SH il .A5-F53 FlStJ U.S. Department of Commerce Volume 113 Number 1 January 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 Administrator for Fisheries Scientific Editor Richard Langton National Marine Fisheries Service Northeast Fisheries Science Center Maine Field Station 17 Godfrey Drive, Suite 1 Orono, ME 04473 Associate Editor Kathryn Dennis National Marine Fisheries Service Office of Science and Technology 1845 Wasp Blvd., Bldg. 176 Honolulu, Hawaii 96818 Managing Editor Sharyn Matriotti National Marine Fisheries Service Scientific Publications Office 7600 Sand Point Way NE Seattle, Washington 98115-0070 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. 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Editorial Committee Richard Brodeur John Carlson Kevin Craig Jolm Graves Rich McBride Rick Methot Bruce Mundy David Sampson Michael Simpkins Dave Somerton Mary Yoklavich National National National Virginia National National National Oregon National National National Marine Fisheries Service, Newport, Oregon Marine Fisheries Service, Panama City, Florida Marine Fisheries Service, Beaufort, North Carolina Institute of Marine Science, Gloucester Point, Virginia Marine Fisheries Service, Woods Hole, Massachusetts Marine Fisheries Seivice, Seattle, Washington Marine Fisheries Sen/ice, Honolulu, Hawaii State University, Newport, Oregon Marine Fisheries Service, Woods Hole, Massachusetts Marine Fisheries Service, Seattle, Washington Marine Fisheries Service, Santa Cruz, California Fishery Bulletin web site: www.fisherybulletin.noaa.gov The Fishery Bulletin carries original research reports on investigations in fishery sci- ence, engineering, and economics. It began as the Bulletin of the United States Fish Commis- sion in 1881; it became the Bulletin of the Bureau of Fisheries in 1904 and the Fishery Bulle- tin of the Fish and Wildlife Service in 1941. Separates were issued as documents through vol- ume 46; the last document was no. 1103. Beginning with volume 47 in 1931 and continuing through volume 62 in 1963, each separate appeared as a numbered bulletin. A new system began in 1963 with volume 63 in which papers are bound together in a single issue. Beginning with volume 70, number 1, January 1972, Fishery Bulletin became a periodical, issued quarterly. In this form, it is available by subscription from the Superintendent of Documents, U.S. Government Printing Office, Washington, DC 20402. It is also available free in limited numbers to libraries, research institutions, state and federal agencies, and in exchange for other scientific publications. I U.S. Department of Commerce Seattle, Washington Volume 1 13 Number t January 2015 Fishery Bulletin Contents Articles 1-14 Aalbers, Scott A., and Chugey A. Sepulveda Seasonal movement patterns and temperature profiles of adult white seabass (Atractoscion nobilis) off California 15-26 Bacheler, Nathan M., and Kyle W. Shertzer Estimating relative abundance and species richness from video surveys of reef fishes 27-39 Burton, Michael L., Jennifer C. Potts, Daniel R. Carr, Michael Cooper, and Jessica Lewis Age, growth, and mortality of gray triggerfish ( Batistes capriscus) from the southeastern United States 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. 40-46 Niamaimandi, Nassir, and Gholam-Abbas Zarshenas Economic valuation of stock enhancement of banana prawn ( Fenne - ropenaeus merguiensis ) in the Strait of Hormuz 47-54 Elzey, Scott P., Katie A. Rogers, and Kimberly J. Trull Comparison of 4 aging structures in the American shad (Alosa sapidissima) 55-68 Duarte, Luis Felipe de Almeida, Evandro Severino-Rodrigues, Marcelo A. A. Pinheiro, and Maria A. Gasalla The NMFS Scientific Publications Office is not responsible for the contents of the articles or for the standard of English used in them. Slipper lobsters (Scyllaridae) off the southeastern coast of Brazil: relative growth, population structure, and reproductive biology II Fishery Bulletin 1 13(1) 69-81 Ligas, Alessandro, Francesco Coiloca, Mathieu G. Lundy, Alessandro Mannini, Paolo Sartor, Mario Sbrana, Alessandro Voliani, and Paola Belcari Modeling the growth of recruits of European hake (Merluccius merluccius) in the northwestern Mediterranean Sea with generalized additive models 82-96 Lindholm, James, Mary Gleason, Donna Kline, Larissa Clary, Steve Rienecke, Alii Cramer, and Marc Los Huertos Ecological effects of bottom trawling on the structural attributes of fish habitat in unconsolidated sediments along the central California outer continental shelf 97-99 Guidelines for authors NOAA National Marine Fisheries Service Fishery Bulletin fa- established 1881 n?. Spencer F. Baird First U S. Commissioner of Fisheries and founder of Fishery Bulletin Seasonal movement patterns and temperature profiles of adult white seabass {Atractoscion nohilis ) off California Abstract— To better understand the seasonal movement patterns of adult white seabass ( Atractoscion nobilis ), 173 depth- and temperature-sensi- tive data storage tags were deployed at various sites within the Southern California Bight during 2008-2011. Commercial and recreational fishing crews recaptured 41 tagged individ- uals (24%) between La Salina, Baja California Norte, Mexico (32°01'N, 116°53'W), and Half Moon Bay, Cali- fornia (37°28'N, 122°28'W ). Tagged fish were at liberty for an average duration of 468 days (range: 9-1572 days), and mean net displacement between the points of release and recapture was 229 km (range: 2-624 km). Collectively, 9130 days of ar- chived data revealed distinct sea- sonal trends in depth distribution, and significantly deeper profiles during the winter months. Minor differences in mean depth values were evident between daytime (14.9 m [±standard deviation (SD) 5.1]), nighttime (15.5 m [SD 5.1]), and twi- light periods (16.8 m [SD 6.8]). How- ever, the vertical rate of movement (VROM) was significantly greater during twilight hours (48.9 m h_1 [SD 12.3] when compared with day and night VROM values (39.6 m h-1 [SD 10.8] and 41.1 m hr1 [SD 13.2]). The greatest depth achieved by any individual was 245 m; however, 95% of all depth records were less than 50 m. Ambient water temperatures ranged from 8.7° to 23.6°C, and had a mean value of 15.2°C (SD 1.4°C). A vertical shift toward the surface as water temperatures increase dur- ing the spring and summer months contributes to heightened vulner- ability during the spawning season, presenting management challenges toward the long-term sustainability of this resource. Manuscript submitted 13 August 2013. Manuscript accepted 27 October 2014. Fish. Bull. 113:1-14 (2015). doi: 10.7755/FB.113.1.1 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. Scott A. Aalbers (contact author) Chugey A. Sepulveda Email address for contact author: scott@pier.org Pfleger Institute of Environmental Research (PIER) 2110 South Coast Highway, Unit F Oceanside, California 92054 The white seabass (Atractoscion no- bilis) supports lucrative recreational and commercial fisheries through- out California and Baja California, Mexico (Vojkovich and Crooke, 2001; Rosales-Casian and Gonzalez-Cama- cho, 2003). Because of their high rec- reational and market value, white seabass are targeted opportunisti- cally and fishing effort is influenced by local availability (Skogsberg, 1939; MacCall et al„ 1976; CDFG, 2011). During periods of heightened abundance, persistent localized ef- fort is directed toward white seabass by both recreational and commercial operations throughout much of the range of this species (Whitehead, 1929; MacCall et al., 1976). Over the past century, landings and catch per unit of effort (CPUE) of white seabass in California have fluctuated dramatically, reaching peak levels in the early 1920s and late 1950s that were followed by troughs in the late 1920s and 1960s (Whitehead, 1929; MacCall et ah, 1976; CDFG1). Vojkovich and Reed (1983) suggested that prolonged in- tervals of reduced landings off Cali- fornia are likely a response to pe- riods of overexploitation and other 1 CDFG (Calif. Dep. Fish Game). 2002. Final white seabass fishery manage- ment plan (WSFMP), 161 p. [Available from https://nrm.dfg.ca.gov/FileHandler. ashx?DocumentID=34195&inline=true, accessed March 2014.] unknown factors. Collective land- ings and CPUE from California rec- reational and commercial fisheries have steadily increased since 1998, indicating a recent stock resurgence from levels of record-low abundance in the 1980s (Vojkovich and Reed, 1983; Allen et al., 2007; CDFG, 2011). The majority of California’s white seabass harvest typically occurs from April to September along the southern coast from Point Concep- tion to San Diego and throughout the Channel Islands (Skogsberg, 1925; Thomas, 1968). Landings north of Point Conception have increased dramatically since 2008; commercial hook-and-line catches north of Point Arguello increased from 1% of the total California harvest in 2008 to 22% of annual state landings in 2010 (CDFG, 2009; 2011). Over the same period, recreational catches north of Point Arguello increased from 3% to 38% of total state landings. Height- ened landings from the northern re- gion have been coupled with a sharp increase (266%) in the numbers of vessels entering the white seabass fishery (CDFG 2011), rising from 93 permitted boats in 2009 to 254 com- mercial vessels in 2011 (CDFG2). A 2 CDFG (Calif. Dep. Fish Game). 2012. White seabass fishery management plan annual 2010-2011 review, 6 p. [Avail- able from https://nrm.dfg.ca.gov/File- Handler.ashx?DocumentID=75302&inli ne=true, accessed March 2014.] 2 Fishery Bulletin 1 13(1) comparable northward shift in fishing effort was docu- mented from 1957 to 1961 and was also coupled with a sharp increase in the number of vessels that entered the fishery (Vojkovich and Reed, 1983). During this pe- riod, commercial landings of white seabass reached a record high of more than 1500 metric tons in 1959, 36% of which came from the waters north of Point Concep- tion (Thomas, 1968; Vojkovich and Reed, 1983). Inter- annual shifts in the latitudinal distribution of white seabass have been suggested in the past (Skogsberg, 1939; Young3; Maxwell4); however, fishery-independent data on movement patterns and stock structure of white seabass have been limited. Attempts to evaluate movement patterns of juvenile white seabass through a conventional tagging program in the mid-1970s were ineffective because of limited tag deployments (n= 58) and no reported tag recoveries (Maxwell4). An evaluation of movement patterns based on historical fishery data indicates that white seabass occur off Baja California during winter and move north- ward along the coast of California as water tempera- tures increase during the spring and summer months (Skogsberg, 1939; Maxwell4; Vojkovich and Crooke, 2001). Spawning is thought to occur with northward advancement from March to July (Skogsberg, 1925; Thomas, 1968; Young3), although little information is available regarding spawning activity north of Point Conception. Fish harvested along California and Baja California are currently considered to be from a contin- uous spawning population with a high level of genetic diversity (Maxwell4; Coykendall, 1998; Rios-Medina, 2008). Discrepancies in this single-stock model have been indicated by Franklin (1997), and the existence of regionally discrete stocks with limited rates of mixing has been considered (Vojkovich and Crooke, 2001). Despite a robust history of white seabass catch data since the 1890s, essential fishery information on the geographic distribution of stocks, habitat use, and sea- sonal movement patterns remains largely unavailable (Skogsberg, 1939; Vojkovich and Reed, 1983; CDFG1). Additional uncertainties on spatial and temporal as- pects of white seabass depth distribution, residence pe- riods, and exploitation rates present major challenges for effective fishery management, particularly for a population that is harvested by more than one nation (Thomas, 1968; Maxwell4; CDFG1). Regulations that re- duce the likelihood of overexploitation are currently in place; however, additional research and adaptive man- agement strategies are necessary for the sustainable 3 Young, P. H. 1973. The status of the white seabass re- source and its management. Calif. Dep. Fish Game Mar. Resour. Tech. Rep. 15, 10 p. [Available from http://aquatic- commons.org/756/l/Technical_Report_ 1973_No._15_A.pdf, ac- cessed April 2014.] 4 Maxwell, W. D. 1977. Progress report of research on white seabass, Cynoscion nobilis. Calif. Dep. Fish Game Mar. Re- sour. Admin. Rep. 77-14, 14 p. [Available from http://aquat- iccommons.org/76/l/Marine_Resources_Administrative_Re- port_NoIlf_77-14.pdf, accessed April 2014.] use of this valuable fishery resource (Vojkovich and Reed, 1983; CDFG1). Fishery-independent informa- tion on fine- and course-scale fish movements has been identified as essential to adequately assess fishery im- pacts and address questions related to seasonal distri- bution and stock structure of white seabass (Thomas, 1968; CDFG1). Our objectives were to assess movement patterns, temperature preferences, and recapture rates of adult white seabass off the California coast. Materials and methods Tagging procedure and sampling regime Cefas G55 and G5 long-life data storage tags (DSTs; Ce- fas Technology Limited, Lowestoft, UK) were surgically implanted in the peritoneal cavity of white seabass by using techniques modified from Stutzer (2004). Wild- caught white seabass were tagged and released around Santa Catalina Island (n=107) and along the southern coastline of California {n=6 6) during the spring and summer months of 2008-2011 (Table 1). After capture on hook and line, fish were brought alongside the ves- sel and transferred in a knotless nylon-mesh dip net (Duraframe, Viola, WI) to an onboard tagging cradle. A conventional identification marker (FIM-96; Floy Tag, Inc., Seattle, WA) was inserted into the dorsal muscula- ture traversing the dorsal-fin pterygiophores. Upon se- curing the fish ventral-side up within a tagging cradle, a 2-cm incision was made with a scalpel through the dermal layer adjacent to the ventral midline approxi- mately 8 cm anterior to the anal vent. A stainless steel trocar was used to penetrate the ventral musculature, and a DST was inserted into the peritoneal cavity. The incision was closed around an external identification stalk with a PDS II surgical-grade suture and a CP-1 reverse cutting needle (Ethicon, Somerville, NJ) along with a 35-wide stainless-steel skin stapler (PGX-35W; 3M, St. Paul, MN). Fish total length (TL) was measured to the near- est centimeter, sex was recorded, and the hook was removed before release. Sex was determined by both the audible detection of low-frequency sound produc- tion by males during the capture and tagging process and the presence or absence of milt upon application of pressure to the abdominal region. All tagging was conducted during the spawning season when mature males are consistently running ripe and characteris- tically produce low-frequency sound upon handling (Aalbers and Drawbridge, 2008; Gruenthal and Draw- bridge, 2012). Total handling time onboard the vessel ranged from 65 to 135 s. Because postrelease survival of white seabass hooked in the visceral region has been shown to be 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. Aalbers and Sepulveda: Seasonal movement patterns and temperature profiles of adult Atractoscion nobilis off California 3 Table 1 Tag deployment and recovery statistics for 41 adult white seabass ( Atractoscion nobilis) recaptured between La Salina, Baja California Norte, Mexico, and Half Moon Bay, California, from June 2008 to July 2013. DAL=days at liberty, rec. hook- line=recreational hook and line, com. hook-line=commercial hook and line. * isn Deployment Recapture total Net Recapture Tag no. length Date Latitude Longitude DAL Date Latitude Longitude movement gear A02049 132 cm 5-19-08 33°18' N 1 18°18' W 1154 7-18-11 33°20' N 118°29' W 16 km rec. hook-line A02066 127 cm 5-19-08 33°18' N 118°18' W 1572 9-11-12 36°57' N 121°57' W 542 km com. hook-line A02055 119 cm 5-25-08 33°18' N 118°18' W 767 6-30-10 34°13'N 119°20' W 144 km U.S. gill net A02071 114 cm 5-25-08 33°18' N 118°22' W 31 6-25-08 34°14' N 119°25' W 144 km U.S. gill net A02143 97 cm 6-02-08 33°28' N 118°36' W 798 8-10-10 37°28' N 122°28' W 624 km com. hook-line A02054 124 cm 6-12-08 33°18' N 118°18' W 746 6-28-10 33°39' N 118°12' W 40 km U.S. gill net A02118 117 cm 6-12-08 33°18' N 118°18' W 1342 2-13-12 34°18' N 119°27' W 211 km U.S. gill net A02119 117 cm 6-12-08 33°18' N 118°18' W 377 6-24-09 33°40' N 118°13' W 19 km rec. hook-line A02159 1 19 cm 6-12-08 33°18' N 118°18' W 764 7-26-10 34°00' N 118°48' W 90 km speargun A02075 91 cm 6-26-08 33°18' N 118°21' W 371 6-30-09 34°14' N 119°19' W 125 km U.S. gill net A02105 122 cm 7-15-08 33°18' N 118°21' W 350 6-29-09 34°12' N 119°19' W 141 km U.S. gill net A02131 109 cm 5-06-09 33°24' N 118°22' W 76 7-21-09 36°58' N 121°56' W 576 km rec. hook-line A03604 152 cm 5-14-09 33°18' N 118°21' W 690 4-06-11 32°01' N 116°53' W 195 km Mexico gill net A02128 127 cm 6-05-09 33°24' N 118°22' W 896 11-21-11 36°58' N 122°08' W 600 km com. hook-line A03606 114 cm 6-08-09 33°18' N 118°21' W 490 10-12-10 36°37' N 121°52' W 512 km com. hook-line A03609 124 cm 6-16-09 CO CO o f— 1 00 N 118°20' W 741 6-27-11 33°40' N 118°12' W 45 km U.S. gill net A03613 79 cm 6-23-09 CO CO oo N 118°21' W 16 9-07-09 33°19'N 118°25' W 11 km rec. hook-line A02094 102 cm 6-29-09 33°20' N 117°34' W 820 9-27-11 32°01' N 116°53' W 192 km Mexico gill net A02325 112 cm 6-29-09 33°20' N 117°34' W 354 6-18-10 33°39' N 118°12' W 45 km U.S. gillnet A02161 132 cm 6-30-09 33°20' N 1 17°34' W 744 7-14-11 34°24' N 119°49' W 237 km speargun A03595 122 cm 7-09-09 33°20' N 1 17°34' W 722 7-01-11 33°17' N 117°29' W 6 km speargun A03596 124 cm 7-10-09 33°20' N 1 17°34' W 439 9-22-10 36°37' N 121°54' W 587 km com. hook-line A03591 152 cm 7-18-09 33°23' N 1 17°37' W 346 6-28-10 32°47' N 117°17' W 72 km com. hook-line A02109 109 cm 3-16-10 32°50' N 1 17°18' W 146 8-08-10 35°06' N 120°39' W 448 km com. hook-line A02111 104 cm 3-17-10 32°50' N 117°18' W 153 8-15-10 32°51' N 117°18' W 2 km rec hook-line A02133 1 14 cm 3-17-10 32°50' N 117°18' W 493 7-24-11 32°09' N 116°54' W 86 km Mexico gill net A06101 124 cm 5-05-10 33°17' N 1 17°29' W 17 5-22-10 32°5r N 1 17°17' W 56 km speargun A06097 135 cm 5-20-10 33°20' N 117°34' W 416 7-10-11 36°57' N 121°57' W 602 km com. hook-line A06065 137 cm 5-26-10 33°18' N 118°22' W 27 6-22-10 33°39' N 118°15' W 45 km U.S. gill net A06089 86 cm 5-26-10 33°19' N 118°23' W 386 6-16-11 34°13' N 1 19°26' W 120 km U.S. gill net A06101b 140 cm 5-26-10 33°18' N 1 18°22' W 155 10-28-10 36°37' N 121°52' W 520 km com. hook-line A06067 114 cm 5-27-10 33°18' N 118°22' W 97 8-31-10 36°32' N 121°56' W 506 km com. hook-line A06076 117 cm 5-27-10 33°18' N 118°22' W 385 6-16-11 34°15' N 119°20' W 120 km U.S. gill net A06117 130 cm 6-12-10 33°36' N 117°58' W 106 9-26-10 36°37' N 121°52' W 552 km com. hook-line A06122 104 cm 6-12-10 33°36' N 117°58' W 11 6-23-10 33°40' N 118°17' W 32 km U.S. gill net A06118 102 cm 6-13-10 33°36' N 117°58' W 8 6-22-10 33°39' N 118°16' W 29 km U.S. gill net A06120 130 cm 6-13-10 33°36' N 117°58' W 765 7-18-12 36°57' N 121°57' W 568 km com. hook-line A06107 130 cm 6-24-10 32°47' N 117°17' W 355 6-14-11 32°42' N 1 17°16' W 8 km speargun A06073 91 cm 6-07-11 33°18' N 118°20' W 110 9-24-11 33°23' N 1 18°29' W 19 km speargun A02143 127 cm 3-17-10 32°50' N 1 17°18' W 1155 5-17-13 32°42' N 117°16' W 12 km speargun A06108 135 cm 6-25-10 32°47' N 117°17' W 695 7-17-13 32°42' N 117°16' W 11 km com. hook-line compromised (Aalbers et al., 2004), only mouth-hooked individuals in good physical condition (e.g., no hook damage) were selected for tagging. Fish were captured at depths of 3-33 m. Most individuals were positively buoyant upon capture as a result of gas bladder expan- sion; however, artificial deflation of the gas bladder was unnecessary, and all tagged fish were able to return to depth after release. Contact and reward information was printed upon both the stalk and body of the DSTs as well as on ex- ternally affixed conventional tags. Information on re- capture vessel, geographic location, fish size, sex, and general fish condition was documented upon communi- cation with fishermen that reported tag recoveries. A $200 reward, tagging project T-shirt, and a summary of statistics for the recaptured individual were sent out to fishermen upon recovery of a DST. DSTs were programmed by using 3 sampling re- 4 Fishery Bulletin 113(1) gimes to maximize fine-scale data acquisition within the constraints of tag memory capacity and battery life. In 2008, Cefas G5 DSTs were programmed to record depth (0.15 m resolution) every 2 min and temperature (0.1°C resolution) every 4 min. In 2009, Cefas G5 long- life DSTs stored depth and temperature records every 2 min, and tags in 2010 recorded depth at 1-min inter- vals and temperature every 2 min. Time-series data for cumulative analyses were standardized to a sampling regime of 2-min intervals for depth and 4-min intervals for temperature for all tag recoveries. Upon recovery, fine-scale depth and temperature data were downloaded from all DSTs and complete time-series records over the entire deployment period were recovered from 22 DSTs. Battery life expired before recovery of 11 DSTs; however, the time-series data for the active recording life of these 11 DSTs were retrieved and provided by the tag manufacturer (Cefas Technology Limited). Four of the internally im- planted DSTs were either shed through the incision site or incidentally discarded along with the viscera during fish processing, as only conventional identifica- tion markers were reported by fishermen Subsequent investigations should incorporate 3 recovered data sets because recaptures were reported after comple- tion of comprehensive data analyses, and 1 DST was lost in the mail. Data analysis Time-series data were formatted in Excel worksheets before export into an Access database (Microsoft Of- fice 2010, Redmond, WA). All records were classified as day , night , or twilight values on the basis of the mean monthly time (Pacific Standard Time [PST]) of sunrise, sunset, and nautical twilight at the initial tagging loca- tion from the Astronomical Applications Department of the U.S. Naval Observatory data services portal (http:// aa.usno.navy.mil/data/index.php). Daytime was defined as the average monthly time of sunrise until the aver- age time of sunset; nighttime was assigned to all val- ues between the mean time of nautical twilight at dusk until the mean time of nautical twilight at dawn; and twilight values included all data between mean time of sunset and nautical twilight at dusk as well as from nautical twilight at dawn until mean time of sunrise for each month. Vertical rate of movement (VROM) was calculated for each fish (n= 33) as the absolute difference of all subsequent records of depths taken every 2 min. In- dividual VROM values were converted to m h-1 before subsequent analyses. For all fish, VROM values that exceeded 150 m Ir1 were binned by hour of the day to further evaluate daily periods of peak vertical activity. Depth values <5 m were binned by month and by hour to identify periods of surface-oriented behavior. Analy- ses did not control for autocorrelation in the mean com- parisons and descriptive statistics used to characterize vertical data by time of day and season. Seasonal depth statistics were evaluated for the 16 individual fish for which time-series data was collected for each month of the calendar year. Daily depth and temperature means were calculated and plotted with a 7-day running mean for smoothing. Daily depth prob- ability plots were constructed with Matlab software vers. 6.0 [R12] (The MathWorks, Inc., Natick, MA) for each month with depth bins of 1 h by 2 m to illus- trate the cumulative probability of occurrence for each depth. Spectral analysis by use of the fast Fourier transform (FFT) algorithm was conducted to show the diurnal signal and associated harmonics dominating in the frequency range of 0. 5-8.0 cycles per day (cpd), and a Hanning window was used to reduce overlap between adjacent spectral peaks (Shepard et ah, 2006). Data on mean daily depths were used to remove the diurnal cycle before long-period oscillations in the frequency band of 0.02-0.14 cpd were calculated for the 3 longest time series (721-741 days). A paired /-test was conducted from mean depth val- ues of 16 data sets that contained time-series records for each month of the calendar year to determine if seasonal differences were apparent between winter months (October-March) and summer months (April- September). Paired /-tests were also employed for all white seabass in- 33) to identify differences in VROM values: daytime versus nighttime periods, daytime versus twilight periods, and nighttime versus twilight periods. All mean values are indicated as means with standard deviations (SD) in parentheses, and a<0.05 was used to infer significance. Results Tag deployments and recoveries Between April 24, 2008, and June 8, 2011, 173 adult white seabass, ranging in size from 71 to 152 cm TL (mean=118 cm TL), were affixed with DSTs. Of the 95 individuals for which sex was determined during tag- ging, 76% were identified as females and 24% were sound-producing males. Commercial and recreational crews recaptured 41 tagged individuals (77% female) during the study period, an overall recapture rate of 24% (Table 1). Annual recapture rates varied from a low of 6% (1 of 17) for 2011 deployments to a high of 29% (17 of 58) for 2010 deployments. Collectively, the largest number of tag recoveries also occurred in 2010, with 17 of the 41 tag recoveries (41%) reported during that year. Between the months of April and October, 95% of tag recaptures occurred. Of the 41 recaptured individuals, 13 were harvested by California gillnett- ers, 3 were reported by Mexican gillnetters, 13 were taken by California commercial hook-and-line vessels, 5 were caught by California recreational anglers, and 7 were recovered by California spear fishermen (Table 1). Collectively, 9130 days of time-series data compiled from 33 DSTs provided 6.30xl06 depth and 3.65xl06 Aalbers and Sepulveda: Seasonal movement patterns and temperature profiles of adult Atractoscion nobilis off California 5 Percent occurrence A 0 5 10 15 20 25 30 Temperature (°C) Figure 1 Frequency distributions showing collective (A) depth and (B) temper- ature profiles for 33 adult white seabass ( Atractoscion nobilis) that were tagged and recaptured along the California and Baja California, Mexico, coastlines during 2008-2011. Observations are based on depth bins of 5 m by 2 min and temperature bins of 1°C by 4 min. temperature records at resolutions of 2 min and 4 min. Fish at liberty for periods of up to 1572 days (mean=468 days) provided comprehensive multiyear data sets for an evaluation of seasonal and interannual patterns of depth distribution and habitat use. Vertical movements The cumulative mean depths during the daytime, nighttime, and twilight periods were 14.9 m (SD 5.1), 15.5 m (SD 5.1), and 16.8 m (SD 6.8), respectively. Brief vertical excursions to depths up to 245 m were record- ed; however, 95% of all the recorded depths were <50 m (Fig. 1A). Monthly mean depth values of tagged fish revealed that the fish remained significantly deeper in the water column between October and March (paired £-test: £=14.41, P<0.0001) than between April and Sep- tember, reaching a maximum mean depth of 31.1 m (SD 13.2) in January (Fig. 2). Depth profiles were shallower on average as water temperatures increased during the spring and summer months, reaching a minimum mean depth of 10.5 m (SD 7.3) in August (Fig. 2). Although diel and seasonal depth patterns were con- sistent among most fish, individual variability and in- terannual trends were apparent from mean daily depth and temperature profiles (Fig. 3, A and B). For exam- ple, fish A06097 remained consistently deeper (27.0 m [SD 13.5]) than all other white seabass (9.4 m [SD 4.5], 7i- 4) during the summer months of 2010. In compari- son, fish A03591 occurred at roughly half (14.4 m [SD 3.7]) of the mean depth observed for all other fish (28.9 m [SD 4.5], n=l ) during the winter months of 2009- 2010. Although A03591 was the largest female (152 cm TL) tagged during this study, a consistent correlation was not found between fish size and mean depth, fish size and mean temperature, or sex and mean depth. Mean depth and temperature from August to October in 2010 were considerably less for 5 individuals recap- tured within Monterey Bay than for all other fish re- captured in other areas: 8.7 m and 13.6°C versus 13.0 m and 15.4°C. Depth probability plots constructed for each month represented seasonal shifts in depth, indicating more surface-oriented distributions evident from April to October, transitional periods during March and No- vember, and deeper profiles from December to Feb- ruary (Fig. 4, A-D). Fish showed more of a bimodal depth distribution during transitional periods, with peaks in cumulative probability near 10 m as well as at depths between 15 and 30 m (Fig. 4, B and D). 