QL ENT JAN Q 5 2005 Volume 58 Number 4 16 December 2004 if re IBRARIES ISSN 0024-0966 Journal of the Lepidopterists’ Society Published quarterly by The Lepidopterists’ Society THE LEPIDOPTERISTS’ SOCIETY EXercutTIveE CouNciL James K. Apams, President Nikias Wantserc, Vice President Susan J. Wetter, Immediate Past President Ernest H. Witiiams, Secretary Gary G. AnweILer, Vice President Ketiy M. Ricuers, Treasurer Marc Epstein, Vice President Members at large: William E. Conner Akito Kawahara Robert M. Pyle Rebecca Simmons Jane M. Ruffin John A. Shuey Charles V. Covell Jr. Erik B. Runquist Andrew D. Warren EprrortAL Boarp Joun W. Brown (Chairman) Micnuaer E. Toriver (Journal) Lawrence F. Gari (Memoirs) Puitur J. Scuaprert (News) Joun A. Snyper (Website) Carta M. Penz (at large) Honorary Lire MEMBERS OF THE SOCIETY Cnarzes L. Remincton (1966), E. G. Munros (1973), Ian F. B. Common (1987), Jorn G. Franciemont (1988), Lincoin P. Brower (1990), Doucias C. Fercuson (1990), Hon. Miriam Roruscuitp (1991), CLaupe Lemaire (1992), Freperick H. Rinpce (1997) The object of The Lepidopterists’ Society, which was formed in May 1947 and formally constituted in December 1950, is “to pro- mote the science of lepidopterology in all its branches, . . . to issue a periodical and other publications on Lepidoptera, to facilitate the exchange of specimens and ideas by both the sual astern worker and the amateur in the field; to secure cooperation in all mea- sures” directed towards these aims. Membership in the Society is open to all persons interested in the study of Lepidoptera. All members receive the Journal and the News of The Lepidopterists’ Society. Prospective members should send to the Assistant Treasurer full dues for the current year, to- gether with their full name, address, and special lepidopterological interests. In alternate years a list of members of the Society is is- sued, with addresses and special interests. 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The additional cost for members outside the U.S. is to cover mailing costs. Journal of The Lepidopterists’ Society (ISSN 0024-0966) is published quarterly by The Lepidopterists’ Society, “/o Los Angeles County Museum of Natural History, 900 Exposition Blvd., Los Angeles, CA 90007-4057. Periodicals postage paid at Los Angeles, CA and at additional mailing offices. POSTMASTER: Send address changes to The Lepidopterists’ Society, “ Natural History Museum, 900 Exposition Blvd., Los Angeles, CA 90007-4057. Cover illustration: Fourth instar larvae of Antirrhea weymeri Salazar, Constantino & Lopez, Colombia. See vol. 58(2): pp. 88-93. Photo by Maria Dolores Heredia JOURNAL OF Tae LeEerpiporreristTs’ S oCcIETY 7olume 58 2004 Number 4 Journal of the Lepidopterists’ Society 58(4), 2004, 187-188 A NEW SPECIES OF CARISTANIUS HEINRICH SOUTH LEPIDOPTERA : PYRALIDAE : PHYCITINAE) FROM RN MEXICO H. H. NEUNZIG Department of Entomology, North Carolina State University,Raleigh, N. C. 27695-7613 USA Heinrich (1956), in his revision of the American Phycitinae, proposed the genus Caristanius to accommodate decoloralis described by Walker in 1863 and pellucidella and guatemalella described by Ragonot (1888a, 1888b). I added two species, minimus and tripartitus, in 1977 and 1996, respectively. The genus is entirely New World with representatives mainly in the Neotropics, but with elements in some of the warmer parts of the Nearctic Region. In 1986 I reported the presence of Caristanius decoloralis near Veracruz, Estado de Veracruz, Mexico. Recent additional study by me of the five males and two females on which this record was based has shown that the specimens, although quite similar to C. decoloralis, represent an undescribed species. A description of this new species, as well as a key including it and other known members of the genus, are presented here. CARISTANIUS VERACRUZENSIS, NEW SPECIES _ (Fics. 1-4) Diagnosis. - Caristanius veracruzensis has a small, short, fingerlike, only slightly curved, subcostal process on the valva (Fig. 2). Description. - Forewing length 9.0 - 10.0 mm. Head: vertex pale brown to brown dusted with white; labial palpus pale brown to brown dusted with white and extending obliquely to above vertex in both sexes, robustly scaled and in contact with vertex in male; maxillary palpus ochre, mostly long-scaled in male, pale brown to brown dusted with white, short-scaled in female; antenna of male with sinus and well developed, brown, dusted