey type (i.e., prey types that are not an important part of the predator’s diet). Data points that are scattered across the graph indicate that a population cannot be characterized as one that employs a single feeding strategy; a population may be specialized sometimes and generalized at other times. Data points clustered in the upper right quadrant of the graph indicate a population with a specialized feed- ing strategy, where a high percentage of the population consumes one or more specific prey types. Potential for trophic overlap among each predator pair was tested on mean percent weight and mean per- cent number with the simplified Morisita-Horn (M-H) index (O): 0 = (2E"P?jPik)/(E;''p^ +p^), (3) where n = the total number of prey item groups; Pij = the proportion of the prey item i used by predatory; and Pik = the proportion of the prey item i used by predator k (Wolda, 1981; King and Beamish, 2000). Both mean percent weight and mean percent number were examined to provide the most robust evidence of potential overlap because both variables are biased when viewed independently owing to the broad range of prey sizes (Graham et al., 2007). The M-H index ranges from 0 to 1, with diet overlap increasing as the index approaches 1 (Zaret and Rand, 1971; Labropoulou and Eleftheriou, 1997; King and Beamish, 2000; Graham et al., 2007; Rodrigues and Vieira, 2010). Results Analysis of similarity revealed that differences among predator species were significant (goodness of fit: coef- ficient of determination [r2]=0.112, P=0.001); however, for a given predator, the differences among years, re- gions, and seasons were not statistically significant and depth, temperature, and salinity were not correlated with diet composition. Therefore, for the remainder of the analyses, we combined seasons and regions to in- vestigate differences in diet composition among preda- tors and combined years for all analyses except IRI._ where Si = sum of prey i; and St = sum of all prey items found in only those predator stomachs that contained prey I. Although the summed variable can be composed of the number or the volume or weight of prey items, we used weight and lowest possible prey taxon. The spread and location of points on an Amundsen plot indicate Weakfish For this study, 349 individuals with an average size of 21 cm TL for young-of-the-year fish through adult fish, were examined. Of the 349 stomachs extracted, 276 contained food (79%; Table 1) and prey represented 71 taxa (Table 2). 294 Fishery Bulletin 113(3) Table 1 Number of stomachs extracted for this study, according to year, region, and season, from weakfish (Cynoscion regalis), southern kingfish (Menticirrhus americanus ), and Atlantic croaker ( Micropogonias undulatus ) collected from 2008 through 2010 during nearshore trawl surveys conducted by the Southeastern Monitoring and Assessment Program — South Atlantic. 2008 2009 2010 Southern Atlantic Southern Atlantic Southern Atlantic Weakfish kingfish croaker Weakfish kingfish croaker Weakfish kingfish croaker Spring Region Florida 5 5 1 4 2 7 7 23 6 Georgia 1 4 1 2 6 6 South Carolina 1 8 3 Long Bay 11 14 7 1 6 4 Onslow Bay 9 15 8 15 20 9 Raleigh Bay 8 9 8 16 25 4 All areas 7 17 5 34 46 36 39 74 23 Summer Region Florida 2 5 8 1 7 1 Georgia 1 2 5 1 4 8 4 9 13 South Carolina 2 3 5 12 24 17 6 4 15 Long Bay 1 1 2 7 5 7 Onslow Bay 4 2 7 4 5 4 10 5 11 Raleigh Bay 4 2 3 7 4 9 All areas 11 9 20 27 43 48 28 30 47 Autumn Region Florida 4 11 10 3 22 12 Georgia 9 18 18 7 17 17 5 11 12 South Carolina 7 12 6 9 20 19 7 11 8 Long Bay 1 2 1 6 7 9 12 14 8 Onslow Bay 15 20 25 5 3 7 1 8 2 Raleigh Bay 15 4 6 11 8 6 13 15 6 All areas 47 56 56 42 66 68 41 81 48 Total 65 82 81 103 155 152 108 185 118 Bony fishes, mostly bay anchovy ( Anchoa mitchilli), striped anchovy (A. hepsetus), and other members of the class Actinopterygii, dominated the diet of weakfish, with a frequency of occurrence of 63% in stomachs that con- tained food (Table 2). The diet composition by weight con- sisted of 70% bony fishes. The highest diet component by number was nondecapod crustaceans (69%). In addition to bony fishes, the most frequently consumed prey items were mysids, the sergestid shrimp Acetes amei'icanus car- olinae, and various crustaceans. Values of mean percent weight and mean percent number predictably showed bony fishes to be the dominant prey consumed (44% and 35%, respectively); however, decapod crustaceans (32%) and nondecapod crustaceans (29%) had similarly high values for mean percent number (Fig. 2, A and B). Results from the use of the Amundsen method indi- cate that the feeding strategy of weakfish was mixed because individuals sometimes chose specific prey but the population was often opportunistic with regard to what prey were selected. The top left portion of the graph in Figure 3A shows that many individuals chose specific prey types; however, the specific prey selected by each individual differed (Fig. 3A). The data points scattered throughout the center of this graph indicate a mixed feeding strategy, suggesting that, occasionally, the population would feed opportunistically. Southern kingfish Stomachs were processed for this study from 486 indi- viduals, with an average size of 21 cm TL (for young- of-the-year fish through adult fish), and 422 of those stomachs contained food (86%; Table 1). Prey repre- senting 86 taxa were identified (Table 2). Decapod and nondecapod crustaceans were present in the majority of stomachs. Collected stomach sam- Willis et al.: Feeding behavior of 3 sciaenids along the southeastern United States 295 Tabie 2 Frequency of prey occurrence (%F), diet composition by number (%N), diet composition by weight (%W), and index of relative importance expressed as a percent (IRI) of prey items found in stomachs of 3 predator species — weakfish (Cynoscion regalis ), southern kingfish (Menticirrhus americanus), and Atlantic croaker ( Micropogonias undulatus) — sampled off the Atlantic coast of the southeastern United States from 2008 through 2010. Weakfish Southern kingfish Atlantic croaker %F %N %W IRI %F %N %W IRI %F %N %W IRI Bony fishes 62.7 7.4 70.27 4869.91 24.5 7.6 21.87 722.02 25.6 7.6 21 732.17 Actinopterygii 39.13 5.1 8.98 550.89 20.1 6.78 9.82 333.68 18.8 5.19 3.62 165.74 Anchoa hepsetus 10.51 0.96 30.1 326.35 0.25 0.09 0.38 0.12 1.42 0.21 8.99 13.11 Anchoa mitchilli 4.35 0.24 5.81 26.32 0.25 0.03 0.3 0.08 1.42 0.46 2.01 3.52 Anchoa spp. 4.35 0.36 3.85 18.3 1.23 0.3 1.19 1.82 2.85 0.88 4.37 14.96 Centropristis striata 1.45 0.08 2.73 4.07 Clupeiformes 0.36 0.02 0.24 0.1 Cynoscion nothus 1.45 0.1 2.54 3.82 0.28 0.04 0.79 0.24 Cynoscion spp. 2.17 0.16 1.86 4.39 0.49 0.06 0.35 0.2 1.14 0.17 0.81 1.11 Engraulidae 0.72 0.04 <.01 0.03 0.49 0.06 0.06 0.06 0.57 0.25 0.21 0.26 Harengula jaguana 0.36 0.02 0.23 0.09 Larimus fasciatus 0.36 0.02 <.01 0.01 Leiostomus xanthurus 2.54 0.18 9.17 23.72 0.25 0.03 0.27 0.07 Ophichthidae 0.25 0.03 0.05 0.02 Mugil ceplialus 0.36 0.02 4.17 1.52 Prionotus spp. 0.36 0.02 <.01 0.01 0.25 0.03 4.28 1.06 Selene setapinnis 0.25 0.03 0.79 0.2 Sciaenidae 0.36 0.02 0.01 0.01 0.85 0.38 0.2 0.49 Stellifer lanceolatus 1.09 0.06 0.59 0.7 0.49 0.06 0.21 0.13 Symphurus plagiusa 0.25 0.03 3.49 0.86 Syngnathus spp. 0.49 0.06 0.68 0.36 Decapod crustaceans 54 23.1 20.52 2355.48 67.9 30.9 33.97 4404.99 45.3 18.8 21.53 1826.77 Acetes americanus carolinae 30.43 18.04 5.64 720.7 5.39 4.8 1.38 33.28 8.55 7.37 3.15 89.89 Albunea catherinae 0.49 0.06 0.76 0.4 0.28 0.04 0.26 0.09 Albuneidae 0.25 0.03 0.08 0.03 0.57 0.08 0.89 0.56 Axiidae 0.28 0.04 0.53 0.16 Brachyura 9.78 0.98 0.06 10.22 15.2 2.37 5.21 115.13 7.69 1.47 0.84 17.72 Callianassidae 0.85 0.21 0.09 0.25 Decapoda 1.45 0.1 0.07 0.24 4.9 0.98 0.57 7.59 2.85 0.71 0.1 2.33 Heterocrypta granulata 0.25 0.03 0.04 0.02 0.28 0.04 0.45 0.14 Latreutes parvulus 0.74 0.09 0.01 0.07 1.42 0.29 0.06 0.5 Leptochela sp. 5.8 0.64 0.21 4.93 12.5 3.26 0.83 51.11 7.41 1.38 0.38 13.07 Leucosiidae 0.74 0.09 0.25 0.25 Lucifer faxoni 2.17 0.12 0.01 0.28 0.74 0.09 <.01 0.07 1.71 0.25 0.01 0.45 Ogyrides sp. 2.17 0.24 0.12 0.77 15.93 4.62 1.33 94.76 8.26 1.63 1.11 22.62 Paguroidea 3.43 0.44 2.52 10.19 3.7 0.59 1.58 8.04 Palaemonidae 0.98 0.12 0.01 0.12 0.85 0.13 0.01 0.12 Panopeidae 1.72 0.3 2.49 4.78 1.42 0.21 1.59 2.56 Pelia mutica 0.36 0.02 0 0.01 Penaeidae 1.81 0.12 0.18 0.54 17.16 5.15 3.07 141.1 4.27 0.67 4.41 21.7 Pinnotheridae 3.26 0.26 0.1 1.16 9.07 1.69 1.34 27.46 4.27 1.05 0.5 6.61 Porcellanidae 1.81 0.1 0.01 0.19 0.49 0.12 0.6 0.35 Portunidae 4.35 0.48 0.1 2.54 7.84 1.39 5.37 53.06 0.28 0.13 0.28 0.12 Rimapenaeus constrictus 11.23 1.57 5.6 80.52 14.71 5.21 7.6 188.46 5.98 2.13 1.93 24.32 Sicyonia laevigata 0.25 0.03 <.01 0.01 Thalassinidea 2.17 0.36 5.87 13.54 0.49 0.06 0.49 0.27 1.42 0.25 1.93 3.11 Xanthoidea 0.36 0.02 <.01 0.01 0.25 0.03 0.02 0.01 0.85 0.13 1.42 1.33 Xiphopenaeus kroyeri 0.36 0.06 2.57 0.95 Table continued 296 Fishery Bulletin 113(3) Table 2 (continued) Weakfish Southern kingfish Atlantic croaker %F %N %W IRI %F %N %W IRI %F %N %W IRI Echinoderms 0.5 0.1 0.02 0.06 16.5 2.8 4.93 127.58 Echinoidea 0.49 0.06 0.02 0.04 0.57 0.08 0.01 0.05 Holothuroidea 1.99 0.67 1.29 3.91 Ophiuroidea 13.96 2.09 3.63 79.86 Mollusca 5.8 0.3 1.54 10.68 19.1 2.4 1.05 65.84 12.8 1.9 15.84 227.1 Arcidae 0.85 0.13 2.55 2.29 Bivalvia 4.9 0.62 9.97 51.91 4.84 0.71 4.21 23.83 Gastropoda 1.42 0.21 0.18 0.56 Mollusca 5.8 0.32 1.54 10.8 5.88 0.71 1.94 15.62 4.56 0.67 4.69 24.42 Solenidae 8.58 1.1 6.98 69.25 1.14 0.17 4.21 4.99 Nondecapod crustaceans 47.8 68.7 7.29 3632.32 62.3 41 14.73 3472.26 55.8 54.2 5.84 3350.01 Copepoda 8.33 6.26 0.12 53.18 0.74 0.65 0.01 0.48 7.12 7.37 0.08 53.03 Crustacea 18.12 1.1 1.87 53.89 12.5 2.4 1.13 44.06 20.8 4.02 2.6 137.58 Cumacea 2.54 2.63 0.01 6.69 18.87 10.48 0.31 203.76 5.13 1.63 0.06 8.67 Gammaridea 8.33 0.78 0.07 7.08 20.83 5.15 0.19 111.39 20.8 5.23 0.29 114.84 Isopoda 2.9 0.18 0.02 0.57 2.7 0.44 0.04 1.3 1.14 0.21 0.05 0.3 Mysidae 33.33 57.37 5.02 2079.4 35.05 21.23 1.19 785.77 25.64 35.5 2.59 976.51 Stomatopoda 4.35 0.34 0.2 2.34 4.9 0.68 11.87 61.51 1.42 0.21 0.17 0.54 Polychaetes 4.3 0.3 0.38 2.92 44.6 10 18.22 1258.49 51 12.1 28.95 2093.69 Ampharetidae 0.36 0.02 <.01 0.01 6.37 1.21 1.88 19.74 4.27 0.75 7.86 36.82 Aphroditidae 0.49 0.06 2.15 1.08 Annandia agilis 7.11 1.72 0.37 14.86 4.56 0.96 0.43 6.36 Capitellidae 0.74 0.09 0.49 0.43 0.85 0.13 0.6 0.62 Cirratulidae 0.28 0.04 <.01 0.01 Glyceridae 1.09 0.06 0.06 0.13 3.92 0.47 0.98 5.71 3.7 0.54 3.04 13.26 Goniadidae 1.23 0.18 0.05 0.27 1.42 0.25 0.04 0.42 Lumbrineridae 1.47 0.18 1.27 2.13 0.85 0.13 0.3 0.36 Maldanidae 3.43 0.41 0.99 4.8 7.12 1.21 0.88 14.89 Nephtyidae 3.43 0.44 0.25 2.4 0.28 0.04 0.02 0.02 Nereididae 0.25 0.03 0.01 0.01 1.42 0.33 0.35 0.97 Oenonidae 1.47 0.18 0.08 0.38 2.56 0.38 0.5 2.25 Onuphidae 1.45 0.08 0.29 0.53 9.8 1.75 3.59 52.35 7.41 1.17 2.29 25.62 Opheliidae 0.74 0.09 0.02 0.08 3.13 0.54 0.46 3.16 Orbiniidae 0.49 0.06 0.03 0.04 3.42 0.54 0.18 2.48 Pectinariidae 0.49 0.06 0.19 0.12 0.85 0.13 2.83 2.52 Phyllodocidae 0.98 0.12 0.11 0.23 0.57 0.08 0.01 0.06 Polychaeta 1.45 0.14 0.03 0.24 11.03 1.45 2.18 40.03 16.52 2.43 6.11 141.1 Polynoidae 0.28 0.04 0.06 0.03 Sabellariidae 0.25 0.03 <.01 0.01 2.6 1.09 0.25 3.49 Sigalionidae 0.25 0.03 0.01 0.01 0.57 0.08 0.01 0.05 Spionidae 1.47 1.13 0.29 2.08 5.7 1 1.06 11.76 Terebellidae 2.21 0.36 3.26 7.97 0.57 0.08 0.04 0.07 Trichobranchidae 0.28 0.08 1.63 0.49 Other 0.4 0.2 <.01 0.08 4.2 7.5 1.06 35.95 1.7 0.4 0.19 1 Branchiostoma sp. 1.23 0.24 0.07 0.37 Chaetognatha 0.36 0.18 <.01 0.07 0.98 6.9 0.13 6.89 0.57 0.17 0.01 0.1 Cnidaria 2.21 0.38 0.16 1.2 3.99 2.26 1.72 15.88 Echiura 0.28 0.04 0.14 0.05 Glottidia pyramidata 1.96 0.36 0.19 1.08 0.57 0.13 0.03 0.09 Sipuncula 0.25 0.03 0.67 0.17 Tubificidae 0.28 0.08 0.01 0.03 Total 100 100 100 100 100 100 Willis et al Feeding behavior of 3 sciaenids along the southeastern United States 297 ■■■ Weakfish l l Southern kingfish r . ,..i Atlantic croaker Weakfish Southern kingfish W Atlantic croaker jr j?' rf & & )+(A +£pj)Lit)] Others Maximum observed age, tmax Length and age at recruitment, Lr, tT Length and age at first capture, Lc, tc a, b = 4.56 x lO-8, 3.55 £LW ~ N(0, 3.93 x 10-4) L^,K, t0 = 1024, 0.12, -0.69 £GR~N(0, 3.10x 10-2) M = 0.18/year £M ~ N(0, 1.98 x 10-5) Fcur ~ Gamma with mean of 0.12 and variance of 1.06 x 10-2, a0, a1= -4, 0.02 P0, Pi= -13.31,0.02 £/)0 ~ N(0, 1.36) and Epl ~ N(0, 4.04 x 10-6) 16 years 55 mm, 0.489 year 200 mm, 1.15 year Four Fbrps were calculated to compare with Fcur( 0.120/year, Lin et al., 2010b): Fmax, the fishing mortality at which yield per recruit is at its maximum; Fo.i, the fishing mortality at which the increase of yield per recruit is only 10% of the increase of yield per recruit when fishing mortality is zero (King, 2007); and FpQ% and Fx,o%, the fishing mortality rates at which the SPR is 30% and 50% of the SPR when fishing mortality is zero (Goodyear, 1993). The reference points Fmax and Fq i can be regarded as boundaries in order to constrain harvesting below the level within which the fish population can produce maximum sustainable yield (United Nations, 1995), and they usually are used as limiting and precaution- ary indicators of growth overfishing, respectively; fish- ing mortality rates above Fmax indicate that fish are caught before they reach optimal size given the rate of natural mortality and their growth rate (Gabriel and Mace, 1999; Quinn and Deriso, 1999). Fishing mortali- ties at 30% and 50% of SPR, compared with SPR at F= 0, are considered to be the limiting and precaution- ary levels for anguillid eels (ICES1). Therefore, Fpo% and F 50% were considered the limiting and precaution- ary reference points for recruitment overfishing, where the spawners are insufficient in numbers to produce enough offspring to replace themselves (Sissenwine and Shepherd, 1987). Incorporation of uncertainties in parameters We used Monte Carlo simulation, which has been wide- ly applied to other species (e.g., Chen and Wilson, 2002; Grabowski and Chen, 2004; Chang et al., 2009; Lin et al., 2010a) to incorporate the uncertainties of the pa- rameters into the models. In each run, random errors for natural mortality (£m) and for coefficients in the logistic maturation curve (epQ and fp1), as well as 1 ICES (International Council for the Exploration of the Sea). 2002. Report of the ICES/EIFAC Working Group on Eels. ICES Council Meeting (C.M.) Documents 2002/ACFM:03, 55 p. [Available at website.] Lin et al.: Sensitivity of models to bias and imprecision in life history parameters 305 Table 2 Summary of the 9 scenarios for evaluation of the sensitivity of the results from models of yield per recruit and spawning biomass per recruit to dif- ferent degrees of bias and imprecision in several parameters: natural mor- tality (M), von Bertalanffy growth coefficient (K), asymptotic length (L„), and current fishing mortality rate (.Fcur). Also the multiplicative error in the growth curve (cgr) and the length-weight (LW) relationship (£Rw) are modeled. In each scenario, the mean or standard deviation (SD) of only one parameter was changed. Scenario Description Parameter Range 1 Standard scenario Unchanged 100% 2 Mean of M M 10-1000% 3 SD of M eM 10-1000% 4 Mean of K K 10-1000% 5 Mean of 50-200% 6 Error in growth curve £GR 10-1000% 7 Error in LW relationship £lw 10-1000% 8 Mean of Fcur F 1 cur 10-1000% 9 SD of F cur fFCur 10-1000% and £gr> were generated from normal distribution with the means and variances listed in Table 1. These ran- dom errors were incorporated into the YPR and SPR formulae provided in Table 1, and then 4 Fbrps (F max> Fo.i, F 3q%, and F 50%) were calculated. For each simula- tion scenario, this process was repeated 5000 times to produce 5000 corresponding sets of Fbrp values from which the empirical distributions of the 4 Frrps were generated and composite risks were calculated. Calculation of composite risks Because Fcur and the Frrps are not fixed constants, we applied composite risk analysis that allowed for the incorporation of the uncertainty in both indicator and management reference points (Prager et al., 2003; Jiao et al., 2005). By the discrete approach proposed by Jiao et al. (2005), the composite risks were calculated as the expected probability of one random variable being larger than another. Let fix) be the empirical probabil- ity density function of the Fbrp of interest (e.g., Fmax) and giy) be the empirical probability density function of Fcur with a corresponding cumulative density func- tion of Giy) and then, let Ax be a small increase in x (i.e., the Frrp), and by summing x over its range, the composite risk of Fcur exceeding Fbrp is calculated with the following equation: P(Fcur > Fbrp = 1 - ]T'^o0O[G(x)/’(x)]Ax (3) culation of composite risks in discrete approach, refer to Jiao et al. (2005). Sensitivity analysis For the sensitivity analysis, the pa- rameter values in Table 1 were set as the standard scenario (scenario 1; Ta- ble 2). The parameters for which mean and SD values may potentially affect results of YPR and SPR models were investigated in 9 scenarios, in which the mean or SD of only one parameter was changed (Table 2): the mean of M (scenario 2) and its SD (£m, scenario 3), the mean of K (scenario 4), and the mean of L ^ (scenario 5). In practice, the bias in K can result from aging er- ror and the use of different estimation approaches, and the bias in often results from unrepresentative sam- pling schemes. Therefore, we assumed that the sources of biases in K and are unrelatedand they were modeled independently. Because modeling the estimation errors in the coefficients K and can lead to underestima- tion of the actual uncertainty in the data (Lin et al., 2012), the error was modeled on the growth curve (£qr) rather than coefficients (scenario 6). The remaining scenarios are £rw (scenario 7) and the mean and SD values of Fcur and £pcur (scenarios 8 and 9). For scenarios 1-7, the mean and SD values of the parameters, except for L^, were decreased to 10% with an increment of 5% or were increased to 1000% with an increment of 50% to cover the possible magnitudes of biological variation (as applied in Goodyear, 1993). Because information about L can be obtained from the maximum observed length in the data, that pa- rameter may be subject to less bias and imprecision and was set from 50% to 100% with an increment of 5% and from 100% to 200% with an increment of 10% (Table 2). For scenarios 8 and 9, because of less computational load (calculation of an Fbrp is inde- pendent of Fcur, and, therefore, we needed to compute only composite risks of overfishing), we used finer in- crements: the mean and SD of Fcur were decreased to 10% with an increment of 1% or increased to 1000% with an increment of 10%. The relative change (RC) between the mean or SD of one Fbrp for increment i in scenario j ( RC "p ) and the mean or SD of that Frrp in the standard scenario was used to quantify the sensitivity of a given Fbrp for all scenarios except 8 and 9. RC is defined with the following equation: Here, we assume a gamma distribution for Fcur because 1) our previous study (Lin and Tzeng, 2008) indicated that gamma distribution fitted better for the distribu- tion of fishing efforts, 2) it produces nonnegative val- ues, and 3) it is flexible in shape. For details in cal- RC'i = 100 x TS x(Tp T1, PRRP PRRP tBRP ’ (4) Where TS = the statistic (mean or SD) of the Fbrp Rrrp -Divr of interest (e.g., Fmax) for increment i in scenario j; and 306 Fishery Bulletin 113(3) Table 3 Mean and standard deviation (SD) per year of 4 fishery-mortality-based reference points(FBRPs( — the fishing mortality at which yield per recruit is at its maximum (Fmax),the fishing mortality at which the increase of yield per recruit is only 10% of the increase of yield per recruit when fishing mortality is zero(Fo.i), and the fishing mortality rates at which the spawning biomass per recruit (SPR) is 30% and 50% of the SPR when fishing mortality is zero(F30%and ^50%) — and the composite risks, PlFcur^BRPk calculated as percentages, of current fishing mortality, Fcur(0. 