6 Fishery Bulletin 1 13(1) Month Jan Feb Mar Apr May Jun July Aug Sept Oct Nov Dec 35 20 19 18 w 3 ST 3 -o o 3 (D 6 13 12 17 16 15 14 Figure 2 Mean seasonal depth (bars) and temperature (line) profiles from time-series records of 16 wild-caught white seabass ( Atractoscion nobilis) at liberty along the coast of California and Baja California, Mexico, throughout all months of the year. Collectively, the time-series data span from May 2008 to June 2011. Error bars indicate ±1 standard error of the mean. Depth probability plots summarized for 16 fish over a 24-h period also exhibited increased vertical activity around dawn and dusk throughout all months of the year (Fig. 4, A-D). Consistent daily (24-h) and semidaily (12-h) peaks in spectral density were evident from FFTs of depth data for multiple individuals (n=16), indicating strong diel periodicities in vertical movement patterns (Fig. 5A). Longer-term periodicities (0.02-0.14 cpd), on the scale of days to months, were not persistent among in- dividuals (Fig. 5B). Although variability in harmonic frequencies (cpd) was apparent between individuals (72 = 16), spectral density peaks were perceptible for 9 individuals between 0.044 and 0.048 cpd (21-23 days). Five individuals also showed predominant peaks in spectral density at 0.033 cpd (30 days); however, corre- lation (coefficient of correlation [r]=0.01-0.19) between depth and lunar luminosity values were low. There was no significant difference in mean values ofVROM between day and night (paired £-test: £=0.49, df=32, P=0.625). However, the mean VROM was signifi- cantly greater during the twilight hours (48.9 m h'1 [SD 12.3] than during the day (39.6 m h_1 [SD 10.8]; paired £-test: £=8.16, df=32, P<0.0001) and nighttime (41.1 m fr1 [SD 13.2]; paired £-test: £=5.30, df=32, PcO.0001). Similarly, VROM values exceeded 150 m h_1 most frequently around 0500 and 1900 PST (Fig. 6A). In contrast, surface-oriented behavior (depths <5 m) reached a minimum during twilight periods, and increased surface activity occurred from 0900 to 1600 PST and from 2300 to 0300 PST (Fig. 6B). Collectively, surface-oriented behavior was heightened from May to September, with a peak in July, but was rarely ob- served from November to February (Fig. 7). Horizontal movements The locations of tag recoveries spanned an 820-km stretch of coastline between La Salina, Baja California Norte (32°01'N, 116°53'W), and Half Moon Bay, Cali- fornia (37°27'N, 122°28'W) (Table 1). The majority of tagged fish (72 =22) moved in a northwesterly direction (300-330° heading; mean: 317°) along the California coastline during their time at liberty. Five recaptured individuals moved southeast of their initial tagging lo- cation (135-158° heading; mean: 151°), 3 of which were recovered below the border of the United States and Mexico. The reported locations for more than half of the tag recoveries (77=22) were >100 km from the tag- ging site, and 21% of fish were recaptured between 20 and 100 km from the point of release. After a mean time at liberty of 433 days (range: 9-1154 days), 11 individuals were recovered within 20 km of their initial tagging site. There was no relationship between fish size and net displacement or between time at liberty and net displacement (Table 1). Aalbers and Sepulveda: Seasonal movement patterns and temperature profiles of adult Atractoscion nobi/is off California 7 Temperature profiles Tagged white seabass experienced water temperatures from 8.8°C to 23.6°C but spent the majority (52%) of time between 13 and 16°C with a peak around 14°C (Fig. IB). Temperatures ranged between 11°C and 19°C for 95% of all records (Fig. IB), and 95% of the time that fish spent at depths <5 m ( i.e. , in surface-oriented behavior) occurred at ambient temperatures between 12°C and 19°C. Mean monthly temperatures reached a minimum of 13.0°C in December and a maximum of 16.0°C in June (Fig. 2). Discussion This study revealed a relatively high tag recovery rate, providing an extensive data set from fish both tem- porally and spatially distributed along the California and Baja California coastlines. Despite differences in deployment times and locations, depth and tempera- ture profiles were markedly similar among most fish, and all individuals exhibited seasonal shifts in depth distribution. A significantly shallower and less variable distribution from April to September (than in winter months) contributes to greater vulnerability to most gear types and validates seasonal fishery trends that were suggested nearly a century ago (Skogsberg, 1939). Seasonal and diel shifts in depth distribution, VROM values, and surface-oriented behavior are all indicative of increased feeding and spawning-related activities as water temperatures increase in the spring and summer months. These data provide insight into the migratory nature of the white seabass, along with the first evi- dence of transboundary movements across the border 8 Fishery Bulletin 1 13(1) Hours in a day Cumulative Hours in a day probability (%) Cumulative probability (%) Hours in a day Cumulative Hours in a day probability (%) Cumulative probability (%) Figure 4 Depth probability plots constructed for the months of (A) January (i!=267,840), (B) March (n=267,840), (C) July 0i=313,706), and (D) November (n=259,200) and summarized over a 24-h period for 16 adult white seabass (Atractoscion nobilis ) at lib- erty for >12 months along California and Baja California, Mexico, during 2008-2011. Dashed vertical lines represent time of sunrise and sunset to illustrate increased vertical movements around dusk and dawn. of the United States and Mexico, further supporting the need for a cohesive international management re- gime for this species. Tag recoveries All recaptured white seabass were reported in good physical condition. The dissection of a 125-cm-TL fe- male recaptured 17 days after release revealed that the tagging incision was completely healed and that there was no infection or postrelease trauma. Similarly, in a controlled study to evaluate the effects of surgically implanting V-16 tags (Vemco, Halifax, Nova Scotia, Canada) in wild-caught white seabass (75-124 cm TL), incision sites healed within 90 days, and there were no indications of necrosis or infection (Stutzer, 2004). Stutzer (2004) also found no long-term (450 days) ef- fects on growth, feeding behavior, or survival for the adult white seabass that received tag implants (n= 30), versus fish in control (n=20) and sham surgery groups (71=20). Although survival of white seabass was not likely influenced by the capture, handling, or tagging processes, it is possible that other factors (e.g., preda- tion and barotrauma) influenced postrelease survival in the study described here. At least 2 tagged individu- als were observed to have been preyed upon by Cali- fornia sea lions (Zalophus californianus) directly after release. Increased vulnerability to predation directly after release likely was associated with the effects of exertion, gas bladder inflation, and equilibrium loss experienced during the capture process (Danylchuk et ah, 2007). Aalbers and Sepulveda: Seasonal movement patterns and temperature profiles of adult Atractoscion nobilis off California 9 A Cycles per day (CPD) B Figure S Results of spectral analysis conducted through the application of a fast Fourier transform algorithm to the 3 tracks of white seabass (Atractoscion nobilis ) with the longest duration (721-740 days; fish A02118, A03595, and A03609) to identify potential depth periodicities on (A) diurnal and (B) monthly cycles along the coast of California and Baja California, Mexico, during 2008-2011. T=time period. Other factors that may have resulted in an under- estimate of the recapture rate include tag shedding and nonreporting of recaptured individuals. Although a $200 reward was offered for the return of DSTs, it is possible that some recoveries were not reported. Four of the tags recovered in this study were not returned for up to 15 months after the recapture date, further indicating the possibility of under reporting. There- fore, the reported 24% recapture rate is conservative because it does not account for tags that were shed or recaptures that were not reported by the time of the analyses for this study. Given that the average time at liberty was 468 days, the recapture rate may increase further with additional tag recoveries. The age and size structure of the fish tagged in this study were representative of fish captured in the com- mercial fishery, as more than 50% of white seabass harvested in California in 2010-2011 were >10 years of age (>112 cm TL) (CDFG2). Given that the mean size of white seabass captured in this study was 118 cm TL, all individuals were mature and most tagged fish were >10 years old, and some individuals exceeded 20 years of age (>150 cm TL) (Clark, 1930; Thomas, 1968; Romo- Curiel et ah, in press). The ratio of commercial (67%) to recreational (33%) landings in California in 2010 was consistent with the ratio of recaptured white seabass observed in this study, with 68% of tags recovered by commercial fisheries and 32% from recreational anglers (in U.S. waters) (CDFG, 2011). Of the white seabass tag recaptures, 95% occurred from April to October, a period that directly aligns with seasonal decreases in depth distribution (Fig. 2) and heightened surface-oriented behavior (Fig. 7). Only a single individual was recaptured from December to March, indicating that white seabass are less vulner- able to exploitation upon their dispersal to deeper waters during the winter months. The associations between fish depth distribution and catchability ob- served in this study are consistent with conclusions on seasonal fishery dynamics from Skogsberg (1939) and others (McCorkle6), who have reported that gill nets traditionally were deployed near the surface until mid-October and then set along the bottom from mid- October to December as fish retired to deeper waters. After December, landings were reduced substantially because fishermen were often unable to locate white seabass until the following summer (Skogsberg, 1939). Seasonal recapture trends align with historical fishery data, which indicate that the majority of white seabass landings in California occur from April to September (Skogsberg, 1925; Thomas, 1968). All tag deployments occurred from March to July and peaked in June, a pe- riod that directly aligns with the white seabass spawn- ing season (Aalbers, 2008) and validates a heightened vulnerability to capture when fish aggregate to spawn. 6 McCorkle, M. 2010. Personal commun. Commercial fish- erman, Santa Barbara, CA 93109. 10 Fishery Bulletin 1 13(1) Upon harvest, 77% of recaptured individuals were identified as female, indicating that white seabass sex can be adequately determined on the basis of the detec- tion of sound production during the spawning season. The skewed sex ratio of 3. 1:1.0 observed in this study may be related to temporal or size-related segregation among sexes; however, practical inferences cannot be made without a suitable sex-ratio estimate for the wild population. Vertical movements The observed shift of white seabass to deeper waters during the winter months may be in response to de- creased thermal stratification or possibly to the in- terrelated effects that these conditions have on prey distribution and availability. As reported for other spe- cies, multiple factors, such as changes in oceanographic conditions and prey distribution, contribute to the ver- tical movements displayed by a species at different times and locations (Hinke et ah, 2005; Shepard et ah, 2006; Schae- fer et ah, 2007; Sepulveda et al., 2010). Annual cycles of surface productivity and temperature structure off the coast of California have been shown to influ- ence the vertical distribution of Chinook salmon ( Oncorhynchus tshawytscha), with deeper profiles documented during the winter months (Hinke et ah, 2005). Seasonal shifts in vertical distribution have also been described for Atlantic cod ( Gadus morhua) (Neat et ah, 2006) and yellowtail flounder (Limanda ferruginea ) (Walsh and Morgan, 2004) in the north- west Atlantic. Given the interannual variability in the depth and temperature profiles ob- served for multiple tagged individuals (Fig. 3, A and B), it is likely that seasonal trends in vertical distribution are closely related to localized oceanic conditions. Interannual variation between consecu- tive winter seasons was evident from the 723-day track of fish A03595, which tran- sitioned from a mean depth of 31.8 m (SD 13.2) in the winter months of 2009-2010 to a mean depth of 8.4 m (SD 3.6) during the winter months of 2010-2011. Simi- larly, 5 tracks that extended throughout the winter months of 2010-2011 exhib- ited a considerable reduction in mean depth (18.4 m [SD 7.3]) compared with the 6 tracks recorded in the winter of 2008-2009 (30.8 m [SD 13.0]), but mean temperature values remained consistent (12.8°C) for both sets of time-series data. Spectral peaks at 1 and 2 cpd may represent increased vertical movements around dawn and dusk, and harmonic peaks at 3 and 4 cpd may indicate weaker movement patterns sur- rounding daily tidal fluctuations (Fig. 5A). Periodic os- cillations in the vertical thermal gradient within the coastal waters off San Diego have been shown to cycle at 6, 8, 12, and 24 h (1, 2, 3, and 4 cpd) relative to in- ternal tidal fluctuations (Cairns, 1968), which typically lag 3 to 5 h behind mixed semidiurnal surface tides (Cairns and LaFond, 1966). Therefore, consistent daily shifts in depth distribution of white seabass may corre- spond with semidiurnal fluctuations in coastal thermo- cline depth. Diel and circatidal rhythms in the vertical movement patterns of basking sharks ( Cetorhinus max- imus) also were identified in the northeast Atlantic on the basis of spectral peaks in fine-scale depth records at periods of 1 and 2 cpd (Shepard et ah, 2006). In the study described here, inconsistent harmonics in longer period (0.02-0.14 cpd) spectral density plots (Fig. 5B) indicate that the time-series data did not continuously Aalbers and Sepulveda: Seasonal movement patterns and temperature profiles of adult Atractoscion nobilis off California 11 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Figure 7 The percent occurrence of all depth values <5 m plotted by month to il- lustrate periods of surface-oriented behavior for 33 adult white seabass ( Atractoscion nobilis) tagged and released off California and Baja Califor- nia, Mexico, from 2008 to 2011. cycle at regular intervals over prolonged time periods (days to months). If this basic assumption of the FFT algorithm has not been met, then discontinuity would disperse energy throughout all frequencies (cpd), caus- ing considerable noise in the spectral density plots. Additional analyses from tracks of multiple individual fish with extended time-series records may further identify rhythms in vertical movements on a monthly (lunar) or seasonal scale. Increased VROM values around dusk and dawn in- dicate heightened crepuscular activity throughout the year. Heightened feeding activity in other fishes and sharks has been associated with crepuscular periods as well as with instances of increased vertical activity (Kitagawa et al., 2004, Sepulveda et ah, 2004, Best- ley et ah, 2008). Higher rates of crepuscular activ- ity indicate that white seabass are effective low-light predators and support fishery information that white seabass are targeted most effectively by hook-and-line fishermen during crepuscular periods (Pfleger7). Be- cause the spawning activity of white seabass peaks just after sunset during the spring and summer months (Aalbers, 2008), the increased VROM around dusk may also correspond with vertical excursions as- ' Pfleger, T. 2010. Personal commun. Pfleger Institute of Environmental Research, 2110 South Coast Hwy., Oceanside, CA 92054. sociated with spawning-related behavior and broadcast spawning events (Aalbers and Drawbridge, 2008). In contrast, diel surface-oriented behavior was observed most consistently during the midday (0900-1600 PST) and predawn (2300-0300 PST) hours, timing that co- incided with periods of reduced vertical activity (Fig. 6, A and B). Surface-oriented behavior has also been described for white seabass during courtship periods within the hours preceding sunset (Aalbers and Draw- bridge, 2008), periods when fish may be more vulner- able to spear fishermen and surface gill nets. Horizontal movements It was not uncommon for individuals to move more than 500 km from their initial point of release, veri- fying that white seabass are a highly mobile coastal species. A 109-cm-TL female travelled a net distance of 555 km over a 76-day period from Santa Catalina Island to Monterey Bay, California, at a rate of 8 km day-1. Collectively, a mean displacement of 229 km from the initial tagging location indicates that white seabass are capable of extensive seasonal migrations. Widespread horizontal movements during the spawn- ing season are consistent with recent data that indi- cate limited residency periods at distinct spawning sites along the southern coast of California (Aalbers and Sepulveda, 2012). The broad movements docu- 12 Fishery Bulletin 1 13(1) mented in our study contrast with the limited home ranges that have been observed in other coastal fishes (Holland et ah, 1996; Lowe et ah, 2003; Neat et ah, 2006). Although 11 of the tagged white seabass were recaptured within close proximity to their release sites after periods of up to 1154 days, interim movements away from the area during their time at liberty may have been substantial. Because fisheries-related infor- mation indicates that white seabass tend to reoccur within specific areas from year to year (Thomas, 1968) and considering the mean time at liberty for recaptures with short displacements was near 1 year in our study, it is possible that white seabass maintain an affinity for distinct sites or habitats that are revisited annually for feeding or spawning. Although the majority of tag deployments occurred around Santa Catalina Island, most tags were recov- ered within the near-coastal waters. Only 2 tagged fish were recaptured around Santa Catalina Island, and interisland movements were not documented in this study. Seven individuals that were tagged around Santa Catalina Island were subsequently recaptured off the coast of Ventura, indicating a consistent route between Catalina Island and the Ventura flats. An ad- ditional 7 fish that were tagged around Santa Catalina Island in May and early June were later caught in the vicinity of Monterey Bay during late July and August of the same or following year, indicating that a portion of the stock traveled up the California coast during the summer months of some years. The high incidence of white seabass tag recaptures in Monterey Bay (26%) corresponds with the recent observed increase in recre- ational (38%) and commercial landings (22%) north of Point Arguello (CDFG, 2011). Trends from tag deployments and recaptures indi- cated that white seabass moved seasonally in a north and westerly direction from July to September, as sea-surface temperatures (SSTs) increased through- out Southern California. Similar movement patterns based on fisheries-related data for Pacific barracuda (, Spliyraena argentea [see Pinkas, 1966]) and yellow- tail jack ( Seriola lalandi [see Baxter, I960]) have been suggested for other predatory species of the Southern California Bight. Northward movements of white sea- bass correspond with latitudinal shifts in SST maxima that follow a seasonal relaxation of coastal wind-driven upwelling and occur later (September-October) to the north of Point Arguello than SST peaks within the eastern Southern California Bight (August) (Legaard and Thomas, 2006; Garcia-Reyes and Largier, 2012). The observed drop in mean temperature values during the months of July-October (Fig. IB), after a peak in June, may represent decreased SSTs when fish moved above Point Arguello during the summer and fall months, where ambient temperatures are consistently lower than those off the southern coast of California (Reid, 1988). An observed decline in mean depths, tem- peratures, and VROM values during the late summer and autumn months supports the Skogsberg (1939) hy- pothesis that white seabass progress northward along thermal fronts as temperatures increase within the Southern California Bight; however, additional data from light-sensitive archival tags with external tem- perature sensors are necessary to better assess annual migration routes and seasonal trends. Temperature profiles Although white seabass occurred across a broad tem- perature range (8-24°C), data indicate that white seabass occupy a relatively narrow thermal gradient, spending more than half of their time at temperatures between 13° and 16°C (Fig. IB). Chinook salmon have also been reported to predominantly inhabit a narrow temperature range (8-12°C), indicating that fish may alter their depth in the water column to maintain a persistent thermal experience (Hinke et ah, 2005). The relatively consistent temperature profiles from annual time-series records indicate that white seabass may al- ter spatial and temporal behavior patterns to occupy a particular thermal niche. Periods of heightened surface-oriented behavior directly aligned with the months in which waters in Southern California exhibit the greatest degree of ther- mal stratification, with a relatively strong and shallow thermocline present from May to September through- out the region (Cairns and LaFond, 1966). Additionally, a peak in white seabass temperature records (Fig. IB) corresponds with the 14°C isotherm that is commonly used to identify thermocline depth along the southern coastline of California (Cairns, 1968). However, because tag sensors were implanted within the peritoneal cav- ity of white seabass, thermal inertia prevented accu- rate measurement of thermocline depth from tag re- cords. Further, because white seabass occurred over a broad stretch of coastline within areas of high mixing (i.e., upwelling zones and offshore islands) it is difficult to ascertain how thermocline depth influenced vertical distribution in this study. Future research and management Heightened fishing effort in conjunction with consider- able limitations in essential fishery information war- rants the continued need for fishery-independent data sources and active management practices for this spe- cies (MacCall et ah, 1976; CDFG1). Supplementary long-term tagging data, including archived light-level and external temperature records, are currently being collected to provide more specific information on white seabass migration patterns relative to seasonal and in- terannual variations in oceanic conditions. Additional time-series records from multiple years across the geo- graphic range of white seabass are needed to provide a more comprehensive understanding of fish habitat use, transboundary movements, and temporal shifts in distribution. Furthermore, complementary studies on white seabass stock structure along with a formal Aaibers and Sepulveda: Seasonal movement patterns and temperature profiles of adult Atractoscion nobilis off California 13 stock assessment with currently available data sources would better enhance our understanding of the popula- tion dynamics of this species and facilitate the develop- ment of long-term management strategies. In conclusion, this work provides insight into the seasonal movement patterns, habitat use, and depth distribution of wild-caught white seabass off the coast of California. Distinct seasonal depth distributions were identified with significantly deeper profiles during the winter months. Despite interannual variability, tagged adults spanned a narrow thermal gradient (13-16°C) centered around the 14°C isotherm, indicating the im- portance of environmental temperature on horizontal and vertical movements. A vertical shift to shallower waters during the spring and summer months directly coincides with the white seabass spawning period and with peak landings and fishing effort. Because of the diverse harvesting methods and seasonally high levels of fishing effort over a broad geographic range, all fish- eries must be considered for the effective management and long-term sustainability of this resource. Acknowledgments We thank T. Pfleger and family, the George T. Pfleger Foundation, the Catalina Seabass Fund, P. Offield, and the Offield Family Foundation for their generous sup- port. We appreciate donations from the San Diego Fish and Wildlife Commission, the Avalon Tuna Club, Oak- power Unlimited, and the Long Beach Neptunes. We also thank Captain T. Fullam, C. Heberer, M. Okihiro, B. Seiler, V. Wintrode, and K. Lafferty for assistance on various aspects of this work. We appreciate assis- tance and support from J. Albright and C. Albright, along with cooperation from all fishers that reported tag recovery information. We also thank J. Stopa for aid with graphic illustrations and J. Sepulveda for editorial support, in addition to valuable recommenda- tions by 3 anonymous reviewers. All experiments were performed under valid California Scientific Collection permit 002471. Literature cited Aaibers, S. A., G. M. Stutzer, and M. A. Drawbridge. 2004. The effects of catch-and-release angling on the growth and survival of juvenile white seabass captured on offset circle and j-type hooks. N. Am. J. Fish. Man- age. 24:793-800. doi: 10.1577/M03-034.1. Aaibers, S. A. 2008. Seasonal, diel, and lunar spawning periodicities and associated sound production management of the white seabass ( Cynoscion nobilis) in California waters. Fish. Bull. 106:143-151. 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Fish Game 21:1-27. 