with white, tuft of scales at base of shaft and with sensilla trichodea (cilia) of shaft abundant and about 1/7 as long as width of shaft just distad of sinus; antenna of female simple. Thorax: dorsum pale brown to brown lightly dusted with white (some specimens with ochre or pale reddish brown scales). Forewing: mostly brown dusted with white; antemedial line very weakly formed, only visible on some specimens on posterior half of wing; brownish red patch shaded by varying amounts of black basad Grantemedial line; postmedial line absent or very faint; discal spots dark brown. Hindwing: above chiefly white, Fic. 1. Caristanius veracruzensis, male (holotype). + some brown along anterior margin. Male genitalia (Figs. 2, 3): uncus short, broader than long with pair of ‘sclerotized, glabrous, divergent arms arising basally from ventrolateral angles: gnathos absent; transtilla absent; juxta a narrow, M-shaped band with long, slender setiferous, lateral arms; valva slender (particularly in distal 2/3) with short, fingerlike, slightly curved, subcostal process: sacculus with short, blunt, setiferous distal projection; aedoeagus slender; vesica with strongly formed, slightly hooked, cormutus (cornutus about 1/2 as long as aedoeagus); vinculum longer than greatest width. Female genitalia (Fig. 4): ostium bursae broad, strongly sclerotized; ductus bursae flattened, sclerotized, except near distal extremities of apophysis anterioris, and with many scobinations toward corpus bursae; corpus bursae elongate, scobinate near junction with ductus bursae, and with two longitudinal plates and one transverse plate; plates fused together in posterior half of corpus bursae and bearing large spines; corpus bursae indented where transverse plate extends to lateral mar gin of corpus bursae; ductus seminalis attached to corpus bursae near junction of ductus bursae and corpus bursae. Holotype: ¢. 5 km. S. of Veracruz, Estado de Veracruz, Mexico, 23-VIT-1984, H. H. and K. M. Neunzig, genitalia slide 987 HHN [USMN]. Paratypes: 4 ¢ HHN [NCSU]. 2 2. Same collection data, genitalia slide 988 Etymology. - The specific epithet is based on the type locality (Veracruz). Remarks. - The male and female genitalia of 188 JOURNAL OF THE LEPIDOPTERISTS’ SOCIETY Fics. 2-4, Caristanius veracruzensis: 2, male genitalia (aedoeagus omitted). 3, aedoeagus. 4, female genitalia. KEY TO SPECIES OF MALE CARISTANIUS 1. Uncus with broad, multiridged collar surrounding a slender, setiferous, posteriorly directed protuberance (iNiemmavalereriel Diogy IGE ties QUE))5 o5-o8 Gene Uc Ewoa Kean we oo oo an aa ne neds GA Be omoe Ba De 35 guatemalellus (Ragonot) = Uncus with pair of glabrous arms arising basally from its ventrolateral angles ........ 2. 0. 0. 0. ee ee wD OF Subcostal process of valva with distal part folded and contorted (Heinrich 1956, Fig. 297).................. pellucidellus (Ragonot) — Subcostallprocess.of valva not foldedandicontorted distally 7 io. aa tas eRe Ses) aie ee cee yee nee eer 3: @ccurshinjsoutheastem\Wmited( States: 2 qeveecis ends bie melee sieicis ie eis cianer men ee) eae ear en esate are 4 — @ccurspmsNeorropicsiey: cesses yee wees tases eke re woe, ellie thse een shenede Maauein “ple a GEA pent ta Se ae eee 5 4. Cornutus of vesica about as long as aedoeagus (Neunzig 1977, Fig. 4)......0..00 00000 minimus Neunzig — Cornutus of vesica as long as aedoeagus (Heinrich 1956, Fig. 298a; Neunzig 2003 text Fig.94b)............... decoloralis (Walker) 5. Subcostal process of valva long, about as long as valva (Neunzig 1996, Fig. 59). Distribution: Dominican Republic — Subcostal process of valva short, about 1/5 to 1/4 as long as valva (Fi Caristanius veracruzensis are most similar to those of Caristanius decoloralis. In C. veracruzensis the subcostal process of the valva is essentially straight with only a slight curve distally, the cormutus of the vesica is about 1/2 x as long as the aedoeagus, and the corpus bursae is significantly indented and strongly spined laterally. In C. decoloralis the subcostal process of the valva is sinuate throughout its length, the cornutus of the vesica is as long as the length of the aedoeagus, and the corpus bursae is not significantly indented and not strongly spined laterally. LITERATURE CITED Hernricu, C. 1956. American Moths of the Subfamily Phycitinae. U.S. Nat. Mus. Bull. 207 : 1-581. Neunzic, H. H. 1977. A new species of Caristanius from Florida (Lepidoptera : Pyralidae : Phycitinae). Proc. Entomol. Soc. Washington 79 : 555-558. ——. 