120/year), exceeding FbrPs after repeating the standard scenario 1000 times. Numbers in the parentheses provide the ranges of relative changes in means and SDs from random Monte Carlo simulation with data for female Japanese eel ( Anguilla japonica ) in the Kao-Ping River in southern Taiwan. Fbrp Mean SD 1 max Fo.i F30% F50% 0.156 (99.95-100.04%) 0.111 (99.96-100.03%) 0.129 (99.97-100.03%) 0.073 (99.97-100.03%) 1.6xl0-3 (97.23-103.89%) 9.2xl0-4 (97.24-103.90%) 8.7xl0-4 (97.32-104.44%) 4.6xl0-4 (97.31-104.43%) P(FCUT>Fmax) P(Fcut>Fqi) P(Fcur>F; 30%) P(Fcur>F50%) 13.44 56.44 35.48 94.31 0.47 0.70 0.65 0.32 Tp = the same statistic of the same Fbrp from the standard scenario. The sensitivity of an Frrp also has to be distinguished from the random variation that results from Monte Carlo simulation, namely the variation that results from the incorporation of random errors in M, length- weight relationship, and maturation process. To under- stand the scale of this random variation, the standard scenario (scenario 1, without any biasesor impreci- sion in parameters) was repeated 1000 times, produc- inglOOO corresponding RC values for the means and SDs of Fbrps- The minimum and maximum values of RC from these 1000 repetitions of scenario 1 were used as the lower and upper limits of random variation from the Monte Carlo simulation. The effect of changes in the mean or SD of a parameter was considered sig- nificant only when its RC is lower than the minimum or larger than the maximum RC. All the computations and simulations were completed in R, vers. 3.1.0 (R Core Team, 2014). Results Magnitude of the random variation from Monte Carlo simulation Running the Monte Carlo simulation of the stan- dard scenario 1000 times produced RC values for the means of Fmax, Fo.i, F3o%,and F^q% that ranged from 99.95% to 100.04%, from 99.96% to 100.03, from 99.97% to 100.03, and from 99.99% to 100.03%, respectively (Table 3). The SD values of the Frrps had larger RC values that ranged from 97.23% to 103.89% for Fmax, from 97.24% to 103.90% for Fq.i, from 97.32% to 104.44% for F3o%, and from 97.31% to 104.43% for F50%(Table 3). Therefore, variation of RC within 0.05% for the mean and within 4.50% for the SD of the Fbrp was applied as the criterion for significance of ef- fects; that is, we considered the effect of changing one parameter on the Fbrp to be significant when the resultant RC was wider than this criterion. Sensitivity of reference points from the YPR model The means of Frrps from the YPR model, namely Fmax and Fo.i, were sensitive to both the means of M and K, which had similar trends but different magnitudes (Fig. 1, left panels). The RC values for the means of Fmax and Fo.i decreased slowly to 75-80% when M and K decreased to 5%. As M and K increased to 1000%, their RC values rose with an accelerating trend, especially for Fmax, to more than 12,000% and 1100%, respectively. However, the means of Fmax and Fq.i were not sensi- tive to changes in L „ and £gr because their RC varied less than 0.05%. The had marginal effects on the mean of Fmax and Fo.i, given that the RC was around 100.6% when became 1000% (Fig.l, left panels). The SD values of Fmax and F0.1 were also sensitive to the means of M and K with similar accelerating trends. The SD of Fmax was more sensitive to changes in M and K than was the SD of Fq.i (Fig. 1, right panels). In addi- tion, the SD values of Fmax and Fq.i were nearly related linearly to Em- Similar to the means, the SD values of Fmax and F0.1 did not show significant sensitivity to and £gr, and their RC values did not exceed the significance level of 4.50%. Sensitivity of reference points from the SPR model The means of Frrps from the SPR model, F3o%, and F§o%, were sensitive to the mean of M, but their RC values (from 90% to 170%; Fig. 2, left panels) were smaller than those of Fmax and Fo.i- When K decreased to 40%, the RC for the mean of F3q% and F5 0% reached a minimum of around 80%. As K increased to 1000%, the RC of the means of F3o% and F5 q% increased to 300% and 400%. They also were affected by L0 0 such that the RC was around 85-125% as LM increased from 50% to 200%. Neither cm nor £qr affected the means of F 30% and F5 0%. The SD values of F30% and F50% showed the highest sensitivity to the mean of M, with Lin et al.: Sensitivity of models to bias and imprecision in life history parameters 307 Parameter magnifier (%) Parameter magnifier (%) Figure 1 Relative changes determined from Monte Carlo simulation with data collected during 1998-2006 for female Japanese eel (Anguilla japonica) in the Kao-Ping River in southern Taiwan. The relative changes are measured as percentages for the means (shown in the left panels) and standard deviations (SD; shown in the right panels) of fishery-mortality-based refer- ence pointslFBRpg) in scenarios 2-6 of the yield-per-recruit model, where the mean and SD of the natural mortality (M and Em), the von Bertalanffy growth coefficient (K), the asymptotic length (LM), and the multiplicative error in the growth curve (cgr) were under-specified from 5% to 95% and over-specified from 150% to 1000% (except forvalues of that went from 50% to 200%). In each graph, the solid line indicates fishing mortality at which yield per recruit is at its maximum, and the dashed line indicates fishing mortality at which the increase of yield per recruit is only 10% of the increase of yield per recruit when fishing mortality is zero. Because of the large variation in RC values for the different scenarios, the scales of the y-axes differ greatly to allow changes to be seen. Under=underspecified parameters; Over=overspecified parameters; £M=the SD of M\ Fcur=current fishing mortality and; e/pcur=SD of Fcur. the RC changing from 70% to around 4000%. The pa- rameter K had high influence on the SD values of F^q% and ^50%, with RC changing from 20% to 1500% (Fig. 2, right panels). The parameters £m and had con- siderable effects on the SD values of F%q% and F§q%, with RC ranging from 90% to 400% and from 40% to 150%, respectively. The SDs of F^q% and ^50% were not affected by £gr- Sensitivity of the composite risks of overfishing The composite risks of growth overfishing (Fcur ex- ceeding Fmax and Fq 1) decreased with increasing means of M and K and did not depend on changes in L0 o, £qr, and £m (Fig. 3). The risks of recruitment overfishing ( Fcur exceeding F 30% and F. 50%) showed the greatest sensitivity to K followed by M. The risk of recruitment overfishing was affected also by chang- es in L«, but with less sensitivity. The parameters £m and £(jr did not contribute to noticeable changes in the risks of overfishing. The risks of both growth and recruitment overfishing showed strong sensitivity to both the mean and SD of Fcur. As the mean of Fcur increased from around 150% to 225%, the risks ap- proached 100%. The risks of overfishing decreased with increasing SD for Fcur. 308 Fishery Bulletin 113(3) NO ON CD O) c 03 -£= o ro a> GC 20 40 60 80 100 200 400 600 800 1000 Parameter magnifier (%) Figure 2 Relative changes from the Monte Carlo simulation with data collected during 1998-2006 for female Japanese eel (Anguilla japojiica) in the Kao-Ping River in southern Taiwan. The relative changes are measured as percentages, for the means (shown in the left panels) and SDs (shown in the right panels) of fishery-mortality-based reference points(EBRPs) in sce- narios 2-6 of the spawning-biomass-per-recruit model, where the mean and SD of the natural mortality (M and ejy), the von Bertalanffy growth coefficient ( K ), the asymptotic length ( L „,), and the multiplicative error in the growth curve ( qr) were under-specified from 5% to 95% and over-specified from 150% to 1000% (except forvalues of that went from 50% to 200%). In each graph, the solid line indicates the fishing mortality rate at which the spawning biomass per recruit (SPR) is 30% of the SPR when fishing mortality is zero, and the dashed line indicates the fishing mortality rate at which the SPR is 50% of the SPR when fishing mortality is zero. Because of the large variation in RC values for the different scenarios, the scales of the y-axes differ greatly to allow changes to be seen. Under=underspecified parameters; Over=overspecified parameters. Effects of multiplicative error in the length-weight relationship The changes in £pW resulted in nonsignificant changes in the mean and SD of the 4 Fbrps. They also did not affect the composite risks of exceeding these Fbrps. Discussion Effects of uncertainty in mean and SD of natural mortality Estimates of the mean of M are usually highly uncer- tain, possibly because of the lack of appropriate data for direct estimation, data such as those from tag-re- capture experiments (Vetter, 1988). As M increases, the YPR curve becomes flatter with a decreasing maximum value and decreasing slope at the origin (fig. 17.18 in Beverton and Holt, 1957). This change in the shape of YPR curve accounts for the nonlinear accelerating trend of Fmax and Fq.i found in our study. Uncertainty in the mean (bias) of M can also cause significant bi- ases in results of the model for SPR, particularly at a high level of fishing mortality (Goodyear, 1993). A higher mean of M led to a steeper SPR curve, but the general shape of the curve was not altered, explain- ing the lower sensitivity of ^30% and F^,q% to M. On the other hand, the SD (imprecision) of M resulted Lin et al.: Sensitivity of models to bias and imprecision in life history parameters 309 in significant changes only in the SDs of the 4 Fbrps examined. Therefore, as indicated in the Appendix Figure, the risks of both growth and recruitment overfishing were affected more by the changes in the mean of Mthan by changes in the SD. The bias in M seems to be more im- portant than the imprecision in M in influencing the risks of overfishing. Effects of uncertainty in growth parameters The shape of the YPR curve also was altered by K (fig. 17.22 in Beverton and Holt, 1957). The flattening of the YPR curve with decreas- ing K accounts for the accelerating increase in the mean and SD of Fmax. On the other hand, Beverton and Holt (1957) found that the changes in Woof equivalent to under the same length- weight relationship) did not affect the shape of the YPR curve. This insensitivity of the YPR shape on L«, explains our finding that changes in Loo did not affect the mean and SD of Fmax and Fq i or the corresponding risk of growth overfishing. The peaks in the values of RC in the means and SDs of F^q% and F§q% when K and L^were around 40-60% possibly resulted from the use of a length-dependent maturation curve for an- guillids (Davey and Jellyman, 2003) in the cal- culation of SPR. In the cases with extremely small values of K or the proportion of ma- ture eels was close to zero even at the maxi- mum age (16 years). A very small part of the spawning biomass was lost because of fishing, consequently resulting in higher Fqq% and Fqq% values. Effects of current fishing mortality The bias and imprecision in Fcur played an im- portant role in determining risks of overfishing. Greater effects due to changes in the mean of Fcur on the risks of both growth and recruit- ment overfishing were expected because differ- ences in the mean played an important part in influencing the composite risk, as in the ex- ample of 2 standard normal random variables (Appdx Fig.). Given the same difference in the means, a larger SD leads to lower composite risks (Appendix. Figure, panels B and D), ac- counting for the observed decreasing risks of overfishing with increasing £pcur. Given that FCur is from the gamma distribution, decreas- ing composite risks with increasing £pcur also resulted in the convergence of 4 risks of over- fishing. This finding indicates that a high £pcur value may mask the distinction between target (usually Fq i or Fqq%) and threshold (Fmax or Fqq%) ^BRPs because the risks of target and threshold Fq rp are similar. Parameter magnifier (%) Figure 3 The composite risks of overfishing in scenarios 2-6, 8, and 9, where the mean and standard deviation (SD) of the natural mortality (M and Cm), the von Bertalanffy growth coefficient ( K ), the asymptotic length (L„), the multiplicative error in the growth curve (cgr)- and the mean and SD of current fishing mortality (Fcar and £fciu) were under-specified from 5% to 95% and over-specified from 150% to 1000% (except forvalues of that went from 50% to 200%). The black solid line indicates the composite risk of Fcur exceeding the fishing mortality at which yield per recruit is at its maximum, the black dashed line indicates the composite risk of Fcur exceeding the fishing mortality at which the increase of yield per recruit is only 10% of the increase of yield per recruit F=0,and the gray solid and dashed lines indicate the composite risk of Fcur exceeding the fishing mortality rates at which the spawning biomass per re- cruit (SPR) is 30% and 50% of the SPR when F= 0. 310 Fishery Bulletin 113(3) The assumption of a gamma distribution of Fcur may be the reason for increasing risks of exceeding Fm ax when fpcur lies between 5% and 200%. When £Rcur was 50% or less, the gamma distribution of Fcur resembled the normal distribution with density highly concentrat- ed around its mean. Because Fmax (0.151) was much larger than Fcur (0.120), the area of the distribution of Fcur that exceeded Fmax became smaller and smaller as fpcur decreased, resulting in lower risks. Asymmetry in the sensitivities of reference points The responses of the means and SDs of 4 Fbrps to the changes in the means of M or K showed disproportion- ate increases, indicating that the means and SDs of FrrPs were more sensitive to over-specification. This accelerating trend, arising from the nonlinear relation- ship between these parameters and Frrps (Schnute and Richards, 1998), indicates that under the same degree of misspecification (e.g., 50%) an over-specified mean of M or K could result in seriously overestimated values of Frrps. Consequently, the risks of overfish- ing would be underestimated, potentially leading to overexploitation. In summary, bias in life history parameters, such as M, Fcur, K, and L <*,, resulted in considerable changes in the means and SDs of 4 selected Frrps: Fmax, Fq i, F%q%, and F 50%. Different degrees of the imprecision in the life history parameters did not affect the means of Fbrps but substantially influenced their SDs. Over- specification of the mean of M and K led to larger val- ues of RC in the means and SDs of Frrps than did under-specification of the means of M and K. The composite risks of Fcur exceeding these 4 Frrps were affected mainly by bias in the life history pa- rameters rather than by their imprecision. Both bias and imprecision in Fcur played crucial roles in deter- mining the risks of Fcur exceeding these 4 Frrps. The variation in growth curves and length-weight rela- tionships did not affect results of the per-recruit mod- els. 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United Nations Conference on Straddling Fish Stocks and Highly Migratory Fish Stocks, Sixth session, New York, 24 July-4 August 1995. A/CONF. 164/37, 40 p. [Available at website.] Vetter, E. F. 1988. Estimation of natural mortality in fish stocks: a re- view. Fish. Bull. 86:25-43. 312 Fishery Bulletin 1 13(3) Appendix This appendix presents changes in composite risks of 2 random variables, X and Y, under different means and standard deviations. Appendix Figure The composite risks of Y exceeding X, or P(Y>X), measured in percent- ages, in which X is a standard normal variable (X~N[0,lj) and Y is a random normal variable with changing mean and standard deviation (SD) (py, °y>- (A) Reference case: (py, cry)=(from 0 to 1, from 0.05 to 1); (B) large SD of Y case: (py, cy)=(from 0 to 1, from 0.5 to 10); (C) large difference in mean case: (py, ay)=(from 0 to 10, from 0.05 to 1); and (D) large difference in mean and SD of Y case: (py, oy)=(from 0 to 10, from 0.5 to 10). 313 NOAA National Marine Fisheries Service Abstract— Seasonal migration of commercial-size (>102 mm carapace width [CW]), morphometrically ma- ture (MM) snow crabs (Chionoecetes opilio ) from the eastern Bering Sea was examined in relation to the sum- mer distribution of mature females to identify spatiotemporal overlap of males and females and determine the likelihood of mating associations for specific reproductive stages. Depth variation associated with this migration was examined to deter- mine whether seasonal migrations contribute to previously recognized spatial differences in distributions of commercial-size males caught in the winter fishery and in the Na- tional Marine Fisheries Service sum- mer bottom trawl survey. Depth data from 33 data storage tags attached to commercial-size MM males dur- ing 2010 and 2011 indicated that most males moved inshore during spring — a movement that would al- low them to mate with multiparous females but not with pubescent-pri- miparous females. Smaller tagged males (100-102 mm CW) underwent more extensive inshore migrations, and several of them traveled more than 100 km in one direction. Both tagging and distribution data indi- cated that most commercial-size MM males remained predominantly on the outer shelf throughout the year (despite some inshore movements during spring) and, therefore, these males did not contribute greatly to the spatial differences observed be- tween winter and summer. Manuscript submitted 13 November 2014. Manuscript accepted 15 May 2015. Fish. Bull. 113:313-326 (2015). Online publication date: 4 June 2015. doi: 10. 7755/FB. 113.3.7 The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA. Fishery Bulletin nr established 1881 Spencer F. Baird First U S. Commissioner of Fisheries and founder of Fishery Bulletin Seasonal migrations of morphometrically mature male snow crab ( Chionoecetes opilio ) in the eastern Bering Sea in relation to mating dynamics Daniel G. Nichol (contact author) David A. Somerton Email address for contact author: dan.nichol@noaa.gov Resource Assessment and Conservation Engineering Division Alaska Fisheries Science Center National Marine Fisheries Service, NOAA 7600 Sand Point Way NE Seattle, Washington 98115 Migrations of snow crabs (Chionoece- tes opilio ) differ between sexes and among different size classes, result- ing in distributions that are highly structured and complex (Ernst et al., 2005). In the eastern Bering Sea, these migrations depend partially on bottom temperature gradients (Ernst et al., 2005) and can vary annually depending on the extent of the “cold pool” (Kotwicki and Lauth, 2013), a near bottom layer of cold (<2°C) water that forms across mid-depths (50-100 m) of the eastern Bering Sea shelf. On the basis of data from the eastern Bering Sea shelf collected during the National Marine Fisher- ies Service (NMFS) annual summer bottom-trawl survey, immature crabs of both sexes undertake down-slope ontogenetic migrations that are generally from the northeast to the southwest (Otto, 1998; Zheng et al., 2001; Ernst et al., 2005). Upon reach- ing full maturity, both sexes undergo a terminal molt in the spring, after which they are thought to continue to migrate into deeper water (Ore- sanz et al., 2004; Ernst et al., 2005; Parada et al., 2010). For commer- cial-size males, >102 mm in cara- pace width (CW), this migration is assumed to culminate on the outer shelf (depths of 100-200 m), where the winter commercial fishery is con- centrated (Orensanz et al., 2004). Less is known about smaller termi- nally molted males, but they are as- sumed to reside inshore of the com- mercial-size males. Male migrations likely differ be- fore and after the terminal molt. Because the transformation from a small-clawed “adolescent” stage to a large-clawed morphometrically ma- ture (MM) stage coincides with the terminal molt for males, these stages have been distinguished by using the relationship of carapace width (CW) to chela height (CH) (Comeau and Conan, 1992; Stevens et al., 1993; Rugolo et al.1; Tamone et al., 2007). Because members of a cohort can reach maturity over multiple ages, the size distribution of MM males overlaps that of adolescent males. Although adolescent males are some- times capable of mating, MM males 1 Rugolo, L., D. Pengilly, R. Macintosh, and K. Gravel. 2005. Reproductive po- tential and life history of snow crabs in the eastern Bering Sea. In Bering Sea snow crab fishery restoration research: final comprehensive performance report. (D. Pengilly and S. E. Wright, eds.), p. 57-323. NOAA Cooperative Agreement NA17FW1274. Div. Commer. Fish., Alaska Dep. Fish Game, Juneau, AK. 314 Fishery Bulletin 113(3) have a distinct competitive advantage in securing mates (Sainte-Marie et al., 1997). Seasonal inshore migrations of post-terminal-molt MM male snow crabs, at least in waters of eastern Canada, have been attributed to mating behavior. These migrations are either targeted toward pubescent- primiparous females, those that will soon terminally molt and then brood their first clutch after mating, or toward multiparous females, those carrying clutches in subsequent years (Lovrich et al., 1995; Sainte-Marie et al., 2008). In the eastern Bering Sea, pubescent-pri- miparous females reside in shallower water and mate 1-3 months (February to March) earlier than multipa- rous females (Somerton, 1982; Ernst et ah, 2005; Kruse et ah, 2007). Peak spawning and subsequent mating among multiparous females in the eastern Bering Sea occur between March and April (Rugolo2), although a small percentage may be in a receptive condition until July (Somerton, 1981). Whether commercial-size MM males in the east- ern Bering Sea undergo a seasonal inshore migration for the purpose of mating is unknown. If multiparous females in the eastern Bering Sea are relatively sed- entary, as they are in eastern Canada (Lovrich et ah, 1995), an inshore migration by commercial-size MM males may be necessary for successful mating. Earlier and more extensive inshore migrations would certainly be required to mate with pubescent-primiparous fe- males (Parada et ah, 2010). Theoretically, there may not be a need to migrate toward and mate with multip- arous females because these females can store sperm over multiple years (Sainte-Marie and Carriere, 1995). However, depending on the sex ratios of functionally mature crabs, ratios that can affect mate choice (Sainte Marie et ah, 2008; e.g., the southern Tanner crab [C. bairdi ], Webb and Bednarski, 2010), most multipa- rous females are presumed to mate annually if males are available. An exception to this assumption occurs among some females that reside in colder-water areas (<1.5°C) of the eastern Bering Sea and that spawn bi- ennially (Rugolo et al.1). Compared with the ontogenetic migrations of ju- venile snow crabs in the eastern Bering Sea, little is known about the seasonal migration patterns of MM males because of the paucity of sampling during times other than those of the NMFS summer bottom trawl survey and the winter commercial fishery. The offshore migration of recently terminally molted MM males in the eastern Bering Sea was demonstrated by a study of the Alaska Department of Fish and Game (ADFG), during which MM males were tagged with spaghetti tags during summer, on the middle shelf, and many were recaptured near the outer shelf during the fol- lowing winter snow crab fishery (Gravel et ah, 2006; Pengilly3). However, because the fishery and, therefore, 2 Rugolo, L. 2014. Personal commun. Alaska Fish. Sci. Cent., Seattle, WA 98115. 