15 NOAA National Marine Fisheries Service Abstract— Underwater video sam- pling has become a common ap- proach to index fish abundance and diversity, but little has been pub- lished on determining how much video to read. We used video data collected over a period of 6 years in the Gulf of Mexico to examine how the number of video frames read af- fects accuracy and precision of fish counts and estimates of species rich- ness. To examine fish counts, we fo- cused on case studies of red snapper ( Lutjanus campechanus), vermilion snapper ( Rhomboplites aurorubens), and scamp (Mycteroperca phenax). Using a bootstrap framework, we found that fish counts were unbi- ased when at least 5 of 1201 video frames within a 20-min video were read. The relative patterns of coeffi- cients of variation (CVs) were nearly identical among species and declined as an inverse power function. Initial decreases in CVs were rapid as the number of frames read increased from 1 to 50. However, subsequent declines were modest, decreasing only by ~50% when the number of frames read increased by 300%. Es- timated species richness increased asymptotically as the number of frames read increased from 25 to 200 frames, and reading 50 frames documented 86% of the species ob- served across all 1201 frames. Last- ly, we used a generalized additive model to show that the most likely species to be missed were fast-swim- ming fishes that are solitary or form relatively small schools. Our results indicate that the most efficient use of resources (i.e. , maximum informa- tion gained at the lowest cost) would be to read -50 frames from each video. Manuscript submitted 30 July 2013. Manuscript accepted 13 November 2014. Fish. Bull. 113:15-26 (2015). doi: 10.7755/FB.113.1.2 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 fv established 1881 • Vftrue Therefore, Pv p is a proportion equal to zero if no spe- cies known to be present were detected on average or equal to one if all possible species were detected on average. To better understand the estimates of species rich- ness, we related the probability of being observed to behavioral characteristics of those species in videos. Specifically, we considered 2 characteristics of each priority species (s): 1) the mean number of individuals (Ns) seen in a video and 2) the mean duration (Ds; in seconds) each individual was observed in the videos. These mean values for each species were taken across videos in which a particular species was present. To re- move rare species for which mean characteristics may be poorly estimated, species were included in this anal- ysis only if observed in at least 10 videos. We then used a generalized additive model (GAM) to relate Ns and Ds, and their interaction, to the proportion of bootstrap replicates (Ys) in which species s was observed, from all videos where the species was present and where the number of frames read was F= 25. We used 25 frames in this study to provide a meaningful contrast across families in the probability of being observed; making such distinctions is important for detecting the ef- fects of predictor variables. All priority species were included in this analysis. Before fitting the GAM, the response variable Ys was transformed from probability space by using the arcsin squareroot transformation to achieve approximate normality, and predictor variables were taken in log space: arcsin = ^(logOVg)) + g2(loglDs ))+ g3(log(Ns), (log(Z),)), (6) where gi, g 2, and gq represent spline functions. The GAM approach strikes a balance between more simple and more complicated models, and it was chosen for its flexibility and for providing a straightforward interpretation of results. The GAM was implemented in the R programming language, vers. 2.15.1 (R Core Team, 2012) with the mgcv library (Wood, 2006). For presentation, the fitted response was transformed back into probability space by squaring the sine of the response. Lastly, we summarized the mean duration in a 20-m video segment, mean number of individuals in each vid- Bacheler and Shertzer: Estimating relative abundance and species richness from video surveys of reef fishes 19 Table 1 Mean duration and standard error of the mean (SE), measured in seconds (s), of individual fishes in video, mean number of individuals in videos, and mean probability that a fish species would be seen in a video segment (for those videos in which that species occurred) summarized by family for only those species seen in at least 10 videos from footage collected during the National Marine Fisheries Service’s reef fish video survey conducted in the Gulf of Mexico in 2001-2002 and 2004-2007 as part of its Southeast Area Monitoring and Assessment Program. Mean probability of being seen in a video was calculated for each species as the mean proportion of videos in which a species was observed (on the basis of 25 randomly selected frames) over all videos in which that species was present. Note that the family names for Labridae, Serranidae, and Scaridae follow the Integrated Taxonomic Information System (http://www.itis.gov). Standard errors of the means (SE) are provided in parentheses. Number of Mean duration Mean number Probability of being Family Common name species (s) of individuals seen in video Opistognathidae jawfishes i 504 22 1.00 Priacanthidae bigeyes 2 921 (SE 127) 3 (SE 1) 0.99 (SE 0.01) Holocentridae squirrelfishes 1 132 10 0.96 Pomacanthidae angelfishes 5 44 (SE7) 16 (SE 9) 0.85 (SE 0.03) Balistidae triggerfishes 3 66 (SE 40) 11 (SE 4) 0.84 (SE 0.07) Pomacentridae damselfishes 5 35 (SE 6) 23 (SE 7) 0.84 (SE 0.04) Labridae wrasses 7 15 (SE 2) 31 (SE 8) 0.80 (SE 0.06) Serranidae sea basses and groupers 23 30 (SE 2) 12 (SE 2) 0.78 (SE 0.02) Chaetodontidae butterflyfishes 3 31 (SE 3) 11 (SE 2) 0.77 (SE 0.03) Malacanthidae tilefishes 2 28 (SE 11) 8 (SE 0) 0.76 (SE 0.05) Sparidae porgies 6 14 (SE 2) 22 (SE 10) 0.75 (SE 0.03) Acanthuridae surgeonfishes 3 26 (SE 6) 6 (SE 1) 0.73 (SE 0.02) Haemulidae grunts 4 25 (SE 8) 22 (SE 6) 0.73 (SE 0.05) Lutjanidae snappers 7 12 (SE 1) 37 (SE 9) 0.73 (SE 0.04) Scaridae parrotfishes 4 23 (SE 2) 13 (SE 5) 0.71 (SE 0.05) Tetraodontidae puffers 2 25 (SE 7) 4 (SE 1) 0.64 (SE 0.13) Mullidae goatfishes 2 11 (SE 4) 14 (SE 6) 0.60 (SE 0.00) Muraenidae morays 2 40 (SE 4) 4 (SE 2) 0.60 (SE 0.07) Carangidae jacks 6 6 (SE 1) 14 (SE 2) 0.40 (SE 0.04) Sphyraenidae barracudas 1 18 4 0.34 Scombridae mackerels 1 5 2 0.17 eo segment, and probability of being observed in each video for each of the families of fishes included in the analysis described previously in this section (Table 2). The purpose of including this table is to inform read- ers working in tropical and subtropical oceans about those groups of species they are likely to see and those groups that they are likely to miss if adopting a Mean- Count approach where a subset of frames is read. Results MeanCount bias and precision The MeanCount estimator behaved similarly for the 3 species that we used as case studies. The central tendency across bootstrap replicates, represented by mean MeanCount, converged rapidly for red snapper, vermilion snapper, and scamp as the number of frames read increased (Fig. 2). MeanCount values for scamp and red snapper were less variable than the results for vermilion snapper (on the basis of 5th and 95th percen- tiles), and variability for all 3 species decreased when more frames were read (Fig. 2). Across all sampling events (i.e., all 20-min videos analyzed) in which the focal species was observed, there were no obvious biases in MeanCount for red snapper, vermilion snapper, or scamp at any level of sampling intensity for 25 to 200 frames read (Fig. 3). The variance for each species decreased as the number of frames read increased, a finding consistent with the results of the individually selected video analysis pre- viously described (Fig. 3). Furthermore, the variance surrounding MeanCount was approximately 50% lower for scamp than for either red snapper or vermilion snapper (Fig. 3). The relative patterns of MeanCount CVs were near- ly identical among the 3 species (Fig. 3). As the num- ber of frames increased from 1 to 200, the decrease in CV was initially rapid and then more gradual as more frames were read (Fig. 3). Because of this pat- tern, the largest reduction in CVs for all 3 species oc- curred as the number of frames read increased from 1 to 50. When frames read increased from 50 to 200 (i.e., 20 Fishery Bulletin 1 13(1) A C Fsgyre 2 MeanCount, which is calculated as the mean number of in- dividual fish observed in a series of frames over a viewing interval, of a single sampling event (i.e., a 20-min video seg- ment) in the northern Gulf of Mexico as a function of the number of video frames that were read for (A) red snapper C Lutjanus campechanus), (B) vermilion snapper (Rhombop- lites aurorubens), and (C) scamp (Mycteropei-ca phenax). In each panel, the heavy solid line represents the mean of 1000 bootstrap replicates, the lower dotted line represents the 5th percentile, the upper dotted line represents the 95th percen- tile, the thin solid line is a single bootstrap iteration, and the filled circle on the right is the true MeanCount across all 1201 frames that were analyzed for this study. 300% increase in frames read), CVs only declined by approximately 50% for all 3 species. In all cases, the relationship between mean CVs and number of frames read was described well by power functions (coefficient of determina- tion [r2]>0.99; P<0.0001 for F-statistics). Among the 3 species, the estimated relationships show differences in scale (a') but similar rates of de- cline ( b ). The mean estimates of parameters and standard errors of the mean (SE) were a'=1.324 (SE 0.004) and b=-0.525 (SE 0.001) for red snap- per, a'=1.585 (SE 0.004) and 6=-0.524 (SE 0.001) for vermilion snapper, and q'=0.981 (SE 0.004) and b=- 0.525 (SE 0.001) for scamp. Because the rates of decline were similar across species, the same number of frames could be read for each if the goal is to achieve a proportional reduction in CV from each species’ maximum (which occurred at F= 1). However, if the goal is to achieve a par- ticular CV, then each species would require a dif- ferent number of frames read. For example, a CV of 0.4 would require F=71 for red snapper, F=119 for vermilion snapper, and F= 37 for scamp. Species richness For illustration, we chose 3 example videos with varying levels of species richness to show general patterns in estimates of species richness. In these example videos, the estimated species richness (number of species observed) increased asymptoti- cally as more frames were read (Fig. 4). Although these 3 videos were chosen simply as examples, they show that the estimates of species richness increased stepwise as the number of frames read was incremented. That is, with the inclusion of each additional frame read, the species count ei- ther remained the same if that frame contained no new species or it increased by the number of new species observed. In these examples, the me- dian estimate captured 100% of the species pres- ent by around 50 frames for the videos with 3 or 7 species observed but not until around 100 frames for the video that contained 17 species (Fig. 4). Across all 1543 videos, the proportion of spe- cies observed increased with sampling intensity. Most species (median proportion=0.75) were ob- served in each video when only 25 of the 1201 frames were read, and the median proportion in- creased when 50 frames (0.86), 100 frames (0.95), or 200 frames (0.99) were read (Fig. 5). On the ba- sis of the interquartile range, however, there was substantial variability among videos, particularly when fewer than 100 frames were read (Fig. 5). When 100 or more frames were read, the vari- ability was lower but some rare species in some videos were still missed. The GAM explained 87.2% of the deviation in the probability that a species would be observed Bacheler and Shertzer: Estimating relative abundance and species richness from video surveys of reef fishes 21 ~ 0.04 3 o 0 02- c 03 ^ o.oo- LU cc -0.02- -0.06- A 0.06- B 0.06- T 0.04- -r- 0.04- | — r— _ 0.02- T -r- 0.02- 1 1 1 ' 1 1 ' 1 1 ' | n no □ □r 0 00- r~l l l “ uuu _i_ -1- ^ -0.02- -0.02- 4- -0.04- -0.04- -0.06- -0.06 - “I T 25 50 100 200 "T T 25 50 100 200 I 1 1 I I 25 50 100 200 n a; ra o v) > O 6- 4- D 8- _ M 00 L I 6- 4 - | 1 4- V 2 - 2 - - — r--.- 0- 0- 50 100 150 200 Number of frames 50 100 150 200 Number of frames I 50 T 0 50 100 150 200 Number of frames Figure 3 Top row: mean relative error (MRE) of MeanCount, the mean number of individual fish observed in a series of frames over a viewing interval, across all videos analyzed in this study from the northern Gulf of Mexico in 2001-2002 and 2004-2007, as a function of the number of video frames read for (A) red snapper (Lutja- nus campechanus), (B) vermilion snapper ( Rhomboplites aurorubens), and (C) scamp ( Mycteroperca phenax). Boxes represent the interquartile range, thick solid lines represent medians, and whiskers extend to the most extreme data point within 1.5 times the interquartile range from the box. Bottom row: coefficient of variation (CV) of MeanCount as a function of the number of video frames read for ( D ,) red snapper (Lutjanus campechanus ), (E) vermilion snapper (Rhomboplites aurorubens), and (F) scamp (Mycteroperca phenax ). In each panel, curves represent CVs from each sampling event (i.e. , each 20-min video collection), computed from 1000 bootstrap replicates. Each CV curve is scaled to its minimum. in 25 frames on the basis of the mean duration of each species in a video (estimated degrees of freedom [edf] = 1.5; F= 36.6; PcO.0001), mean number of indi- viduals in a video (edf=1.0; F= 43.9; P<0.0001), or their interaction (edf=7.8; F= 0.7; P=0.004). Species were ob- served with higher probability as their mean time in the videos increased; however, this probability saturat- ed near 1.0 for mean times of 100 s or more (Fig. 6A). Similarly, the probability of being observed increased as the mean number of individuals increased, but, the trend was nearly linear over the range of the predictor (Fig. 6B). The families of fishes that were most likely to be observed in 25 frames of video were the generally sedentary groups like jawfishes, bigeyes, squirrelfishes, angelfishes, and triggerfishes, and those families most likely to be missed were fast-moving groups like tunas and mackerels, barracudas, and jacks (Table 2). Discussion In many places around the world, underwater video has become a common approach to monitor the abun- dance and distribution of marine fish and invertebrate species and to quantify marine biodiversity (e.g., Heag- ney et al., 2007; Stobart et al., 2007; Brooks et al., 2011; Merritt et al., 2011; Gladstone et al., 2012). For many such studies, BRUVS have been used and have provided an index of the abundance of various species through the use of a stationary point-count with the MinCount method (Ellis and DeMartini, 1995; Willis et al., 2000; Murphy and Jenkins, 2010). Recent re- search has indicated that MeanCount is more linearly related to true abundance than is MinCount (Conn, 2011; Schobernd et al., 2014). To provide the next logi- cal step in the evaluation of the MeanCount approach, 22 Fishery Bulletin 1 13(1) Figure 4 Examples of species richness (total number of species) observed as a function of the number of video frames that were read for this study of the use of video surveys to index abundance and diversity of reef fishes in the northern Gulf of Mexico in 2001-2002 and 2004-2007. Each panel is from a different 20-min video segment that was analyzed and selected to represent a relative- ly (A) low, (B) medium, or (C) high number of species. In each panel, the solid line is the median value from bootstrap replicates, the lower dashed line is the lower 5th percentile, the upper dashed line is the 95th percen- tile, and the dotted horizontal line is the total number of species observed in the full video (across all 1201 video frames). we examined the tradeoff between time spent reading videos and the information obtained. In this study, we found that reading more frames decreased variability surrounding MeanCount for 3 reef fish species and in- ■o a> > a) if) n o in a> o CD CL if) 1.0- 0.8- 0.6- o 0.4- c o o 0.2- o al 0.0- 1 1 1 1 r- 25 50 100 150 200 Number of frames Figure 5 Proportion of species observed across all 20-min videos analyzed in this study as a function of the number of video frames that were read for this study of the use of video surveys to index abundance and diversity of reef fishes in the northern Gulf of Mexico in 2001-02 and 2004-2007. A value from each 20-min video was computed as the mean estimate of species richness (i.e., mean of the number of species observed across 1000 bootstrap replicates) divided by the total number of species known to be present in that video segment (i.e., observed in any of the 1201 video frames). Boxes represent the interquartile range, thick heavy lines represent medians, and whiskers extend to the most extreme data point within 1.5 times the interquartile range from the box. creased the total number of species observed, but bias was negligible even when a small number of frames were read (e.g., F= 25). These results will be useful to researchers in designing and tailoring their underwa- ter video surveys to incorporate MeanCount for estima- tion of relative abundance or species richness. Previous studies have shown that the number of taxa encountered in a wide variety of fisheries and wildlife monitoring studies is related to the spatial or temporal extent of sampling (Fuller and Langslow, 1984; St. John et ah, 1990; Barker et ah, 1993; Gled- hill, 2001). We observed an inverse power relationship between CVs and number of frames read and an as- ymptotic relationship between the number of species observed and the number of frames read. Therefore, CVs decreased and the number of species observed in- creased dramatically as the number of frames read in- creased from 1 to 50, but gains in precision were much more modest after that point. These results are simi- lar to results from studies of stream fishes that have documented a threshold of sites sampled beyond which the increase in species observed was negligible (Anger- meier and Smogor, 1995; Cao et ah, 2001; de Freitas Terra et ah, 2013). The number of frames that should Bacheler and Shertzer: Estimating relative abundance and species richness from video surveys of reef fishes 23 Figure 6 Relationship between the probability of a species being observed in a video segment and (A) its mean time in video or (B) the mean number of individuals of that species observed in each video. Included in the analysis were 90 reef fish species present in at least 10 videos in the National Marine Fisheries Service’s reef fish video survey conducted in the northern Gulf of Mexico in 2001-2002 and 2004-2007 as part of its Southeast Area Monitoring and Assessment Program. The solid black lines indicate fitted relationships from a gener- alized additive model, the dashed lines are 95% confi- dence intervals, and the tick marks on the x-axis show the distribution of values from the 90 species that were included in this analysis. be read is likely study-specific and would depend on the total number of videos to be read, the relative im- portance of rare species, the total resources available for video reading, and time constraints for video read- ing (Gledhill, 2001). Our results indicate that reading approximately 50 frames from each video may provide a reasonable compromise between costs and informa- tion gained, if one can accept that about 14% of species would be missed at each site compared with a reading of all frames in an entire 20-min video segment. As shown by our GAM results, behavioral character- istics largely determined how likely a species was to be observed or missed in a subset of video frames. Wheth- er a species is observed in a subset of video frames is almost entirely dependent on 2 behavioral character- istics: 1) the mean duration of time spent by each fish in the video viewing area and 2) the mean number of individuals present in each video. Fast-swimming and relatively infrequent fishes, such as tunas, mackerels, barracudas, and jacks, were the ones most likely to be missed and, therefore, tended to be underrepresented in estimates of species richness. These same taxa also had higher absolute CVs around indices of abundance than those for fishes like groupers and snappers that were observed more frequently. We also showed that CVs from observations of a fast-moving, schooling species (vermilion snapper) were more than twice as high as CVs for a slow-moving, nonschooling species (scamp), but the relative pattern of CVs was the same for both species. Clearly, researchers must carefully consider the behavior of their target species when de- signing a BRUVS sampling strategy with a MeanCount approach, for instance, by allocating significantly more video-reading effort if fast-moving, infrequently en- countered species are targeted. We estimated the proportion of species observed in a subset of frames compared with the number observed in all frames of a 20-min video segment, but note that reading all frames in a 20-min video segment likely underestimates all the species present at a site. For instance, Gledhill (2001) showed that approximately 68% of reef fish taxa in the Gulf of Mexico that were observed in a continuous 60-min video segment were observed in analysis of a 20-min segment. Further- more, given the exclusively diurnal sampling in our study, nocturnal fishes were likely poorly detected, as were small, cryptic species (Collette et al., 2003; Smith- Vaniz et al., 2006; Williams et al., 2006). Therefore, our results (from an approach for which a subset of frames was read) should be interpreted as a reduction in spe- cies observed compared with results from reading of a 20-min video segment, not a comparison with the true species richness at a site. Researchers could consider approaches that account for the fact that all video reading methods likely miss some reef fish species that are actually present at a site. First, occupancy or W-mixture modeling approach- es can estimate detection or capture probabilities sepa- rately from the underlying distribution or abundance of a species (MacKenzie et al., 2002; Royle, 2004), but multiple site visits may be necessary each year (Issaris et al., 2012) unless spatial aritocorrelation is modeled (Johnson et al., 2013). Second, if the emphasis is on es- 24 Fishery Bulletin 1 13(1) timation of species richness over an entire study area, species accumulation (i.e., rarefaction) curves may be a useful approach (e.g., Nichols et al., 1998; Thompson et al., 2003). Species accumulation curves and related ap- proaches (Angermeier and Smogor, 1995) may be espe- cially useful in diverse systems with many rare species (Green and Young, 1993; Gotelli and Colwell, 2001). Our study design included several simplifications. First, with our bootstrap procedure frames were se- lected at random for analysis. Alternative approaches may select frames systematically, either with fixed intervals (e.g., one frame every 30 s; Bacheler et ah, 2013) or through adaptive sampling. Second, we esti- mated the proportion of species observed in a subset of frames in relation to all of the species observed in each 20-min video segment. Ideally, our estimates would have been compared with the total number of species occupying the site, but true species richness at each site was unknown (Gotelli and Colwell, 2001). Third, we lacked information on current direction or magni- tude; therefore, we were unable to estimate the size or shape of the bait plume, information that can be impor- tant in determining the catch or counts of fishes made through the use of baited gears (Collins et al., 2002; Jamieson et al., 2006). Fourth, we did not account for temporal autocorrelation (i.e., samples taken closer in time are likely more similar than those taken further apart; Strachan and Harvey, 1996) when analyzing frames within a particular video. Temporal autocorre- lation violates the standard statistical assumption of independence among observations and, when present, may affect the estimated CVs. Temporal correlation is problematic for characterization of diel or seasonal variability but not for quantification of the density or number of species captured in a video. Temporal cor- relation could be minimized or avoided in practice by not choosing frames clustered in time. Fifth, our study would have been more informative if the costs of read- ing video frames were known, allowing for explicit cost-benefit analyses related to optimum sample sizes (Cochran, 1977; Thompson, 1992). However, these video data were recorded in a time in-time out format and not by individual frames, and, therefore, the costs of reading each frame could not be estimated. MeanCount, computed from a sequence of video frames, has been shown to track linearly with true abundance at a site (Conn, 2011; Schobernd et al., 2014) — a critically important issue when standard- izing survey data to produce abundance indices for use in stock assessment models (Maunder and Punt, 2004). Our study is the first, however, to document how the number of frames read can relate to CVs around MeanCount for reef fish species and the proportion of reef fish species observed at a site. Previous research has documented the general relationship between the spatial or temporal extent of sampling and CVs or the number of species observed (Fuller and Langslow, 1984; St. John et al., 1990; Barker et al., 1993; Gledhill, 2001). Similarly, we showed that the number of frames read was negatively related to CVs and positively re- lated to the proportion of species observed. More impor- tant, however, both relationships were nonlinear and indicate that the information gain slowed substantially after reading approximately 50 frames. Video studies that apply the MeanCount approach to other systems could use our GAM results to help broadly understand how many frames to read, accounting for the behaviors of the species of interest. Acknowledgments We thank M. Campbell, C. Gledhill, A. Pollack, and the Pascagoula laboratory of the NOAA Southeast Fisheries Science Center for providing access to the Gulf of Mexico reef fish video data, the staff and crew members who participated in data collection, and the Southeast Area Monitoring and Assessment Program for funding. We also thank M. Campbell, A. Chester, P. Conn, A. Hohn, T. Kellison, P. Marraro, Z. 