1986. New records of Phycitinae from Mexico and a descrip- RAR ren eo tin meats CIURe Ain aioMadid cos yb 60° tripartitus Neunzig . 2). Distribution: southern Mexico 66d A010.0.9.0 O)D.cads0l ‘Dine o%0 od b-O'd-dho 9) 6.060. 'a/0'9,d.0.0 o'0.0-0-8 veracruzensis T.Sp. tion of a new genus and species (Lepidoptera : Pyralidae). Proc. Entomol. Soc. Washington 88 : 122-126. 1996. New species of Phycitinae (Lepidoptera : Pyralidae) from the Dominican Republic. Proc. Entomol. Soc. Washington 98 : 744-801. ——. 2003. Pyraloidea, Pyralidae (part), Phycitinae (part). In Do- minick, R. B., et al., The Moths of America North of Mexico, fas- cicle 15.5 : 1-338. Neunzic, H. H. anp L. C. Dow. 1993. The Phycitinae of Belize (Lepidoptera : Pyralidae). North Carolina Agr. Res. Serv. Tech. Bull. 304 : 1-131. Raconot, E.-L. 1888a. [Les diagnoses de cing espéces nouvelles de microlépidoptéres de Porto Rico]. Bull. Séances et Bull. Biblio- graph. Soc. Entomol. France (6) 8 : exxxviii - exl. . 1888b. Nouveaux Genres et Espéces de Phycitidae & Galleri- idae. Paris. 1-52. WALKER, F. 1863. List of the Specimens of Lepidopterous Insects in the Collection of the British Museum 27 : 1-286. Received for publication 25 January 2004; revised and accepted 7 July 2004 Journal of the Lepidopterists’ Society 58(4), 2004, 189-195 RELATIONSHIPS AMONG POPULATION ESTIMATION TECHNI UES: AN EXAMINATION FOR PARNASSIUS SMINTHEUS DOUBLEDAY (PAPILIONIDAE) STEPHEN F. MATTER Cincinnati Museum Center 1301 Western Ave Cincinnati OH 45203 and Department of Biological Sciences, University of Cincinnati. Cincinnati OH 45221. email: mattersf@email.uc.edu AND JENS ROLAND Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9 Canada Estimating the abundance of organisms is an important aspect of ecology. In fact, if we adhere to Krebs' (1972) definition of ecology as “the scientific study of the interactions that determine the distribution and abundance of organisms” it is fundamental to the field. Estimates of population size form the basis for ecological and conservation studies. A multitude of methodologies exist to estimate population abundance. These methods differ in their suitability for species, the assumptions involved, the accuracy of the estimates, and the effort and cost needed to perform. The most appropriate technique will likely depend on the objectives of the study and a balance between the precision and parameters needed and the cost and effort of each method. Because of differences in methodology, estimates of abundance may not be directly comparable among studies. Here, we examine the relationships among Several common population estimation techniques need for butterflies. Butterflies are popular study organisms for a variety of ecological and evolutionary questions and many species are often used as indicators in conservation studies (Blair 1999, Brown and Freitas 2000). It is our hope that this study will allow more meaningful comparisons of population data collected using different methods and provide guidance in selecting among common techniques. MATERIALS AND METHODS Study species and site. The butterfly Parnassius smintheus Doubleday (Papilionidae) is abundant within subalpine meadows in the Rocky Mountains, although congeners are threatened elsewhere (Kuras et al. 2000). The butterflies! host plant, Sedum lanceolatum Torr. (Crassulaceae), occurs in gravelly sites above tree-line (Fownes and Roland 2002). Parnassius smintheus is univoltine with a flight period from mid July to September in our study area. Adults nectar yellow flowered species such S. on as lanceolatum, Solidago multiradiata (Asteracae), and Senecio lugens (Asteracae) (Matter and Roland 2002). Transect surveys and mark-recapture of P. smintheus were conducted in nine meadows within a network of 21 meadows located along Jumpingpound Ridge, Alberta, Canada (51° 57'N, 114° 54'W). Each meadow was considered as containing a 'population.' Meadows are comprised of grasses, sedges, and wildflowers, and are bordered on their lower slopes by forest consisting of Pinus contorta, Abies lasiocarpa, and Picea engelmannii. Population estimation methods. For transect surveys, each observer walked a path through the middle (along the longest axis) and around the circumference of a meadow tallying the number of P. smintheus observed at any distance in front of them. As P. smintheus fly more frequently when it is sunny (Ross et al., in press), observations were conducted during full sun. As a rubric, we stopped walking and counting if we could no longer see our shadow. For each survey there were between two and four observers. Transect surveys were conducted prior to mark-recapture, on the same date, to provide comparisons. For mark-recapture estimates, we captured butterflies using hand nets and each newly captured butterfly was given a unique 3-letter code on the upper surface of each hind wing using a felt-tipped pen. For all captures, we recorded the date, time, location, and identity mark (Roland et al. 2000, Matter and Roland 2002). To equilibrate effort among populations, recapture continued until ~75% of recaptured butterflies had been previously captured that day. Populations were sampled from 3-7 times between July 27 and August 20, 2001. Transect surveys. Transect surveys are perhaps the This method assumes, if multiple observers or observations simplest population estimation technique. are involved, a consistent path or amount of time is 190 used, and that observers have similar ability in identification (Pollard 1977, Thomas 1983). To arrive at a population estimate for transect surveys, we calculated the mean and variance of the number of butterflies reported by the observers. Number of individuals captured. This was the simplest mark-recapture Perec For this estimate we tallied the total number of caught during a sampling session. This and all other methods inv olvi ing marked individuals that marks are not lost, and that marking and handling different individuals (below) assume do not affect behavior, survival, or the probability of capture. Craig's Method. Craig's method is a slightly more complicated mark-recapture technique based on the frequency of capture during a single sampling session (Craig 1953, see also Southwood 1994). Thus, it uses some data often discarded by other methods, and may not be applicable for small mammals or other organisms which are usually caught only once per session or with unequal capture probability (Edwards and Eberhardt 1967, Nixon et al. 1967). Population estimation assumes that the frequency of butterflies captured once, twice, thrice, etc. follows a Poisson distribution. The number of butterflies the zero of the not caught, term distribution, is estimated and 'added' to the number of individuals caught to arrive at an estimate of population size. This method incorporates all the assumptions of marking and further assumes that all individuals in the population are at equal risk of capture at all times, i.e. there is instantaneous re-mixing upon release and no handling or marking effects that would effect capture. Craig's method also assumes that the population is closed, that is there is no birth, death, during sampling. Population size was estimated using or migration the equation: InN—In(N—r)=s/N where N is estimated population size, r is the number of individuals captured, and s is the total number of captures (Craig's method 1, Craig 1953). We solved the equation above using the fsolve routine of Maple V. Variance of the estimate was calculated as: a 5 N Op aaa ‘er =1= KX where A = s/N (Southwood 1994). Capture probability can be estimated as p = r/N. Given N and A, the expected number of individuals caught x times can be calculated from the Poisson equation: JOURNAL OF THE LEPIDOPTERISTS’ SOCIETY x Eyecam x x! Goodness of fit was evaluated by comparing these expected values to the where (observed - expected)’/expected follows a ?- distribution. Evaluation can be made for each class of observed values, sae of captures with one degree of freedom, or overall, by summing capture classes with degrees of freedont equal to the number of summands. Geometric Model. Similar to Craig's method, the geometric model is also based on the frequency of capture and assumes a closed population. However the assumption of equal capture probability is modified and the model treats the number of times that an individual is captured as a geometric distribution. Population size was estimated using the equation: we r(s—1) Siamt la and variance of the estimate as: Ngl@q°, where g = (s-r)/(s-1) and g = 1- q (Pollard 1977). Note that @ is used rather than the traditional p to avoid confusion with capture probability. Capture probability can be estimated as p = r/N. Given N, q and g, the expected number of butterflies caught x times can be calculated as: Bd d= Nena Goodness of