3 Pengilly, D. 2014. Personal commun. Alaska Dep. Fish Game, Kodiak, AK 99615. recaptures occur only on the outer shelf, the fraction of MM males that migrate to the outer shelf is unknown, and nothing is known about the possibility of these males migrating back to the middle shelf. Furthermore, because of the reliance on the fishery for recaptures, ADFG tagged only commercial-size males, and informa- tion on migration and distribution for small MM males (70-100 mm CW), which are prevalent in the eastern Bering Sea (Otto, 1998) and potentially important con- tributors to breeding, is lacking. For commercial-size MM males, fishery managers have recognized a seasonal change in distribution, which is centered on the middle shelf of the eastern Bering Sea (bottom depth: <100 m) during the summer (Foy and Armistead, 2013) but shifts to the outer shelf (bottom depth: 100-200 m) from January to March when and where the fishery typically occurs (Orensanz et al., 2004; Bowers et al., 2011; Turnock and Rugolo4). Part of this distributional shift may be explained by the post-terminal-molt migration from the middle to the outer shelf (Orensanz et al., 2004), but an inshore spring migration by outer shelf males may contribute to this shift as well. Such a migration was documented by Lovrich et al. (1995), who found that MM male snow crabs <70 mm CW in the Gulf of St. Lawrence migrat- ed to shallow water during early spring to mate with pubescent-primiparous females. In that study, however, large MM males tended not to migrate as far inshore or as early in the year as males <70 mm CW, therefore, limiting their mating to multiparous females. Determining where and when large (>100 mm CW) and small (70-100 mm CW) MM males may migrate, and where they are spatially distributed in relation to pubescent-primiparous and multiparous females, can help elucidate which mating associations occur in the eastern Bering Sea. Although at least some large, re- cently terminally molted MM males migrate into deep- er water after summer, it is not known whether these males seasonally migrate back inshore to mate with multiparous females or perhaps to shallower waters where pubescent-primiparous females reside (Parada et ah, 2010). If seasonal inshore migrations do occur, it is not known how much they contribute to tempo- ral differences in the spatial distribution of large MM males. For small MM males in the eastern Bering Sea, it is unclear what component of the mature female stock they associate with and mate with, because of the difficulty in recapturing small, tagged animals in the fishery and because the spatial distribution of these small MM males has not been examined separately from that of adolescents. Using data storage tags (DSTs) that were capable of timed depth recordings and were deployed on com- 4 Turnock, B. J. and L. J. Rugolo. 2011. Stock assessment of eastern Bering Sea snow crab. In Stock assessment and fishery evaluation report for the king and Tanner crab fish- eries of the Bering Sea and Aleutian Islands regions. 2011 crab SAFE, 37-168 p. North Pacific Fishery Management Council, Anchorage, AK [Available at website.] Nichol and Somerton: Seasonal migration of mature males of Chionoecetes opilio in the eastern Bering Sea 315 mercial-size MM male snow crab, we examined the sea- sonal inshore and offshore migrations of these males to determine if their migrations contribute to the report- ed differences between distribution of MM male snow crab during summer and their distribution during win- ter. Second, by examining the summer distribution of mature females, we attempted to infer the components of the female stock that are associated with and mate with large MM males. Finally, we compared the distri- bution of both large and small MM males with that of mature females to assess the potential for size-specific male-female mating associations. Materials and methods Tagging A total of 277 morphometrically mature male snow crab (96-134 mm CW) were tagged and released with pressure-and-temperature-recording DSTs on 18-22 April 2010 (n=120) and 7-8 March 2011 (n=157), near the end of each fishing season to ensure that tagged crab were not recaptured until the following year. Tag- ging operations occurred on the winter snow crab fish- ing grounds northwest of the Pribilof Islands at ap- proximately 57°35 N in 2010 and about 100 km farther north at 58°30 N in 2011 (Fig. 1). DSTs were attached to spaghetti tags that were wrapped around the cara- pace of the crab between the first and second walking legs. Because male snow crab do not molt after they reach maturity, the effect of tagging on their behavior and mortality was assumed to be negligible. In April 2010, an additional 221 snow crab were tagged and released with numbered spaghetti tags without an at- tached DST as a control to determine whether the ad- ditional DST attachment affected capture rate, as well as to help examine site fidelity. Crabs were captured and tagged aboard commercial crab pot fishing vessels Kiska Sea (in 2010) and Pacific Sun (in 2011) during normal commercial fishing opera- tions, and they were released within 10 min of capture at the same location. All tagged male crabs had large claws and had new to slightly worn hard shells, condi- tions that predominated in the catches during the time of tagging. Only crabs that possessed all their limbs were selected for tagging. Tagged crabs were recap- tured by commercial crab pot vessels during the fol- lowing winter and spring snow crab fisheries in 2011 and 2012, and a tag reward program was implemented to provide an incentive to return tags. Locations where crabs were recaptured were documented by the fisher- men who returned tags. The DSTs, Cefas G5 Long Life5 tags with 2 MB of memory (Cefas Technology Limited, Lowestoft, UK), measured depth (pressure) at 1-min intervals, with an 5 Mention of trade names or commercial companies is for iden- tification purposes only and does not imply endorsement by the National Marine Fisheries Service, NOAA. accuracy of ±2 m and precision of <0.08 m, and temper- ature at 30-min intervals, with an accuracy of ±0.1°C and precision of 0.03°C. DSTs were bullet-shaped with dimensions of 8x31 mm and weighed 1 g in water. Analyses of snow crab depth and ambient temperature The shelf of the eastern Bering Sea slopes down gradu- ally from northeast to southwest from the Alaska main- land ( i.e. , north of 58°N) out to the shelf break (bottom depth: approximately 200 m); therefore, changes in tag depth were used as proxies or indicators of inshore and offshore movements (Fig. 1). Because migrations likely included movements parallel to bottom depth contours (i.e., movements in northwest and southeast directions), exact migration pathways could not be determined. For each recaptured crab, the recorded tag depths were plotted against time (e.g., month) to determine whether seasonal inshore and offshore migrations were made and whether migrations were consistent among all individuals. Temperatures also were plotted against time to document the temperatures of areas inhabited by snow crabs in the eastern Bering Sea. In a few cas- es, tag temperatures were compared with temperatures collected during the NMFS summer bottom trawl sur- vey, to corroborate the position of a crab from release and recapture positions and to indicate their proximity to the cold pool. Distribution of mature females The distributions of primiparous and multiparous fe- males were plotted with data from the 2010 and 2011 NMFS summer bottom trawl surveys (Foy and Ar- mistead, 2013; Lauth and Nichol, 2013) to examine the extent to which their distributions overlapped with tagged MM males and to infer whether the migration of large MM males would be necessary to create mat- ing opportunities. A critical assumption for this com- parison was that the mature (i.e., primiparous and multiparous) female distributions observed during the summer survey were representative of the mature fe- male distributions during the preceding winter-spring mating period. Primiparous females were identified as those females with uneyed eggs, clutch sizes 1/8 to 3/4 full, and soft to clean hard shell conditions. Multipa- rous females were identified as those females with ei- ther uneyed or eyed eggs, full clutch sizes, and hard shells with scratches or wear. Distribution of morphometrically mature males Broad-scale geographic distributions of MM male snow crabs during summertime were analyzed with data col- lected annually (1989-2011) during the NMFS summer bottom trawl survey (Foy and Armistead, 2013; Lauth and Nichol, 2013), where stations were fixed and posi- tioned 37 km apart from each other. Distributions were plotted for 4 male categories; that is, for 2 different size classes (70-100 mm CW and >100 mm CW), each 316 Fishery Bulletin 1 13(3) 58" N 57" N 174° W 172" W 170" W Figure 1 Release and recapture locations of morphometrically mature male snow crabs ( Chi - onoecetes opilio) tagged with data storage tags (DSTs) during 2010 and 2011 in the eastern Bering Sea, northwest of the Pribilof Islands, which include St. Paul Island. Small black triangles indicate releases in 2010 of crabs with DSTs and spaghetti- only tags. Large and small gray triangles indicate recaptures of DSTs and spaghetti tags, respectively, from crabs released in 2010. Small black squares indicate releases in 2011 of crabs with DSTs. Large gray squares indicate recaptures of DSTs from crabs released in 2011. Lines with numbers indicate contours of bottom depths. with 2 post-terminal-molt age categories represent- ing MM males that recently terminally molted (in the current year; having a new shell) or in previous years (having an older shell). The new- and older-shell cat- egories correspond to the shell conditions <2 and >3, respectively, as defined in Foy and Armistead (2013). MM males were distinguished from adolescent males by using a linear regression function relating ln(CH) to ln(CW) as calculated in Rugolo et al.1, where for each measured specimen s, MM status was assigned where qjj > g1.2899xln(CWs)-2.8628 Q) Because crabs measured for CH were subsampled from the catch at each station, their numbers were extrapolated to the entire catch at each station. Also, because males subsampled for CH were too few in number (mean: 24/station/year) to examine geograph- ic distributions on an annual basis, data were pooled across years (1989-2011) for each station in the sur- vey. For each survey station i, the relative proportion of MM males (PROP) was calculated with the following equation: PROP, V^L (2) where Ny = the extrapolated number of MM males at station i during year j. If CHs were not measured within a particular year and station, each missing value of Ny was estimated as the Nichol and Somerton: Seasonal migration of mature males of Chionoecetes opilio in the eastern Bering Sea 317 tion. Distributions were plotted as described previously for the size classes of 70-100 mm CW and >100 mm CW by using the data pooled across 1989-2011 and by using cal- culated relative proportions at each station. mean N; during years when sampling occurred. Alge- braically, this mean is expressed as v.. AT. N.=hl£LLt (3) »i where n; = the number of years in which CHs were measured at station i. Distribution of adolescent males Adolescent males were also identified as above with the CH-CW regression provided in the previous sec- Results Time at liberty and recapture locations A total of 33 male snow crabs with DSTs were recaptured, of which 4 individuals were 100-102 mm CW and the rest ranged in size from 106 to 126 mm CW. In addi- tion, 43 males with only spaghetti tags (not DSTs) were recaptured with sizes ranging from 101 to 130 mm CW (Fig. 1). Among males tagged with DSTs in 2010, 22 were recaptured in 2011 after 280-333 days at liberty and 1 was recaptured in 2012 after 640 days at liberty. Of the males re- leased in 2011 with DSTs, 9 were recaptured in 2012 after 439-458 days at liberty. Among males tagged with spaghetti tags in 2010, 42 were at liberty between 274 and 319 days before recapture, and 1 other male was re- captured after 777 days. Recapture rates for snow crabs released in 2010 (and recaptured in 2011) were 18.3% (n= 22) for those tagged with DSTs and 19.0% (n=42) for those tagged only with spaghetti tags, indicating essential- ly no difference in recapture rates between the 2 tag types. The attachment of the DSTs to spaghetti tags, therefore, was assumed to have no added effect on crab behavior or sur- vival. Compared with males tagged in 2010, those males tagged in 2011 were recaptured later in the year (May-June, in 2012) and at a lower rate (5.7%; n= 9), owing to ice condi- tions that limited access to the fishing area during winter and caused the fishing season to be extended (Gutierrez, 2012). Recapture locations of both types of tags indicate some site fidelity, as indicated by the low degree of area overlap between crabs recaptured in 2011 and 2012 and released approximately 100 km apart (Fig. 1). Occurrence and extent of inshore-offshore migrations Individual depth trajectories among tagged males were highly variable within the depth range they inhabited (90-172 m), indicating a wide variety of individual migration routes (Fig. 2, A and B). For the crabs re- leased in 2010, 3 general movement patterns were ob- served: 1) extensive upslope (i.e., inshore) movements, or changes in depth, >20 m to depths <120 m with- in 1 month after tagging; 2) very limited upslope or 318 Fishery Bulletin 113(3) 456789 10 11 12 1 23456789 10 11 12 1 2 2010 201 1-2012 Month and year Figure 3 Timed depth (black line) and temperature (gray line) recordings from a data storage tag attached to a 100-mm (carapace width) morphometrically mature male snow crab (Chionoecetes opilio ) released in the eastern Bering Sea in 2010. This crab was at liberty for 640 days, although the depth sensor ceased to func- tion approximately 5 months before its recapture. downslope movements (depth changes <10 m), remain- ing in depths >120 m; and 3) initial downslope move- ments of more than 20 m followed by extensive upslope movements, remaining in depths >120 m (Fig. 2A). For crabs released in 2011 (north of 2010 releases), all 9 of the males that were recovered moved upslope im- mediately after release in the spring, but their depth changes were less extensive than those of tagged males released in 2010 (Fig. 2B), with changes ranging from 7 to 16 m (mean: 10.5 m). Of the 5 males that were still at liberty during the following spring, in 2012, only 1 appeared to move upslope during the second spring. Two of the 4 small tagged males (100-102 mm CW) undertook relatively long inshore migrations of -100 km, in depths ranging from 120 to 90 m (Fig. 1) during the spring and summer followed by an offshore migra- tion during fall and winter. They did not migrate to- gether because the timing of their inshore and offshore movements was offset by about 1 month (Fig. 2A). A third small individual (100 mm CW), released in 2010 and at liberty 640 days, undertook inshore and offshore migrations in both 2010 and 2011, but it did so dur- ing different months and to differing extents (Fig. 3). During successive spring periods, it resided at different depths (by approximately 20 m) and different locations (separated by a distance of approximately 50 km), in- dicating that individuals can undergo variable migra- tions from year to year. The fourth small male ( 100 mm CW), released in 2011, migrated inshore but not to the extent of the other 3 small tagged male snow crabs. Temperatures encountered Temperatures encountered by the tagged males ranged from -0.5°C to 4.5°C (Fig. 4, A and B), although those males that were released at the more northern location in 2011 (n= 9) experienced temperatures about 1°C colder (mean: 2.3°C) than the temperatures experi- enced by males (n= 24) released farther south in 2010 (mean: 3.3°C). Seasonally, tagged males encountered the warmest tem- peratures during winter (~No- vember-January) and the cold- est temperatures during spring (~February-June). Annual dif- ferences in ambient temperature were apparent from DST data ob- tained from 2011 released males that were at liberty for more than 14 months (Fig. 4B); spring temperatures averaged 2.3°C in 2011 compared with 1.3°C in 2012. The coldest temperatures (<1°C) were encountered by the 2 males that, in 2010, migrated farthest inshore to a depth of 90 m (Fig. 4A), where, on the basis of the spatial distribution of bottom temperatures of the eastern Bering Sea shelf measured during the sum- mer bottom trawl survey (Lauth, 2011), each of them migrated to the edge of the cold pool before initiating a return offshore migration. Both crabs remained at these colder temperatures for approximately 1 month before migrating offshore. Proximity of mature females to tagged males On the basis of the 2010, 2011, and 2012 data of the summer distributions of mature females, multiparous females were in close proximity (< 10 km) to the loca- tions where tagged males were released (Fig. 5, B, D, and F). In addition, the inshore migrations of tagged males during spring (Fig. 2) indicated that there was a broad overlap with multiparous females at the time of multiparous mating (March-April). The increase in the abundance of multiparous females in the vicinity of the tag release areas from 2010 to 2011 indicates that more females were available to tagged males for breeding in 2011 than in 2010. In contrast, primiparous females were found much farther east (by distances >50 km) of the tagged males during all 3 years (Fig. 5, A, C, and E). Bathymetric overlap of tagged males and mature females The extent of cross-shelf inshore migrations by tagged males, defined here as the minimum depth reached dur- ing their time at liberty, increased (e.g., decreasing min- imum depth) with decreasing crab size (Fig. 6; linear regression: n- 33, coefficient of determination [r2]=0.39, P<0.001). Considering the depths where multiparous females were found during the NMFS summer bottom trawl surveys (Fig. 5), all tagged males occupied ar- Nichol and Somerton: Seasonal migration of mature males of Chionoecetes opilio in the eastern Bering Sea 319 eas where these females resided, including 9 of the large males (>113 mm CW) that re- mained at depths >120 m and did not make a dedicated inshore migration. Therefore, they all had an opportunity to mate with mul- tiparous females. In contrast, opportunities to mate with pubescent-primiparous females were unlikely given that these females were concentrated (Fig. 5) much farther to the east (shallower waters) and to the north. The two small tagged males that migrated to a 90-m depth were the exception; however, the months during which these males resided at a depth of 90 m (June-July), were well past the period of pubescent-primiparous mating (February-March). Summer distributions of morphometrically mature and adolescent males Small MM males (70-100 mm CW) were concentrated farther north and east (shal- lower water) of areas where large MM males (>100 mm CW) of the same shell condition resided, and new-shell MM males were con- centrated farther east (shallower) than that where older-shell MM males of the same size class resided (Fig. 7, A-D). Large older- shell MM males were primarily distributed over the outer shelf (depths of 100-200 m), whereas new-shell MM males, from both size classes, were primarily distributed over the middle shelf (depths of 50-100 m), at least south of 59°N. Adolescent males of both size classes were distributed over the middle shelf (i.e., south of 59°N), and small individuals were distributed more to the northeast of areas where large individuals were distributed (Fig. 7, E and F). Discussion Most of the tagged MM males migrated in- shore either shortly after their release dur- ing spring or during the following winter or spring. These migrations were not extensive enough to have contributed to the spatial difference in distributions between large males observed on the middle shelf dur- ing the NMFS summer bottom trawl survey and those males targeted on the outer shelf during the winter fishery. A seasonal shift in distribution of large males would be expected because of the fall migration of re- cently terminally molted males to deeper water, but this shift should be more prominent if these and older- shell MM males migrate back inshore every spring. Although springtime inshore migrations did occur, all but 2 of the tagged males remained on the outer shelf (depths >100 m) throughout their time at liberty. The summer distribution of large, older-shell MM males (Fig. 7D) in waters deeper than 100 m con- firmed the supposition that few of these individu- als migrated back inshore to the middle shelf. The highest concentrations of large males found over the middle shelf (depths 50-100 m) during the summer survey (Orensanz et al., 2004; Turnock and Rugolo4), therefore, likely were not composed of MM males that seasonally migrated inshore but of recently ter- minally molted MM males that had yet to migrate 320 Fishery Bulletin 1 13(3) 176°E 180° 176°W 172°W 168°W 164°W 160“W 176“W 172°W 168°W 164”W 160”W 62°N 60°N 58°N 56“N 60“N 58°N 56“N 54“N 2011 "1 110,000 I females/km2 0 100 200 km D 176“E 180“ 176°W 172°W 168'W 164°W 160”W 176"W 172°W 164“W 160“W 60°N 58"N A 2011 62°N 60°N 58°N 56°N 176“E 180“ 172”W 164°W -160°W 176“W 172°W 168“W 164"W 160°W 62“N 60“N 58°N 56°N A 2012 58°N 56“ N 54“N 110,000 females/km2 60“N 176°W 172°W 168“W 176“E 176°W 172“W 168“W 164“W 160“W 62°N 58“N 56”N 60°N 58°N 56°N A 2012 54“N Figure 5 Summer distributions of primiparous female snow crabs (Chionoecetes opilio) during (A) 2010, (C) 2011, and (E) 2012 and of multiparous females during (B) 2010, (D) 2011, and (F) 2012, determined from data collected from the National Marine Fisheries Service summer bottom trawl surveys of the eastern Bering Sea. Bar heights indicate the catch per unit of effort (number of females per square kilometer). Ellipses indicate the tag release locations of morphometrically mature males. The black line indicates the 100-m bottom-depth contour, designating the ap- proximate border between the middle and outer shelves. Nichol and Somerton: Seasonal migration of mature males of Chionoecetes opilio in the eastern Bering Sea 321 o ro D) £ D. 100 km) migrated and that the interpreted periods of grasping and carrying (>2 months) are longer than those reported in the lit- erature (Sainte-Marie et ah, 2008). 