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Detection of spatial variability in relative density of fishes: comparison of visual census, angling, and bait- ed underwater video. Mar. Ecol. Prog. Ser. 198:249- 260. doi: 10.3354/mepsl98249. Wood, S. N. 2006. Generalized additive models: an introduction with R, 392 p. CRC Press, Boca Raton, FL. 27 NOAA National Marine Fisheries Service Abstract— Gray triggerfish ( Bati- stes capriscus) sampled from rec- reational and commercial vessels along the southeastern coast of the United States in 1990-2012 (n=6419) were aged by counting translucent bands on sectioned first dorsal spines. Analysis of type of spine edge (opaque or translucent) revealed that annuli formed during March-June, with a peak in April and May. Gray triggerfish were aged up to 15 years, and the larg- est fish measured 567 mm in fork length (FL). Weight-length relation- ships from a different set of sampled fish were ln(W)=2.98xln(FL)-17.5 (n=20,431; coefficient of determi- nation [r1 2 * *]=0.86), In-transform fit; W=3.1xl0-5 TL2-88 (n=7618), direct nonlinear fit; and FL=30.33+0.79xTL (77=8065; r2=0.84), where W=whole weight in grams, FL=fork length in millimeters, and TL=total length in millimeters. Mean observed sizes at ages 1, 3, 5, 10, and 15 years were 305, 353, 391, 464, and 467 mm FL, respectively. The von Berta- lanffy growth equation for gray trig- gerfish was Lt= 457 ( l-e(“°-33u+1'58,)). Natural mortality (M) estimated by Hewitt and Hoenig’s longevity-based method that integrates all ages was 0.28. Age-specific M values, estimat- ed with the method of Charnov and others, were 0.65, 0.45, 0.38, 0.34, and 0.33 for ages 1, 3, 5, 10, and 15, respectively. Gray triggerfish recruit- ed fully to recreational fisheries by age 4 and to the commercial fishery by age 5. Estimates of total mortal- ity averaged 0.95 across all fisheries for the years 1986-2011. Manuscript submitted 2 August 2013. Manuscript accepted 17 November 2014. Fish. Bull. 113:27-39 (2015). doi: 10.7755/FB.113.1.3 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 Hr established 1881 ■60% of the width of the previous opaque zone. On the basis of edge frequency analysis, all samples were assigned a chronological, or calendar, age obtained by increasing the translucent zone count by one if the fish was caught before that increment was formed and had an edge with an opaque zone that was moderate to wide (type 3 or 4). All fish caught after translucent zone formation would have a chronological age equivalent to the translucent zone count. Burton et al . : Age, growth, and mortality of Batistes capr/scus from the southeastern United States 29 Growth Von Bertalanffy (1938) growth parameters were es- timated from the observed length-at-age data. The chronological age of the fish was adjusted for the time of year caught ( Moc ), therefore, creating a fractional age (Age f) from the chronological age ( Agec ) on the ba- sis of a July 1 birth date ( Mo b ): Age f = Agec + (( Moc - Mo b)/ 12). ( 1) This birth date was selected on the basis of repro- ductive studies that show that peak spawning of gray triggerfish occurs during June-July in waters off the SEUS (Moore, 2001) and in the GOM (Simmons and Szedlmayer, 2012). Parameters were derived with the PROC NLIN procedure and the Marquardt option in SAS5 statistical software, vers. 9.3 (SAS Institute, Inc., 1987). A Student’s t-test (P< 0.05) was used to detect if there were significant differences in mean sizes be- tween sectors for the purpose of determining whether pooling of data across sectors was appropriate. We also performed an analysis of covariance (ANCOVA) of length-at-age data by sector (recreational versus commercial), using age as the covariate, to determine whether pooling of data was appropriate (i.e., there were no significant differences in length at age by sector). Weight-length relationships We regressed fish whole weight (W, in grams) on fish FL (in millimeters, n=20,431) and TL (in millimeters, «=7618), using data for all gray triggerfish measured by the SRHS from 1972 to 2010 and not just those fish sampled for aging structures. Total length was not measured for many of the fish, and some fish were not weighed. The fish used for age analysis (n=6419) were a subset of the total number of gray triggerfish measured by the SRHS (rc=20,431). We regressed FL on TL (n=8065), also with the SRHS data set. For all relationships, we evaluated both a nonlinear fit, using nonlinear least squares estimation in SAS software (SAS Institute, Inc., 1987), and a linearized fit of the log-transformed data, examining the residuals to deter- mine which regression was appropriate. Total mortality Age-length keys (Ricker, 1975) were developed for 25- mm intervals by using all aged specimens and the cal- culation of the age distribution (measured as a percent- age) for each interval. Age frequencies for unagecl fish by sector were developed with age-length keys (for aged fish) weighted by annual landings from the respective sector and length frequencies (for unaged fish); data 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. for both the landings and length frequencies were ac- quired from the SRHS, the NMFS Marine Recreational Information Program (MRIP) for samples from recre- ational fishermen other than those on headboats, and the SEFSC TIP. To optimize the accuracy and precision of our estimates, we ensured that we met the criteria of Coggins et ah (2013) with respect to total sample size (500-1000) and number of aged fish per length bin (at least 10 fish per bin). Total instantaneous mortality rates (Z) were es- timated by using catch curve analysis (Beverton and Holt, 1957). Only fully recruited ages (modal age+1) were used to estimate Z because the age group at the top of the catch curve may not be fully vulnerable to the fishing gear (Everhart et ah, 1975). Natural mortality We estimated the instantaneous rate of natural mortal- ity ( M ) using 2 methods. 1) Hewitt and Hoenig’s (2005) longevity mortality relationship: M = 4.22 Amax, (2) where tmax is the maximum age of the fish in the sample; 2) Charnov et ah’s (2013) method, where von Berta- lanffy growth parameters are used: M = (L/LcJ-1-5 x K, (3) where L„ and K are the von Bertalanffy growth equa- tion parameters (asymptotic length and growth coef- ficient); and L = fish length at age. With the Hewitt and Hoenig method, life span or lon- gevity is used to generate a single point estimate, and it is an improvement to the original equation of Hoenig (1983). The newer Charnov method, which incorporates growth parameters, is an improvement to the empiri- cal equation of Gislason et al. (2010) and is based on evidence that indicates that M decreases as a power function of body size. The Charnov method generates age-specific rates of M and is currently in use in South- east Data Assessment and Review (SEDAR) stock as- sessments (Williams6). Results Age determination A total of 6419 first dorsal spines of gray triggerfish were sectioned. The distribution of samples by area and fishery sector is shown in Table 1. The majority of sam- ples came from the commercial sector in North Caro- 6 Williams, E. 2013. Personal commun. Southeast Fisher- ies Science Center, National Marine Fisheries Service, Beau- fort, NC 28516-9722. 30 Fishery Bulletin 1 13(1) Table 1 Number of samples of first dorsal spines that were available for our age and growth study of gray triggerfish (Balistes capriscus) collected during 1990-2012, primar- ily from fisheries landings along the coast of the southeastern United States. Five samples were collected during fishery-independent trap sampling off Florida’s east coast. Values in the columns for the recreational sector include samples from both the headboat component and the component that includes private recreational boats and charter boats. Samples were collected in the following states: Florida (FL), Georgia (GA), North Carolina (NC), and South Carolina (SC). Commercial Recreational Year FL-GA NC SC FL-GA NC SC 1990 18 1991 5 33 4 1994 1 1997 2 2001 2 2002 8 5 2003 43 2004 3 188 60 2005 386 157 1 2006 327 140 91 7 13 2007 493 203 17 36 26 2008 676 88 6 13 15 2009 648 92 5 6 21 2010 695 297 1 69 28 2011 1052 220 3 36 23 2012 5 lina and South Carolina. Approximately 10% of aging samples were from Florida, and the majority of those samples were from the headboat component catches of the recreational sector. Translucent zones were counted on 6267 (97.7%) of the 6419 sectioned spines. Sections from the other 152 spines (2.3%) were determined to be unreadable and were excluded from this study. For our analysis of increment periodicity, we as- signed an edge type to all 6267 samples. Translucent zones were present on the spine marginal edge in all months (Fig. 1); the highest percentage of gray trig- gerfish with translucent zones occurred from March to June and the lowest from September to February; peak formation occurred in April and May (Fig. 1A). A clear pattern of the width of the opaque margin was noted (Fig. IB). The narrowest opaque margins (e.g., edge type 2) occurred during June-September, which follows the period of peak formation of the translucent zone. The widest opaque margins occurred during De- cember-March, when the translucent zones start form- ing again. We concluded that translucent zones on gray triggerfish spines were annuli. Chronological ages re- sulting from edge analysis were assigned as follows: for fish that were caught from January to June and had an edge type of 3 or 4, the chronological age was the annuli count increased by one; for fish that were caught during the same period and had an edge type of 1 or 2, the chronological age was equivalent to the annuli count; and, for fish that were caught from July to December, the chronological age was equivalent to the annuli count. Growth increments of gray triggerfish were moder- ately difficult to interpret. Based on Campana’s (2001) acceptable values of APE (5%), agreement was moder- ate across all 3 readers (MLB-JCP APE=11%, n = 198; MLB-MC APE=9%, n=100; JCP-MC APE=12%, n = 100; overall APE=11%). Percent agreement values between the 2 primary readers (MLB and JCP) were low (34%) but increased for estimates within (±) 1 year (67%) and within (±) 2 years (86%). An age bias plot indicates that the second primary reader, in comparison with the first primary reader, underestimated gray triggerfish ages, starting at age 5 (Fig. 2), but also shows that the average difference between readers for ages 5-10 was only 1.2 years. These results indicate acceptable between-reader agreement; hence, we included ages from all 3 readers in further analyses. Growth Gray triggerfish in this study (n=6267) ranged in size from 173 to 567 mm FL and in age from 0 to 15 years. A single age-0 fish was captured by fishery-indepen- Burton et al: Age, growth, and mortality of Balistes capriscus from the southeastern United States 31 0 Edge type 4 □ Edge type 3 □ Edge type 2 ■ Edge type 1 10 11 12 Figure 1 Monthly percentages of (A) spine sections with translucent margins on their edges, with monthly sample sizes, and (B) monthly percentages of all edge types for gray triggerfish ( Balistes capriscus) collected from the southeastern United States in 1990-2012. Edge codes: l=translucent zone on edge, indicating annulus formation; 2=small opaque zone, <30% of previ- ous increment; 3=moderate opaque, 30-60% of previous increment; 4=wide opaque, >60% of previous increment. dent trap gear, but there were only 13 fish older than age 11 (Table 2). Length and age distributions of the samples by sector (commercial versus recreational) are shown in Figure 3. Visual examination of size and age frequency plots showed no apparent differences in both distributions by sector, with the exceptions that no fish older than age 9 occurred in the recreational samples and commercial samples had fish up to age 15 (Fig. 3A). Modal lengths were 350 mm FL for the commer- cial sector and 325 mm FL for the recreational sector (Fig. 3B). Mean fork lengths of the specimens by fish- ery were significantly different: 383 mm FL (standard error [SE] 0.7) for the commercial sector versus 350 mm FL (SE 1.9) for the recreational fishery (£=16.72; df=6253; P=0.0001). The modal age frequency for both fisheries was 4 years (Fig. 3A). Mean ages were found to be significantly different between fisheries: 4.6 years (SE 0.02) versus 4.0 years (SE 0.04) for commercial and recreational sectors, respectively (£=11.9; df=1042.3; P=0.0001). 32 Fishery Bulletin 1 13(1) Primary Reader Figure 2 Age bias plot for 198 gray triggerfish (Batistes capriscus ) sampled from the southeastern United States during 1990-2012 and aged by 2 primary readers. The first reader’s mean age estimates are plotted against the second reader’s age estimates. Error bars indicate standard deviations. An ANCOVA of length at age for individual ages revealed no significant differences in size at age be- tween the 2 sectors (P=0.33) for 7 of the 9 ages for which comparisons could be made (Table 3). When the ANCOVA was performed for state, 9 of 11 tests were nonsignificant. On the basis of these results, we pooled data across sectors and states. The resulting von Ber- talanffy growth equation was Lt = 457( l-e_0-33(t + L58)) (4) for all sectors, states, and sexes combined (n- 6267) (Table 4; Fig. 4). Weight-length relationships Statistical analyses revealed an additive error term (variance not increasing with size) in the residuals of the W-TL relationship, indicating that a direct nonlin- ear fit was appropriate. This relationship is described by the following regression: W = 3.1 x 10-5 TL2-88 (n=7618). (5) Residuals of the W-FL relationship exhibited multipli- cative error, indicating that a linearized ln-transform fit of the data was appropriate. This relationship is de- scribed by the following regression: ln( Wj = 2.98 ln(FL) - 17.5, (ra=20,431; r2=0.86) (6) where r 2 is the coefficient of determination. This equa- tion was transformed back to the form W = axFLh (7) after adjustment of the intercept for log-transformation bias with the addition of one-half of the mean square error (MSE) (Beauchamp and Olson, 1973), resulting in this relationship: W = 2.55 x 10-5 FL2-98 (rc=20,431; MSE=0.035). (8) The relationship between FL and TL is described by the following equation: FL = 30.33 + 0.79 x TL (72=8065; /-2=0.84). (9) Natural mortality Hewitt and Hoenig’s (2005) method, which uses maxi- mum age or life span (15 years in this study), esti- mated that M was 0.28. The method of Charnov et al. (2013), which produces age-specific estimates of M with the use of von Bertalanffy growth parameters, resulted in estimates of 0.65 for age-1 fish, 0.38 for age-5 fish, 0.34 for age-10 fish, and 0.33 for age-15 fish (Table 2). Burton et a!.: Age, growth, and mortality of Bahstes capriscus from the southeastern United States 33 Table 2 Observed and predicted mean fork length (FL), measured in millime- ters, and natural mortality at age (M) data for gray triggerfish (Bali- stes capriscus) collected in 1990-2012 along the coast of the southeast- ern United States. Standard errors of the means (SE) are provided in parentheses. Age n Mean FL (SE) FL range Predicted FL M 0 i 173 _ 181 0.94 1 23 305 (11) 201-394 257 0.65 2 451 333 (2) 214-560 312 0.52 3 1470 353 (1) 190-530 351 0.45 4 1773 375 (1) 229-550 380 0.41 5 1336 391 (1) 221-526 481 0.38 6 684 411 (2) 300-546 417 0.36 7 313 428 (3) 295-543 428 0.36 8 130 444 (4) 330-567 436 0.35 9 53 468 (6) 330-546 442 0.34 10 22 464 (11) 360-550 446 0.34 11 6 416 (30) 323-513 449 0.34 12 4 482 (23) 417-520 451 0.34 13 1 410 - 453 0.33 14 1 496 - 454 0.33 15 1 467 — 455 0.33 Total mortality Gray triggerfish were fully recruited to the headboat fishery by age 4, to the private recreational fishery by ages 4-5, and to the commercial fishery by age 5. Es- timates of Z were similar among all 3 of these sectors. Mean annual estimates of Z for the years 1986-2011 (from all available data) were 0.94 for the headboat fishery and 0.89 for the other recreational fishery. Mean annual total mortality for the commercial fishery was 0.91 for available data (1995-2011, except for 1997 and 2002). Through the use of a pooled catch-at-age matrix across all sectors, Z was estimated at 0.95 (n = 15; stan- dard deviation=0.02; range=0.93-0.97). These results equate to an average annual mortality rate of 0.61 across all 3 sectors. Ricker (1975) defined the annual mortality rate A as “the number of fish which die dur- ing a year (or season) divided by the initial population number.” Discussion Gray triggerfish are admittedly difficult to age. First, the use of an external bony structure, the first dor- sal spine, to age the fish has some inherent problems, such as possible resorption of the material or damage to the structure — both of which would not likely affect otoliths. Second, the interpretation of the increments on the spines was variable, for reasons such as the spacing between increments and the subjectivity of the presence of false annuli. Because of these problems, we, along with members of the staff of another laboratory that has been involved in aging fishery-independent samples of gray triggerfish, held a workshop to ad- dress issues with aging this fish. A robust set of cri- teria for interpreting the increments on the spine was established during this workshop. Using these newly established criteria, we reread a set of their samples. We found consistent agreement between readers and within readers in our own study, as evidenced by the APE calculations presented in the previous section. Therefore, the results of this study represent the best available information on the longevity and growth of gray triggerfish. The spine edge analysis conducted in this study strongly indicates that gray triggerfish deposit one an- nulus per year from March to June and that peak an- nulus formation occurs in April and May. This result is similar to findings in other studies where peak annulus formation occurred in June and July in gray triggerfish in the Gulf of Mexico (Johnson and Saloman, 1984) and in June in fish from the east coast of the United States (Moore, 2001) (Table 4). The timing of the deposition of a growth increment in Moore’s study was concurrent with peak spawning in June and July. Gray triggerfish in the Gulf of Mexico also have exhibited temporally similar times of annulus formation and peak spawning (Simmons and Szedlmayer, 2012). Weight-length relationships were nearly identi- cal for gray triggerfish from the SEUS and the Gulf of Mexico. The relationship between FL and TL was also similar: EL=30.33+0.79xTL for fish off the Atlantic 34 Fishery Bulletin 1 13(1) o c c r 0) 1800 1600 1400 1200 1000 800 600 400 200 0 1 S Commercial ■ Recreational .1, 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Age (years) B 1400 cr CD 1200 1000 800 600 400 200 Q Commercial 0 Figure 3 Distributions of (A) age frequency and (B) length frequency, by fishing sector, for aging samples of gray triggerfish (Bcili- stes capriscus ) collected from the southeastern United States in 1990-2012. coast versus FL= 29.70+0.77 xL for the Gulf population (Johnson and Saloman, 1984). Gray triggerfish grew moderately fast, attaining an average observed size of 353 mm FL (14 in) by age 3 (Table 2). This result compares favorably with the find- ing of Johnson and Saloman (1984) that gray trigger- fish from the Gulf of Mexico also grow moderately fast at earlier ages, attaining an average size of 357 mm FL by age 3, growing an average of an additional 50 mm per year through age 5, and averaging gains in growth of 15 mm per year at ages 6-13. Growth of fish in our study slowed after age 3, reaching 496 mm FL by age 5, and then averaging annual size increment increases of 21 mm through age 10. Several previous studies have found that male gray triggerfish are substantially larger than female fish (Johnson and Saloman, 1984; Moore, 2001; Simmons and Szedlmayer, 2012). These findings justify the gen- eration of sex-specific growth curves if possible. Unfor- tunately, the specimens we used were collected under sampling protocols that did not allow for the collection of sex-specific data. We recommend that strategies to obtain these data would be beneficial in future studies, if possible. Because our aging structures came from specimens acquired exclusively from fishery-dependent sources and, therefore, may be more representative of the fished population than the whole population, we advise caution in interpretation of gray triggerfish growth curves, especially for the region of the curve that de- scribes the youngest ages. Minimum size regulations could have an effect on the size of fish available to Burton et al.: Age, growth, and mortality of Bcilistes capriscus from the southeastern United States 35 Table 3 Results of analysis of covariance of length at age testing for differences by fishery (rec- reational and commercial) and state (NC, SC, FI^GA) between gray triggerfish ( Bcilistes capriscus) aging samples collected during 1990-2012. An asterisk (*) indicates a sig- nificant probability value. A dash indicates that the sample distribution did not allow for a test of significance. Age n Fishery State Fishery*State 0 i _ _ _ 1 23 F=0.03,P=0.87 F=5.76, P=0.02* - 2 451 F=2.01, P=0.157 F=1.59,P=0.20 F=7.02, P=0.001* 3 1470 F=16.74,P=0.001* F=0.94, P=0.39 F=1.27, P=0.28 4 1773 F=0.33,P=0.56 F=1.46,P=0.23 F=0.83, P=0.43 5 1333 F=0.23, P=0.63 F=0.81,P=0.44 F=2.76, P=0.06 6 684 F=2.27,P=0.13 F=0.001, P=0.99 F=2.80, P=0.06 7 313 F=4.58, P=0.03* F=2.06, P=0.12 F=1.09, P=0.33 8 130 F=2093, P=0.09 F=0.63,P=0.53 F=0.03, P=0.43 9 53 F=1.82,P=0.18 F=10.75,P=0.0001* - 10 22 - F=0.14, P=0.71 - 11 8 - F=1.08,P=0.34 - 12 4 - - - 13 1 - - - 14 2 - - - 15 1 - - generate growth estimates. Even though size limits existed only for fish taken from waters off the east- ern coast of Florida during our study (432 of 6267 fish, or 7%), we re-ran the growth model using the method of McGarvey and Fowler (2002), which adjusts for the bias imposed by minimum size limits, and we found no effect of minimum size limits on our parameter es- timates. We are confident that our samples represent the smallest fish recruited to the hook-and-line gears. Nevertheless, we collected few fish younger than age 2. It is probable that more comprehensive sampling with fishery-independent gear would capture younger gray triggerfish. As another strategy to address the lack of smaller, younger fish and the effect this deficiency may have on estimation of the early part of the growth curve, Table 4 Comparison of life history parameters of gray triggerfish ( Batistes capriscus ) from various studies. L00=asymptotic length; F=growth coefficient; fo=theoretical age at length of zero; SEUS=southeastern United States; and FL=fork length. Parameter Study (mm) K to Peak in translucent edges Peak spawning Maximum age (yr) Johnson and Saloman ( 1984) — U.S. Gulf of Mexico 466 FL 0.38 - 0.19 June-July April-May 13 Moore (2001)— SEUS Males 521 FL 0.17 -2.03 June June-July 10 Females 443 FL 0.19 -2.26 June May-Sept 9 Escorriola (1991) 571 FL 0.19 -0.15 July-Sept - 13 Burton et al. (current study) 457 FL 0.33 -1.58 April-May - 15 36 Fishery Bulletin 113(1) 600 500 3- 400 LL E E £ 300 CD C 200 100 0 it=457(l-e<-°-3300141-6. Farmer, A. S. D. 1981. Historical review of the Kuwait shrimp culture project. Kuwait Bull. Mar. Sci. 2:3-9. Frederick, J. L. 1997. Evaluation of fluorescent elastomer injection as a method for marking small fish. Bull. Mar. Sci. 61:399-408 Frusher, S. D. 1985. 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An approach to evaluating the potential for stock enhancement of brown tiger prawns ( Penaeus esculentus 46 Fishery Bulletin 113(1) Haswell) in Exmouth Gulf, Western Australia. In Stock enhancement and sea ranching: development, pitfalls and opportunities, 2nd ed. (K. M. Leber, S. Kitada, H. L. Blankenship, and T. Svasand, eds.),p. 444-464. Black- well Publ., Oxford, UK. Loneragan, N. R., Y. Yimin, R. A. Kenyon, and M. D. E. Haywood. 2006. New directions for research in prawn (shrimp) stock enhancement and the use of models in provid- ing directions for research. Fish. Res. 80:91-100. doi: 10.1016/j.fishres.2006.03.014. Lorenzen, K., K. M. Leber, and H. L. Blankenship. 2010. Responsible approach to marine stock en- hancement: an update. Rev. Fish. Sci. 18:189-210. doi: 10.1080/10641262.2010.491564. Meager, J. J. 2003. The microhabitat distribution of juvenile banana prawns, Penaeus merguiensis de Man and processes affecting their distribution and abundance, Ph.D. thesis, 221 p. Queensland Univ. Technol., Brisbane, Australia. Neal, R. A. 1969. Methods of marking shrimp. FAO Rep. 57(3): 1149-1165. Niamaimandi, N. 2006. Bio-dynamics and life cycle of shrimp (Penaeus semisulcatus de Haan), in Bushehr coastal waters of the Persian Gulf. Ph.D. thesis, 206 p. Univ. Putra Malay- sia, Kuala Lumpur, Malaysia. Preston, N. P, D. C. Brennan, and P. J. Crocos. 1999. Comparative costs of postlarval production from wild or domesticated Kuruma shrimp, Penaeus japonicus (Bate), broodstock. Aquacult. Res. 30:191-197. doi: 10. 1046/j. 1365-2109. 1999.00306.x. Rothlisberg, P. C., D. J. Staples, and P. J. Crocos. 1985. A review of the life history of the banana prawn. Penaeus merguiensis, in the Gulf of Carpentaria. In Second Australian National Prawn Seminar; Kooral- byn, 22-26 October 1984 (P. C. Rothisberg, B. J. Hill, and D. J. Staples, eds.), p. 125-136. NPS2, Cleveland, Australia. Staples, D. J. 1985. Habitat requirements of juvenile prawns. In Sec- ond Australian National Prawn Seminar; Kooralbyn, 22-26 October 1984 (P. C. Rothlisberg, B. J. Hill, and D. J. Staples, eds.), p. 52-55. NPS2, Cleveland, Australia. Staples, D. J., and D. J. Vance. 1985. Short-term and long-term influences on the immi- gration of postlarval banana prawns Penaeus merguien- sis, into a mangrove estuary of the Gulf of Carpentaria, Australia. Mar. Ecol. Prog. Ser. 23:15-29 Van Zalinge, N. P. 1984. The shrimp fisheries in the Gulf between Iran and the Arabian Peninsula. In Penaeid shrimps — their bi- ology and management (J. A. Gulland and B. J. Roths- child, eds.), p. 71-78. Fishing News Books, Farnham, England. Vance, D. J., M. D. E. Haywood, D. S. Heales, R. A. Kenyon, N. R. Loneragan, and P. C. Pendrey. 1996. How far do prawns and fish move into mangroves? Distribution of juvenile banana prawns, Penaeus mer- guiensis and fish in a tropical mangrove forest in north- ern Australia. Mar. Ecol. Prog. Ser. 131:115-124. doi: 10.3354/mepsl31115. Ward, R. D. 2006. The importance of identifying spatial popula- tion structure in restocking and stock enhancement programmes. Fish. Res. 80:9-18. doi: 10.1016/j. fishres.2006.03.009. Wang, Q., Z. Zhuang, J. Deng, and Y. Ye. 2006. Stock enhancement and translocation of the shrimp Penaeus chinensis in China. Fish. Res. 80:67— 79. doi: 10.1016/j.fishres.2006.03.015. Xu, J., M. Xia, X. Ning, and C. P. Mathews. 1997. Stocking, enhancement, and mariculture of Penae- us orientalis and other species in Shanghai and Zheji- ang Provinces, China. Mar. Fish. Rev. 59:8-14. 47 NOAA National Marine Fisheries Service Abstract— Multiple structures can be used for the age determination of fishes. Choosing the structure that provides the most precise ages is important for the provision of con- sistent data for the management of commercially and recreationally im- portant species, such as the Ameri- can shad (Alosa sapidissima). In this study, we compared the precision of age estimates obtained from sagit- tal otoliths, vertebrae, scales, and opercula as structures for the age determination of American shad. Two readers examined structures removed from 462 American shad, which were collected from the Mer- rimack River in Lawrence, Massa- chusetts, during May and June of 2008-2010. The precision of age es- timates were evaluated by compari- sons of ages from different readers and structures. Age estimates deter- mined from otoliths were the most precise (76.2% agreement, 2.99% co- efficient of variation). Ages derived from scales were overestimated in young (<5 years) fish and underesti- mated in older (>7 years) fish, com- pared with ages determined from otoliths. Age estimates determined from vertebrae agreed with those ob- tained from otoliths better than ages from any other structure tested, but they were less precise and vertebrae required more processing than oto- liths. Opercula were difficult to read, resulting in underestimation of the ages of fish that were age 5 and old- er. The results of this study indicate that the sagittal otolith is the most appropriate structure for determin- ing the age of American shad. Manuscript submitted 25 October 2013. Manuscript accepted 25 November 2014. Fish. Bull. 113:47-54 (2015). doi: 10.7755/FB.113.1.5 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 -7 years) fish than were age estimates ob- tained from vertebrae. For these reasons, the scale is not viewed as a preferred aging structure. The use of scales for age determination had the advantage of being the only nonlethal method tested in this study. However, we found that many scales were regener- ated and, therefore, not suitable for age determina- tion. Although scales can provide data regarding re- peat spawning behavior (Cating, 1953), information that is used in the management of the American shad (ASMFC2), the spawning marks left by reabsorption of the scale margin during a freshwater spawning run (Cating, 1953) can hinder the use of scales for accurate age determination. If enough of the scale is reabsorbed, annuli laid down in previous years can be very difficult to interpret. The results of our study agree with the findings of McBride et al. (2005) that indicate that scales produce biased ages, where readers tend to over-age young (<5 o 2 4 6 8 10 12 "O a> 2 4 6 8 10 12 Otolith age (years) Figure 3 Ages from otoliths of American shad ( Alosa sapidissi- ma) collected in May and June during 2008-2010 from the Merrimack River in Lawrence, Massachusetts, com- pared with the average ages assigned through the use of vertebrae, scales, and opercula by (A) reader 1 and (B) reader 2. The diagonal line represents agreement with otoliths. Filled symbols represent ages that are significantly different (P<0.05) from ages from otoliths; empty symbols are not. Significance was tested with Wilcoxon rank sum tests for ages 4-10. Significance was not tested for ages 3 or 11 because of a sample size of 1 for each age. years) fish and under-age older fish. Furthermore, Up- ton et al. (2012) showed a 50% error in scale ages of American shad of known age. This trend of otoliths providing better precision and a larger range of ages than those provided by scales has been shown in sever- al other species as well (Barnes and Power, 1984; Welch et ah, 1993; Secor et al., 1995; Sipe and Chittenden, 2001; Zymonas and McMahon, 2009). Opercula resulted in the least reliable readings in this study of aging structures for American shad. Opercula were difficult to read, required more process- ing than scales or otoliths, and provided estimates of the lowest precision compared with results from the other structures examined. Contrary to the findings of Elzey et al: Comparison of 4 aging structures for Alosa sapidissimo 53 Yilmaz and Polat (2002) with pontic shad, we did not find annuli easy to distinguish in opercula of the Amer- ican shad, especially in older (>6 years) fish. Further- more, our ages determined from opercula were biased compared with ages derived from otoliths, leading to fish of age 5 and older being under-aged. The results of this study support the use of otoliths for age determination of American shad. Ages estimat- ed from otoliths were more precise (between and with- in readers) than ages derived from any of the other structures examined. Campana (2001) suggested a CV of 5% or less is ideal for a species of moderate longev- ity. In this study, only ages from otoliths achieved a CV of less than 5% between and within readers. Ages esti- mated from scales and vertebrae were higher in young (<5 years) fish than ages determined from otoliths. Furthermore, ages estimated from scales and opercula were lower than ages from otoliths in older (<7 years) fish. If possible, a reference collection of otoliths should be compiled for each region for which age estimates would be useful. Such a collection could provide a valu- able tool for training inexperienced readers of annuli, as well as would prevent a long-term drift for age esti- mates determined by experienced personnel (Campana, 2001). Acknowledgments We would like to thank the employees of the Massa- chusetts Division of Fisheries and Wildlife that helped sample American shad at the Essex dam in Lawrence. We also thank S. Turner for her help in processing samples. We also appreciate the thorough comments provided by M. Armstrong and G. 