fit can be evaluated using the same methods as for Craig's method (previous section). Lincoln-Petersen. As opposed to the previous methods, the Lincoln-Petersen method requires captures on multiple occasions, in our case consecutive days. This method is based on the assumption that the ratio of marked individuals to the total population size will equal the proportion of marked individuals in a second sample. It assumes the assumptions for marked individuals, that populations are closed during and between sampling periods, and a constant capture probability. The equation: eS mn ING= Fa was used to estimate population size, where m is the number of individuals marked on the first occasion, r is the number of recaptures, and n is the total number of individuals captured on the second occasion. For samples under 20, we used a small sample approximation (Baily 1952): VOLUME 58, NUMBER 4 i m(n+ 1) rt+l Variance of the estimate was calculated as: aes m-n(n—r) N re and as: = m>(n+1)\(n—r) i (r +1)? (r+ 2) for the small sample approximation (Southwood 1994). Estimated capture probability during the recapture period for the can be calculated as fp = r/m (Skalski and Robson 1992). Jolly-Seber. The Jolly-Seber method is similar to Lincoln-Petersen, but requires capture on three or more occasions. Importantly, this method relaxes the assumption of a closed population. Animals may enter the population via immigration or birth and leave the population via emigration or death. Without additional information, estimates can only be made for the combined effects of each, that is, total gain and loss to the population. The model is stochastic assuming that there is a probability that organisms will survive (not die or emigrate) from each census period to the next and that capture probability may also vary. Survival (6), capture probability (j), and population size (X) were estimated using the program Jolly. We assumed fully parameterized models (time varying capture and survival probabilities) unless simpler models with constant survival, constant capture probability, or both constant did not significantly differ from the full model. Analysis. We used linear regression to build predictive relationships between the population estimation methods. We constructed a separate model for each pair of methods. Because of non-linearity between some estimates, data were log, transformed prior to analysis. Standard diagnostic techniques for regression were used including inspection of residuals and outliers. Not all population estimation techniques could be used for each sample date, e.g. sampling needed to be conducted on consecutive days for Lincoln-Petersen estimates. Thus, sample size varies among the techniques. We considered each population estimate to be an independent observation. It should be noted that some relationships involve cases where the dependent and independent variables are calculated using the same data (e.g. Lincoln-Petersen and Jolly- Seber both incorporate captures in the estimate of population size). In such cases correlations will be greater than expected by chance, affecting statistical 19] inference; however, the regression equations describing the relationships are still valid. Estimates for a population of known size. To estimate the accuracy of the techniques, we released a known number of male butterflies (24) into a meadow at lower altitude where they had never been observed and their host plant does not occur, but many of their nectar flowers do occur. Butterflies were released onto a nectar source at varying positions throughout the meadow. Sampling began 30 min after release. Butterflies were marked and recaptured as in the population surveys. Three observers who did not know the number of butterflies released, conducted the transect surveys and mark-recapture. We conducted one transect survey and two mark-recapture sessions separated by one hour for this population. We computed population estimates as for the natural populations. As there were only two capture sessions Jolly-Seber estimates could not be calculated. RESULTS There were significant, positive correlations among all the population estimation techniques (Table 1, Fig.1). Transect surveys produced the lowest estimates, while the geometric distribution provided the highest estimates of population size. Models for which a test could be preformed showed no lack of fit except for Craig's method for meadow Z For the population of