322 Fishery Bulletin 113(3) 62°N 61°N 60°N 59° N 58°N 57°N 56° N 55°N 54° N 53"N 62°N 61°N 60°N 59° N 58°N 57°N 56°N 55°N 54'N 53°N 62°N 61°N 60° N 59° N 58° N 57°N 56°N 55°N 54°N 53°N Distributions of morphometrically mature (MM; large-clawed) and adolescent (small-clawed) male snow crabs ( Chionoecetes opilio) in the eastern Bering Sea during July, based on data collected annually (and pooled across years; 1989-2011) during National Marine Fish- eries Service summer bottom trawl surveys. Distributions are classi- fied within 4 categories of males: (A) small (70-100 mm in carapace width [CW]) males with new-shell condition (B) large (>100 mm CW) males with new-shell condition, (C) small males with older-shell con- dition, and (D) large males with older-shell condition. Distributions Assuming, on the basis of the data from DSTs, that large commercial-size MM males do not migrate inshore far enough, or soon enough, to mate with pubescent-primiparous females, the most likely partners for pubes- cent-primiparous mating were small (70-100 mm CW) MM males. Adolescent males from the Gulf of St. Lawrence have been found to mate with pubescent-primparous females in the laboratory (Moriyasu and Conan6; Sainte- Marie and Lovrich, 1994; Sainte-Marie et ah, 1997), but their reproductive contribution in the field was thought to be limited (Sainte- Marie et al., 1999; Sainte-Marie et ah, 2008). Instead, small MM males were found to be the primary partners of pubescent-primipa- rous females (Sainte-Marie and Hazel, 1992). It is not known if MM males <100 mm CW in the eastern Bering Sea undergo seasonal migrations, but given their close proximity to primiparous females during summer (Figs. 5 and 7C), they were the most readily available group of males to mate with these females. Differences in the male-female mating dy- namics of snow crabs from the eastern Bering Sea and those from eastern Canada are like- ly. Opportunities for different mating associ- ations among the various reproductive stages (e.g., pubescent-primiparous and multiparous females and adolescent and MM males) could be greater in areas of steep bathymetry, for example, as a result of shorter migratory distances (Sainte-Marie et al., 2008) and re- lated energetic costs (Foyle et al., 1989). The eastern Bering Sea shelf is flatter and wider than the Gulf of St. Lawrence. Because snow crabs are distributed along depth and tem- perature gradients according to their size and reproductive stage, the physical separa- tion of these different groups may be greater over the eastern Bering Sea shelf than over the Gulf of St. Lawrence. Despite the geo- 6 Moriyasu, M., and G. Y. Conan. 1988. Aquari- um observation on mating behavior of snow crab, Chionoecetes opilio. ICES Council Meeting (C.M.) Documents 1986/K:9, 21 p. [Available at web- site.] Figure 7 legend cont. of adolescent males are classified by (E) small (70-100 mm CW) and (F) large (>100 mm CW) size classes. Relative abundance at each station was quantified as the proportion of MM males at each station in relation to MM males summed over all stations for all years. Dot sizes represent the following proportion ranges from smallest to larg- est: <0.002; 0.002-0.004; 0.004-0.008; 0.008-0.020; >0.020. Values of Zij AVjj are the sum of males cap- tured at all stations i for all years j. The black line indicates the 100-m bottom-depth contour. Nichol and Somerton: Seasonal migration of mature males of Chionoecetes opilio in the eastern Bering Sea 323 graphic differences, however, migration habits among large MM males in the 2 regions appear to be quite similar. In both locations, large MM males migrate to deeper water after their terminal molts (Ernst et ah, 2005), make limited seasonal migrations back inshore, overlap the distribution of mature multiparous females during the spring mating season, and exhibit size de- pendence in regard to migration distance. Assuming that large MM males seasonally migrate for the purpose of mating, we believe the extent and timing of their migrations is likely to depend on both the distribution of mature females and the seasonal timing of their reproductive cycle. Snow crab distri- butions have been shown to contract northward after years of warmer bottom temperatures (e.g., 1975-1979; Orensanz et al., 2004), and to shift back to the south (Turnock and Rugolo4) after a series of more recent colder-than-average years (2007-2010) and more exten- sive cold pools (Stabeno et ah, 2012). The tagged MM males in this study were, therefore, at liberty during a relatively cold period. As indicated in this study, mul- tiparous females were in close proximity to the tagged males, but perhaps, when waters are warmer, a shift in male and female distributions may necessitate longer migrations for mating. Colder temperatures also delay seasonal embryo hatching (Moriyasu and Lanteigne, 1998; Webb et al., 2007) and consequently subsequent mating, and therefore may result in earlier occurrence of migrations during warmer years. Although the tagging data indicate timed migra- tions across depth gradients, and therefore inshore and offshore movements, we could not resolve move- ments that may have occurred along depth isobaths and therefore could not describe distinct migration routes for individuals. Another limitation of our study is that, although data from the NMFS bottom trawl surveys provided a clear pattern for the summer dis- tribution of mature females, we did not have similar information collected during the mating period. Simi- larly, the distributional data for small MM males was limited to summer samples, and their overlap (or lack of) with tagged males during other seasons could not be determined. Additionally, although broad-scale dis- tributional differences were found among adolescent and MM males of different size classes and with dif- ferent shell conditions, annual differences in their distributions could not be determined because of a lack of annual CH-CW data needed to differentiate between adolescent and MM males. This shortcoming highlights the need for more comprehensive annual CH-CW collections. Because of the lack of a substantial inshore mi- gration of large MM males, it is important to rec- ognize the component of the population targeted by the fishery and the impact of the fishery on female mating dynamics and reproductive success. Because large commercial-size MM males remain on the outer shelf, the existence of a summer-winter spatial dif- ference among large males (including adolescents) on the outer shelf must, in part, be due to the annual removal of MM males by the fishery. The highest con- centrations of commercial-size males observed during the NMFS summer bottom trawl survey in 2010 were found near the Pribilof Islands on the middle shelf (Turnock and Rugolo4), but our tag recoveries do not indicate that this finding is a result of migration of commercial-size MM males. Instead, these males must have been recently terminally molted MM males (i.e., new shell males) that had yet to migrate offshore, as well as adolescents. Again, considering what appears to be low relative abundance of large MM males on the outer shelf during summer, there must be some level of large MM male depletion during winter, and the winter fishery must be largely dependent on the annual recruitment of these new-shell MM males to the outer shelf. Because of significant removals of commercial-size MM males by the fishery on the outer shelf, female spawners could become more reliant on either small MM males or adolescent males for mating (see En- nis et al., 1990). As stated earlier, because pubescent- primiparous females reside on the middle shelf, they are likely to mate with small resident MM males. For multiparous females, which reside on the out- er shelf, their likely mates are the large MM males targeted by the fishery. However, because the fish- ery in the eastern Bering Sea typically occurs from January through March, just before multiparous mat- ing ( -March-July), the capture of large MM males would exclude them from multiparous mating. Con- sidering that recently terminally molted males can- not mate for perhaps 3 months (Conan and Comeau, 1986; Paul et al., 1995; Sainte-Marie et al., 1999), even those large recently molted males that survive the fishery may not contribute to multiparous mating that year. Of concern here, other than the reliance of the fish- ery on only one pseudocohort (individuals that termi- nally molted in the same year; see Ernst et al., 2005), is whether the male sperm contribution to spawning is sufficient in terms of both quantity and quality. Are the numbers of mature males that remain after fishery harvesting abundant enough to provide the sperm reserves necessary for healthy clutch fertiliza- tion and subsequent robust populations? Preliminary research on spermathecal loads among primiparous and multiparous females in the eastern Bering Sea has shown that they were significantly lower than those of females in the Gulf of St. Lawrence (Rugolo et al.1; Slater et al., 2010). Although there was no evi- dence of sperm limitation within the eastern Bering Sea stock, there is still a concern that the stock could be vulnerable to recruitment overfishing that results from reliance on a male-only fishery. The question remains, do multiparous females then become more reliant on stored sperm from pubescent-primiparous mating that occurred before their own offshore migra- tion, or do they become more reliant on sperm from small, noncommercial-size MM males (e.g., Ennis et al., 1988; 1990) and potentially bias the genetic pool 324 Fishery Bulletin 1 13(3) toward smaller terminal sizes (Elner and Beninger, 1995; Tamone et al., 2005; Sainte-Marie et al., 2008)? Reduced reproductive output from multiparous fe- males could place greater reliance upon mating and spawning of pubescent-primiparous females, which are known to have a lower fecundity (Haynes, et al., 1976; Sainte-Marie, 1993). Because multiparous mat- ing is important for long-term sustainability of the snow crab in the eastern Bering Sea, it is important to ensure that adequate numbers of large MM males survive each year. Acknowledgments D. Pengilly provided the impetus for the research. R. Alinsunurin, J. Conner, and C. 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Smith, and D. Withered, eds.), p. 233-255. Univ. Alaska Fairbanks, Alaska Sea Grant College Program AK-SG-01-02. 327 NOAA National Marine Fisheries Service Fishery Bulletin .%• established 1881 Spencer F. Baird First U S. Commissioner of Fisheries and founder of Fishery Bulletin Effects of oyster harvest activities on Louisiana reef habitat and resident nekton communities 1 School of Renewable Natural Resources Louisiana State University Agricultural Center 124 Renewable Natural Resources Bldg. Baton Rouge, Louisiana 70803 2 U.S. Geological Survey Louisiana Cooperative Fish and Wildlife Research Unit School of Renewable Natural Resources Louisiana State University Agricultural Center 124C Renewable Natural Resources Bldg. Baton Rouge, Louisiana 70803 Abstract— Oysters are often cited as “ecosystem engineers” because they modify their environment. Coastal Louisiana contains extensive oyster reef areas that have been harvested for decades, and whether differences in habitat functions exist between those areas and nonharvested reefs is unclear. We compared reef physi- cal structure and resident commu- nity metrics between these 2 sub- tidal reef types. Harvested reefs were more fragmented and had low- er densities of live eastern oysters ( Crassostrea virginica) and hooked mussels (Ischadium recurvum) than the nonharvested reefs. Stable iso- tope values ( 13C and 15N) of domi- nant nekton species and basal food sources were used to compare food web characteristics. Nonpelagic source contributions and trophic positions of dominant species were slightly elevated at harvested sites. Oyster harvesting appeared to have decreased the number of large oys- ters and to have increased the per- centage of reefs that were nonliving by decreasing water column filtra- tion and benthopelagic coupling. The differences in reef matrix composi- tion, however, had little effect on resident nekton communities. Un- derstanding the thresholds of reef habitat areas, the oyster density or oyster size distribution below which ecosystem services may be compro- mised, remains key to sustainable management. Manuscript submitted 9 January 2014. Manuscript accepted 21 May 2015. Fish. Bull. 113:327-340 (2015) Online publication date: 9 June 2015. doi: 10.7755/FB.113.3.8 The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA. Steve Beck1 Megan K. La Peyre (contact autSior)1-2 Email address for contact author: mlapey@lsu.edu Ecologists have long recognized the importance of “ecosystem engineers” in organizing and maintaining eco- systems through their modification of the availability of resources in the environment (Jones et ah, 1994, 1997). Oysters are commonly ac- knowledged as ecosystem engineers of shallow-water estuaries. Oysters modify the local environment by pro- viding refuge and foraging habitat (Peterson et ah, 2003; Coen et ah, 2007), by altering local hydrodynam- ic processes (Lenihan, 1999), and by affecting local water quality (Newell et ah, 2005; Piehler and Smyth, 2011; zu Ermgassen et ah, 2013). Glob- ally, more than 85% of oyster reefs have been identified as functionally extinct; disease, poor water quality, and destruction of the physical habi- tat have been identified as the major proximate causes (Beck et ah, 2011). More specifically, the loss of vertical relief and complexity of oyster reefs, largely a result of commercial har- vesting, is often cited as the primary factor that drives reef decline (Roths- child et ah, 1994; Kirby, 2004). Changes in the physical structure of reefs through natural processes, such as storm events or human ac- tivities associated with harvest, may affect the habitat value of reefs by altering refuge availability and reef community structure (Breitburg, 1999; Soniat et ah, 2004; Humphries et ah, 2011a). Alteration of the physi- cal structure of reefs directly affects nekton populations by changing the availability of potential habitat, and several studies have highlighted the cascading effects of altered reef prop- erties on trophic dynamics within an oyster reef community (Lenihan et ah, 2001; Grabowski and Powers, 2004; Grabowski et ah, 2008). Other stud- ies have highlighted the impacts of re- duced biomass of oysters, or other fil- ter feeding organisms, on ambient wa- ter quality (Cloern, 1982; Fulford et ah, 2007; zu Ermgassen et ah, 2013). More than 40% of the commer- cial production of the eastern oyster (Crassostrea virginica ) in the conti- nental United States occurs in coast- al Louisiana estuaries (LDWF1), and oysters are the dominant reef-form- 1 LDWF (Louisiana Department of Wildl- life and Fisheries). 2012. Oyster stock assessment report of the public oyster areas in Louisiana: seed grounds and seed reservations. Oyster Data Rep. Ser. 18, 88 p. [Available from Louisiana Dep. Wildl. Fish., RO. Box 98000, Baton Rouge, LA 70898.] 328 Fishery Bulletin 113(3) ing organism within these estuaries. Harvest activi- ties occur across large areas of oyster reefs (LDWF1), but the effects of harvest and management on resident nekton communities, reef structure, and trophic inter- actions have yet to be quantified. Reefs in this region are characterized as largely subtidal, located in a mic- rotidal, well-mixed environment, and have limited ver- tical relief (<50 cm). Therefore, the effects of harvesting on reefs in Louisiana may not be evident in large-scale changes in vertical relief but may be observed more in oyster density and size and in alteration of the reef matrix; oyster density and size, and alteration of the reef matrix may in turn affect refuge value and filtra- tion capacity of an oyster reef (e.g., Summerhayes et al., 2009; La Peyre et ah, 2014a). We compared reef physical structure and resident community metrics on commercially harvested and nonharvested oyster reefs in coastal Louisiana. We quantified and characterized the abundance and com- position of the resident nekton community at these oyster reefs. These data were examined to determine whether any differences in resident nekton community structure could be attributed to changes in reef char- acteristics. Lastly, using stable isotope analyses, we ex- amined whether differences in reef characteristics were associated with differences in food web dynamics, such as the contributions of basal food sources, trophic level, and niche breadth of abundant resident organisms. Materials and methods Study area This study was conducted on subtidal reefs located in estuarine shallow-water areas of coastal Louisiana. The coastal bays and estuaries in Louisiana are microtidal (tidal range: <1 m), and most water depths were within a range of 1-4 m. Oyster reefs are located in mid-sa- linity (salinity range=5-25) areas within the extensive salt and brackish marsh regions of the Louisiana coast and tend to cover large, heterogeneous areas. The reefs are often extensive and unmapped, and, therefore, they are difficult to delineate. We selected paired harvested and nonharvested sites, all located within similar sa- linity zones and on public oyster seed grounds that are managed by the Louisiana Department of Wildlife and Fisheries (LDWF2, 2010; Fig. 1). For this study, harvest activities included removal of oysters for harvesting, as well as management activities, such as deposition of cultch (i.e., shell and limestone) to provide recruitment substrate. Nonharvested reefs were areas where it has been illegal to harvest oysters for several decades. Two sites, Sabine Lake and northern Calcasieu Lake, have been closed to harvesting activities for more 2 LDWF (Louisiana Dep.Wildl. Fish.). 