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Commissioner of Fisheries and founder of Fishery Bulletin Slipper lobsters (Scylfaricfae) off the southeastern coast of Brazil: relative growth, population structure, and reproductive biology Luis Felipe de Almeida Duarte (contact author)1 Evandro Severino- Rodrigues2 Marcelo A. A. Pinheiro3 Maria A. Gasalia4 Email address for contact author: duarte.mepi@gmail.com Abstract— The hooded slipper lobster (Scyllarides deceptor) and Brazilian slipper lobster (S. brasiliensis) are commonly caught by fishing fleets (with double-trawling and longline pots and traps) off the southeastern coast of Brazil. Their reproductive biology is poorly known and research on these 2 species would benefit ef- forts in resource management. This study characterized the population structure of these exploited species on the basis of sampling from May 2006 to April 2007 off the coast of Santos, Brazil. Data for the abso- lute fecundity, size at maturity in females, reproductive period, and morphometric relationships of the dominant species, the hooded slipper lobster, are presented. Significant differential growth was not observed between juveniles and adults of each sex, although there was a small in- vestment of energy in the width and length of the abdomen in females and in the carapace length for males in larger animals ( >25 cm in total length [TL] ). Ovigerous females were caught more frequently in shallow waters in August-September than in January-February, indicating a pos- sible migration to spawn. Fecundity ranged from 55,800 to 184,200 eggs (mean fecundity: 115,000 [standard deviation 43,938] eggs). The spawn- ing period occurred twice a year, with a higher relative frequency between July and October, and the length at 50% maturity for females was ~25 cm TL; both these findings should be considered by resource manag- ers. Proper management of catches of slipper lobsters is important be- cause of the high economic value of this fishery. Manuscript submitted 18 June 2013. Manuscript accepted 2 December 2014. Fish. Bull. 113:55-68 (2015). doi: 10.7755/FB.113.1.6 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. 1 Departamento de Zoologia Campus de Rio Claro Universidade Estadual Paulista Avenida 24 A, 1515 13506-900, Rio Claro Sao Paulo, Brazil 2 Instituto de Pesca Agencia Paulista de Tecnologia dos Agronegocios Secretaria de Agricultura e Abastecimento Governo do Estado Sao Paulo Avenida Bartolomeu de Gusmao, 192 11030-906, Santos Sao Paulo, Brazil Few species-specific fisheries world- wide exist for the slipper lobsters (Scyllaridae), in contrast to those for the spiny lobsters (Palinuridae) and clawed lobsters (Nephropidae), although some slipper lobsters have significant commercial value (Spani- er and Lavalli, 2007; Duarte et ah, 2010). According to Holthuis (1991), of the 85 species of lobsters record- ed (see Lavalli and Spanier, 2007), 35.3% are of commercial interest, and of these interest has increased in species of the genus Scyllarides, such as the Brazilian slipper lob- ster ( S . brasiliensis), Mediterranean slipper lobster (S. latus), and blunt slipper lobster (S. squamiyiosus). In addition, other species of Scyllaridae have commercial value, including 4 species of the genus Ibacus, the vel- vet fan lobster (7. altricrenatus), Jap- anese fan lobster (I. ciliatus), smooth fan lobster, (I. novemdentatus), and butterfly fan lobster (I. peronii), as 3 Laboratorio de Biologia de Crustaceos Grupo de Pesquisa em Biologia de Crustaceos Campus Experimental do Litoral Paulista Universidade Estadual Paulista Praca Infante D. Henrique s/n°1 1330-900, Sao Vicente Sao Paulo, Brazil 4 Laboratorio de Ecossistemas Pesqueiros Departamento de Oceanografico Biologica Instituto Oceanografico Universidade de Sao Paulo Praca do Oceanografico, 191 Cidade Universitaria 05508-900, Sao Paulo Sao Paulo, Brazil well as the sculptured mitten lobster ( Parribacus antarcticus ) and flathead lobster ( Thenus orientalis). The reproductive biology of mem- bers of the Scyllaridae (Lavalli and Spanier, 2007) has been studied for the genera Thenus (Kagwade and Kabli, 1996; Courtney et ah, 2001) and Ibacus (Stewart et al., 1997; Haddy et ah, 2005) with emphasis on the genus Scyllarides (Hardwick and Cline, 1990; Spanier and Lavalli, 1998; DeMartini and Williams, 2001; DeMartini et ah, 2005; Hearn and Toral-Granda, 2007; Oliveira et al., 2008). According to the above men- tioned authors, the sizes of females at maturity are smaller in species of the genera Ibacus (butterfly fan lobster) and Thenus (flathead lobster and T. indicus) than in species of the genus Scyllarides (blunt slipper lobster, Galapagos slipper lobster [S. astori], and hooded slipper lobster [S. deceptor]). Moreover, species of Iba- 56 Fishery Bulletin 1 13(1) cus and Thenus show lower fecundity than species of Scyllarides. A new, species-specific study for the hooded slip- per lobster is needed to gain a better understanding of biological patterns in this species. The variability in the reproductive biology of species of Scyllarides has been shown to be relatively high. For example, the hooded slipper lobster has 2 spawning seasons per year (Oliveira et ah, 2008) — a difference from the Galapagos slipper lobster (Hearn and Toral-Granda, 2007)— and a mean tail width at maturity of 62.6 mm (Oliveira et ah, 2008), compared with a mean tail width of 47.6 mm for the blunt slipper lobster (DeMartini et al., 2005). Studies of Scyllarides species are needed to estimate size at sexual maturity, fecundity, and reproductive pe- riod and to determine locations that are favorable for spawning in order to better understand the life cycle of these species and, therefore, to improve fisheries man- agement toward a more sustainable resource (Sparre and Venema, 1998; Chubb, 2000). Chace (1967) reported that a population of the red slipper lobster (S. herklotsii ) supported an intense fish- ing effort at Saint Helena (South Atlantic), and DeMar- tini and Williams (2001) noted that the blunt slipper lobster accounted for 64% of the lobster catch at Maro Reef (Northwestern Hawaiian Islands). Species of Scyl- laridae also are targeted by other fisheries (e.g., in the Mediterranean Sea, Australia, the Galapagos Islands, India, and Australia); however, the numbers of fisher- ies landings from lobster catches have declined rapidly worldwide, and fisheries failures have occurred or are likely to occur in the near future (Lavalli and Spanier, 2007; Spanier and Lavalli, 2007). Studies show that generally in several places in the world most fisheries that have targeted slipper lobsters lacked effective reg- ulations for the conservation of stocks and the econom- ic maintenance of local fisheries (Lavalli and Spanier, 2007). A similar situation exists in Brazil, where there are no regulations that govern the extraction of these resources and where there is little specific knowledge about the basic biology of these species. In Brazil, there are 3 genera of Scyllaridae: Scyl- larus , Parribacus, and Scyllarides. Two species of Scyl- larides occupy the south and southeast: 1) the Brazil- ian slipper lobster, distributed at depths of 20-130 m from Antilles to Brazil (Maranhao to Sao Paulo), and 2) the hooded slipper lobster, distributed at depths of 6-420 m from Argentina to Brazil (Rio de Janeiro to Rio Grande do Sul) (Holthuis, 1985, 1991; Melo, 1999; Oliveira et al., 2008; Duarte et al., 2010). Brazilian slipper lobsters are caught by 2 kinds of commercial fishing fleets in southeastern Brazil: 1) medium-size double trawlers that target mostly shrimp and 2) pot- and-trap fleets that target the common octopus ( Octo- pus vulgaris). The lobsters caught by these fleets are traded intact (whole). Species of Scyllarides are not the main target of the majority of the fisheries off south- eastern Brazil. In the same region, Duarte et al. (2010) have shown a significant reduction in the abundance of the hooded slipper lobster despite a relatively low fish- ing effort. This reduction can be explained by its slow rate of population growth, high total mortality (Duarte et al., 2011), and late maturity (Oliveira et al., 2008) compared with other species of the same family. Also, traders have noted a smaller size of individuals in the catch in recent years (Duarte et al., 2011). Brazil currently has no fishery management legis- lation that regulates the extraction of slipper lobsters in its waters, and data on the reproductive biology of these species of Scyllaridae would provide important life-cycle information that could be used for decision- making. Therefore, the aims of this study were to de- scribe the relative growth (biometrics) and reproduc- tive biology (maturity, reproductive period, fecundity, and spawning sites) of the hooded slipper lobster. We also sought to identify different population strata by sex, size, fishing area, and coloration of the carapace and to contribute the resulting data to inform future management recommendations that would promote sustainability and conservation of this species in com- mercial fisheries. Materials and methods Data collection on land Weekly monitoring (through visits to landing sites) and 2 or 3 sampling efforts during the year were conducted for this study from May 2006 to April 2007 at all the in- dustrial landing sites in the State of Sao Paulo, Brazil (at the sites of these 7 companies: 1) Cooperativa Mista de Pesca NIPO Brasileira, 2) Alianga, 3) Franzese, 4) Itafish, 5) Balan, 6) TPPS-Santos, and 7) Araripe1). About 70% of all the fishing landings that occurred in this study period were monitored, and, of the 100 fishing landings that were monitored, 72 landings were from medium-size double trawlers and 28 landings were from the pot-and-trap fleet (Institute de Pesca, Governo do Estado de Sao Paulo, ProPesq, http://www.pesca.sp.gov. br/estatistica.php). As part of this monitoring, the total catch of hooded slipper lobster and information about the fishing areas (depth, latitude, and substrate type) were recorded. The double trawler vessels have 2 identical semi- conical nets. The vertical opening of each net is created by a flotation device from a headrope 20.0 m in length, each mouth opening is 15.0 m wide by 1.5 m high, and trawl doors (weighing 60-80 kg) keep the net open. The majority of these vessels preserve their catch on board with ice (see illustrations in Duarte et al., 2010). Fishing vessels that target common octopus have refrigerators for storage of their catch (Castanhari and Tomas, 2012). Each of these vessels can include up to 1 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. Duarte et al: Relative growth, population structure, and reproductive biology of slipper lobsters (Scyllaridae) 57 Figure 1 Carapace color patterns established for specimens of the hooded slipper lobster ( Scyllarides decep- tor) observed at fishery landings in southeastern Brazil from May 2006 to April 2007: red (R), light (L), dark (D), intermediate (I), light red (LR), dark red (DR), and mixed (M). 10 longlines with 2500 pots and 150 interspersed traps per longline, providing a total of 25,000 pots and 1500 traps for an individual fishery. The traps are baited (with remains of fishes) to catch octopuses, fishes, and slipper lobsters, and the pots are not baited, (Duarte et ah, 2010; Castanhari and Tomas, 2012). Pots have a minimum internal diameter of 15 cm and are used as a shelter by common octopus. The number of pots cannot exceed 20,000 units per boat, and baited pots are not permitted with this type of fishing (SEAP, 2005) (see trap differences in Duarte et ah, 2010). Lobsters are not caught in these pots. Slipper lobster species were identified in this study by examination the morphological structure of the pos- terior margin of the 2nd abdominal pleura (Melo, 1999), which is a large concave spine in the hooded slipper lobster and straight or slightly convex in the Brazilian slipper lobster. Sex of lobsters was determined by the location of the gonopores on the base of the 3rd or 5th pair of pereiopods in males and females, respectively (Abele, 1982; Hardwick and Cline, 1990). Sampling efforts conducted at landing sites during the study period resulted in the collection of 1032 speci- mens, which were measured for biometric relationships and size structure with a tape measure attached to a wooden board for total length (TL), with a caliper for other linear measurements, and with a manual balance for the total weight (Abele, 1982). With a tape measure, TL was measured in centimeters from the distal tip of the antenna to the posterior end of the telson. The following measurements were obtained in millimeters with a caliper: carapace length (CL) between the distal extremity of the rostrum to the posterior margin of the carapace; carapace width (CW) between the sides of the carapace at its midpoint; abdomen width (AW) between the sides of the 1st and 2nd abdominal somites; abdo- men length (LA) between the posterior margin of the carapace and the posterior end of the telson; and an- tenna length (AL) from the base to the distal tip. The total weight (Wz) was measured in grams by weighing the intact, fresh animal. The carapace color of each specimen was recorded upon landing and was classified according to 7 pat- terns (Fig. 1), 3 of which were established by the pre- dominant color (>75%): red (R), light (L), and dark (D). The remaining 4 patterns were classified by their color tone. For 3 of the remaining patterns, -50% of a cara- pace had to have an intermediate (I), light red (LR), or dark red (DR) tone; for the fourth pattern, -33.3% of a carapace had to have a mixed (M) tone. All the ovigerous females (100%, ft =22) were re- corded and collected during the sampling efforts from May 2006 to April 2007. During the study period, this subsample of 22 female specimens, with lengths that ranged from 22.5 to 32.0 cm TL, were collected from different boats, and their stage of embryonic develop- ment was categorized according to the classification of DeMartini and Williams (2001). The animals were placed in individual plastic bags and kept in crushed ice before laboratory analysis. Laboratory processing Females also were collected at the time of landing and were later dissected for macroscopic examination of their gonads, which were categorized according to the classification proposed by Stewart et al. (1997) and Haddy et al. (2005). This classification was established for lobster species from the genus Ibacus and is also valid for the species in our study because of identi- cal macroscopic characteristics. Five maturation stages were established: the first 2 stages for juvenile indi- viduals and stages 3-5 for mature individuals. At stage 1, the ovary is small, narrow, translucent to white, and has no visible oocytes. A female at stage 2 has a small and cream to yellow ovary with no visible oocytes. At 58 Fishery Bulletin 1 13(1) stage 3, the ovary is developed, has a small volume and is orange, and has visible oocytes at the ovary wall. At stage 4, the ovary is largely inflated, fills the whole carapace cavity, and is bright orange, with oocytes clearly visible along the ovary wall. Finally, at stage 5, the ovary is developed but has a flaccid appearance and is cream to yellow; there may still be some oocytes on the ovary wall — a specific peculiarity of this stage. Individual fecundity was quantified volumetrically (Vazzoler, 1996) by using females with eggs in the early stages of embryonic development (orange in color). This method avoided underestimation caused with females at later stages, when there was the possibility of loss of eggs with catching and handling, or early larval hatch- ing (DeMartini and Williams, 2001). The laboratory protocols were the same as those of Vazzoler (1996); eggs were removed from pleopods by dissociation in 10% NaCIO, and were then vigorous stirred. The oo- cytes from each egg mass were transferred to a 1-L beaker and homogenized with a glass rod, and seven 5-mL subsamples were removed with a pipette. The oo- cytes were placed in gridded petri dishes for counting under a stereomicroscope (20x). We estimated individ- ual fecundity (F) according to the method proposed by DeMartini and Williams (2001), counting the number of eggs in subsamples, discarding the extreme values (minimum and maximum), and calculating the mean individual fecundity of the 5 remaining subsamples (fs) with the following equation: F = (tv x fs) / dv, (1) where tv = total volume of the egg mass with a dilution of 1 L; and dv = the dilution volume of the egg subsample or 5 mL). The relationship of TL to the number of eggs (NE) was calculated with the following equation: NE = (b x TL) — a, (2) where a = the intercept; and b = the slope of linear regression. Data analysis The statistical analyses for this study were performed with R software, vers. 2.13.0 (R Development Core Team, 2011) (Ihaka and Gentleman, 1996), and the fisheries were mapped with the Surfer contouring and 3-D mapping package, vers. 8 (Golden Software, Golden, CO). We adopted the TL as the size indicator for the hooded slipper lobster, as was done in previ- ous studies of lobsters of the genus Scyllarides (Hearn, 2006; Pessani and Mura, 2007). The relative growth of each sex was assessed by a regression analysis of the empirical points for mor- phometric relationships given by the power function y=axb, and then a i-test was used to check for possible differences in allometry (Huxley, 1950). The following morphometric relationships were evaluated: ALxTL, CLxTL, LAxTL, AWxTL, CWxTL and WxTL (Abele, 1982). These relationships indicated the possible differ- ences between the linear regressions obtained for each sex by comparisons with an analysis of covariance of constants a and b in the linear regressions of the bio- metric relationships (Zar, 1999; Faraway, 2002). To represent the allometric relationships from the power function in a linear form, the dependent ty-axis) and independent (x-axis) variables were transformed by natural logarithms (In). This transformation, lny = lna + (bx lruc), (3) facilitates the use of a least squares fitting technique with linear regression: y = a + (b x x). (4) This mathematical procedure transforms the curvilin- ear relationship into a linear equation or equations and enables graphic comparisons of linear growth phases for the evaluation of biometric distinctions between developmental stages (juvenile and adult). Therefore, the linearized data (lny=lna + [6xlrLr]) for each relation- ship were assessed with the segmented library (Mug- geo, 2008) in R (vers. 2.13.0) to identify significantly different growth rates during ontogeny, according to procedures used by Pardal-Souza and Pinheiro (2012). This method of regression analysis seeks to partition the independent variable into intervals at break points, separating line segments that are fitted to each inter- val. The mean length at which 50% of females reached maturity (L50) was estimated, under sigmoid adjust- ment, from the proportion of individuals with mature gonads (females in stages 3-5) in size classes of 1 cm TL (Hovgard and Lassen, 2000): P = 1 / (1 + e-r(i - L5o>), (5) where P = the probability that a female is mature; r = the slope; L50 = the mean TL where the probability of mature females is 50%; and L = the mean TL. Data on the carapace color were analyzed in relation to size class, sex, the area of capture, and fishing gear. Five major fishing areas were established by mapping the fishing grounds of 2 types of vessels with different storage types (double trawlers that store their catch on ice and vessels that use pots and traps and store catch in refrigerators) on the basis of their similar lati- tudes and depths of fishing grounds for lobster species. Size composition and sex also were evaluated by fish- ing area, season, and month of capture. Size distribu- tion was compared between sexes by using a t-test (Zar, 1999). An analysis of variance was used, separately for each variable, to evaluate the occurrence of different color patterns by sex (exclusivity or predominant pat- terns), fleet (differences in storage type), capture pe- riod (month and season), and fishing area, as well as to Duarte et al: Relative growth, population structure, and reproductive biology of slipper lobsters (Scyllaridae) 59 Table 1 Morphometric relationships for the hooded slipper lobster ( Scyllarides deceptor) sampled from May 2006 through April 2007 from pot-and-trap and double-trawler fleets that operate off southeastern Brazil. Data include results from mathematical equations (power function and log transformation), adjustments (coefficient of determination [r2]), and analysis of covariance between the regressions of each biometric relation and allometric representation with 5% significance (f-test). AL=antenna length; LA=abdomen length; CL=carapace length; TL=total length; abdomen width=AW; CW=carapace width; W=weight; 0=isometric growth (6=1); +=positive allometric growth (6>1); -=negative allometric growth (6<1); M=males; and F=females. The relationship of the weight of animals was compared with the value 3 for 6 from the morphometric analysis. Significance codes: ns=P>0.05; *=P<0.05; **=P<0.01; and **:|:=P<0.001. Morphometric relation Sex n Power function Y = axb Power function (linear form) lny = Ino + (6 x lmc) r 2 Intercept (a) Slope allometry (6) (P< 0.05) ALxTL M 189 AL= 0.243 TL0-973 lnAL=- 1.48+0.973 InTL 0.85 0.021 0.111 0 F 184 AL=0.281 TL0944 lnAL=-l. 27+0.944 InTL 0.92 * ns - CLxTL M 191 CL=0.515 TL0 919 lnCL=-0.664+0.919 In TL 0.92 0. 