known size (24 butterflies), the mean of the three observers' transect counts was 7.3 + 5.3 (Var.). There were 16 and 14 captures for the first and second census, respectively. Craig's estimate for the first census was 24.4 + 28.9 and 26.3 + 69.5 for the second. The estimates from the geometric distribution were 40.0 + 150.0 and 44.3 + 304.2. The Lincoln- Petersen index estimated population size as 18.5 + 3.5 butterflies. DISCUSSION The significant, positive relationships among the population estimation techniques were reassuring. Our limited investigation of the accuracy of the techniques shows that transect counts and the number of captures underestimate the actual population size. Craig's estimates were accurate while the Lincoln-Petersen estimate was lower than the actual population size, but provided a reasonable estimate. The geometric model overestimated population size. This experiment also allowed us to test our model and illustrate its utility and limitations. Note that the prediction of a single value of Y and its error for a given X in regression (prediction differs from, and_ is than the distribution of Y (confidence interval) at a particular X (Zar 1999, p. 341). As an example, our transect count of interval) greater JOURNAL OF THE LEPIDOPTERISTS’ SOCIETY 192 See c80O 820 TOPO! c6Ll prO 1002 L60E 964 9F0 SOSIT 6tth e8ll 70 SB8Le ecSc_ _9SI CCIc £6 10/r1/8 Z V/N 80 O01 V/N ORES COI CS eer ch Cinmen 0. 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SPOLl dl < VOLUME 58, NUMBER 4 Q 7.3 results in predictions of 26.0 + 4.6 (95% P.1.) for Craig's estimate, 12.9 + 3.5 for the number of captures, and 32.5 + 3.9 for the Lincoln-Petersen estimate. The actual estimates fall within the prediction intervals for Craig's estimate and the number of captures, but not for the Lincoln-Petersen method. This demonstration illustrates both the utility of our model and _ its difficulties. For small population sizes it may be difficult to obtain a precise estimate. This problem can especially be seen by the fact that the intercepts of some relationships were significantly different from zero (Table 2). For example, a transect count of zero may indeed indicate the presence of no butterflies, but could result in an estimate of 6.6 based on the Lincoln- Petersen estimate. Although the equations presented here apply only to P. smintheus at our study site, the results do illustrate the relative strengths and weaknesses of the various techniques. Given the varying reasons for estimating population abundance, a variety of methods have been and will continue to be used. For butterflies, transect surveys are perhaps the easiest and least disruptive method of population estimation requiring only the ability to identify species on the wing. For some groups or assemblages this may be quite difficult, necessitating either netting or grouping of species that cannot be distinguished. For conspicuous, easily identifiable, species transect surveys are an efficient means to generate relative estimates provided observability (capture probability in mark-recapture terminology) does not vary. However, transect surveys do not provide accurate estimates of population size, nor do they allow for estimation of observability which limits their utility for comparison. Transect surveys, as conducted here under highly favorable conditions, result in large underestimates of population size. This underestimation is especially important in determining presence or absence. A transect survey producing no butterflies does not mean that the species is absent. Accurate determination of local absence or extinction always will require additional, intensive sampling. All other methods investigated here require both the capture and marking of individuals which may alter behavior (Mallet 1987). In general, capture temporarily reduces the propensity of butterflies to fly. Reduced flight in turn lowers the capture probability of marked individuals relative to unmarked individuals for the length of time that the butterflies are affected (Gall 1985). Frequency of capture methods (Craig's and geometric) will be more influenced by a temporary change in behavior than other methods. If marked idivideale temporarily have a lower capture probability than unmarked individuals, estimates of population size 193 will be higher than the actual population size (Gall 1985). For other mark-recapture methods, any temporary handling effect usually will