2010. Oyster stock assessment report of the public oyster areas in Louisiana: seed grounds and seed reservations. Oyster Data Rep. Ser. 16, 92 p. [Available at website.] than 50 years, and they are the only substantial non- harvested subtidal oyster reefs in the state. There is no evidence that cultch deposition has occurred at these sites in the last 50 years. The sites were initially closed for health concerns that no longer persist, and over the last 5 years, there has been enormous pressure to open these areas to harvest. The remaining 2 areas, south- ern Calcasieu Lake and Sister Lake, are actively har- vested with dredges. The most recent cultch deposition in these areas occurred on southern Calcasieu Lake in 2009 (0.06 km2 of no. 57 limestone), and on Sister Lake in 2009 (0.63 km2 of no. 57 limestone). Sites were paired on the basis of ecological similar- ity and not proximity. The sites of northern and south- ern Calcasieu Lake were sampled as 1 pair; these 2 sites are located within the same waterbody and ex- perience similar salinity regimes (long-term mean sa- linity: 13.9-16.1) and storm events. Sabine Lake and Sister Lake were paired because of similarities in sa- linity regimes (long-term mean salinity: 11.9-15.1) and water depths, and both sites are considered interior, large, shallow waterbodies. Although these 2 sites were farther apart from one another geographically than the other paired sites, the assumption was made that if harvest causes significant effects on the habitat, dif- ferences that result from harvest activities would be greater than differences associated with actual coastal location. Data collection Field data Reefs were located within each site with side-scan sonar data (ENCOS3) for Sabine, Southern Calcasieu, and Sister lake sites and with GPS coordi- nates from a planting of oyster shell cultch in 1969 for northern Calcasieu Lake. At each of the 4 sites, 3 sample stations, measuring 10 mxlO m, were estab- lished on reef habitat located more than 100 m from the marsh edge and in the centers of reef areas to re- move confounding effects of adjacent habitats and reef edge (Fig. 2; Acosta and Robertson, 2002; Grabowski et ah, 2005). At each sample station, reef structure, water quality, and resident nekton communities were sampled according to protocols listed below. All sample stations in Sabine Lake and Sister Lake were sampled twice during summer (July-August) 2010, and all sam- ple stations in northern and southern sites in Lake Calcasieu were sampled twice during fall (September- October) 2010. For each summer sampling event, 3 replicate sam- ples per station were taken (with trays, which are de- scribed in the next section); because of high tray loss in the summer, 4 replicate samples were taken per sample station for each fall sampling event to increase 3 ENCOS. 2008. Water bottom assessment of selected por- tions of public oyster seed grounds within Cameron Parish, Louisiana: Calcasieu and Sabine Lakes, 391 p. Prepared for the Louisiana Dep. Wildl. Fish. [Available from Louisiana Dep. Wildl. Fish., P.O. Box 98000, Baton Rouge, LA 70898.] Beck and La Peyre: Effects of oyster harvesting activities on Louisiana reef habitat and resident nekton communities 329 94°0'0"W 93°0'0"W 92°0'0"W 91 WW 31°0'0"N- -31°0’0"N Texas Louisiana Mississippi 30°0'0"N- Sabine Lake S Calcasieu Lake (northern) y “30°0'0"N Calcasieu Lake (southern) O Nonharvested reef areas # Actively harvested reef areas Sister (Caillou) Lake 29°0'0"N- 0 15 30 60 90 120 I kilometers -29°0'0"N 94°0'0"W 93°0'0"W 92<50’0"W 91 WW Figure 1 Map of the locations of the 4 sites, Sabine Lake, Sister Lake, and northern and southern Calcasieu Lake, in coastal Louisiana where data were collected in 2010 to describe oyster reef characteristics and associated resident reef community. the number of trays successfully retrieved (for summer sites: 2 treatmentsx3 sample stationsx3 traysx2 sam- ple events=36 samples planned; for fall sites: 2 treat- mentsx3 sample stationsx4 traysx2 sample events-48 samples planned). Resident nekton Resident nekton were sampled by us- ing a benthic sample tray with an added mesh draw- string bag that was pulled closed before tray retrieval to prevent escape of mobile organisms. Trays are frequent- ly used to sample oyster reef residents (Lehnert and Al- len, 2002; Yeager and Layman, 2011) because of the im- practicality of using nets to capture the cryptic species that live within the complex oyster reef matrix. Trays consisted of 0.22-m2 plastic trays (0.47 mx0.47 mx0.08 m), which had their sides and bottoms lined with 3-mm mesh (Fig. 3). At deployment, trays were filled with lo- cal oyster reef substrate collected with a small dredge at adjacent reefs more than 100 m from sampling sta- tions and with the amount needed to displace 5.0 L of water volume. The volume of 5.0 L was chosen because it completely fills the tray with substrate. Deployment times ranged from 1 to 3 weeks be- cause weather affected our ability to retrieve the trays. Lehnert and Allen (2002) and others have found that tray soak times of 2-7 days were adequate for sam- pling resident nekton at subtidal oyster shell habitats and that the communities recruited to trays did not change significantly after 7 days. Upon retrieval, all organisms were collected, placed on ice, and taken to the laboratory, where they were identified with the use of field guides to the lowest practical taxon (Felder, 1973; Thompson, 1986; Hopkins et al, 1987; Hoese and Moore, 1998; Kells and Carpen- ter, 2011), measured (total length in millimeters for fish and shrimp, carapace width in millimeters for crabs, and wet-weight in grams), and frozen at a tempera- ture of -20°C. If a tray was dumped during retrieval ( i.e. , some tray contents were lost because of improper net function), organisms were still collected and identi- fied for possible use during stable isotope analyses but were not included in species abundance comparisons. All data for densities of organisms are reported as the number of individuals per square meter. Reef structure Reef composition was determined by counting and measuring material placed in each tray before deployment. Volume of loose shells and shell clusters was measured by water displacement. Shell clusters were defined as having a minimum of 3 fused oyster shells. The volume of loose shells and clusters provides a proxy for the availability of small and large 330 Fishery Bulletin 113(3) 29°48'0"N 93°56'0"W Point Louisiana O Sample stations Land Reef areas 93°20'0"W Dredge Spoil g Island Figyre 2 Maps of the locations of the 3 stations (o) at each of 4 sites in coastal Louisiana where resident reef communities and reef structure were sampled in 2010: (A) Sabine Lake, (B) Sister Lake, (C) northern Calcasieu Lake, and (D) southern Calcasieu Lake. All reef areas were determined from sonar data, ex- cept the reef area in northern Calcasieu Lake, which is based on only GPS coordinates for the footprint of a cultch planting in 1969. The sites at Sabine and Sister lakes were sampled in summer 2010 with 3 samples per station; the northern and southern sites at Calcasieu Lake were sampled in fall 2010 with 4 samples per station. interstitial reef space, respectively. Total numbers of oysters, of market-size oysters (shell height: >75 mm), and of seed oysters (shell height: 25-75 mm) were counted. At tray retrieval, the number of hooked mus- sels ( Ischadium recurvum) within 1.0 L of substrate per tray was counted as an indicator of settlement of other (nonoyster) sessile organisms. Reef integrity and vertical relief were estimated at each sample station. To estimate reef integrity (per- centage of area that consisted of solid reef), 20 hap- hazard measurements were taken by quickly tapping the bottom of the seafloor twice with a long pole and recording the bottom type (solid, mixed shell and mud, or mud). Solid reef was assigned a value of 1.0, mixed shell and mud was assigned a value of 0.5, and mud was assigned a value of 0.0. An index of integrity was calculated by adding the assigned values and dividing by 20. To measure vertical relief, 20 haphazard depth measurements were taken at each station. The differ- ence between the 2 extreme depth measures was used as an index of vertical relief. Water quality Upon retrieval of each nekton sampling tray, dissolved oxygen (DO; measured as milligrams per liter), salinity, and temperature (measured in degrees Celsius) data were collected at each sample station at the surface (~10 cm below the surface) and the bottom ( ~ 10 cm above the bottom) of the water column with a YSI Model 854 multiparameter sensor (YSI, Inc., Yellow Springs, OH). One surface water sample was collected 4 Mention of trade names or commercial companies is for iden- tification purposes only and does not imply endorsement by the U.S. government. Beck and La Peyre: Effects of oyster harvesting activities on Louisiana reef habitat and resident nekton communities 331 Figure 3 The modified sample tray used for sampling resident communities of oyster reefs in 2010 in coastal Louisiana, showing (A) the mesh drawstring as it would be when deployed and (B) the mesh drawstring pulled for tray retrieval. at each station with a 250-mL, opaque Nalgene bottle, placed on ice, taken to the laboratory, and immediately analyzed for chlorophyll-a (measured in micrograms per liter) (Arar5 * * * * *) and total particulate matter (TPM; measured in milligrams per liter) (Rice et ah, 2012). Isotope samples Sample collection Resident organisms used for stable isotope analyses were taken from tray samples. For each species found across all sites, only organisms of similar size were used in order to remove any effects of ontogenetic dietary shifts; organisms had to be com- bined across stations to obtain adequate numbers of each species from each site. Organisms collected in- cluded the eastern oyster, hooked mussel, the flatback mud crab ( Eurypanopeus depressus ), grass shrimp (. Palaemonetes spp.), the naked goby ( Gobiosoma bosc), the freckled blenny ( Hypsoblennius ionthas), and the skilletfish ( Gobiesox strumosus). Adductor muscle tis- sue was used for eastern oysters, and the entire or- ganism was used for hooked mussels (excluding their shells), flatback mud crabs, and grass shrimp. Tail por- tions were used for naked goby and skilletfish samples, and epaxial muscle tissue was used for freckled blenny. Samples of basal food sources were collected at each site: fine particulate organic matter (FPOM; <200 pm, pelagic source) and dominant marsh plants (nonpelag- ic, detrital source). For FPOM samples, a 1-L bottle of water was collected from each station (3 samples per 5 Arar, E. J. 1997. Method 446.0: In vitro determination of chlorophylls a\, b\, c\ + C2 and pheopigments in marine and freshwater algae by visible spectrophotometry, rev 1.2, 26 p. National Exposure Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency. [Available at website.] site), filtered through 200-pm mesh, and placed on ice. Three samples clipped from the stems of the marsh plant (Spartina spp.) were collected (20 m apart from each other) from each site and placed on ice. Coarse particulate organic matter (CPOM; >200 pm) was col- lected with a ring-net plankton tow (3-string bridle, 50- cm diameter) fitted with 200-pm mesh, pulled at each station for 2 min at a speed of 2.6 m/s (5 kn). Plank- ton tow contents were placed in a 1-L opaque bottle after visible detritus were removed and these bottles were placed on ice and taken to the laboratory for con- tent analysis. FPOM and CPOM samples were filtered through Whatman glass microfiber filters (GF/F, pre- combusted for 3 h at 450°C) until flow was obstructed, and the filters with the filtrate were frozen at -20°C. Sample preparation and analyses All samples were dried to a constant weight at 60°C, they ground to a powder, and treated to remove lipids. Inorganic carbonates were removed from shrimp, crabs, FPOM, and CPOM through treatment with minute quantities of IN hydrochloric acid until the reaction ceased (Jacob et al., 2005). Lipids were extracted in 2 separate 24-h decantations with hexane at room tem- perature (Fry et al., 2003). Once they were treated for lipids and inorganic carbonates, samples were placed back into a drying oven at 60°C until they reached a constant weight. Faunal tissue samples of 1 mg (stan- dard error [SE] 0.2) and plant tissue samples of 2-3 mg were weighed for stable isotope analyses. For fil- tered FPOM and CPOM samples, a small portion cut from the center of the filter was used for analyses. All samples were analyzed for 815N and 813C by the Uni- versity of California Stable Isotope Facility with a PDZ Europa ANCA-GSL elemental analyzer (Sercon, Ltd., 332 Fishery Bulletin 1 13(3) Crewe, UK) interfaced with a PDZ Europa 20-20 iso- tope ratio mass spectrometer (Sercon, Ltd.). Data analyses Field data Data on water quality, reef structure, and organism abundance (dependent variables) were ana- lyzed separately by season. For all analyses, a sig- nificance level of alpha=0.05 was used, and results are presented as means with standard errors. Unless otherwise indicated, SAS software, vers. 9.2 (SAS In- stitute, Inc., Cary, NC) with the GLIMMIX procedure was used for all analyses. Data for water quality, reef structure, and resident oyster reef community were analyzed by using separate generalized linear mixed models (GLMMs) to test for the effects of harvesting (independent variable), with station used as a nested random effect to remove effects of station variation. Bottom DO, salinity, temperature, chlorophyll-a, TPM, water depth, and index of integrity were examined by harvesting treatment (actively harvested and nonhar- vested) with GLMMs that used station as a nested random effect to remove effects of station variation. To examine differences in depth and index of integrity, GLMMs were run with a normal distribution. Densi- ties of market- and seed-size oysters, mussel density, volume of loose shells, and volume of shell clusters were also analyzed by harvest treatment with station as a nested random effect; in addition, a negative bi- nomial distribution with a log-link function was used to account for overdispersion. Significant results for water quality and reef structure parameters were de- termined with a type-III test of fixed effects. Vertical relief for the 2 harvesting treatments was compared with a 2-sample /-test. Specifically, vertical relief, the difference between the 2 extreme depth measures, was calculated at each station, for 3 stations per site (N=6 [3 stationsx2 sites]). For resident oyster reef communi- ties, GLMMs with a negative binomial distribution and a log-link function to account for overdispersion were run on common species density (species representing >1% of total abundance), invertebrate density, fish den- sity, total nekton density (fishes and invertebrates com- bined), and total number of species. Significant results for resident community parameters were determined with a type-III test of fixed effects. For examination of species— environment relation- ships, canonical correspondence analysis (CCA) was performed with CANOCO software, vers. 4.5 (Wa- geningen UR, Netherlands; ter Braak and Smilauer, 2002) to analyze the relationship between abun- dances of common resident species and environmen- tal variables (water quality and reef structure), by combining all summer and fall catches. Summer and fall catches were combined to increase the number of samples per species and to focus on species-envi- ronment relationships that held true, regardless of season. The number of environmental variables was reduced by using backward selection, sequentially re- moving the least influential variable until 4 variables remained. Species abundances were logU +1) trans- formed for the CCA to improve normality. A Monte Carlo simulation test was used to determine statisti- cal significance of canonical axes with 1000 simula- tions on the full model. Stable isotope data Isotope data were analyzed by sea- son. Isotope values of 815N to 813C were used to deter- mine contributions of basal food sources (BFSs; marsh plant and FPOM) and consumer trophic positions (de- pendent variables). Contributions of BFSs to naked goby, freckled blenny, skilletfish, grass shrimp, flatback mud crabs, eastern oysters, and CPOM were deter- mined for each site by using a 2-source mixing model (Fry, 2006), with the mean S13C values of dominant marsh plants and FPOM from each site. Trophic posi- tion (TP) was determined with the following equation: TP = 1 + (8iriNorganism — 815Ngase)/T'F)F1 (Post, 2002), where a trophic enrichment factor (TEF) of 2.54% was used (Vanderklift and Ponsard, 2003; Caut et ah, 2009). Separate 2 sample /-tests were used to test for dif- ferences between harvest treatments (independent variable) for the trophic position and BFS contributions of dominant species (Post, 2002; Layman et ah, 2007). The convex hull area (the smallest area that incorpo- rates all isotope biplot points for individual species or communities) were calculated and used as a means to represent the trophic diversity within a food web (Lay- man et al., 2007), but they were not statistically tested because there was only one set of convex hull areas per site (no replication). Convex hull areas were con- structed with the convex hull option in the XTools Pro toolbar in ArcMap, the central application of ArcGIS, vers. 9.3.1 (Esri, Redlands, CA). Data for harvest treat- ments that were not normally distributed were com- pared with a nonparametric Wilcoxon rank-sum test. Results Field data Water quality In the summer, there were no differ- ences in temperature, salinity, and DO between har- vested and nonharvested treatments (Table 1). Levels of TPM and chlorophyll-a were higher at the harvested site, Sister Lake (44.2 mg/L [SE 3.2] and 18.0 pg/L [SE 2.0]), than at the nonharvested site, Sabine Lake (17.9 mg/L [SE 3.5] and 8.2 pg/L [SE 0.4]). In the fall, there were no differences in temperature or DO between harvest treatments (Table 1). Chloro- phyll-a levels were higher at the harvested site, south- ern Calcasieu Lake (16.9 pg/L [SE 0.4]), than at the nonharvested site, northern Calcasieu Lake (8.6 pg/L [SE 0.3] ). Salinity was significantly higher at the non- harvested site (20.0 [SE 0.2]) than at the harvested site (19.2 [SE 0.2]), although the difference was prob- ably not ecologically important. Beck and La Peyre: Effects of oyster harvesting activities on Louisiana reef habitat and resident nekton communities 333 TabSe 1 Mean measurements of water quality and reef structure for sampled oyster reefs in Louisiana during summer and fall 2010. Degrees of freedom (dD for P-values are provided in parentheses and apply to all results except for reef vertical re- lief, for which df=2 and a 2-sample f-test was used to compare treatments. Significant differences (P< 0.05) between harvest treatments are indicated with asterisks (*). Standard errors of the mean are provided in parentheses. NH=not harvested; AH=actively harvested. Summer Fall Parameter Sabine Lake (NH) Sister Lake (AH) F- value P-value North Calcasieu (NH) South Calcasieu (AH) E-value P-value Temperature (°C) 31.0 (0.2) 31.1 (0.2) 0.02 0.89 26.4 (0.8) 24.9 (1.1) 1.28 0.32 Salinity 13.0 (1.2) 12.0 (0.4) 0.56 0.49 20.0 (0.2) 19.2 (0.1) 12.53 0.024* Dissolved oxygen (mg/L) Total particulate 5.2 (0.3) 4.4 (0.3) 0.38 0.57 6.9 (0.1) 6.3 (0.2) 2.55 0.19 matter (mg/L) 17.9 (3.5) 44.2 (3.2) 9.78 0.04* 75.6 (1.1) 90.2 (5.3) 6.36 0.07* Chlorophyll-a (pg/L) 8.2 (0.4) 18.0 (2.0) 18.89 0.01* 8.6 (0.3) 16.9 (0.4) 244.88 <0.0001* Cluster volume (L) 3.9 (0.1) 2.9 (0.2) 3.82 0.12 4.4 (0.1) 1.8 (0.1) 221.38 <0.0001* Loose shell volume (L) 0.3 (0.1) 0.8 (0.2) 1.8 0.25 0 2.0 (0.1) 80.7 0.0008* Reef integrity (unitless) 0.8 (0.1) 0.6 (0.1) 10.06 0.004* 0.9 (0.1) 0.8 (0.1) 4.52 0.04* Reef depth (m) 2.6 (0.02) 1.9 (0.03) 10.58 0.03* 1.2 (0.01) 1.8 (0.01) 88.32 0.0007* Reef vertical relief (m) Total oyster density 0.20 (0.00) 0.17 (0.03) 1.00 (df=2) 0.42 0.67 (0.03) 0.10 (0.00) 1.00 (df=2) 0.42 (no./tray) Market size oyster density 67.0 (2.9) 114.8(16.4) 0.83 0.41 70.5 (4.5) 20.7 (1.1) 131.22 0.0003* (no./tray) Seed size oyster density 32.3 (1.8) 9.2 (1.1) 40.54 0.003* 17.5 (0.4) 12.6 (0.7) 6.42 0.06 (no./tray) 34.7 (2.3) 101.5 (16.5) 2.02 0.23 43.1 (3.9) 6.0 (0.7) 58.12 0.0016* Mussel density (no./tray) 636.4 (61.0) 319.2 (79.2) 2.39 0.2 1424.7 (22.5) 54.7 (5.7) 3724.47 <0.0001* Reef structure In the summer, there were no differenc- es in the volume of loose shells, shell clusters, vertical relief, total oyster density, seed oyster density, or mus- sel density (Table 1). Reef integrity, depth, and density of market-size oysters were lower at the harvested site (0.6 [SE 0.1], 1.9 m [SE 0.03], and 9.2 individuals/tray [SE 1.1], respectively) than at the nonharvested site (0.8 [SE 0.1], 2.6 m [SE 0.02], and 32.3 individuals/tray [SE 1.8], respectively). In the fall, there were no differences in vertical relief or in density of market-size oysters (Table 1). Volume of shell clusters was higher at the nonharvested site than at the harvested site: 4.4 L (SE 0.1) versus 1.8 L (SE 0.1). Conversely, loose shell volume was higher at the harvested site than at the non-harvested site: 2.0 L (SE 0.1) versus 0.0 L (SE 0.0). Reef depth was greater at the harvested site than at the nonharvested site: 1.8 m (SE 0.01) versus 1.2 m (SE 0.01). Total oyster density, seed oyster density, and mussel density were higher at the nonharvested site (70.5 individuals/tray [SE 4.5], 43.1 individuals/tray [SE 3.9], 1424.7 individ- uals/tray [SE 22.5], respectively) than at the harvested site (20.7 individuals/tray [SE 1.1], 6.0 individuals/tray [SE 0.7], 54.7 individuals/tray [SE 5.7], respectively). Nekton community In the summer, 14 tray samples were collected at the nonharvested site, and 12 tray samples were collected at the harvested site (48% tray retrieval success rate) for a total of 26 trays. Densities of naked goby and estuarine mud crabs ( Rhitliropano - peus harrisii ) were higher at the harvested site (102.8 individuals/m2 [SE 21.4], 20.1 individuals/m2 [SE 6.3]) than at the nonharvested site (9.4 individuals/m2 [SE 1.6], 0.7 individuals/m2 [SE 0.4]) (Table 2). The num- ber of invertebrate species and total number of species also were greater at the harvested site (5.5 individu- als/m2 [SE 0.4], 9.0 individuals/m2 [SE 0.5]) than at the nonharvested site (3.4 individuals/m2 [SE 0.2], 6.2 individuals/m2 [SE 0.3]). In the fall, 15 tray samples were collected at the nonharvested site, and 17 tray samples were collected at the harvested site (66% tray retrieval success rate) for a total of 32 trays. Densities of grass shrimp were greater at the nonharvested site, with a mean of 132.6 individuals/m2 (SE 17.0) than at the harvested site, with a mean of 65.6 individuals/m2 (SE 12.7) (Table 2). The number of fish species was also greater at the non-harvested site than at the harvested site: 2.5 indi- viduals/m2 (SE 0.2) versus 1.5 individuals/m2 (SE 0.2). Species environment The CCA indicated a significant relationship between nekton assemblage structure and environmental variables (P=0.001; Fig. 4). The horizontal axis, which explained 58.3% of the variation 334 Fishery Bulletin 113(3) labile 2 Mean species density (individuals/m2), mean number of species captured, and F-values and P-values from generalized linear mixed models run, by site for species collected in summer and fall 2010 at actively harvested (AH) and nonharvested (NH) oyster reefs in Louisiana. Degrees of freedom for F-values are provided in parentheses. Significant differences (P<0.05) be- tween harvest treatments are indicated by asterisks (*). Only species that contributed to more than 1% of the total catch were analyzed statistically. Note that n refers to the number of trays successfully sampled for abundance data. Standard errors of the mean are provided in parentheses. Summer Fall Scientific name Sabine Lake (NH) 71=14 Sister Lake (AH) 71=12 F( 1,4) P-value North Calcasieu Lake (NH) tz=15 South Calcasieu Lake (AH) 72 = 17 F (1, 4) P-value Gobiosorna bosc 9.4 (1.6) 102.8 (21.4) 19.26 0.01* 49.7 (6.2) 51.9 (2.8) 0.06 0.82 Hypsoblennius ionthas 7.8 (2.1) 18.2 (5.0) 0.08 0.8 1.5 (0.6) 0.8 (0.4) 0.27 0.63 Gobiesox strumosus 3.3 (0.9) 10.6 (2.9) 1.32 0.31 3.9 (0.9) 0.8 (0.6) 6.17 0.07 Chasmodes bosquianus 0.7 (0.4) 2.3 (1.0) 1.5 (0.6) 0.8 (0.4) Opsanus beta 3.3 (1.2) 1.5 (0.9) 0 0.3 (0.3) Myrophis punctatus 0 2.7 (1.6) 0 0 Lutjanus griseus 0 0.4 (0.4) 0.6 (0.4) 0 Chaetodipterus faber 0.3 (0.3) 0.4 (0.4) 0 0 Gobionellus boleosoma 0.3 (0.3) 0.4 (0.4) 0 0 Paralichthys lethostigma 0.3 (0.3) 0 0 0 Fish density 25.4 (3.4) 139.2 (26.0) 10.17 0.03* 57.3 (6.2) 54.6 (2.8) 0.17 0.7 Number of fish species 2.8 (0.3) 3.5 (0.4) 1.16 0.34 2.5 (0.2) 1.5 (0.2) 11.69 0.03* Eurypanopeus depressus 74.8 (12.1) 106.9 (15.3) 1.96 0.23 173.5 (17.9) 171.0 (14.3) 0.03 0.87 Palaernonetes spp. 207.7(28.8) 103.9 (36.3) 2.02 0.23 132.6 (17.0) 65.6 (12.7) 8.98 0.04* Panopeus simpsoni. 