006 0.626 - F 182 CL=0.470 TL0-934 lnCL=-0.755+0.934 InTL 0.97 ns - LAxTL M 190 AL=0.339 TL1 054 lnAL=-1.081+1.054 InTL 0.89 0.0002 0.352 0 F 184 AL=0.321 TL1 068 lnAL=-l. 14+1.067 In TL 0.97 *** ns + AWxTL M 163 AW=0.312 TL0-951 lnAW=-1.16+0.951 InTL 0.93 <2.10-16 0.066 0 F 171 AW=0.269 TL0-986 lnAW=-1.31+0.986 InTL 0.93 *** ns 0 CWxTL M 272 CW= 0.653 TL0-869 lnCW= -0.427+0.869 InTL 0.9 0.225 0.376 - F 266 CW= 0.657 TL0-86 8 lnCW=-0.419+0.868 InTL 0.95 ns ns - Total 538 CW=0.655 TL0 860 lnCW=-0.401+0.864 InTL 0.94 - - - WxTL M 392 W=0.0644 TL2 13 lnW=-9.037+2.73 InTL 0.93 0.289 <2.10-16 - F 437 W=0.0771 TL2-67 lnW=-8.707+2.67 In TL 0.93 ns *** - evaluate the size of the specimens by sex. Interactions between variables were not evaluated. In al! cases, the means were compared by a posteriori multiple compar- ison with Tukey’s honestly significant difference test (Zar, 1999; Faraway, 2002). The chi-square (%2) test was used to evaluate whether the sex ratio was different from 1:1 in samples with a sample size in) >10 indi- viduals (Zar, 1999), depending on the month, season, size class (TL, measured in centimeters), fishing gear, and fishing area. Results Distributions of fishing cruises and specimens caught Of the 72 landings by 25 double trawlers that operated at depths of 40-220 m between the latitudes 23°20'S and 26°13'S during the study period from May 2006 to April 2007, 51.4% contained specimens of the hood- ed slipper lobster. Lobster occurred in 100% of the 28 landings of the pot-and-trap fleet, which operated at depths of 43-180 m and at latitudes between 23°30'S and 27°00'S. During the study period, 1029 specimens were counted, with most obtained by the pot-and-trap fleet (65.2%) rather than by double trawlers (34.8%). The hooded slipper lobster was abundant during all months of the study period. A small number of specimens of the Brazilian slipper lobster were captured in April 2007 from a single double trawler landing from a depth between 45 and 130 m farther north in the study area (from 23°30'S, 43°00'W to 24°19'S, 45°09'W). Relative growth All the morphometric relations showed a coefficient of determination (r2) with values between 0.85 and 0.97 (Table 1). The relation ALxTL (females), as well as the relations of CLxTL, CWxTL, and WxTL (both sexes), showed a negative allometry of the dependent variables in relation to body size (TL) of hooded slipper lobster. The allometric growth was positive only for the rela- tion LAxTL (females) (6>1), indicating a higher growth rate of the dependent variable in relation to the body size of this sex. For other cases, the growth was isomet- ric (6=1), indicating no change in growth rate between the variables during ontogeny. However, no inflection (or break point) was observed during the segmentation analysis of the regression lines, indicating no signifi- cant morphometric differences between juveniles and adults for both sexes of the hooded slipper lobster. In the analysis of covariance (Table 1), the linear growth phases of juveniles and adults were observed to be similar between the sexes in the CWxTL linear equations and could be grouped for the total number of individuals of both sexes combined. This phenomenon was not observed for the other relationships (ALxTL, 60 Fishery Bulletin 1 13(1) CLxTL, LAxTL, and AWxTL), where statistically sig- nificant differences were detected between the indexes of origin a (intercept) but not between the values of b (slope), indicating mild sexual dimorphism. This analy- sis indicates that males had higher values of AL and CL than females for the same reference size (TL). The same was true for females, compared with males, with regard to LA and AW. However, the relationship WxTL differed significantly between the sexes for the value b in the linear regression, giving greater weight to larger males. Reproduction For this study, 49 female hooded slipper lobster (13.0-36.0 cm TL) were dissected, and their stag- es of gonad development were categorized. Of these females, 29 were classified as adults and 20 were classified as juveniles, resulting in an L50 of 25.3 cm TL (Fig. 2). Only 22 ovigerous females were recorded in landings between May 2006 and April 2007 (pots and traps, 72 = 13; double trawlers, n= 9), corre- sponding to 11.2% of the 170 adult females caught and with sizes ranging from 22.5 to 32.0 cm TL. The spawning period occurred twice a year (Fig. 3), and a higher relative frequency occurred be- tween July and October (60.5%) and a lower rela- tive frequency, in January and February (7.2%). Mean individual fecundities for 8 females (22.1-32.6 cm TL) ranged from 55,800 to 184,200 eggs. The linear relationship of number of eggs (NE) to TL (NExTL) was NE = (11,268x770-183,361 (77=8, r2=0.82). (6) Size structure and sex ratio The population structure of the hooded slipper lobster was very different among months as a function of TL, carapace color, fishing area, and season, both for males (Tukey’s test: 3.690.101), where sizes ranged from 14.0 to 36.0 cm TL in the double-trawler fleet and from 11.0 to 36.0 cm TL in the pot-and-trap fleet. On the basis of analysis of their individual sizes, a high percentage of females were determined to be immature (double trawlers: 65.8%; pots and traps: 68.1%), and the monthly per- centage of capture of immature females ranged from Table 2 Depths of the 5 fishing areas of the double-trawler and pots-and-trap fleets that operate off southeastern Brazil and catch hooded slipper lobster ( Scyllarides deceptor). Standard devia- tions (SD) of the means are provided in parentheses. Depth (m) Double trawlers Pots and traps Fishing area Min. Max. Mean (SD) Min. Max. Mean (SD) Area 1 40 100 59.9 (16.8) 70 99 89.4 (10.2) Area 2 40 80 58.3 (13.3) 43 100 79.2 (16.8) Area 3 41 150 100.1 (38.2) 43 68 58.8 (12.3) Area 4 100 165 134.5 (23.9) 100 180 120.0 (31.0) Area 5 135 220 171.6 (44.0) - - - Total 40 220 91.1 (42.3) 43 180 81.4 (18.2) Duarte et al: Relative growth, population structure, and reproductive biology of slipper lobsters (Scyllaridae) 61 40.5% (in December) to 83.3% (in November), indepen- dent of the fishing gear used, and higher levels were recorded in trawls (84.2%) during the spring and in pots and traps (72.6%) during the winter. Size (TL) composition showed significant monthly variation, regardless of sex (P<0.001), with greater dif- ferences between the monthly means for males (from 23.6 cm TL [standard deviation (SD) 3.4] in August to 19.6 cm TL [SD 2.8] in October) than for females (from 24.5 cm TL [SD 4.1 in May to 21.7 cm TL [SD 4.9] in November). No significant seasonal differences were observed in the size composition for each sex (P=0.14) or in the sex ratio of hooded slipper lobster (P>0.05). In general, the sex ratio of hooded slipper lobster (Table 3) did not differ significantly from a proportion of 1:1 (P>0.05), regardless of the fishing gear used (P=0.85). However, males predominated in smaller length classes (11.0-24.0 cm TL) and females in larger sizes ( >24 cm TL). The t-test confirmed that females tended to be larger than males (males: 21.9 cm TL [SD 3.0]; females: 23.9 cm TL [SD 3.7]; PcO.OOl). The spatial distribution of the fishing areas for both fleets (areas 1-5; Fig. 4; Table 2) showed that the dou- ble-trawler fleet that caught Brazilian slipper lobster operated farther south (between the latitudes 25°00'S and 26°24'S) than the pot-and-trap fleet, at depths of 40-165 m, and particularly in areas 1 and 4. On the other hand, the pot-and-trap fleet concentrated fishing efforts in shallower waters (at depths of 43-100 m), be- tween the latitudes 24°00'S and 25°00'S, and operated preferentially in area 2. The males from area 5 were significantly smaller than those caught in areas 2 and 4 (P<0.01) (Fig. 5). Females from area 5 also were smaller than females caught in areas 3 and 4 (P<0.05). The proportion of immature females among the adults caught in the trawl fleet ranged from 55% (area 4) to 90% (area 3), whereas, in the pot-and-trap fleet, the percentages of immature females were between 56.5% (area 2) and 75.9% (area 3). In all fishing areas, males caught by double trawlers had a lower median size (20.7 cm TL) than males captured in pots or traps, and small- er individuals were observed in area 3. Females were more abundant in area 1 (%2: P=0.036), and males were more abundant in area 2 (%2: P=0.01). Carapace color was used to classify 871 speci- mens of the hooded slipper lobster. The 7 cate- gories evaluated were ranked in descending or- der (the absolute frequency for each category is shown in parentheses): D(259) > DR(247) > L( 108) > R(103) > LR(91) > 1(37) > M(26). The posteriori multiple comparison conducted with Tukey’s test revealed significant differences between some of the color patterns for males (patterns: R?tL, I, and M; P<0.05) and females (patterns: R^L, I, LR, and M; PcO.OOl). The R pattern showed the smallest variation (by size [TL]) and was characteristic of smaller individuals (mean: 21.5 cm TL [SD 2.7]), regardless of sex (Fig. 6). In addition, all females with this carapace color (n= 8, 27.6% of immature females) were identified by dissection as juveniles, and the other color patterns were found on both juveniles and adults. Therefore, an association between R pattern and a rel- atively narrow range of TLs was verified for both sexes. This relationship was not affected by the sex of the lobster, fleet composition (despite differences in storage of catch), month of capture, or fishing area. Discussion For the hooded slipper lobster, the r2 values for mor- phometric relationships showed an excellent linear cor- relation. Females tended to show an increase in LA, therefore, enhancing their capacity for oviposition and for hatching a greater number of eggs in the bristles of their pleopods (individual fecundity) (Stewart et ah, 1997; Demartini and Williams, 2001; Oliveira et al., 2008). Although the average female is larger than the average male, it is possible that an increase in body size (TL) in males facilitates the selection, grasping, and manipulation of females at the time of copulation, as has been observed in lobsters of the genus Panulirus (Lavalli and Spanier, 2007). Therefore, in general, sig- nificant differential growth was not observed between the juveniles and adults of each sex, nor was there ob- vious sexual dimorphism, although there was a small investment of energy in the width and length of the ab- domen in females and in the carapace length for males in larger animals ( >25 cm TL). Various biometric equations presented high values of r2 and thereby reinforced their suitability for use in 62 Fishery Bulletin 1 13(1) Table 3 Sex ratios (maleifemale) of the hooded slipper lobster (Scyllarides decep- tor ) by size classes (total length [TL]) caught by double-trawler and pot- and-trap fleets off southeastern Brazil from May 2006 through April 2007. Significance codes based on chi-square test (x2): ns=P>0.05; * P<0.05; ** PcO.Ol; and *** P<0.001. Size classes (cm TL) Number of specimens Sex ratio (M:F) p (y2) M F Total 11-12 1 0 1 _ 12-13 0 0 0 - - 13-14 2 0 2 - - 14-15 5 0 5 - - 15-16 12 7 19 01:00.6 0.25 ns 16-17 14 14 28 01:01.0 1.00 ns 17-18 20 19 39 01:01.0 0.87 ns 18-19 37 14 51 01:00.4 0.0013** 19-20 53 26 79 01:00.5 0.0024** 20-21 71 33 104 01:00.5 0.0002*** 21-22 62 58 120 01:00.9 0.53 ns 22-23 80 46 126 01:00.6 0.0025** 23-24 59 52 111 01:00.9 0.51 ns 24-25 41 71 112 01:01.7 0.0046* 25-26 18 53 71 01:02.9 0.0327* 26-27 12 42 54 01:03.5 0.0446* 27-28 11 25 36 01:02.3 0.0196* 28-29 7 16 23 01:02.3 0.0406* 29-30 5 11 16 01:02.2 0.13 ns 30-31 3 10 13 01:03.3 0.0522 ns 31-32 2 7 9 - - 32-33 1 3 4 - - 33-34 0 3 3 - - 34-35 0 1 1 - - 35-36 0 2 2 - future interconversion between size variables, particu- larly measures of the abdomen (LA and AW) and indi- vidual body size (TL or CL). Currently, in Brazil, some boats have begun landing only the abdomen of lobsters (“headless” lobsters) — a trend that will hamper the use of CL for monitoring this resource in the future. Total length is measured routinely and is easier for fisher- men to understand compared with the other measure- ments of size used in this study (Sparre and Venema, 1998; Chubb, 2000). Values of L50 were smaller in species of the gen- era Ibacus (e.g., butterfly fan lobster) and Thenus (e.g., flathead lobster and T. indicus), with a species mean of 19.1 cm TL (SD 6.1) (Stewart et al., 1997; Courtney et ah, 2001), compared with L50 values for species of the genus Scyllarides (e.g., blunt slipper lobster, Gala- pagos slipper lobster, and hooded slipper lobster), with a species mean of 25.0 cm TL (SD 5.6) (Demartini et al., 2005; Hearn and Toral-Granda, 2007; Oliveira et ah, 2008). Oliveira et al. (2008) estimated that the L50 for female hooded slipper lobster was 25.1 cm TL — a finding that is very similar to a result of our study (L5o=25.3 cm TL). Oliveira et al. (2008) noted that copulation in the hooded slipper lobster occurs immediately after female molting — an aspect of the reproductive biology of this species that could not be assessed in this study be- cause of the absence of molting or recently molted spec- imens. The absence of molting specimens in landings is most likely related to their reduced movement and the absence of feeding behavior at this stage (Lavalli and Spanier, 2007). These behaviors would preclude a molting lobster from entering a trap; therefore, fishery samples would not provide accurate copulation data. This bias was not present in a study by Oliveira et al. (2008), who used data from monthly lobster popu- lation surveys conducted during diving expeditions at Santa Catarina Island (in southern Brazil), in June at the beginning of the molting and copulation season. Spanier et al. (1988) observed that the Mediterranean slipper lobster begins these biological processes during the same month in the southeastern Mediterranean, Duarte et al: Relative growth, population structure, and reproductive biology of slipper lobsters (Scyllaridae) 63 Spatial distribution of sampled effort of the double-trawler and pot-and-trap fleets that caught hooded slipper lobster (Scyllarides deceptor) off southeastern Brazil, within the es- tablished 5 fishing areas (outlined with dashed lines) from May 2006 through April 2007. and Lavalli and Spanier (2007) mentioned the rapid calcification of the exoskeleton in species of this family, with the ovigerous condition occurring shortly thereaf- ter. These observations agree with the finding from our study that the relative proportion of ovigerous females of the hooded slipper lobster is greater during August- September than in other periods and with the results of Oliveira et al. (2008). Another period in our study with a large proportion of ovigerous females occurred during January-Febru- ary, indicating that there are 2 spawning seasons for the hooded slipper lobster. Lavalli and Spanier (2007) previously reported this spawning period for other Scyl- larides species. Larvae released in September would experience a period of high primary production in the environment during October-March, when nutrients from the South Atlantic Central Water are present in shallower water (Rossi-Wongtschowski and Madureira, 2006). This reproductive strategy increases the prob- ability of larval survival because complete larval de- velopment for Scyllarides spp. requires approximately 8 months (Booth et al., 2005). The range of fecundity values and mean fecundity of hooded slipper lobster in this study were similar to those values reported for other species of the same ge- nus (see review by Oliveira et al., 2008). According to these authors, hooded slipper lobster (n= 29) had fecun- dities between 58,871 and 517,675 eggs (mean=191,262 eggs (SD 17,811). Research by Vazzoler (1996) suggested that the early maturity of a species lowers fecundity and increases oo- cyte size to preserve energy per egg and improve larval survival and reproductive success. This reproductive strategy is evident in Scyllaridae, as seen in the rela- tionship between the mean sizes of lobster species and their gonadal maturation, fecundity, and egg diameter. According to Oliveira et al. (2008), the species of Iba- cus and Thenus showed lower fecundity (13,000-21,000 eggs) and larger egg diameters (1. 1-1.2 mm) than the fecundity (90,000-224,000 eggs) and egg diameters (0.60-0.67 mm) of species of Scyllarides. This observa- tion reflects the reproductive strategy in Scyllaridae, which appears to differ depending on the bathymetric distribution of a given species. Species that are coastal, for example, tend to have lower fecundity and larger egg sizes (e.g., the flathead lobster and butterfly fan lobster, according to Courtney et al. [2001] and Stewart et al. [1997]) than species that inhabit deeper waters (e.g., the blunt slipper lobster, according DeMartini et al. [2005], and the hooded slipper lobster, as observed in this study). Results from our study indicate that females of the hooded slipper lobster reach a larger size (maximum TL) than males (female: 36.0 cm TL; male: 32.6 cm TL), 64 Fishery Bulletin 1 13(1) > 'i n ( b \ 0.00 ■J y Q V 'W . - V 10 15 20 25 30 35 10 Total length (cm) Total length (cm) Figure 5 Density curves for different fishing areas for (A) males and (B) females and medians, quartiles (Ql=lower quartile, cuts off lowest 25% of data and Q3=upper quartile, cuts off highest 75% of data), and ranges for (C) males and (D) females of the total lengths of the hooded slipper lobster (Scyllarides deceptor) caught by pot-and-trap and double-trawler fleets off southeastern Brazil from May 2006 through April 2007. The different shadings for graphics located on the right side: from the darker to lighter (top to bottom) indicate areas in numerical order (1, 2 (dashed lines in white], 3, 4, and 5, respectively). Arrows mark the capture of juvenile and adult females. in agreement with the results of Oliveira et al. (2008), who observed females that were 36.0 cm TL and males that were 31.0 cm TL. This characteristic is common in the Scyllaridae, but the opposite phenomenon occurs in the Palinuridae and Nephropidae (Spanier and Lavalli, 2007). In our study, the maximum sizes obtained were larger than the 32 cm TL reported by Holthuis (1991) and Spanier and Lavalli (2007). However, the hooded slipper lobster measured in our study were captured farther southeast in Brazil than were the hooded slip- per lobster observed by Holthuis (1991) and Spanier and Lavalli (2007), and the lobster in our study were caught at maximum sizes that were similar to those of lobster found south of Brazil by Oliveira et al. (2008). Those authors also identified 2 migration patterns for the hooded slipper lobster. One of them occurs daily and relates to foraging, and the other is seasonal for the hatching of larvae in shallower water. This latter migration pattern was confirmed in our study because only 4.5% of females were recorded at depths >100 m (area 4), and the remaining females were captured in shallow areas (mean depth <100 m): 27.3%, 63.6%, and 4.5% in areas 1, 2, and 3, respectively. According to information from fishermen in both fleets, each fish- ing area has the following typical substrate proper- ties (granulometric predominance): area l=sand, mud, and gravel (calcareous algae); area 2=mud and sand; area 3=sand and gravel; area 4=mud and sand; and Duarte et al: Relative growth, population structure, and reproductive biology of slipper lobsters (Scyllaridae) 65 10 15 20 25 30 35 10 15 20 25 30 35 Total length (cm) Total length (cm) Figure 6 Density curves for the various carapace color patterns, red (R), light (L), dark (D), intermediate (I), light red (LR), dark red (DR), and mixed (M) for (A) males and (B> females and medians, quartiles (Ql=lower quartile, cuts off lowest 25% of data and Q3=upper quartile, cuts off highest 75% of data), and ranges for (C) males and (D) females of the total lengths of the hooded slipper lobster ( Scylla - rides deceptor) caught by pot-and-trap or double-trawler fleets off southeastern Brazil from May 2006 through April 2007. The different shadings for graphics located on the right side: from the darker to lighter (top to bottom) indicate various carapace color patterns (R, L, D (diagonal white lines], I, LR, DR, and M, respectively). The arrows mark the capture of juveniles and adult females. area 5=mud and sand. However, Figueiredo and Tes- sler (2004) report that the substrate varies greatly in microscale and therefore hampers association analyses. In decapod crustaceans, carapace color patterns are a result of hormonal control of chromatotropines (Rao, 1985), combined with external factors, such as food sources, substrate color, and seasonal and environmen- tal variations (Rao, 1985; Bedini, 2002). These patterns may also be associated with intrinsic biological fac- tors, such as growth, reproduction, mating, and sexual maturation during ontogeny (Ryan, 1967; Pinheiro and Taddei, 2000). Analysis of the carapace color patterns of the hooded slipper lobster in this study did not help to identify the reproductive period, timing of molting, or fishing areas for this lobster. Chromatic changes during the ontogeny of crusta- ceans have been reported by Abele ( 1982) and Dalabona et al. (2005), particularly changes associated with mat- uration, as observed for other decapods of the genera Callinectes (Baldwin and Johnsen, 2012) and Arenaeus (Pinheiro and Taddei, 2000). In this study, there was a relationship between the size (TL) of females with red carapaces (range: 16.5-29.0 cm TL; mean; 22.7 cm TL [SD 2.9]) and L50 (25.3 cm TL), a size that was very 66 Fishery Bulletin 1 13(1) similar to the smallest ovigerous female registered in this study (22.5 cm TL). Therefore, it may be that the red chromatic pattern is related to maturation changes for this species, and this relationship should be evalu- ated in future experiments. The other coloration pat- terns were observed in lobster with a great range in size (TL) and were common to both sexes, possibly be- cause color changes are more related to the time since molting, microscale substrate type, and trophic ecology of this species. There is a lack of specific studies con- cerning these influences, however. For species of Scyllaridae, males are smaller than females (Lavalli and Spanier, 2007; Oliveira et ah, 2008) and become mature at smaller sizes (e.g., Ibacus spp., according to Stewart et al., 1997). It is possible that red coloration may be used as an indicator of the chromatic changes in maturing males because the size distribution for this coloration was restricted to the range of 16.0 to 25.5 cm TL, with a mean of 20.4 cm TL (SD 2.7). On the basis of these results, it is likely that the L50 for males was approximately 23 cm TL, al- though more detailed analyses are required to confirm this hypothesis. The reduction in stock sizes of hooded slipper lob- ster in our study area (see Duarte et ah, 2010) presum- ably was enhanced by the capture of immature females (66.9%) with the 2 fishing methods: 1) trawlers and 2) pots and traps. On the basis of that observation, our research results indicate that the following potential measures could be investigated for the hooded slipper lobster fisheries in southeastern Brazikl) the use of a minimum landing size of 25 cm TL for this species, re- gardless of sex, and the release of individuals smaller than this size; 2) the release of ovigerous females im- mediately after capture to prevent an effect on recruit- ment; and 3) a closed season for fisheries from August to September, when there is the greatest reproduc- tive activity (proportion of ovigerous females) for this species. However, because discard mortality can be high in spiny lobsters (Gooding, 1985; O’Malley, 2008), whether discarding of hooded slipper lobster would be effective for stock protection is uncertain. Nevertheless, Cas- tro et al. (2003) demonstrated the efficacy of releas- ing caught fish of the genus Nephrops as a manage- ment measure. Haddy et al. (2005) and Spanier and Lavalli (2006) suggested that slipper lobsters are more resistant to discard mortality, because of their thicker carapace (Melo, 1999), and usually return alive to the water. In addition, management actions, such as size limits, release of ovigerous females, and closed seasons were effective management controls for the Panulirus cygnus fishery (Hall and Chubb, 2001), indicating that such measures could be pertinent for slipper lobster fisheries. In this study, we examined the life history aspects of the hooded slipper lobster landed as bycatch in 2 fisheries in Brazil. The biometry, reproductive status, and size structure were documented. Our main find- ings were that maturity was related to the sizes of ab- domen (females) and carapace (males); the ovigerous specimens occurred mainly in shallow waters, where fisheries were more intense; and higher numbers of ju- veniles than of adults were reported by fishing fleets with landings in the study area. In addition, it is pos- sible that the red color of the carapace was related to maturation changes for this species. These results agree with evidence of fishing pressure on the slipper lobster population that was documented in other stud- ies (Lavalli and Spanier, 2007; Spanier and Lavalli, 2007; Duarte et al., 2010). Nevertheless, further studies are clearly still neces- sary, especially those that examine the life cycle and other parameters of the current populations of slip- per lobsters in Brazil to understand mortality, growth, recruitment, stock identities, and stock levels of the hooded slipper lobster in waters of southeastern Brazil. Acknowledgments We thank all of the captains, fishermen, and dock workers at the various landings who contributed to this study. We also recognize the Instituto de Pesca (Santos, Sao Paulo), its Graduate Program in Fisheries and Aquaculture, and several colleagues for their input and help. We acknowledge the advice and help received from several colleagues, especially G. Pinheiro, who gave special attention to the figures in our manuscript. M. Pinheiro and M. Gasalla are grateful to Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) for the research fellowships provided. We also thank the reviewers who contributed much to improve this study. 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Prentice Hall, Upper Saddle River, NJ. 69 NOAA National Marine Fisheries Service Abstract— In this study, the growth pattern of juvenile European hake ( Merluccius merluccius ) was ana- lyzed in relation to oceanographic and ecological factors in the Ligu- rian Sea and northern Tyrrhenian Sea, both part of the Mediterranean Sea. The ages of juvenile European hake, collected during a trawl sur- vey in June 2011, were estimated by reading otolith daily growth rings. The growth pattern (length-age relationship) of juvenile European hake recruited to the population (<1 year old) was analyzed by fitting a multivariate generalized additive model with explanatory variables: depth, bottom temperature, sea-sur- face temperature, scalar wind speed, chlorophyll-a concentration, and fish density (number of individuals per square kilometer). A significant ef- fect of density on the length-age relationship was found, and an in- creased growth rate at densities >3000 individuals km-2. This ob- served positive effect of density on growth could be argued to be a con- sequence of favorable environmental conditions, such as food availability and temperature, where both fish density and growth are maximized. Conversely, areas of lower density correspond to habitats of low suit- ability, where growth is impaired. Manuscript submitted 10 August 2013. Manuscript accepted 3 December 2014. Fish. Bull. 113:69-81 (2015). doi: 10.7755/FB.113.1.7 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 Hr established 1881 Spencer F. Baird First U.S. Commissioner of Fisheries and founder of Fishery Bulletin Modeling the growth of recruits of European hake C Merluccius merluccius ) in the northwestern Mediterranean Sea with generalized additive models Alessandro Ligas (contact author)1 Francesco Colloca2 Mathieu G. Lundy1 Alessandro Mannini3 Paolo Sartor4 Mario Sbrana4 Alessandro Voliani5 Paola Belcari6 Email address for contact author: alessandro.ligas@afbim.gov.uk 1 Fisheries and Aquatic Ecosystems Branch Agri-Food and Biosciences Institute 18a Newforge Lane BT9 5PX, Belfast, United Kingdom 2 Istituto per I'Ambiente Marino Costiero Consiglio Nazionale delle Ricerche Via Vaccara 61 91026 Mazara del Vallo (Trapani), Italy 3 Dipartimento di Scienze della Terra dell'Ambiente e della Vita Universita delgi Studi di Genova Corso Europa 26 16132 Genova, Italy 4 Centro Interuniversitario di Biologia Marina ed Ecologia Applicata "G. Bacci' Viale Nazario Sauro 4 57128 Livorno, Italy 5 Risorse Ittiche e Biodiversita Marina Agenzia Regionale per la Protezione Ambiente della Toscana Via Marradi 1 14 57126 Livorno, Italy 6 Dipartimento di Biologia Univerisita di Pisa Via Derna 1 56126 Pisa, Italy The European hake ( Merluccius mer- luccius) is a demersal fish widely distributed in the Mediterranean Sea and in the northeastern Atlantic (Murua, 2010). In the Mediterranean Sea, it is a major component of the demersal fish assemblages on both the continental shelf and the upper slope (Orsi Relini et ah, 2002; Col- loca et ah, 2004). Juvenile European hake aggregate in nursery areas lo- cated on the continental shelf break (Maynou et ah, 2003; Abella et ah, 2005; Bartolino et ah, 2008a; Hidalgo et ah, 2008), and adult fish can be found in a wider depth range from the shelf to the upper slope (Alde- bert et ah, 1993; Sbrana et ah, 2007; Cartes et ah, 2009; Bartolino et ah, 2011). Because of its abundance and wide spatial distribution, the Euro- pean hake is one of the most highly exploited species in the Mediterra- nean Sea, targeted by multigear fish- eries. The bulk of the catch of this species is obtained from trawl fisher- ies, which mainly exploit the young- est portion of the population (<30 cm in total length [TL] ). However, there are still relatively high discard rates of undersize fish (Cardinale et ah, 2011) despite an amendment in 2010 in the European Union Council Regulation to increase trawl codend mesh size (European Union Council Regulation 1967/2006). The adult fraction ( >40 cm TL) is exploited by gillnet and longline fisheries (Sbrana 70 Fishery Bulletin 113(1) et al., 2007; Bartolino et al., 2011). This pattern results in high exploitation rates across the entire population, from small individuals (< 15 cm TL) to large females (>60 cm TL) in spawning aggregations (Aldebert et ah, 1993) and highlights the importance of management measures to reduce the catch of both juveniles and spawning adults (Drouineau et al., 2010). The very high concentration of juvenile European hake along the coasts of Italy in the Ligurian and Tyr- rhenian Seas indicates that these areas are the main European hake nurseries in the northwestern Mediter- ranean basin (Orsi Relini et ah, 2002; Colloca et al., 2009). Orsi Relini et al. (2002) estimated mean den- sities of European hake recruits to be up to 8 times higher than densities reported for other nurseries in the Mediterranean Sea. In the Tyrrhenian Sea, at the boundary between the continental shelf and the upper slope, densities >25,000 individuals km-2 have been ob- served (Colloca et ah, 2009). Despite many studies of the biology of European hake in the Mediterranean Sea, the growth pattern of juveniles is still controversial (Drouineau et ah, 2010). It is not clear whether the reported variability in the growth rate of European hake juveniles is due to meth- odological differences in the approaches used for age determination or due to natural variability in growth processes. Atmospheric processes and oceanographic features are known to have a key role in recruit condition and recruitment strength of other fishes. A link between en- vironmental variables (e.g., climate variability, temper- ature, and phytoplankton production) and recruitment of Atlantic cod ( Gadus morhua) in the North Sea and northeastern Atlantic has been described previously (Koster et al., 2005; Steingrund and Gaard, 2005; Stige et ah, 2006; Beggs et ah, 2014). Furthermore, increases in temperature in the North Sea have been reported to affect growth dynamics of haddock ( Melanogram - mus aeglefinus) (Baudron et al., 2011). Thermal con- ditions have been reported to affect recruitment and distribution of Pacific cod (Gadus macrocephalus ) in the eastern Barents Sea (Hurst et ah, 2012), of Pacific hake ( Mei'luccius productus ) along the western coast of North America (Agostini et al., 2008), and of Chilean hake (Merluccius gayi gayi) in the south Pacific (San Martin et ah, 2013). Within-year variability in growth of recruits of Argentine hake (Merluccius hubbsi) in re- sponse to environmental variables was found by Norbis et al. (1999) along Uruguayan coasts, and interannual variability in growth was found in Pacific hake (Wood- bury et al., 1995). Density-related growth relationships also have been described for a range of species: Bromley (1989) found a negative relationship between growth and fish densi- ty in both 1-year-old (I group) and 2-year-old (II group) Atlantic cod, whiting (Merlangius merlangus), and haddock in the North Sea: fish in areas of low density were larger than fish in areas of high density, possibly because of feeding competition in high density areas. Although environmental and oceanographic features are known to affect recruit condition and recruitment strength of European hake (Alvarez et al., 2001; May- nou et al., 2003; Olivar et ah, 2003; Abella et ah, 2008; Bartolino et ah, 2008a; Hidalgo et ah, 2008), under- standing of the effect of those factors on the growth dynamics of juvenile European hake is still limited. The aim of the present study was to model the growth of European hake juveniles to determine the effects of environmental variables (i.e., sea-surface temperature, bottom temperature, depth, scalar wind speed, chlorophyll-a) and population factors (i.e., fish density) using a generalized additive model (GAM) (Hastie and Tibshirani, 1990). Materials and methods Study area For this study, the growth pattern of juvenile Europe- an hake was analyzed in northwestern Italian waters, which include the Ligurian Sea and the northern Tyr- rhenian Sea (Fig. 1). The Tyrrhenian Sea is generally considered a distinct entity within the western Medi- terranean basin because it is semi-enclosed between the islands of Corsica, Sardinia, and Elba and the mainland (Italy) and is separated from the rest of the western basin by a channel of moderate depth, about 1500 m (Orfila et al., 2005). Along the central western Italian coasts, the Tyrrhenian Current, also called the Eastern Corsica Current, flows northward through the Corsica Channel into the Ligurian Sea. The Corsica Channel is the passage between the islands of Corsica and Elba that connects the northern Tyrrhenian Sea to the southern Ligurian Sea. It plays a key role for water circulation in the northwestern Mediterranean Sea be- cause the water exchange that runs through it involves the whole water column (Gasparini et al., 1999). The general seasonal pattern of phytoplankton dy- namics is typical of subtropical areas, with a bloom period of maximum productivity from February to April and a period of minimum productivity in sum- mer months. The intensity of this winter-spring bloom varies significantly between years. In the Ligurian Sea, a substantial positive correlation links the intensity of the phytoplankton winter-spring bloom with a strong autumn-winter water turbulence (which is mainly driven by winds), and reduced wind mixing in March (Nezlin et ah, 2004). Trawl sampling and environmental data Specimens of juvenile European hake were collected from 13 of the 120 trawl stations sampled in June 2011 during an experimental bottom trawl survey, the Mediterranean International Trawl Survey (MEDITS; see Bertrand et al., 2002, for technical specifications) in the Ligurian and northern Tyrrhenian Seas (Fig. 1). To Ligas et al.: Modeling the growth of recruits of Merluccius merluccius in the northwestern Mediterranean Sea 71 Longitude Figure 1 Map of the study area in the Ligurian Sea and northern Tyrrhenian Sea. Black circles indicate the 13 sites where European hake ( Merluccius merluccius) were sampled in June 2011 during the Mediterranean International [bottom] Trawl Survey (MEDITS). Gray lines show the 100-, 200-, 500-, 1000- and 1500-m isobaths. cover the relevant nursery areas, identified by Colloca et al. (2009), 5 of the 13 stations from which specimens were collected were located in the Tyrrhenian basin and 8 were located in the Ligurian Sea. For each station, a suite of oceanographic and ecolog- ical variables that potentially affect growth processes of the European hake was obtained (Table 1). Satellite data at a fine spatial scale for sea-surface temperature (SST, degrees Celsius), scalar wind speed (meters per second), and chlorophyll-a concentration (milligrams per cubic meter) were used (MyOcean follow-on proj- ect, http://www.myocean.eu); daily data were averaged for the period of January-March 2011. Bottom tem- perature (degrees Celsius) was measured and mean depth (meters) was recorded at each station by using a DST centi-TD1 temperature and depth probe, with 1 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. 72 Fishery Bulletin 1 13(1) TabSe 1 Environmental and ecological variables used in the generalized additive model (GAM) of environmental effects on growth of juvenile European hake (Merluccius merluccius) in the northwestern Mediterranean Sea. European hake were sampled in June 2011 in the Tyrrhenian Sea (Tyr) and Ligurian Sea (Lig). Latitude (Lat.) and longitude (Long.) of the mean point of each haul are shown, as well as the number of specimens (otoliths), mean bottom temperature (Bottom temp.), mean depth, and recruit density (number of individuals per square kilometer) recorded in each haul, the mean sea-surface temperature (SST), mean wind scalar speed, and mean concentration of chlorophyll-a (chl-a) used in the GAM. Recruit Haul code Area Lat. Long. Number of otoliths Bottom temp. (°C) Mean depth (m) density (individuals km-2) SST (°C) Mean scalar wind speed (m s-1) Chl-a (mg m-3) 42 Tyr 4208.07 1121.43 14 13.9 156 3214.0 14.00 6.53 0.449 43 Tyr 4211.32 1116.55 22 14.0 124 3571.0 14.00 6.53 0.443 59 Tyr 4227.59 1052.53 24 13.9 131 8319.0 13.80 6.31 0.438 62 Tyr 4237.86 1051.43 22 13.9 109 6631.0 13.87 6.31 0.413 63 Tyr 4232.51 1047.81 23 13.8 164 7377.0 13.83 6.31 0.424 91 Lig 4255.79 1015.80 21 13.7 113 1008.0 13.87 5.57 0.457 94 Lig 4313.1 1 958.73 21 13.6 251 3159.0 13.50 7.74 0.448 98 Lig 4332.80 952.79 19 13.5 241 6835.0 13.42 7.74 0.441 100 Lig 4312.68 1003.93 20 13.6 153 1819.0 13.63 7.74 0.408 103 Lig 4306.27 1006.32 28 13.6 150 1378.0 13.62 7.74 0.426 115 Lig 4344.53 950.26 18 13.4 205 3197.0 13.42 8.54 0.449 126 Lig 4309.57 1020.49 22 13.8 101 1072.0 13.59 7.74 0.434 131 Lig 4359.29 941.66 17 13.4 140 2003.0 13.48 8.54 0.414 supporting SeaStar software (Star-Oddi, Gardabaer, Iceland), attached to the trawl net. European hake ju- veniles were identified according to the morphological features described by Murua (2010). At each station, density (number of individuals per square kilometer) of juvenile European hake was computed as the ratio be- tween the number of recruits and the swept area (unit of measurement km2). Otolith reading All specimens of European hake that were caught at the 13 selected stations were measured in TL to the nearest 0.5 cm; otoliths (sagittae) were removed from a subsample of 318 individuals that ranged in size from 4.5 to 18.0 cm TL. The upper size limit of 18.0 cm TL was used to define European hake recruits (fish in their first year of life) (Belcari et al., 2006). The length-frequency distribution of the specimens caught at the 13 stations was broken down into normal compo- nents by using Batthacharya’s method (Bhattacharya, 1967). Left sagittae were ground on wet sandpaper, polished on abrasive cloth with alumina slurry, and mounted external-side up on glass slides with a 2-component epoxy resin; a second grinding and polishing procedure was performed to obtain thin frontal sections (Belcari et al., 2006). Microstructure analysis (counting of daily growth rings) of otolith sections was carried out with a compound green-light, polarizing microscope with plan apochromatic objectives. The number of daily in- crements deposited within the primordium, the central area of the otolith (Morales-Nin and Moranta, 2004), was recorded to estimate the duration of the presettle- ment period of this species (Arneri and Morales-Nin, 2000; Morales-Nin and Moranta, 2004; Belcari et al., 2006). Otolith readings were used to back-calculate the hatching-date distribution by subtracting the fish age from the date of capture. An indirect validation of the periodicity of increment formation was obtained by comparing the estimated hatching-date distribution with the spawning period of the species (Arneri and Morales-Nin, 2000; Panfili et ah, 2002; Belcari et al., 2006). To estimate the age-frequency distribution and to back-calculate the hatching-date distribution, the age-length key that resulted from the readings was applied to the length-frequency distribution that was obtained from the 13 stations that were sampled. In addition, a subsample of 40 otoliths was reread by the same operators for evaluation of the match between the readings (Belcari et al., 2006). Data analysis A multivariate GAM with Gaussian distribution was used to describe the growth of juvenile European hake, specifically the length-age relationship and environ- mental covariates. For the initial model that was used Ligas et al. : Modeling the growth of recruits of Merluccius mer/uccius in the northwestern Mediterranean Sea 73 r'J E w re d "D > TO C > 55 c a> Q 500 400 - 300 - 200 - 100 _ 0 _ TL (cm) Figure 2 Length-frequency distribution of European hake ( Merluccius merluccius) ob- tained from 13 stations sampled in the Ligurian Sea and northern Tyrrhenian Sea in June 2011 during the Mediterranean International [bottom] Trawl Survey (MEDITS). Lengths for fish <18 cm in total length (TL) are shown in size classes of 0.5 cm TL. to define the length-age relationship with covariates, the following equation was used: Length = a + f\(Age) + (bottom T) + fgidensity) + f 4 depth) + f5(SST) + fglwind) + fq( chl-aj + fg(depth:density)+ factor(Area) + £,, (1) where bottom T, density, and depth = the bottom temper- ature, European hake recruit density, and depth from each station, respectively; and SST, wind , and chl-a = sea-surface temperature, scalar wind speed and chlorophyll-a concentration averaged over the period of January-March 2011. To evaluate possible differences in recruit growth patterns, the area (Ligurian Sea or Tyrrhenian Sea) was included in the analysis and treated as a fac- tor (Area). Following the findings by Bartolino et al. (2008b), which included observation of a stable pattern of depth preference by juvenile European hake, the in- teraction between depth and fish density (fg) was also included in the GAM. Two forms of this model were constructed. With the first, a continuous variable of density was assumed; this first form was compared with a second model in which density was treated as a 3-level factor: low (<2000 in- dividuals km-2), medium (2000-4000 individuals km-2) and high (>4000 individuals km-2). Then, the fit of these models was compared. Analysis of variance was used to test for a significant difference in model fit, and the model with the lowest Akaike’s information crite- rion (AIC) was selected as the best model, which is the model that best fits the set of data. The degree of collinearity between explanatory vari- ables was tested with plots of paired variables (pair- plots), a matrix of scatter plots that show the bivariate relationships of variables, and variance inflation fac- tor (VIF) values (Zuur et al., 2009). Variables with a high Pearson’s correlation coefficient (r) (>0.8, absolute value) and a high VIF value (>3) were considered cor- related, and one of the pair was removed. A backward stepwise model selection procedure based on analysis of variance and on the AIC was used to identify the most parsimonious model with the greatest explanato- ry power. The significance of each variable in the GAM was determined by means of analysis of variance (F- test). The levels of constraints ( k ) for splines were re- duced from a maximum, but still achieving convergence to 1. The level of constraint for the number of splines that were used in the final analysis was selected by a comparison of AIC scores. Model residuals were tested for assumptions of homogeneity and normality (Zuur et al., 2009). A multiple linear regression model that used the final selected explanatory variables also was compared with the GAM model by using analysis of variance and AIC. Data exploration and analyses were carried out with the package R, vers. 2.15.2, and the associated mgcv package (R Core Team, 2012). An as- sumed significance level of 5% was used in all statisti- cal analyses. 74 Fishery Bulletin 1 13(1) Month Figure 3 Distribution of back-calculated hatching dates for recruits of European hake (Merluccius merluccius ) caught in June 2011 during the Mediterranean Interna- tional [bottom] Trawl Survey (MEDITS) in the Ligurian Sea and northern Tyr- rhenian Sea. Results At the 13 selected stations, 3123 specimens of Euro- pean hake were caught during the 2011 MEDITS in the Ligurian Sea and northern Tyrrhenian Sea. Sizes ranged from 4.0 to 41.0 cm TL; the length-frequency distribution of the specimens belonging to the first year class (up to 18 cm TL) is shown in Figure 2. The length-frequency distribution showed a single normal component with mean size of 9.0 cm TL (standard de- viation [SD] 2.0). Counts of otolith daily increments from microstruc- ture analysis ranged from 77 to 340. The number of in- crements within the primordium of the otolith ranged between 36 and 70, with an average of 50 (SD 5). The results of the rereading of 40 otolith slides used by Bel- cari et al. (2006) showed no discrepancies larger than 10%, a proportion that is considered a reading preci- sion threshold (Arneri and Morales-Nin, 2000), provid- ing further support for the reading method used in the present study. Back-calculation of hatching dates provided esti- mates of the main hatching period to be from Decem- ber 2010 to March 2011, with a peak during January- February 2011 (Fig. 3). A subsample of 271 individuals was used to fit the growth model by means of GAM. The 271 individu- als were born during the main hatching period (De- cember 2010-March 2011) with a size range between 4.5 and 13 cm TL and an age range between 77 and 205 days (Fig. 4); therefore, they represented a single cohort. Data exploration highlighted collinearity between area, bottom temperature, SST, and scalar wind speed (Fig. 5), supported by r >0.8 and VIF values >3. There- fore, area, SST, and scalar wind speed were removed from the model, and a model containing age, bottom temperature, fish density, depth, chlorophyll-a, and the second-order interaction depth:density as explanatory variables was tested by means of analysis of variance and backward selection: Length = a + fi(Age) + fcfbottom T) + f^(density) + f\(depth) + f$(c\\\-a) + fs(depth:density) + £p (2) Based on backward selection, the best model (Table 2), with variables significant only at the 5% level and with the lowest AIC (689.3), contained only age and density as explanatory variables: Length = a + f\(Age) + f^density ) + £p (3) That final model explained 81% of the total devi- ance, with a generalized cross-validation score of 0.727. The multiple linear regression model fitted with the same explanatory variables had heterogeneity within the model residuals, as well as a higher AIC (704.2). The analysis of variance between these models was sig- nificant (F=9.221, P<0.05), indicating that the smooth- ers were not linear. The explanatory variable age had a linear effect, al- though with some fluctuations, especially in the first Ligas et at: Modeling the growth of recruits of Merluccius mer/uccius in the northwestern Mediterranean Sea 75 14 A 12 _ 10 E u, _] H 8 50 o (no o© o o © oo © o ©0u©00 OB© OO 0©©©OCX3EO© (3D OO o ooannnx©© oo otmnrrm ®) ons©©oO O o o GnmD® © o ©o o O 0©0©©0 © (© O oanxDO © oo o o o o o o ®® ©o o o o oooo © oocoo O O © 00 o ©oo o o o © o 100 150 Age (days) 200 14 12 10 8 6 4 4 I B 0 0 1008 1378 2003 3197 3571 6835 Density (individuals krrr2) 8319 Figure 4 For the subsample of 271 European hake (Merluccius merluc- cius) recruits caught in June 2011 during the Mediterranean International [bottom] Trawl Survey (MEDITS) in the Ligurian Sea and northern Tyrrhenian Sea, (A) length-at-age data distri- bution and (B) a boxplot of length data conditional on density. part of the age range. However, in the older part of the age range, the smoothing function that describes the relationship between age and length flattened, indicat- ing a decrease in growth rate. The effect of density on the growth rate was positive up to 3000 individuals km-2, and had a weak negative effect at higher densi- ties (Fig. 6). At the stations that had a recruit density higher than 3000 individuals km-2, the length at age was on average 0.5 cm TL greater than the length at age observed at stations with lower densities. The value of k selected for the final analysis of the effect of density, by comparison of AIC scores, was 4. The AIC was higher when values of k >4 were used, and a “dome-shaped” effect caused by the lack of obser- vations of densities between 3700 and 6000 individuals km-2 was evident. With k set at a value of 4, the effect of density showed an increasing trend up to 3700 individuals km-2 and then a rather con- stant pattern at higher densities, limiting the effect caused by fitting the model in the area where values of density were missing in the database. Further, the use of the variable den- sity as a factor (3-level factor) was tested. The results were similar to those obtained with the model that had a continuous variable of density: increasing growth rate with density, although with a slight decrease at very high densities. However, this model had a higher AIC and, therefore, was less suitable in its fit to the data than the model that used density as a continuous variable and a k value of 4. An inspection of the graphs for the model (Fig. 7) shows that there was no evidence of a pattern within the model residuals. Discussion Despite the ongoing debate about general is- sues of age estimation in European hake, read- ing daily growth rings on otoliths has proved to be a useful tool in the understanding of the first year of growth (Arneri and Morales-Nin, 2000). The use of annual rings on otoliths led to the assumption that the European hake grows slowly (Drouineau et ah, 2010), but fur- ther studies on adult growth that have used tagging campaigns (de Pontual et ah, 2003; Pi- neiro et ah, 2007) and analysis of otolith daily increments in juveniles (Arneri and Morales- Nin, 2000; Morales-Nin and Moranta, 2004; Kacher and Amara, 2005, Belcari et ah, 2006; Pineiro et ah, 2008; Otxotorena et ah, 2010) have revealed that the growth rate is probably much faster than previously thought. Results from the present study are consis- tent with the main findings of recent studies on juvenile European hake growth in both the Atlantic and the Mediterranean Sea, which in- dicate a fast growth rate of about 0.6 mm day-1 during the first year of life (Morales-Nin and Moranta, 2004; Kacher and Amara, 2005; Belcari et ah, 2006; Otxo- torena et ah, 2010). Also, the results of back-calcula- tions of birth dates are in agreement with the available knowledge on spawning and recruitment of European hake in the western Mediterranean Sea (Maynou et ah, 2003; Abella et ah, 2005; Belcari et ah, 2006; Recasens et ah, 2008). The present study is one of the first attempts to fit a recruit growth model for European hake with factors that could potentially affect growth dynamics. Through the application of a GAM on the length-age relation- ship, recruit density (number of individuals per square kilometer) was found to have a significant effect on the growth dynamics of European hake recruits; however. 76 Fishery Bulletin 1 13(1) Ag ...k 1.0 1 .4 1 .8 J I I I I L 100 150 200 250 J I I L 13.4 13.7 14.0 1..I I I I I, 2.0 1.8 1.6 - 1.4 - \2 1.0 -k -0.8 0.3 -0.7 depth density _ -0.8 0.7 -0.8 0.5 -0.4 -0.9 0.41 0.43 0.45 J I I I 80 120 180 i r i i i r 13.4 13.7 14.0 1 r 2000 6000 i i i i r 5.5 6.5 7.5 8.5 m - 200 180 160 140 120 100 - 80 14.0 - 13.9 - 13.8 - 13.7 - 13.6 - 13.5 - 13.4 8000 6000 4000 - 2000 8.5 8.0 7.5 7.0 6.5 6.0 5.5 Figure S Pairs plot for all the explanatory variables in the data set used for this study of ( Merluccius merluccius) in the northwestern Mediterranean Sea. The upper diagonal panel shows the Pearson’s correlation coefficient, and the lower diagonal panel shows the scatterplots with a smoother added to visualize the pattern. The font size of the correlation coefficient is proportional to its estimated value. no evidence of effects exerted by oceanographic fea- tures were found. Atmospheric processes and oceano- graphic features instead played a role in determining variations in recruitment strength of European hake (Alvarez et al., 2001; Maynou et al., 2003; Olivar et ah, 2003; Abella et ah, 2008; Bartolino et ah, 2008a). Also, although Hidalgo et ah (2008) found spatial and temporal differences related to environmental and hy- drographical variables in recruitment processes and condition of European hake around Balearic Islands, they did not observe any differences in growth of this species. The observed positive effect of recruit density could be interpreted as an optimal density window where growth is maximized. Fast growth was observed for densities of around 3000 individuals km-2, and growth remained slightly constant at higher densities. Still, recruit growth remained greater in areas of high den- sity of recruits than in areas with low density, which could correspond to habitats of low suitability, where Ligas et al.: Modeling the growth of recruits of Merluccius merluccius in the northwestern Mediterranean Sea 77 Table 2 Summary of the backward selection of the best model in the generalized additive model. The best model, with smoothers that are all significant and that has the lowest AIC value, is highlighted in bold. Explanatory vari- ables included mean bottom temperature (temp.); mean depth; recruit density (number of individuals per square kilometer); mean concentration of chlorophyll-a (chl-a); and age (days). Depth:density is the interaction; “y” and “n” indicate the explanatory variables included and excluded in GAMs. Measures of model fitness were deviance explained (Dev. expl.), coefficient of determination (r2), generalized cross-validation score (GCV), and Akaike’s information criterion (AIC); ns=not significant: P>0.05; **=P<0.01; ***=P<0.001. Mean bottom Mean Recruit Depth: Dev. expl. temp. depth Chl-a density Age density (%) r2 GCV AIC yns yns yns y** y*** yns 80.7 0.795 0.731 692.4 yns yns yns y** y*** n 80.7 0.794 0.734 691.1 n yns yns y** y*** n 80.6 0.794 0.737 692.3 n n yns y*** y*** n 80.6 0.795 0.728 690.1 n n n y*** y*** n 80.7 0.795 0.727 689.3 impaired. Bromley (1989) i found a negative ent study; also, see Belcari et al., 2006), Europeai relationship between density and growth in some ga- doid (Atlantic cod, whiting, and haddock) juveniles in the North Sea. The ecological factors that affect differences in growth between areas deserve further multiyear inves- tigations, for example, through sampling to examine the abundance of prey, such as macrozooplankton, in the main nursery areas (Ferraton et ah, 2007; Cartes et ah, 2009). Indirect evidence of the environmental quality of European hake nurseries in the Mediterra- nean Sea has been inferred from their high spatiotem- poral stability (Fiorentino et ah, 2003; Colloca et ah, 2009). In the Ligurian Sea and Tyrrhenian Sea, after 2 months spent in the pelagic environment (in the pres- larvae were transported by eddies and frontal systems to areas of relatively high planktonic production that resulted from upwelling (Abella et ah, 2008). These ar- eas are located along the shelf break (Colloca et ah, 2004), where production is enhanced by upwelling and water turbulence, both of which increase the transport and nutrient input of organic matter into the water column (Pinazo et ah, 1996). The entire trophic chain, therefore, is increased, including a positive effect on the main prey of European hake recruits, in particular eu- phausiids and mysids, which reach their highest diur- nal abundance on the shelf break (Colloca et ah, 2004). The high spatial stability over time of the main hake nurseries in the Ligurian and Tyrrhenian Seas 78 Fishery Bulletin 113(1) Residuals Theoretical quantiles Figure 7 Graphs for the validation of the best model of the generalized additive model in age and fish density were used as explanatory variables. Residuals versus explanatory variables were (A) age and (B) density to assess homo- geneity and (C) a histogram of residuals and (D) a Quantile-Quantile (Q-Q) plot to assess normality. The model was developed from data for recruits of European hake ( Merluccius merluccius) caught in June 2011 during the Mediterranean International [bottom] Trawl Survey (MEDITS) in the Ligurian Sea and northern Tyrrhenian Sea. presents a potentially valuable feature for conserva- tion and management purposes — one that, for instance, could be leveraged to ensure long-term effectiveness of no-take areas: Colloca et al. (2009) estimated that the closure of highly persistent nurseries would result in a small reduction of the exploitable fishery area (around 5%) and the protection of a considerable fraction (40%) of the estimated total number of recruits. In a recent study, Cannella et al. (2011) found high hepatosomatic index values, a proxy for body condi- tion, in recruits of European hake from areas of high density in the Tyrrhenian Sea, support the hypothesis that high-density nurseries around the shelf break are high-quality areas where juveniles find environmental conditions of food and temperature that are appropri- ate for survival and growth. The present study is limited to growth estimation from a single year. However, although a longer time series of multiyear data is needed to sufficiently under- stand the role of environmental variables and density- based factors on growth, the results from the present study provide a first baseline and rationale in corrobo- rating the key role played by high-quality nurseries for recruitment success. The results from this study indicate that European hake recruits grow faster in- side their main nurseries than outside them, thereby increasing their chance to survive before they migrate to shallower areas on the continental platform. Accord- ing to the definition by Dahlgren et al. (2006), these areas can be regarded as “effective juvenile habitats.” In the areas that were identified as effective juvenile habitats, environmental characteristics (e.g., food avail- Ligas et al.: Modeling the growth of recruits of Merluccius merluccius in the northwestern Mediterranean Sea 79 ability and protection to predation) enhance juvenile condition and growth. Juveniles of European hake are exposed to trawl fisheries after bottom settlement in their nursery grounds. Therefore, a reduction in fishing mortality of immature fish could be a fundamental prerequisite for sustainable fisheries. The implementation of the fol- lowing requirements — use of a large mesh size, square- mesh panels, and selection grids in trawl fisheries — has reduced the bycatch of juvenile European hake (Sarda et al., 2004; Lucchetti, 2008). However, these measures may not be sufficiently effective in protecting juveniles and nursery areas. In fact, the use of gear selectivity as a fishery management tool without adequate research into the fate of escaping juvenile fish should be cause for concern for any fishery (Chopin and Arimoto, 1995). Moreover, trawling activities are known to cause alter- ations to the bottom of the seafloor, reducing habitat complexity and altering benthic community structure (Kaiser et al., 2002), both of which are fundamental components of habitat for juvenile European hake. 