have abated by the next census aartad For P. smintheus the effects of marking on flight however capture probability i is lower for females than for males violating the assumption of equal capture probability for Craig's and the Lincoln-Petersen methods (Roland et al. 2000, Matter and Roland 2002). We note that our estimates for a population of known size used only males, and thus should not violate this assumption; however, this bias will affect estimates for the populations along Jumpingpound Ridge. The number of individuals captured underestimates population size as the capture rate rarely nears 100 percent. However, assuming marks are not lost, the number of individuals captured does provide an estimate of the minimum possible population size. For the effort of tallying the number of times each individual butterfly is captured, Craig's method provides fairly accurate estimates of population size at a specific time, while the geometric distribution overestimated population size. Interestingly, both frequency of capture methods showed good fits to the data despite assuming different distributions for capture frequency. In general, fits were better for Craig's method than for the geometric distribution. This result contrasts with Pollard (1977) who found better fits for the geometric distribution than for the Poisson distribution of Craig's method in his investigation of three butterfly species. Our result is all the more surprising given that the geometric distribution should better accommodate the difference in capture probability between males and females than should the Poisson distribution. The Lincoln-Petersen method requires capture on two or more, and Jolly-Seber on three or more occasions. Both provide good population estimates provided assumptions are met (Southwood 1994). In study, it is unlikely that we meet either the assumptions of a closed population or equal capture probability required by the Lincoln-Peterson method. For the Lincoln Peterson method, the loss and gain of individuals after the initial marking period will result in overestimation of population size (Gall 1985). Jolly- Seber has the advantage of providing parameters for capture, survival, and recruitment, but requires more sampling occasions. are minimal: our ACKNOWLEDGEMENTS We thank R. Cormier, E. Robinson, A. Ross, D. Roth. Schmidt, and D. Sjostrom for assisting with the mark- caste and E. Connor, C. Penz, and two anony mous reviewers for com- ments and suggestions improving the mz anuscript. This research was supported “by NSF grant 03-26957 and an NSERC operat- ing grant. 194 LITERATURE CITED BalLy, N. T. J. 1952. Improvements in the interpretation of recapture data. J. Anim, Ecol. 21:120-127. Barr, R. B. 1999. Birds and butterflies along an urban gradient: Sur- rogate taxa for assessing biodiversity? Ecol. Appl. 9:164-170. Brown, K. S. & A. V. L. Freiras. 2000. Atlantic forest butterflies: In- dicators for landscape conservation. Biotropica 32:934-956, Craic, C. C. 1953. On the utilization of marked specimens in estimat- ing populations of flying insects. Biometrika 40:170-176. Epwarps, W. R. & L. EBERHARDT 1976. Estimating cottontail abun- dance from livetrapping data. J. Wildl. Manag. 31:87-96. Fownes, S. F. & J. RoLAND. 2002. Effects of meadow suitability on fe- male behaviour in the alpine butterfly, Parnassius smintheus Doubleday. Ecol. Entomol. 27:457-466. GALL, L.F. 1985. Measuring the size of Lepidopteran populations. J. Res. Lepid. 24:97-116. KREBS, C. J. 1972. Ecology. Harper and Row, New York 694 pp. Kuras, T., J. BENES, A. CELECHOvskY V. VRABEC & M. KONVICKA. 2000. Parnassius mnemosyne (Lepidoptera: Papilionidae) in North Moravia: review of present and past distribution, proposal for conservation Klapalekiana 36:93-112. MALLET, J., J.T. LoNGINO, D. MURAWSKI, A. MURAWSKI & A, SIMPSON DE Gamboa. 1987. Handling effects in Heliconius: where do all the butterflies go? J. Anim. Ecol. 56:377-386. TaBLE 2. The relationship among population estimation methods. JOURN AL OF THE LEPIDOPTERISTS’ SOCIETY Marre, S. F. & J. ROLAND, 2002. An experimental examination of the effects of habitat quality on the dispersal and local abundance of the butterfly Parnassius smintheus. Ecol. Entomol. 27:308-316, Nixon, C. M., W. R. Epwarps, & L. EBERHARDT. 1967. Estimating squirrel abundance from livetrapping data. J. Wildl. Manag. 31:96-101. PoLLarb, E, 1977. A method for assessing changes in the abundance of butterflies. Biol. Conserv. 