22.4 (2.8) 13.7 (2.7) 4.91 0.09 0.9 (0.7) 15.8 (2.4) 5.97 0.07 Callinectes sapidus 0 14.0 (5.2) 3.28 0.14 13.9 (4.2) 15.5 (5.2) 5.33 0.08 Rhithropanopeus harrisii 0.7 (0.4) 20.1 (6.3) 19.26 0.01* 0 0 Alpheus heterochaelis 0.7 (0.4) 9.1 (2.6) 0.3 (0.3) 4.6 (1.7) Menippe adina 0.3 (0.3) 4.6 (1.3) 2.1 (0.8) 5.6 (1.4) Farfantepenaeus aztecus 0.3 (0.3) 1.5 (1.0) 0 0.8 (0.6) Petrolisthes armatus 0 0 0 0.3 (0.3) Clibanarius uittatus 0 0.8 (0.8) 0 0 Invertebrate density 306.8 (29.8) 274.5 (37.8) 0.41 0.56 323.4 (22.9) 279.2 (22.3) 1.34 0.13 Number of invertebrate species 3.4 (0.2) 5.5 (0.4) 14.26 0.02* 3.2 (0.3) 3.4 (0.2) 4.87 0.09 Total density 332.2 (29.4) 413.7 (55.9) 0.1 0.77 380.7 (21.0) 333.8 (24.5) 1.82 0.25 Total number of species 6.2 (0.3) 9.0 (0.5) 23.9 0.008* 5.7 (0.3) 6.3 (0.3) 1.69 0.26 in nekton assemblage (eigenvalue=0.11), was highly correlated with reef integrity (coefficient of correla- tion [?-]--0.69) and distinguished species that prefer fragmented reef habitats. Species, such as the big- claw snapping shrimp ( Alpheus heterochaelis ) and the estuarine mud crab, were associated with reefs with low integrity values (<50%). The vertical axis, which accounted for 27.7% of the variation (eigenvalue=0.05), was negatively associated with volume of loose shells (r=-0.70) and positively associated with total number of live oysters (r=0.70), and this axis distinguishes spe- cies that prefer live oyster habitats. Species, such as the freckled blenny {H. ionthas) and skilletfish, were strongly positively associated with the number of live oysters. Stable isotopes For the summer sampling, results from a 2-source mix- ing model indicated that pelagic basal food sources (i.e., FPOM) contributed more to the food web of the resi- dent community on the sampled oyster reefs than the nonpelagic sources (i.e., marsh plant) regardless of har- vest treatment (all values of source fractions of FPOM were >0.50; Table 3). The pelagic source contribution was higher for flatback mud crabs at the nonharvested site (0.65 [SE 0.03]) than at the harvested site (0.53 [SE 0.04]). The trophic positions of the hooked mus- sel, eastern oyster, grass shrimp, skilletfish, and naked goby were elevated at the harvested site compared to the nonharvested site (Fig. 5). Beck and La Peyre: Effects of oyster harvesting activities on Louisiana reef habitat and resident nekton communities 335 -1.0 1.0 Figure 4 Canonical correspondence biplot relating species abundances with hab- itat variables at actively harvested and nonharvested oyster reefs of coastal Louisiana during 2010. The horizontal axis accounts for 58.3% of variation (eigenvalue: 0.11), and the vertical axis accounts for 27.7% of variation (eigenvalue: 0.05). Species abbreviations: Asp=bigclaw snapping shrimp (Alpheus heterochaelis ), Ed=flatback mud crab ( Eu - rypanopeus depressus, Gb=naked goby ( Gobiosoma bosc), Gs =skil- letfish ( Gobiesox strumosus ), Hi=freckled blenny ( Hypsoblennius lonthas ), Ps=oystershell mud crab ( Panopeus Si?npsoni), Pspp=grass shrimp ( Palaemonetes spp.), Rh= estuarine mud crab (Rhithropanopeus harrisii). For the fall sampling, pelagic source contributions were also found to contrib- ute more to the resident community food web than the nonpelagic sources at both harvested and nonharvested sites. Pelag- ic source contributions were elevated at the harvested site for all organisms ex- cept skil letfish. The trophic positions of all organisms were elevated at the har- vested site, except that of eastern oysters. Discussion Oyster reef structure, as defined by the extent of solid reef, number and size of live oysters, number of mussels, and in- terstitial space, can be substantially al- tered by oyster harvesting activities in coastal Louisiana. Such changes in reef structure did not translate into signifi- cant differences in the resident nekton community. Although harvested reefs were more fragmented and sometimes had fewer living oysters and mussels than nonharvested reefs, habitat use and food resources associated with the 2 types of reefs were similar. These re- sults indicate that, although oyster har- vest can change the composition of the reef matrix and alter habitat complexity, as long as adequate structural material is maintained, a reef provides suitable habitat for resident communities of small organisms. Most models of reef degradation from harvest indicate that a loss of vertical re- lief and complexity lead toward increased stress on an oyster population and loss of oyster reef function (Rothschild et al., 1994; Lenihan and Peterson, 1998; Leni- han, 1999); however, we dealt with subtidal reefs with limited vertical relief. Vertical relief of all reefs in our study ranged from 10 to 20 cm, and reefs were located in depths of 1.2-2. 9 m. Whether nonharvested reefs lacked relief because of degradation from historic ac- tivities or as a result of environmental constraints is unknown because of a lack of data from the early part of the 20th century. In contrast with a lack of difference in vertical relief, harvested and nonharvested reefs differed substantial- ly in the composition of reef matrix. As expected, more large live oysters, as well as less reef fragmentation and loose shells, were found at nonharvested sites than at the harvested reef areas. The lack of larger oysters at harvested reefs, a direct consequence of harvest ac- tivities, has been documented previously (Lenihan and Micheli, 2000; Lenihan and Peterson, 2004). The in- crease in fragmentation and loose shells at harvested sites may be due to physical damage from a dredge or due to the frequent placement of shells as cultch by the Louisiana Department of Wildlife and Fisheries within the harvested sites (LDWF2). The combined effects of more loose shells, fewer shell clusters, and solid reef area may make the harvested reefs more susceptible to complete reef loss with overharvesting and with the scattering and sedimentation that occurs during storm events. However, as noted previously, flat reefs without small-scale changes in vertical relief are typical of this region. Many of these reefs have existed and been har- vested since record keeping began around 1900. Despite these differences in the oyster reef matrix, there were no consistent differences between treat- ments in the overall abundance or diversity of reef- associated nekton communities during fall and summer sampling. This lack of difference in nekton density at reefs with different physical and biological character- istics is similar to that found with other studies of ar- tificial reefs of varying heights (Lenihan et al., 2001), 336 Fishery Bulletin 113(3) Beck and La Peyre: Effects of oyster harvesting activities on Louisiana reef habitat and resident nekton communities 337 613C B 16 12 ■ 2 in Lo 8 -10 -30 Ik o o -25 -20 513C □ □ -15 1 -10 Figure § Biplot of mean 813C and 815N values of basal food sources and dominant faunal species sampled at 4 sites in coastal Louisiana in 2010: (A) Sabine Lake (nonharvested) and Sister Lake (actively harvested) in the summer and (B) northern (nonharvested) and southern (actively harvested) Calcasieu Lake in the fall. Error bars are omitted for simplicity; standard errors of the mean and sample sizes ( n ) are located in Table 3. Shaded symbols indicate means for harvested sites, and open symbols indicate means for nonharvested sites. Symbols for various organisms: large circle=fine particulate organic matter, square=marsh plant, x=coarse particulate organic matter, large dash=hooked mussel ( Ischadium recurvum), crossed x=eastern oyster ( Crassostrea virginica), diamond=flatback mud crab (Eurypanopeus depressus), short dash=grass shrimp ( Palaemonetes spp.), triangle=skittlefish ( Gobiesox strumosus ), plus sign=freckled blenny ( Hypsoblennius ionthas), and small circle=naked goby (Gobiosoma bosc). shell density and vertical relief (Humphries et ah, 2011b), and reefs with and without the presence of live oysters (Tolley and Volety, 2005; Summerhayes et ah, 2009). Although ecological theory holds that structur- ally complex habitats are expected to sustain higher densities and more diverse communities than structur- ally simple ones, defining structural complexity has never been straightforward (Beck, 1998; Bartholomew et ah, 2000), and it is not clear whether the harvested and nonharvested sites represented different levels of complexity or just differences in habitat characteris- tics. No consensus exists as to how to define oyster reef complexity; in some experiments oyster or shell den- sity, vertical relief, or mixtures of unaggregated shells (simple) versus clusters (complex) were used, making it difficult to determine when complexity had actually changed (Grabowski and Powers, 2004; Grabowski et al., 2008; Humphries et ah, 2011a). The use of similar volumes of reef material in the trays may have contributed to the similarity of resi- dent communities at our paired sites, but observed dif- ferences in the reef matrix may be important in deter- mining preferred habitats of resident organisms. The use of 5.0 L of local reef substrate (an amount that corresponds to 22.7 L/m2) to completely fill each sample tray may have resulted in densities of reef material that were beyond a threshold at which differences in nekton abundances can be noted (e.g., Humphries et ah, 2011b). Samples obtained by diving on historic, cre- ated, and harvested reefs in the region have provided reef material sample volumes up to 11 L/m2 in the top 10 cm of substrate (La Peyre et ah, 2014b). The loose matrix of substrate material created by dredging and filling trays may have resulted in increased small in- terstitial spaces and elevated habitat availability. Despite this potential criticism, tray substrate differ- ences were observed between harvest treatments. The similarity of species diversity and community composi- tion remains striking and indicates that the sampled harvested and nonharvested areas still support similar nekton communities, although specific niches for cer- tain species were identified by apparent preferences for reef subhabitats. The CCA results indicate that the bigclaw snapping shrimp ( Alpheus heterochaelis) and estuarine mud crab are associated with fragmented reef habitats exposed to high levels of chlorophyll-a and that the skilletfish and freckled blenny are associ- ated with the presence of shell clusters (larger intersti- tial spaces) and high densities of live oysters. Oysters are known to transfer nutrients from the water column to the benthos; however, the observed decrease in the number and size of live oysters at harvested sites, compared with the number and size at nonharvested sites, may have other trophic effects beyond a decrease in benthopelagic coupling. Filtration rate on a reef is generally held to increase with oys- ter biomass (Cloern, 1982; Officer et al., 1982; Dame, 1996). In our study, mean levels of chlorophyll-a at 338 Fishery Bulletin 113(3) harvested sites consistently were double the levels at nonharvested sites. The reduced number of large oys- ters and mussels combined with a probable reduction in overall numbers of other sessile filter-feeding organ- isms at harvested reefs may contribute to decreased filtration capacity (Dame et al., 1989; Cressman et al., 2003). Resident communities at both types of oyster reefs appear to depend primarily on pelagic basal food sourc- es (i.e., FPOM). The increase in the fractions of detrital source (i.e., marsh plant), combined with elevated chlo- rophyll-a levels, indicates a reduction in benthopelagic coupling services at harvested reefs. Benthic microal- gae could also contribute to the food webs of oyster reef communities; however, in San Antonio Bay, Texas (also a shallow, turbid estuary), the microphytobenthos con- tributed less than 2% of the primary production found in the water column (MacIntyre and Cullen, 1996). Benthic macroalgae, seagrass epiphytes, and upstream terrestrial plant matter can also contribute to the bas- al food source (Abeels et al., 2012), but these sources were not observed within the studied reef areas. Trophic position of resident organisms on harvested oyster reefs was slightly elevated in comparison with nonharvested reefs, but trophic order was maintained. Although deriving a TEF specific to these systems may result in different estimates of trophic positions, the trends observed would not change. Differences in tro- phic position of resident species have also been found between reefs and mud-bottom sites (Quan et al., 2012) and between reefs that were experiencing different riv- erine exposures (Abeels et al., 2012). In these instances, trophic shifts may be attributed to increased infaunal diversity associated with combined mud and shell substrate or to increased phytoplankton abundance from riverine inputs. For example, there is evidence that a lower abundance of filter feeders may result in increased zooplankton abundance (Lonsdale et al., 2009) and potentially in a more diverse plank- tonic community. Elevated chlorophyll-a levels indicate increased phytoplankton abundance at harvested sites. Increased planktonic diversity or higher densities of top planktonic predators (ctenophores) could explain the increase in the trophic position of CPOM at har- vested reefs. For the remainder of species, the mainte- nance of the trophic order for the 2 reef types and the lack of consistent difference in convex hull areas is an indication that the differences in the reef matrix be- tween the harvested and nonharvested sites that were documented in this study did not result in significant changes in feeding behaviors, but the observed shifts in trophic positions and CCA results indicate that reef alteration may have affected the planktonic and infau- nal forage base. Changes in populations of oysters and in the bio- genic reefs that these ecosystem engineers create are predicted to have effects on surrounding community structure and ecosystem processes. The results of this study indicate that, on the public oyster grounds in Louisiana, effects of harvesting are subtle for reef types in close proximity (northern and southern Cal- casieu Lake) and for those across larger areas (Sabine and Sister lakes). Oyster harvesting practices that al- ter the reef matrix yet preserve live oysters and reef substrate may still provide important habitat for the resident nekton community. What has yet to be exam- ined is whether there is a threshold of reef habitat area, oyster density, or oyster size distribution below which ecosystem services will be severely compromised. Acknowledgments Funding for this project was provided by the Louisiana Department of Wildlife and Fisheries through support to the Louisiana Cooperative Fish and Wildlife Unit of the U.S. Geological Survey. We thank P. Banks, B. Fry, J. Fleeger, M. Kaller, S. Miller, B. Eberline, J. Fur- long, C. Hodnett, C. Duplechain, L. Broussard, G. De- cossas, A. Catalanello, M. Fries, W. 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Smilauer. 2002. CANOCO reference manual and CanoDraw for Windows user’s guide: software for canonical commu- nity ordination (vers. 4.5), 500 p. MicrocomputerPower, Ithaca, NY. Thompson, B. A. 1986. Identification guide to selected estuarine fishes of Louisiana. Louisiana Sea Grant College Program and Louisiana State Univ. Coastal Fisheries Institute LSU-CFI-86-05, 29 p. Center for Wetlands Resources, Louisiana State Univ., Baton Rouge, LA. [Available at website.] Tolley, S. G., and A. K. Volety. 2005. The role of oysters in habitat use of oyster reefs by resident fishes and decapod crustaceans. J. Shell- fish Res. 24:1007-1012. Vanderklift, M. A., and S. Ponsard. 2003. Sources of variation in consumer-diet 15N enrich- ment: a meta-analysis. Oecologia 136:169-182. Yeager, L. A., and C. A. Layman. 2011. Energy flow to two abundant consumers in a sub- tropical oyster reef food web. Aquat. Ecol. 45:267-277. zu Ermgassen, P. S. E., M. D. Spalding, R. E. Grizzle, and R. D. Brumbaugh. 2013. Quantifying the loss of a marine ecosystem service: filtration by the eastern oyster in US estuaries. Es- tuar. Coasts 36:36-43. 341 NOAA National Marine Fisheries Service Abstract— The time series of esti- mated fishery exploitation rates for endangered Sacramento River winter Chinook salmon ( Oncorhyn - chus tshawytscha) is confined to a relatively recent period for which coded-wire tag data have been avail- able. However, the nature of ocean salmon fisheries before this period was substantially different, and it is likely that recent exploitation rates do not represent the level of fish- ing mortality experienced by these Chinook salmon in earlier years. To infer historical exploitation rates, a model was developed to hindcast the impact rate for age-3 winter Chinook salmon (an approximation of the ex- ploitation rate) by using 35 years of fishing effort estimates coupled with contemporary estimates of fishery encounter rates. The impact-rate hindcasts were highest during a pe- riod from the mid-1980s through the mid-1990s. Over time, the proportion of the impact rate attributed to com- mercial and recreational fisheries diverged from approximately equal shares early in the time series to an impact rate mostly composed of rec- reational fishery-induced mortality in more recent years. The inferred exploitation rates provide context for the fishing-induced mortality ex- perienced by winter Chinook salmon both before and after the time of the initial inclusion of this species on the Endangered Species Act (ESA) list in 1989 and through a dynamic period for ocean salmon fisheries in California. Manuscript submitted 1 October 2014. Manuscript accepted 2 June 2015. Fish. Bull. 113:341-351 (2015). Online publication date: 16 June 2015. doi: 10.7755/FB. 113.3.9 The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA. Fishery Bulletin & established 1881 ■20 in [51 cm] in total length) have been imposed on the recreational sector in an effort to reduce retention of SRWC. For a vari- ety of reasons associated with increased constraints on ocean fishing that have resulted from ESA listings and river (versus-ocean) allocations of harvest, the com- mercial sector has seen a reduction in participation of vessels with California salmon permits since the early 1980s (PFMC2). The time series of commercial and rec- reational fishing effort south of Point Arena (Fig. 2) indicates that substantial changes in ocean fishery ef- 2 PFMC (Pacific Fishery Management Council). 