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Walker, A. A. Saveliev, and G. M. Smith. 2009. Mixed effects models and extensions in ecol- ogy with R, 574 p. Statistics for biology and health. Springer, New York, doi: 10.1007/978-0-387-87458-6. 82 NOAA National Marine Fisheries Service Abstract— Bottom trawling has been shown to affect the seafloor and associated biological communities around the world. Considerably less is known about the dynamics of im- pacts to structural attributes of fish habitat, particularly in unconsoli- dated sandy sediments of the con- tinental shelf. We collaborated with commercial fishermen to conduct experimental trawls, with the type of small-footrope trawl required for trawling on the continental shelf, along the 170-m isobath in an area off Morro Bay in central California. The bottom trawling intensity we applied was based on the historical range of fishing effort in the study area and included low-intensity and high-intensity treatments. A remote- ly operated vehicle was used to col- lect continuous video and still photo- graphs in trawled and in untrawled control plots, before trawling and at 2 weeks, 6 months, and 1 year af- ter trawling. Scour marks from the heavy doors of the trawl were ob- served in the seafloor and persisted for at least a year. Although data extracted from the collected imag- ery showed some smoothing of the seafloor in trawled plots, the mini- mal differences between trawled and control plots in microtopographic structure on the seafloor were sta- tistically significant only during one sampling period. Further, there were no significant differences between trawled and untrawled plots with respect to structure-forming inver- tebrates (e.g., sea whips) and mobile invertebrates (e.g., sea stars). The results of our study, part of ongoing efforts to understand and manage fishing impacts, indicate that bottom trawling with a small-footrope gear may have limited effects in some sand habitats. Manuscript submitted 28 August 2013. Manuscript accepted 12 December 2014. Fish. Bull. 113:82-96 (2015). doi: 10.7755/FB.113.1.8 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. Fishery Bulletin a- established 1881 ■ 400 ] TD {_ 300 > 200 (/) £_ CD 100 - T3 C 0 - 03 0 -100 2 -200 - m c 0 "O 120 - B 100 4 80 4 60 4 40 4 »] o -I -20 -40 4- □ [] •g > XD c > 10 individuals m-2 (worms and brittle stars). 88 Fishery Bulletin 1 13(1) Figure 3 Photographs of scour marks created by doors of the bottom trawl used in this study conducted off central California. Images were taken (A) in November 2009, immediately after low-intensity trawling, and (B) in September 2010, 1 year after low-intensity trawling. pling periods and seasons (Figs. 2, A-F). The densities of polychaete worms (Fig. 2A) peaked during 3 separate sampling periods during 2 separate seasons; the larg- est peak (480 individuals m_2, occurred in September 2009, followed by smaller peaks in May 2011 (430 indi- viduals m-2) and May 2012 (390 individuals m-2). No polychaetes were observed in either November 2009 or November 2010. Occurrence of brittle stars (Fig. 2B) was observed at much lower densities. For example, absent from the study area in September and Novem- ber 2009, brittle stars were present during every other sampling period, peaking at 60 individuals m-2 in Sep- tember 2011. Other organisms, including notaspideans (Fig. 20, octopods (Fig. 2D), teuthids (Fig. 2E), and as- teroids (Fig. 2F) were present in very small, although variable, densities over the course of our study. In the broader study area, the north reference site (Fig. 1) had an assemblage of sessile invertebrates that was similar to the assemblage in the primary study area, including sea whips ( Halipteris spp.), sea pens ( Ptilosarcus gui'neyi, Pennatula spp., and Stylatula spp.), and anemones (Halcampidae, Urticina spp., and Pachycerianthus fimbriatus). The south reference site had invertebrates that were more mobile, primarily ocean shrimp ( Pandalus jordani), that were rarely ob- served in the study plots. However, it should be noted that the amount of recent trawling effort in the north and south reference sites was unknown. Low-intensity trawling Trawl doors can create scour marks (or troughs) in the sediment as they are towed along the bottom of the seafloor. Scour marks from the low-intensity trawling effort were clearly evident in the sediment immediate- ly after the directed trawling (Fig. 3A) and were still present 1 year after trawling in September 2010 (Fig. 3B). Demersal fishes, mobile invertebrates, and drift kelp were all observed in and immediately adjacent to these scour marks. The mean percent cover of microtopographic fea- tures was similar between the trawled and control plots in September 2009 before the directed trawling, at 75% and 72%, respectively (Fig. 4A). Immediately following the low-intensity trawling treatment, the percent cover of microtopographic features in control and trawled plots diverged but did not differ statis- tically (Z=0.109, P=0.460). The mean percent cover of microtopographic features in the trawled plots declined by 15%. Interestingly, the percent cover also declined after trawling in the control plots, although by an amount (9%) lower than the decrease in the trawled plots. The small but insignificant difference in complex- ity (Z=0.096, P=0.464) between trawled and control plots persisted at 6 months after trawling, but values in both types of plots stabilized. In August 2010, at 1 year after trawling, the mean percent cover of micro- topographic features declined in both groups of plots over the 6-month period (15% and 17% in control and trawled plots, respectively) but were not significantly different (Z=0.156, P=0.440). The cumulative decline in mean percent cover at 1 year after trawling was -24% and -31% in control and trawled plots, respectively. The densities of both sessile, structure-forming (Fig. 4B) and mobile (Fig. 4C) macro-invertebrates were very low in both trawled and control plots before and after Lindholm et al.: Ecological effects of bottom trawling on fish habitat along the central California outer continental shelf 89 Control Trawled North reference • South reference Figure 4 Results from visual surveys conducted with a remotely operated vehicle between 2009 and 2012 at control (untrawled) and trawled plots before and after low- and high-intensity experimental trawl- ing across the primary study area in waters off Point Buchon and Morro Bay in central California: (A) percent cover of microtopography with bioturbation, ( B ) density of sessile invertebrates, and (C) density of mobile invertebrates, Also shown are values from surveys completed in May 2012 at reference sites north and south of the main study area. Error bars indicate 95% confidence intervals. 90 Fishery Bulletin 1 13(1) low-intensity trawling. The densities of sessile inverte- brates, which peaked at 2.3 individuals 100 m-2, were not significantly different between trawled and control plots at any point over the study period. The densities of mobile macro-invertebrates were higher, peaking at 220 individuals 100 m-2 but did not differ significantly between trawled and control plots after low-intensity trawling activities. High-intensity trawling Scour marks were immediately visible on the substrate during visual surveys conducted 2 weeks after high- intensity trawling — an observation consistent with those of the condition of the seafloor after low-intensity trawling. The mean percent cover of microtopographic complexity features (Fig. 4A) was not significantly dif- ferent between the trawled and untrawled plots in Au- gust 2010, 1 year after low-intensity trawling and ap- proximately one month before the directed trawling in the same study plots at a higher intensity. Immediately after high-intensity trawling, the mean percent cover microtopographic features in both control and trawled plots declined precipitously, 27% and 25% respectively, but did not differ statistically (Z=0.015, P=0.496). However, in May 2011, at 6 months after high-in- tensity trawling, the mean percent cover of microto- pographic features had increased in both trawled and control plots, and a significant increase of 24% in the control plots versus 4% in the trawled plots (Z=2.802, P=0.003). At 1 year after trawling, the mean percent cover had declined again in both types of plots to 37% in control plots and 27% in trawled plots and did not differ statistically (Z=0.675, P=0.251). In May 2012, approximately 1.5 years after trawling, mean percent cover had declined further in both control and trawled plots to 22.2% and 19.4%, respectively. The overall de- cline in mean percent cover of microtopographic fea- tures after the cumulative impact of both low- and high-intensity trawling was -53.96% and -52.43% in control and trawled plots, respectively. The densities of both structure-forming (Fig. 4B) and mobile (Fig. 40 macroinvertebrate organisms continued to be very low in both trawled and control plots after high-intensity trawling. The densities of structure-form- ing invertebrates, which peaked at 0.026 individuals 100 m-2 in the control plots, were not significantly differ- ent between trawled and control plots at any point of the study period. The densities of mobile macroinverte- brates did not differ significantly between trawled and control plots after high-intensity trawling activities. Power analyses The results of power analyses (Fig. 5) for our revised sampling design for both overall comparisons (Ar=1600) and year-to-year comparisons (A=200) indicated that our ability to detect an impact from trawling on mi- crotopographic structure with the Z-test was substan- tial and, therefore, that even a small effect (0.2, as per Lipsey, 1990) would be clearly discernible. That high power declined very little with the t-tests (Fig. 5) for identification of trawling effects on the densities of both structure-forming and mobile macro-invertebrates. Discussion We aimed to quantify impacts of bottom trawling on the structural attributes of fish habitat in unconsoli- dated sandy sediments on the continental shelf off cen- tral California. The persistence of scour marks from the doors of the small-footrope bottom trawl was the primary impact observed in our study. Some smooth- ing of microtopographic structure on the seafloor was observed in the trawled plots compared with control plots (as measured by reductions in the percentage of the seafloor that was observed to have bioturbation). However, the minimal differences in microtopographic structure were statistically significant only during one of 8 sampling periods over the course of this study. Further, even with a high statistical power to discern such effects, no impacts from bottom trawling were observed in the densities of sessile, structure-forming invertebrates, declines of which are a common indica- tor of trawling impacts on fish habitat in other stud- ies worldwide (Auster and Langton, 1999; Kaiser et al., 2002; Barnes and Thomas, 2005; Hiddink et al., 2007). Given the considerable variability observed in the den- sities of mobile macro invertebrates in the study area, no significant differences attributable to trawling ex- isted between trawled and control plots. Microtopographic features on the seafloor have been shown to provide habitat for demersal fishes of a vari- ety of species (Auster et ah, 1995; Auster et al., 1997; Malatesta and Auster, 1999; Tissot et al., 2006), creat- ing the potential for larger, population-scale impacts from bottom trawling (Lindholm et al., 2001; Rooper et ah, 2011). Much of the global literature on the ef- fects of bottom trawling has focused on hard substrates (NRC, 2002) and associated high-relief structural attributes (Freese et ah, 1999; Henry et ah, 2006; Stone, 2006; Hiddink et ah, 2006; Althaus et ah, 2009). The comparatively limited structural attributes in low- relief, unconsolidated sediments (such as sand waves and depressions or burrows) still can provide impor- tant refugia for fishes (Auster et ah, 1997; Gerstner, 1998; Gerstner and Webb, 1998; Sanchez et al, 2000). We expected that impacts to the structural attributes of fish habitat, including physical (microtopographic) and biological (densities of structure-forming inverte- brate) features would be discernible by a difference between control and trawled plots after low-intensity bottom trawling and that the difference would increase following high-intensity trawling. These predictions were based on our understanding of seafloor impacts from other studies (Auster et ah, 1996; Engel and Kvi- tek, 1998; Hixon and Tissot, 2007; de Marignac et ah, Lindholm et al.: Ecological effects of bottom trawling on fish habitat along the central California outer continental shelf 91 1.0 - i i 0.8 - // i i i Power o (T> . L.. i i i i i 0.4 - / / i i 0.2 - t i i i i 1 1 1 1 I 1 5 10 50 100 Sample size 1 1 1 500 1000 5000 Figure 5 Power curves for Z-test conducted on percent cover of microtopographic features (solid curve) and /-tests conducted on densities of sessile and mobile invertebrates (dotted curve) from surveys conducted off central California between 2009 and 2012. The x-axis was log transformed to resolve differences between the 2 curves. The sample size for all 3 met- rics is also provided for overall tests (vertical dashed and dotted lines) and interannual comparisons (vertical dotted line). 2009), global reviews (e.g., Auster and Langton, 1999; Hall, 1994; NRC, 2002; Barnes and Thomas, 2005), and the fact that, at a depth of 170 m, the entire study area was well below the effective depth of storm penetra- tion. For instance, elsewhere along the central coast of California, approximately 375 km to the north of Morro Bay, de Marignac et al. (2009) conducted a study at similar depths and with similar substrate composition and found that numbers of biogenic mounds and de- pressions were significantly higher in a recovering area than in an area that continued to be actively trawled. Yet the expectation of clearly discernible impacts on the seafloor was largely not borne out by the results of our study. After low-intensity trawling, the small but persistent difference in the microtopographic complex- ity of the seafloor between control and trawled plots was indicative of an impact from bottom trawling. We attributed this difference to the smoothing of habitat features by the trawl footrope as it passed over the bot- tom of the seafloor (Auster and Langton, 1999), as well as to the removal of the mobile organisms responsible for bioturbation of the sediment (Lohrer et al., 2004; Meysman et al., 2006). However, the difference was not statistically significant in our analyses, despite a high statistical power (Fig. 5). We expected that any impact from trawling would be most pronounced in this study after high-intensity trawling was conducted a year lat- er at the same study plots; however, the trajectories of the differences in microtopographic complexity at the control and trawled plots were even less clear than those for plots where low-intensity trawling was con- ducted, converging at 2 weeks after trawling, increas- ing while diverging significantly at 6 months, and then converging again at 1 year after trawling. Insofar as our trawling activities represented a type-I disturbance, where a relatively small disturbed area is surrounded on one or more sides by undisturbed habitats or organisms (Connell and Keough, 1985), it is possible that the lack of a significant impact to microtopographic structure on the seafloor resulted from the rapid colo- nization of the patches by bioturbating organisms from surrounding areas. This colonization may also explain why the temporal variation in the data was more pro- nounced than the spatial variation. Despite the minimal reduction in microtopographic complexity observed in the trawled plots, we did find, on a larger scale, altera- tion of the seafloor in the form of scour marks from trawl doors that were visible immediately after both low- and high-intensity trawling and that persisted for up to a year after low-intensity trawling. 92 Fishery Bulletin 1 13(1) The persistence of these tracks is not without prec- edent (Friedlander et al., 1999), yet the ecological ef- fects of these scour marks, which we estimated to be up to 20 cm wide and 10 cm deep and to extend for many meters, are not known. Still, scour marks do represent an alteration of the seafloor. They could positively af- fect organisms through mobilization of key prey items (Shephard et al., 2009) or creation of additional habitat structure (Kaiser and Spencer, 1994). Conversely, the scour marks could negatively affect organisms depend- ing on the nature and extent of their association with the seafloor and the substrate type. Our expectations also were not borne out with re- spect to densities of sessile, structure-forming macro- invertebrates. Biogenic structures on the seafloor have been shown to be important for demersal and ben- thic fishes at multiple life history stages (Baillon et al., 2012; Auster et ah, 2003a). However, in our study, there were no significant differences between control and trawled plots with respect to densities of sessile macroinvertebrates, which were already at relatively low densities at the start of the study. Further, the densities of mobile invertebrates varied considerably over the course of our study but did not differ signifi- cantly between levels observed at control and trawled plots with either low- or high-intensity trawling effort. A brief investigation of infaunal organisms conducted as part of this study (Kitaguchi, 2011) also revealed no differences. Most of the invertebrate groups that we assessed had low densities but showed high spatial and tempo- ral variability. Polychaete worms and ophiuroids were especially patchy and variable in their distributions. Information on the dynamics of organisms in and on unconsolidated sediments of the outer continental shelf off the central California coast continues to be very limited, despite the fact that unconsolidated sedi- ments characterize more than 80% of the continental shelf in California (Allen et al., 2006). Indeed, the dominant characterization of communities on soft sedi- ments worldwide has been one of patchiness at mul- tiple scales (Morrisey et al., 1992; Oliver et al., 2011), where the distributions of organisms are frequently more diffuse than the distributions of species associ- ated with shallow-water reefs where habitats are more discrete. With this considerable variability as a backdrop, we detected no anthropogenic impact from bottom trawling despite the precisely georeferenced trawling effort and post-trawling ROV surveys. However, we expect that the time series data on invertebrate communities (both sessile and mobile) collected as part of this project will ultimately enhance our understanding of the ecology of organisms in unconsolidated sediments, including sea- sonal and interannual variability in the distribution of mobile and epibenthic invertebrates, the patchiness of opportunistic organisms, and interannual variability in invertebrate community structure. The results of any field research project, as well as the implications of those results, must ultimately be contextualized by a variety of factors. We planned sta- tistical analyses to maximize our chances to capture moderate-to-large effects on trawling metrics. This rel- atively high statistical power strongly indicates that moderate to large impacts to the metrics that we ana- lyzed would have been detected if they had occurred. However, the very limited impacts of bottom trawling to the seafloor that we observed must be considered in light of 2 primary factors: the use of a small-footrope bottom and the location of the study area in unconsoli- dated sand sediments. The small-footrope gear was used at 2 distinct trawl- ing intensities (3 and 8 times per trawled plot) that were designed to reflect the low to moderate intensity trawling historically seen in the region off central Cali- fornia (Mason et al., 2012). Yet, with the heterogeneous distribution of trawling effort among fishing vessels, and more specifically, regular focusing of that effort on favored locations that differ among captains, some ar- eas of the seafloor may be impacted more intensively (Auster et al., 1996; Mason et al., 2012). Additionally, much of the historic effort (trawling before the imple- mentation of the federal requirement for small-footrope gear along the continental shelf in 2000) in the study area was prosecuted with a variety of bottom trawls, most of them likely employing larger footrope gear and heavier trawl doors than those on the bottom trawls that we used in our study. As such, the required small- footrope gear may cause less impact than heavier gear, and therefore the extent to which the lack of impacts that we observed can be extrapolated to other gear types is potentially limited. Substrate type is also an important factor that must be considered in any extrapolation of the results of our study, as is the behavior of the organisms found in the study area. Our study was located on the outer con- tinental shelf in an area characterized by low-relief, unconsolidated sandy sediments of relatively low di- versity (Oliver et al., 2011). We considered the area to be broadly representative of the shelf to the north and south of the study area on the basis of prelimi- nary exploratory surveys completed before this study began and on the basis of additional research that we completed elsewhere along the coast. The additional reference sites that we sampled in May 2012 (Fig. 1) appeared to be similar to the study area with respect to the percent cover of microtopographic features (Fig. 4A). However, the density of sessile invertebrates was higher at the north reference site (Fig. 4B), and the density of mobile invertebrates was higher at both ref- erence sites compared with results in the study area (Fig. 40. Again, the patchiness in the distribution of organisms on the continental shelf may explain these differences, and organism responses to trawling may also play a role. A study by Troffe et al. (2005) sug- gested that sea whips of the same genus observed in our study may have the ability to rebound after be- ing knocked over by a passing bottom trawl; however, Lindholm et al.: Ecological effects of bottom trawling on fish habitat along the central California outer continental shelf 93 Malecha and Stone (2009) found that recovery of sea whips damaged by trawling was limited. We focused on the potential impacts of bottom trawl- ing with small-footrope gear on fish habitat on the sea- floor off central California. In the context of ongoing efforts to understand and manage fishing impacts (Din- more et ah, 2003; Hannah, 2003; Bellman et ah, 2005; Ellis et ah, 2008; Hourigan, 2009; de Juan and Lieon- art, 2010), the results of our study indicate that bottom trawling with small-footrope gear may have limited im- pacts in sandy habitats of the outer continental shelf in California. Although the global literature clearly in- dicates that communities on hard substrates are more vulnerable to bottom trawling (see reviews in Dayton et ah, 1995; Kaiser et ah, 1998; Watling and Norse, 1998; NRC, 2002; Barnes and Thomas, 2005), the lack of impacts to unconsolidated sandy sediments at a depth of 170 m as observed in this study indicates that this type of sediment is much less vulnerable, at least at the level of fishing effort undertaken for this study with a bottom trawl that met the federal requirement of a small footrope ( <20 cm in diameter). Identification of habitats and depth zones appropriate for bottom trawling in the “working seascape” among closed areas will be important for efforts to balance regulations of local seafood and fish landings and the needs of fisher- men’s livelihoods with environmental impacts of trawl- ing across the continental shelf and slope habitats. Acknowledgments Generous support for this project was provided by the California Ocean Protection Council through a State Coastal Conservancy Grant to The Nature Conservan- cy (SCC grant no. 10-058), private donations from the Kabcenell Family Foundation and the Seaver Institute, and contributions from the James W. Rote Professor- ship and the Undergraduate Research Opportunities Center at California State University Monterey Bay. We thank the many students who participated through- out this study (including J. Derbonne, who passed away before the completion of the project). For key support in the field, we recognize the captains and crews of the FV Donna Kathleen, FV South Bay, and RV Fulmar and the ROV team from Marine Applied Research and Exploration. We also thank staff from NOAA Fisheries, the West Coast Groundfish Observer Program, and the Morro Bay Harbormaster’s Office. Suggestions provided by 3 anonymous reviewers improved the manuscript. Literature cited Allen, J. I., S. D. 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Disturbance of the seabed by mobile fishing gear: a comparison to forest clearcutting. Conserv. Biol. 12:1180-1197. doi: 10. 1046/j. 1523-1739. 1998. 0120061180.x. 97 Fishery Bulletin Guidelines for authors Manuscript preparation 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. Submission of an article implies that the article is original and is not being considered for publication elsewhere. Articles may range from relatively short contributions (10-15 typed, double-spaced pages [tables and figures not in- cluded]) to extensive contributions (20-30 typed pages). Manuscripts must be written in English; authors whose native language is not English are strongly advised to have their manuscripts checked by English-speaking colleagues before submission. Title page should include authors’ full names and mailing addresses and the senior author’s telephone, fax number, and e-mail address. Abstract should be limited to 250 words (one-half typed page), state the main scope of the research, and emphasize the authors conclusions and relevant findings. Do not review the methods of the study or list the contents of the paper. Because abstracts are circulated by abstracting agen- cies, it is important that they represent the research clearly and concisely. General text must be typed in 12-point Times New Roman font throughout. 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For scientific nomenclature, use the current edition of the American Fisheries Society’s Common and Scientific Names of Fishes from the United States, Canada, and Mexico and its companion volumes (Deca- pod Crustaceans, Mollusks, Cnidaria and Ctenophora, and World Fishes Important to North Americans ). For species not found in the above mentioned AFS publica- tions and for more recent changes in nomenclature, use the Integrated Taxonomic Information System (ITIS) (available at http://itis.gov/), or, secondarily, the Cali- fornia Academy of Sciences Catalog of Fishes (avail- able at http://researcharchive.calacademy.org/research/ ichthyology/catalog/fishcatmain.asp) for species names not included in ITIS. Common (vernacular) names should be lowercase. Citations must be given of taxo- nomic references used for the identification of speci- mens. For example, “Fishes were identified by using Collette and Klein-MacPhee (2002); sponges were iden- tified by using Stone et al. 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