2014. Re- view of 2013 ocean salmon fisheries: stock assessment and fishery evaluation document for the Pacific coast salmon fish- ery management plan, 371 p. (Document prepared for the Council and its advisory entities.) Pacific Fishery Manage- ment Council, Portland, OR [Available at website.] 3 PFMC (Pacific Fishery Management Council). 2015. Pre- season report I: stock abundance analysis and environmental assessment part 1 for 2015 ocean salmon fishery regulations, 135 p. (Document prepared for the Council and its advisory entities.) Pacific Fishery Management Council, Portland, OR. [Available at website.] O'Farrell and Satterthwaite: Inferred historical fishing mortality rates of Oncorhynchus tshawytscha 343 1978 1982 1986 1990 1994 1998 2002 2006 2010 Year Figure 2 Estimates of commercial (black line) and recreational (gray line) sector fishing effort for the years 1978-2012 in ocean areas south of Point Arena, California. Direct estimates of the Sacramento River winter Chinook salmon ( Oncorhynchus tshawytscha) impact rate have been made with cohort reconstruction methods for the years to the right of the dashed line (post-2000). Note that fishing effort units differ between the commercial and recreational fisher- ies and are not directly comparable. fort have occurred since the late 1970s and the inferred fishing effects for recent SRWC cohorts may not be indicative of earlier ex- ploitation patterns. In this article, we describe a model for the hindcasting of fishery impact rates to assess the implications for SRWC fishing mortality resulting from changes in California salmon fisheries that have occurred over the past 35 years. The model uses data on historical fish- ery regulations and estimates of fishing effort in California salmon fisheries in 1978-2012, and it couples these estimates with contact (i.e., fishery encounter) rates per unit of fish- ing effort estimated for recent years (2000- 2012), to generate hindcasts of the impact rate for years when direct estimation is not possible. To fully parameterize the model, we developed a procedure to infer contact rates per unit of effort for months when no direct estimates exist because of the contraction of modern fisheries in relation to fisheries from the 1970s through the 1990s. The model structure is similar to the Winter Run Har- vest Model (WRHM; O’Farrell et al., 2012b), a tool used to forecast the impact rate during the annual PFMC salmon fishery planning process. Although we are not able to recon- struct the complete SRWC exploitation his- tory, the extension of the impact rate time series back to 1978 encompasses a dynamic period for California ocean salmon fisheries and provides more context for the current levels of ocean fishing mortality. Materials and methods Impact-rate model The data and model used for this analysis were strati- fied by year (y), month (t), management area (z), and fishery sector (x). Because harvest of SRWC is rare north of Point Arena, California (O’Farrell et al., 2012a; Satterthwaite et al. 2013), the spatial extent of our model is limited to the 2 ocean management ar- eas south of Point Arena: San Francisco (SF) and Mon- terey (MO) (Fig. 1). The MO management area extends from Pigeon Point to the border of the United States and Mexico, but salmon harvest is generally small and more variable south of Point Sur. Fishery sectors in- clude commercial and recreational. Fishery impacts (I) included fish that died because they were retained as harvest iH), fish that were re- leased because they were smaller than the minimum size limit and died because of release mortality (S), and fish that died from “dropoff” mortality (D) that occurs when fish are encountered by fishing gear but not suc- cessfully retrieved. Mortality related to an encounter with gear can come from multiple sources, such as a hooking injury or predators (PFMC4, and the refer- ences therein). The impact rate is defined as the to- tal fishing mortality, acute and delayed, divided by the starting cohort abundance. The impact-rate model simulates the age-3 cohort abundance from the beginning of age 3, f=February of year by), to t=January of year y+1, Nt+1 = (Nt - h)( 1-v). (1) by deducting monthly impacts, /t = Xz>x^t,z,x’ and ac- counting for the natural mortality rate v. Application of Equation 1 over months t enables the computation of the annual impact rate, defined as the sum of monthly impacts divided by the initial abundance of age-3 fish: i = _ (2) February Impacts are computed from a string of equations initiated by an estimate of the contact rate c, which is formulated as the contact rate per unit of effort (3, multiplied by the amount of fishing effort f, 4 PFMC (Pacific Fishery Management Council). 2000. STT recommendations for hooking mortality rates in 2000 rec- reational ocean Chinook and coho fisheries. STT Rep. B.2, 18 p. Pacific Fishery Management Council, Portland, OR. [Available at website.] 344 Fishery Bulletin 113(3) ct,z,x — A;,z,x x /t,z,x- (3) The number of fish contacted (C) is computed by mul- tiplying the oceanwide abundance of the SRWC age-3 cohort by the contact rate: Ct,Z,X = ct,z,x X -^t) (4) where contacts represent the number of fish that en- countered the fishing gear and were retrieved to the boat. Impacts are the sum of harvest, release, and dropoff mortality: ^t,Z,X = Ht,Z,X + “St.Z.X + ^t,Z,X (5) where Ht,Z,X — C t,z,x x P t,z,x> (6) ^t,Z,X — 1C(;x x d. (8) In these equations, release and dropoff mortality rates are denoted by s and d, respectively, and p is the esti- mated proportion of the cohort that is greater than or equal to the legal size for retention in the fishery. Data, parameters, and variables Effort in California ocean salmon fisheries was es- timated by the California Department of Fish and Wildlife (CDFW) on the basis of landing receipts from the commercial sector and dockside samples from the recreational sector. Units of fishing effort are the number of vessel days (the number of days fished by commercial salmon vessels) for the commercial sector and number of angler days for the recreational sector. Fishing effort for the years 1978-2012 are reported in PFMC2 and an electronic record of the historical ocean salmon fishery effort and landings for the U.S. West Coast (PFMC5), maintained by the PFMC. Records of minimum size limits in California ocean fisheries for the years 1978-2012 were obtained from PFMC2 and an electronic record of the historical ocean salmon fish- ery regulations for the U.S. West Coast (PFMC6), main- tained by the PFMC. Coded-wire tag recovery data from ocean and river sampling programs were used in cohort reconstruc- tions for SRWC to estimate contact and impact rates in ocean fisheries for the years 2000-2012, following the methods described in O’Farrell et al. (2012a). Cohort reconstruction is the sequential estimation of a cohort’s abundance from the end of that cohort’s life span, when abundance is zero, to a specified earlier age (commonly age 2). Age-specific spawner escapement and harvest 5 PFMC (Pacific Fishery Management Council). 2014. Ocean salmon fishery effort and landings (Review Appendix A). Ex- cel workbook. PFMC, Portland, OR. [Available at website.] 6 PFMC (Pacific Fishery Management Council). 2014. Ocean salmon fishery regulations and chronology of events (Review Appendix C). PFMC, Portland, OR. [Available at website.] data are required, and natural mortality rates are as- sumed. Fishery contacts stratified by age, month, man- agement area, and fishing sector were computed by expanding the harvest by the estimated proportion of SRWC expected to be larger than or equal to the mini- mum size limit (C = H/p). Given an estimate of C, and the estimated abundance N, the contact rate was esti- mated by rearranging Equation 4 as follows: c = C/N. The impact rate was estimated from cohort reconstruc- tion in the same manner as that shown in Equation 2. It was implicitly assumed that contact and impact rates estimated from tagged, hatchery-origin fish are representative of the natural-origin SRWC population. Although it is difficult to directly evaluate this com- mon assumption (PSC7), there is some evidence that hatchery-origin indicator stocks have similar ocean dis- tributions and fishery exposure as those estimated for untagged stocks for which they serve as proxies (Weit- kamp and Neely, 2002; Satterthwaite et al., 2014). The hatchery-origin component of the total SRWC abun- dance is only a portion of the total abundance; for the years 2000-2010, the hatchery-origin component of fe- male SRWC spawners was <20% (Winship et al., 2014). Ocean salmon fisheries are sampled by the CDFW with a goal of sampling at least 20% of the harvest in each month, management area, and fishery sector. Heads are taken from all fish with a clipped adipose fin for coded- wire tag extraction and reading. A total of 4036 coded- wire tag recoveries were used in cohort reconstructions, 554 of which were from ocean fisheries (commercial and recreational), whereas the vast majority of the remain- ing recoveries were from spawner escapement surveys. Recreational, river harvest of SRWC is rare because of closures to the Sacramento River salmon fishery during much of the migration and spawning period. Contact rates and fishing effort estimated for each month, area, and sector open to fishing in 2000-2012 were used to calculate the contact rate per unit of ef- fort. For hindcasting purposes, values of the contact rate per unit of effort were derived for the entire peri- od of 1978 to 2012 with the application of the bootstrap method to the estimates of contact rates per unit of ef- fort for 2000-2012 (Efron and Tibshirani, 1993). These derived values of contact rate per unit of effort were then multiplied by the corresponding observed fish- ing effort for 1978-2012 to yield a set of contact rate hindcasts (Eq. 3). The bootstrap method used to char- acterize the contact rates per unit of effort is described later in the “Bootstrap” subsection. For strata for which these rates could not be estimated from available data sources, 2 methods were used to infer contact rates per unit of effort. Data sufficient for estimation of contact rates per unit of effort for recreational fisheries during Febru- ary and March are not available because recreational 7 PSC (Pacific Salmon Commission). 2005. Report of the ex- pert panel on the future of the coded wire tag program for Pacific salmon. Pacific Salmon Comm. Tech. Rep. 18, 230 p. [Available at website.] O'Farrell and Satterthwaite: Inferred historical fishing mortality rates of Oncorhynchus tshawytscha 345 fisheries in the 2000-2012 period were largely closed during these months. To infer contact rates per unit of effort for these strata, we used historical SRWC harvest data derived from marked (fin-clipped) nat- ural-origin fish from the brood years 1969-1970 that were recovered in ocean fisheries as age-3 fish during the calendar years 1971-1972 (CDFG8). Recreational fisheries in SF and MO in 1971-1972 opened in mid- February with a 22-in (56-cm) minimum size limit, and this timing of the start of the season and this mini- mum size restriction were similar for recreational fish- ing seasons through 1983. The average proportion of the recreational harvest of age-3 SRWC south of Point Arena that was taken in February-March for the years 1971-1972 (00 was 0.33. This proportion was assumed to be representative of the average fraction of the rec- reational harvest south of Point Arena that was taken in February and March for the years 1978-1983 ( 02 R Assuming that the contact rate per unit of effort was equivalent for February and March, and in manage- ment areas SF and MO, we used the root finding func- tion uniroot in the R statistical software, vers. 3.0.0 (R Core Team, 2013) to identify the value of contact rate per unit of effort that resulted in the difference between tpi and 02 that equaled zero. Put another way, we solved iteratively for the contact rates per unit of effort for February-March that resulted in 33% of the total recreational sector harvest occurring in Febru- ary-March, on average, for the years 1978-1983. Data sufficient for estimation of contact rates per unit of effort also do not exist for the commercial sec- tor in SF or MO in April and for the recreational sector in MO in October because fisheries in the 2000-2012 period were largely closed for these months. In the case when SF and MO commercial fisheries began in April, the estimate of contact rate per unit of effort for May was assumed. In the case when MO recreational fisher- ies extended into October, the contact rate per unit of effort for September was assumed. These assumptions had little effect on the results because April commer- cial fisheries and MO recreational fisheries in October were relatively rare, were short in duration, and at- tracted little effort. The proportion of SRWC expected to be of legal size for retention was determined on the basis of a size- at-age model derived for SRWC, described in O’Farrell et al. (2012a, 2012b), and the specified minimum size limit for retention in a fishery. For the growth mod- el, the size-at-age of individual fish in each month is assumed to be normally distributed, and the propor- tion of legal-size fish is estimated by evaluating the cumulative normal distribution at the minimum size limit, given the estimated mean and standard devia- tion. When a large minimum size limit is in effect for months when SRWC size-at-age is smallest (i.e., Febru- ary-May), very low estimates of the proportion of legal- 8 CDFG (Calif. Dep. Fish Game). 1989. Unpubl. report. De- scription of the winter Chinook Ocean Harvest Model. Ocean Salmon Project, Calif. Dep. Fish Game, Santa Rosa, CA. size fish can result. This scenario can translate into unrealistically low levels of harvest per contacted fish, and, conversely, into a very large estimate of contacts based on a single retained and sampled fish. As a re- sult, a lower bound on the proportion of legal-size fish of 0.035 is assumed. The value of 0.035 corresponds to the condition where a single coded-wire tag recov- ery results in contacts approximately equivalent to the lowest reconstructed abundance of age-3 fish estimated from cohort reconstruction (O’Farrell et ah, 2012a). Use of this lower bound value reduces the probability that an entire hatchery-origin cohort would be estimated to be contacted by the fishery in order to produce one harvested and sampled fish. Table 1 displays the size- at-age model parameters and the proportion of legal- size fish estimated for commonly employed minimum size limits in both the commercial and recreational fisheries. Release mortality rates were assumed to be 0.26 for the commercial sector and 0.14 for the recreational sec- tor, reflecting the conventional values used for the an- nual assessment of SRWC and other Chinook salmon stocks (PFMC4). An exception exists in the recreational sector, where release mortality rates for 1990-2012 were estimated on the basis of prevalence of mooching (drifting a hooked bait in the California recreational sector), and fish contacted with mooching gear expe- rience a higher rate of gut hooking and, therefore, a higher release mortality rate than that of troll-contact- ed fish (Grover et al., 2002). Derived from the results in Grover et al. (2002), estimates of the recreational release mortality rate range from 0.14 to 0.57 between 1990 and 2012 (Grover9). The dropoff mortality rate was assumed to be 0.05 for all months, areas, and sectors, reflecting the con- ventional value used for PFMC Chinook salmon assess- ment (PFMC4). The natural mortality rate was assumed to be 0.018, the monthly rate corresponding to an annual natural mortality rate of 0.20. The annual natural mortality rate of 0.20 is commonly assumed in many stock as- sessments (Quinn and Deriso, 1999) and is consistent with many PFMC Chinook salmon assessments (e.g., O’Farrell et al., 2012a, 2012b). Bootstrap A key source of uncertainty in the hindcasting of impact rates is variation in estimates of contact rates per unit of effort across years. To account for this variation, we performed 20,000 replicate computations of the impact rate for the years 1978-2012 by randomly sampling, with replacement, estimates of the contact rate per unit of effort from the years 2000-2012. This procedure effectively makes the assumption that annual variation in contact rate per unit of effort in 2000-2012 is rep- resentative of the entire time series for 1978-2012. For 9 Grover, A. 2013. Personal commun. Institute of Marine Sciences, Univ. Calif., Santa Cruz, Santa Cruz, CA 95064. 346 Fishery Bulletin 1 13(3) Table 1 Estimates of the mean (p) and standard deviation (a) of the size-at-age distribution, by month, and the resulting proportion of legal-size fish (p) under three commonly employed minimum size limits (/). Size units are total length in inches. P Year Month P o 1= 20 1= 24 1=26 y Feb 19.74 1.66 0.438 0.035 0.035 Mar 20.77 1.70 0.674 0.035 0.035 Apr 21.85 1.79 0.849 0.115 0.035 May 22.94 1.88 0.941 0.286 0.052 Jun 24.02 1.97 0.979 0.504 0.157 Jul 25.10 2.06 0.993 0.704 0.331 Aug 26.20 2.15 0.998 0.847 0.537 Sep 27.28 2.24 0.999 0.929 0.717 Oct 28.37 2.33 1.000 0.970 0.846 Nov 29.45 2.41 1.000 0.988 0.923 Dec 29.72 2.44 1.000 0.991 0.937 y+ 1 Jan 29.21 2.40 1.000 0.985 0.910 each replication, an estimate of contact rate per unit of effort was sampled independently for each month, management area, and sector in the period 2000-2012 and applied to the years 1978-2012. For the inferred contact rate per unit of effort in February and March for the recreational fishery, the root-finding procedure was performed as previously described in each of the 20,000 replications. Impact-rate uncertainty was char- acterized by the 0.68 percentile interval of the 20,000 replication bootstrap distribution (Efron and Tibshi- rani, 1993). For a normally distributed estimator, the 0.68 percentile interval corresponds to the mean ± 1 standard error (Zar, 1999). Results Model results provide evidence that the highest im- pact rates occurred between the mid-1980s and the mid-1990s followed by a substantial decrease (Fig. 3). For several years in the period 1985-1995, the lower bound of the 0.68 percentile interval exceeded the up- per bound of the 0.68 percentile interval for the post- 2000 period. The hindcasts from the impact-rate model generally captured the variation in the impact rates estimated directly from coded-wire tag data by using cohort reconstruction methods in recent years. There was evidence for a substantial difference in 1980 1985 1990 1995 Year 2000 2005 2010 Figure 3 Time series of hindcast impact rates for the years 1978-2012 for Sacramento River winter Chinook salmon (Oncorhynchus tshawyts- cha) south of Point Arena, California. The black line represents the median, and the shaded area indicates the 0.68 percentile interval of the bootstrap distribution. The dots indicate estimates of the im- pact rate derived with cohort reconstruction methods. the impact-rate trajectories between the commercial and recreational sectors (Fig. 4A). The impact-rate time series for the commercial sector showed a nearly mono- tonic decline from 1978 through 2012. In contrast, the impact rate for the recreational sector exhibited much more variation, and maximum impact rates occurred in the mid- dle of the time series. This pattern of sector- specific impact rates led to divergence in the proportions of the impact rate attributable to the 2 sectors over time (Fig. 4B). In the early portion of the time series (before the mid-1980s), the commercial and recreational sectors contributed approximately equally to the total impact rate. Subsequently, the share of the impact rate attributed to the recreational sector increased and stabilized at approximately 80% of the overall impact rate. Estimates of contact rates per unit of ef- fort that were used to inform the impact-rate hindcasts differed across fishery sectors and management areas (Fig. 5). Distributions of month-specific contact rates per unit of ef- fort in most cases were skewed, with the mean exceeding the median. This pattern was most evident in the MO management area where the maximum contact rates per unit of effort in both the commercial and recreational sectors were much higher than the corresponding sectors in the SF manage- O'Farrell and Satterthwaite: Inferred historical fishing mortality rates of Oncorhynchus tshawytscha 347 ment area, and, therefore, there were larger differences between the median and mean estimates of the con- tact rate per unit of effort in MO in relation to SF. In many cases, the median contact rates per unit of effort were zero, particularly in the commercial sector. For recreational fisheries in February and March, inferred contact rates per unit of effort were much higher than estimates for other months. These values were higher than all estimates of contact rates per unit of effort in the SF management area and were among the highest values observed in the MO area. These high contact rates per unit of effort were not unexpected given the high proportion of the total harvest that occurred in February and March, according to estimates derived from the data for 1971-1972 (0]=O.33), and given the low estimates of the proportion of legal-size fish for these months (Table 1). High levels of contact rates per unit of effort in February and March would be required to result in the substantial harvest propor- tions in those months and, therefore, to approximate the monthly harvest distributions from the data for 1971-1972. To evaluate whether the impact-rate hindcasts had a pattern similar to measures of fishing mortality for other stocks subjected to a common ocean fishery, we compared the median SRWC impact-rate hindcasts with Sacramento River fall Chinook salmon (SRFC) harvest rates directly estimated from coded-wire tag data. The SRFC stock is the largest contributor to ocean salmon fisheries south of Point Arena. Harvest rates were estimated by computing the ratio of SRFC adult (ages 3-5) harvest south of Point Arena to the Sacramento Index (the Sacramento Index is the sum of ocean harvest south of Cape Falcon, Oregon; river harvest; and spawner escapement; see O’Farrell et al., 2013, for a detailed description). The impact-rate hindcasts for SRWC were highly correlated to SRFC harvest rates in 1983-2012, the years for which the SRFC harvest rate is estimable (correlation coefficient [/■] =0.827, PcO.OOl) (Fig. 6). Discussion The large changes in California ocean salmon fisher- ies over the past 35 years have resulted in substantial changes to the levels of fishing mortality experienced by SRWC. Impact-rate hindcasts indicate lower rates in the 2000s than those in the mid-1980s through the mid-1990s. A decline in the impact rate was evident for the recreational sector following a peak in the 1980s and 1990s, and a decline has been observed for the commer- cial sector throughout the entire period. The trajectories of the sector-specific impact rates (Fig. 5A) reflect the observed changes in fishing effort (Fig. 2). The strong correlation between harvest rates for SRFC in the re- gion south of Point Arena and the impact-rate hindcasts for SRWC, where both populations have been subjected to the same fisheries, supports the hindcasting methods for calculating impact rates used in this study. In their analysis of the brood years 1998-2007, O’Farrell et al. (2012a) reported that exploitation rates experienced by SRWC averaged approximately 20% and that the bulk of the ocean impacts were the result of the recreational sector. Although the results from our study are consistent with O’Farrell et al. (2012a) over the common time period, they indicate that recent esti- mates of the impact rate are unlikely to represent the 348 Fishery Bulletin 1 13(3) Month Figure 5 Sacramento River winter Chinook salmon (Oncorhynchus tshawytscha ) contact rates per unit of effort for the (A) commercial and (B) recreational sectors in the San Francisco (SF) management area and for the (C) commercial and (D) recreational sectors in the Monterey (MO) management area. Circles denote estimated values for individual years, triangles indicate mean values, and squares denote median values. The methods used to infer mean and median contact rates per unit of effort for the recreational sector in February and March are described in the text. degree of fishery exploitation experienced by SRWC in earlier years. These impact-rate hindcasts were used to extend the SRWC stock assessment and have contrib- uted important fishing mortality inputs to a life-cycle model for this population (Hendrix et al., 2014). More generally, an extended time series of fishing mortality rates derived with the methods described here could allow for an extended reconstruction of recruit abun- dance useful for stock-recruit analysis (PSC10). 10PSC (Pacific Salmon Commission). 1999. Maximum sus- tained yield or biologically based escapement goals for se- lected Chinook salmon stocks used by the Pacific Salmon Commission’s Chinook Technical Committee for escapement assessment, vol. 1. Pacific Salmon Comm. Joint Chinook The impact-rate estimates derived from cohort re- construction for 2000-2012 reflect many layers of salmon fishery regulations. In particular, ocean fish- eries in California frequently have been constrained by conservation concerns and ocean-versus-river fish- ery allocations for Klamath River fall Chinook salm- on (Prager and Mohr, 2001). A collapse of the SRFC stock (Lindley et ah, 2009) closed nearly all California ocean salmon fisheries in 2008 and 2009 and heavily constrained fisheries in 2010. The first SRWC-specific constraints to fisheries began after the species was list- Tech. Comm. Rep. TCCHINOOK (99)-3, 104 p. [Available at website.] O'Farrell and Satterthwaite: Inferred historical fishing mortality rates of Oncorhynchus tshawytschc 349 ed as threatened under the ESA in 1989. Fishing constraints included establishment of a closed area for the recreational sector near the mouth of San Francisco Bay and implementation of river fishery restrictions (PFMC11). Since those initial SRWC conservation measures were implemented, addi- tional SRWC-focused fishery management mea- sures have been established, including truncation of commercial and recreational fishing seasons, increased minimum size limits, and most recently, impact-rate “caps” set annually by a control rule (see Appendix C in PFMC12). Although we do not directly link changes in the impact rate to particu- lar management measures, the increased fishery constraints over the past 35 years have clearly in- fluenced the impact rate. Estimates of contact rates per unit of effort have a strong effect on the impact-rate forecasts made with the Winter Run Harvest Model (O’Farrell et ah, 2012b) and, therefore, on the hindcasts pre- sented here. We assumed that contact rates per unit of effort estimated with cohort reconstruction methods for the years 2000-2012 are representa- tive of contact rates per unit of effort in the years before 2000. Contact rates per unit of effort are a function of catchability and stock distribution, and, in the absence of large temporal changes in these components, assuming contemporary contact rates per unit of effort for past years without direct esti- mates is reasonable. Large changes in catchability in either the commercial or recreational salmon sectors would be unlikely because modes of fishing and associated fishing gear have changed little over the past 35 years. We would also not expect substantial shifts in SRWC ocean distribution over time because this population has been shown to have a relatively compact southerly distribution (O’Farrell et ah, 2012a; Satterthwaite et al., 2013). Nevertheless, there is likely to be nontrivial process and measurement error associated with the estimates of contact rates per unit of effort. Local conditions undoubtedly affect both the ability of fishing fleets to contact SRWC and the precise local concentration of SRWC cohorts. With regard to sampling error, esti- mates of contact rates per unit of effort are made by using expanded coded-wire tag data and estimates of fishing effort. SRWC coded-wire tag recoveries can be relatively rare for a variety of reasons. SRWC have a lower abundance than that of other Chinook stocks npFMC (Pacific Fishery Management Council). 1990. Pre- season report III: analysis of Council-adopted management measures for 1990 ocean salmon fisheries. Pacific Fishery Management Council, 24 p. Portland, OR. [Available at website.] 12PFMC (Pacific Fishery Management Council). 2013. Pre- season report I: tock abundance analysis and environmental assessment part 1 for 2013 ocean salmon fishery regulations, 135 p. (Document prepared for the Council and its advisory entities.) Pacific Fishery Management Council, Portland, OR. [Available at website.] w o. E "O CD E O oc CO 1^- o in o CM o o d 95 8988 87 90 86 85 02 04 05 91 94 97 93 03 „6 12 99 98 84 83 07 11 10 09 08 I I I I I I I I 0.0 0 1 0.2 0.3 0.4 0.5 0.6 0.7 SRFC harvest rate south of Point Arena Figure 6 Sacramento River winter Chinook salmon (Oncorhynchus tshawytscha) (SRWC) hindcast median impact rates plot- ted as a function of Sacramento River fall Chinook salmon (SRFC) harvest rates for fisheries south of Point Arena, California. Numbers denote the calendar years 1983-2012. that contribute to California fisheries, and only the hatchery-origin component of the population is marked and tagged. Approximately 20% of the landed catch is sampled, and early-season fisheries with large mini- mum size limits would be expected to retain few SRWC because few fish would be greater than the minimum legal size. These sampling issues for rare stocks can read- ily lead not only to an estimate of zero contacts in a month, area, and sector stratum despite nonzero actual contacts but also to cases where a single tag recovery implies a very large number of contacts. In some stra- ta, estimates of SRWC contact rates have been based on a very small number of coded-wire tag recoveries (O’Farrell et al., 2012a). To infer values of potential contact rate per unit of effort for the recreational sector in February and March, we developed a method based on estimates of the monthly distribution of harvest when fisheries were open from February through November. The in- ferred recreational contact rates per unit of effort for February and March from this procedure were higher than estimates of contact rates per unit of effort from months after March, although such high values would be expected given the relatively large proportion of har- vest that was estimated for 1971-1972 and the small proportion of age-3 SRWC expected to be greater than the minimum legal size limit during those months. 350 Fishery Bulletin 113(3) However, these inferences may not adequately describe the pattern of SRWC contacts in these early months. Given the data available, we were unable to make management-area-specific inferences of recreational contact rates per unit of effort for February and March; yet for later months, the estimated contact rates per unit of effort tended to be considerably higher in MO than in SF. Additionally, estimates of fishing effort for 1971-1972 do not exist; therefore, we assumed that the monthly distribution of effort in those years was simi- lar to the distribution during the years 1978-1983. If substantial differences in effort occurred between these 2 periods, those differences would contribute to errors in the inferred recreational contact rates per unit of ef- fort for February and March. Nonetheless, the monthly harvest estimates for 1971-1972 represent the only information on the temporal patterns of recreational harvest over the protracted seasons that characterized historical fishing. To account for uncertainty in the hindcasts of im- pact rates, we incorporated the variation in estimates of contact rates per unit of effort using the bootstrap method. Although this approach did not account for the full spectrum of uncertainty (e.g., natural mortal- ity rate and fishing effort), it is likely that variation in the estimated contact rates per unit of effort rep- resents the dominant uncertainty because of the high level of variability across years and the strong effect that contact rates have on impact-rate projections. Characterizing uncertainty in contact rates per unit of effort by randomly resampling values for month, area, and sector strata, however, may have led to admitting excess uncertainty into the impact-rate hindcasts. For example, in years with extremely high fishing effort (e.g., 1995), a few replications produced unrealistic estimates where fishery impacts exceeded ocean abun- dance. This outcome was caused by randomly sampling a very high estimate of contact rate per unit of effort that was then multiplied by a very high, stratum-spe- cific effort estimate. This outcome is clearly not tenable and correlations may exist between the contact rate per unit of effort and fishing effort that would prevent extinction by ocean fishing. However, strong evidence of correlations between contact rate per unit of effort and fishing effort were not observed (senior author, unpubl. data), and no covariance structure was incorporated into the simulation framework. Ultimately, there is a need to understand the effects of all sources of mortality on the dynamics of the en- dangered SRWC population to better explain its popu- lation dynamics. Winship et al. (2014) estimated low overall productivity for SRWC, likely owing to low fe- cundity and low juvenile survival rates, which result- ed in low sustainable fishing mortality rates. In the absence of hatchery supplementation, Winship et al. (2014) estimated a median maximum sustainable level of fishing mortality (analogous to maximum sustain- able yield) at an impact rate of 0.17, as well as a rate of 0.25 under recent levels of hatchery supplementa- tion. Regular hatchery supplementation began in 1998 at the SRWC-dedicated Livingston Stone National Fish Hatchery, with little or no hatchery-origin contribu- tions to the population in prior years. Given the low sustainable impact rates estimated by Winship et al. (2014), and the relatively high me- dian impact rates inferred for the 1980s and 1990s, it is likely that impact rates exceeded maximum sustain- able fishing mortality levels and that they could have reached levels identified as unsustainable under condi- tions with no hatchery supplementation. However, we note that there was substantial uncertainty estimated for both the maximum sustainable impact rates in Winship et al. (2014) and the historical impact rates inferred here. In addition, the results of Winship et al. (2014) were derived with contemporary (post- 1998) data, and it is not known whether the estimated pro- ductivity, and, therefore, sustainable impact rates, are applicable for earlier time periods. Although we present a specific case study for SRWC, our ability to hindcast exploitation rates (for years be- fore the existence of sufficient data that would have allowed direct estimation of exploitation rates) should be useful for other fishery applications. The use of for- ward projection models in a hindcasting mode can help with a better understanding of the relative effects of past fisheries and management actions on fish stocks. Approaches such as the one developed here have the potential to be useful for integrating long-term records with existing stock assessments and for performing retrospective evaluations of the effectiveness of man- agement measures in data-limited situations. Acknowledgments We would like to thank A. Grover for sharing his insight into historical salmon fisheries and fishery sampling in California. We are also grateful for the thoughtful and thorough reviews provided by M. Mohr, N. Hendrix, and 3 anonymous reviewers. Literature cited Efron, B., and R. J. Tibshirani. 1993. An Introduction to the Bootstrap, 436 p. Chap- man & Hall, New York. Federal Register. 1994. Endangered and threatened species; status of Sac- ramento River Winter-run Chinook salmon; final rule. Federal Register 59:440-450. (Available at website.] Fisher, F. W. 1994. Past and present status of Central Valley Chinook salmon. Conserv, Biol. 8:870-873. Grover, A. M., M. S. Mohr, and M. L. Palmer- Zwahlen. 2002. Hook-and-release mortality of Chinook salmon from drift mooching with circle hooks: management im- plications for California’s ocean sport fishery. In Catch and release in marine recreational fisheries (J. A. Lucy O'Farrell and Satterthwaite: Inferred historical fishing mortality rates of Oncorhynchus tshawytscha 351 and A. L. Studholme, eds.), p. 39-53. Am. Fish. Soc., Bethesda, MD. Haltuch, M. A., A. E. Punt, and M. W. Dorn. 2008. Evaluating alternative estimators of fishery man- agement reference points. Fish. Res. 94:290-303. Hendrix, N., A. Criss, E. Danner, C. M. Greene, H. Imaki, A. Pike, and S. T. Lindley. 2014. Life cycle modeling framework for Sacramento River winter-run Chinook salmon. NOAA Tech. Memo. NMFS-SWFSC-530, 26 p. [Available at website.] Hilborn, R., and C. J. Walters. 1992. Quantitative fisheries stock assessment: choice, dynamics, and uncertainty, 570 p. Chapman & Hall, New York. Johnson, J. K. 1990. Regional overview of coded wire tagging of anadro- mous salmon and steelhead in northwest America. Am. Fish. Soc. Symp. 7:782-816. Lapi, L., M. Hamer, and B. Johnson. 1990. Data organization and coding for a coastwide mark-recovery data system. Am. Fish. Soc. Symp. 7:720-724. Lindley, S. T., C. B. Grimes, M. S. Mohr, W. Peterson, J. Stein, J. T. Anderson, L. W. Botsford, D. L. Bottom, C. A. Busack, T. K. Collier, J. Ferguson, J. C. Garza, A. M. Grover, D. G. Hankin, R. G. Kope, P. W. Lawson, A. Low, R. B. MacFarlane, K. Moore, M. Palmer-Zwahlen, F. B. Schwing, J. Smith, C. Tracy, R. Webb, B. K. Wells, and T. H. Williams. 2009. What caused the Sacramento River fall Chinook stock collapse? NOAA Tech. Memo. NMFS-SWF- SC-447, 61 p. [Available at website.] Milner, G. B., D. J. Teel, F. M. Utter, and G. A. Winans. 1985. A genetic method of stock identification in mixed populations of Pacific salmon, Oncorhynchus spp. Mar. Fish. Rev. 47(11:1-8. Myers, J. M., R. G. Kope, G. J. Bryant, D. Teel, L. J. Lierhe- imer, T. C. Wainwright, W. S. Grant, W. F. Waknitz, K. Neely, S. T. Lindley, and R. S. Waples. 1998. Status review of Chinook salmon from Washing- ton, Idaho, Oregon, and California. NOAA Tech. Memo. NMFS-NWFSC-35, 443 p. [Available at website.] Nandor, G. F., J. R. Longwill, and D. L. Webb. 2010. Overview of the coded wire tag program in the greater Pacific region of North America. In PNAMP special publication: tagging, telemetry and marking measures for monitoring fish populations — a com- pendium of new and recent science for use in inform- ing technique and decision modalities (K. Wolf and J. O’Neal, eds.), p. 5-46. Pacific Northwest Aquatic Moni- toring Partnership Spec. Publ. 2010-002. [Available at website.] O’Farrell, M. R., S. D. Allen, and M. S. Mohr. 2012b. The Winter-Run Harvest Model (WRHM). NOAA Tech. Memo. NMFS-SWFSC-489, 17 p. [Avail- able at website.] O’Farrell, M. R., M. S. Mohr, A. M. Grover, and W. H. Satterthwaite. 2012a. Sacramento River winter Chinook cohort recon- struction: analysis of ocean fishery impacts. NOAA Tech. Memo. NMFS-SWFSC-491, 68 p. [Available at website.] O’Farrell, M. R., M. S. Mohr, M. L. Palmer-Zwahlen, and A. M. Grover. 2013. The Sacramento Index (SI). NOAA Tech. Memo. NMFS-SWFSC-512, 36 p. [Available at website.] Prager, M. H., and M. S. Mohr. 2001. The harvest rate model for Klamath River fall Chinook salmon, with management applications and comments on model development and documentation. N. Am. J. Fish. Manage. 21:533-547. Quinn, T. J., and R. B. Deriso. 1999. Quantitative fish dynamics, 560 p. Oxford Univ. Press, New York. R Core Team. 2013. R: a language and environment for statistical com- puting. R Foundation for Statistical Computing, Vi- enna, Austria. [Available from website, accessed April 2013.] Restrepo, V. R., and J. E. Powers. 1999. Precautionary control rules in US fisheries man- agement: specification and performance. ICES J. Mar. Sci. 56:846-852. Satterthwaite, W. H., M. S. Mohr, M. R. O’Farrell, E. C. Ander- son, M. A. Banks, S. J. Bates, M. R. Bellinger, L. A. Borger- son, E. D. Crandall, J. C. Garza, B. J. Kormos, P. W. Lawson, and M. L. Palmer-Zwahlen. 2014. Use of genetic stock identification data for com- parison of the ocean spatial distribution, size at age, and fishery exposure of an untagged stock and its indi- cator: California Coastal versus Klamath River Chinook Salmon. Trans. Am. Fish. Soc. 143:117-133. Satterthwaite, W. H., M. S. Mohr, M. R. O’Farrell, and B. K. Wells. 2013. A comparison of temporal patterns in ocean spa- tial distribution of California’s Central Valley Chinook salmon runs. Can. J. Fish. Aquat. Sci. 70:574-584. Winship, A. J., M. R. O’Farrell, and M. S. Mohr. 2014. Fishery and hatchery effects on an endangered salmon population with low productivity. Trans. Am. Fish. Soc. 143:957-971. Weitkamp, L. A., and K. Neely. 2002. Coho salmon ( Oncorhynchus kisutch) ocean migra- tion patterns: insight from marine coded-wire tag recov- eries. Can. J. Fish. Aquat. Sci. 59:1100-1115. Yoshiyama, R. M., F. W. Fisher, and P. B. Moyle. 1998. Historical abundance and decline of Chinook salm- on in the Central Valley region of California. N. Am. J. Fish. Manage. 18:487-521. Zar, J. H. 1999. Biostatistical analysis, 4th ed., 663 p. Prentice- Hall, NJ. 352 Fishery Bulletin Guidelines for authors Contributions published in Fishery Bulletin describe original research in marine fishery science, fishery en- gineering and economics, as well as the areas of ma- rine environmental and ecological sciences (including modeling). Preference will be given to manuscripts that examine processes and underlying patterns. Descriptive reports, surveys, and observational papers may occa- sionally be published but should appeal to an audience outside the locale in which the study was conducted. Although all contributions are subject to peer review, responsibility for the contents of papers rests upon the authors and not on the editor or publisher. 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