12:115-134. ROLAND, J., N. Keycuosap! & S. Fownes. 2000. Alpine Parnassius butterfly dispersal: effects of landscape and population size. Ecol- ogy SI: 1642- 1653. Ross, J. A., S. F. Marrer & J. Roanp. In press. The effects of matrix habitat and edge on the movement of the butterfly Parnassius smintheus. Landscape Ecology. SKALSKI, J. R. & D. S. Ropson. 1992. Techniques for wildlife investi- gations. Academic Press, San Diego, California. 237 pp. SouTuwoop, T. R. E. 1994. Ecological Methods. 2nd ed. Chapmen and Hall, London. 524 pp. Tuomas, J. A. 1983. A quick method for estimating butterfly numbers during surveys. Biol. Conserv. 27:195-211. Zak, J. H. 1999. Biostatistical Analysis 4th ed. Prentice Hall, Upper Saddle River, New Jersey 663 pp. Received for publication 8 Setember 2003; revised and accepted for publication 3 February 2004 The dependent variable is in columns and the independent variable is in rows. The regression equation (SE) is on top and statistics for the relationship in the bottom of each cell. All relationships were significant (P < 0.001). A °° indicates that the intercept differs significantly from 0 (P < 0.05). Transect Craig’s Geometric Number of Lincoln- Jolly-Seber — captures Petersen Transect 1.17+0.36** 1.4840.40 0.97£0.29** 1.8940.34** 1.54+0.46** 1.05+0.13 1.12+1.45 0.80£0.11 0.80+0.12 0.7740.16 R*=0.80 R2=0.79 R?=0.78 R*=0.81 R°=0.64 F\16=64.2 F\16=59.7 Fy 16=57.3 F\11=46.41 F\33=22.7 Craig’s -0.41+0.32 0.20+0.04** 0.31+40.33 0.95+0.30** 0.83+0.48 0.77+0.10 1.08+0.01 0.70£0.08 0.79+0.07 0.70+0.12 R°=0.80 R°=0.99 R’=0.82 R°=0.91 R°=0.73 F\\6=64.2 F\\6=1093.2 F\\6=73.5 Fy 1=113.5 F\3=35.2 Geometric -0.18+0.40** 0.19+40.34 0.78+£0.32** 0.72+£0.50 0.93+0.01 0.65+0.08 0.74+0.07 0.65+0.11 R?=0.99 R°=0.82 R?=0.91 R°=0.73 F\\6=1093.2 F\ \6=72.0 Fy =112.3 F\ 13=34.6 Number of -0.41+0.41 0.30+0.43 0.53+0.47 0.74+0.31 0.52+0.34 captures 0.9840.13 1.17+0.14 1.26+0.15 1.04+0.10 1.00+£0.11 R°=0.78 R?=0.82 R?=0.82 R?=0.92 R°=0.87 F\16=57.3 Fy 16=73.5 F\6=72.0 Fy 1=118.7 F\ 13=85.8 Lincoln- -1.42+0.62** -0.77+0.45 -0.58+0.48 -0.39+0.33 0.16£0.60 Petersen 1.01+0.15 1.16+0.11 1.24+0.12 0.88+0.08 0.86+0.14 R°=0.81 R°=0.91 R°=0.91 R*=0.92 R°=0.76 F 1); =46.4 Fy ,=113.5 Fy ,=112.3 Fy 1=118.7 Fy ))=35.5 Jolly- -0.37+0.64 0.14+0.65 0.34+0.70 -0.07+0.34 0.80+0.56 Seber 0.83+£0.17 1.05+0.18 1.13+0.19 0.874£0.09 0.8940.15 R°=0.64 R*=0.73 R°=0.73 R°=0.87 R’=0.76 F\3=22.7 Fy 3=35.2 F)\ 13=34.6 F) 3=85.8 F) )1=35.5 195 VOLUME 58, NUMBER 4 “sisATVUL O07 LOLI POULLLOFSUR.Q "BOY o.19A\ RILCL * 9 OOM SNAY TU uoyrpndod peioros SuUIsN SMOPLOLU OULU UT SOLU J-E WOT] Powe 4aqas-Ajjor UaS19}9qg-UJOOU!) OIsso.LBOA ABOU BU sn 1 poqenyead svar sanbrurpoo) Jo umd tova usoayjaq diysuonpee.t ‘sont dd Ayjoyng oy} Jo sozis uonLndog “spoyjout UoAeuyse uoyRndod Suour sdit djawoas seu yoasues | = daqas-Ayjor v uassa}ag-ujooury = painjdeo sjenpiaipuj oujewoag sbies9 pasues, i) WONVLUL so ORY, "LOL 196 JOURNAL OF THE LEPIDOPTERISTS’ SOCIETY Journal of the Lepidopterists’ Society 58(4), 2004, 196-202 MANUAL VERSUS AUTOMATIC MOTH SAMPLING AT EQUAL LIGHT SOURCES - A COMPARISON OF CATCHES FROM MT. KILIMANJARO JAN C, AAMACHER Institute 410C, University of Hohenheim, 70593, Stuttgart, Germany; email: jan.axmacher@web.de AND KONRAD FIEDLER Department of Population Ecology, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria; email: konrad.fiedler@univie.ac.at ABSTRACT. Nocturnal moth ensembles are frequently assessed using either catches from automatic light traps or manually col- lected samples at artificial light sources. Up to now, ie studies have compared the influence of these methodological differences on the samples. We compared such samples, attracted by identical light sources, using geometrid moths in the montane rainforest belt of Mt. Kilimanjaro, Tanzania, as an example. The average number of moths caught manually from 1900 h to 2200 h at a light tower - a reflective gauze cylinder with a lamp placed in the middle - was more than ten times higher than that caught in a light trap, with more than half of all species only recorded at the light tower. With regard to individuals sampled, catches were biased towards the subfamily Ennominae in the traps (51% versus 30%) and towards Larentiinae in the manual samples (68% versus 44%). It remains to be tested whether the relatively higher representation of larger-sized Ennominae in the trap catches is due to later flight activity or some behavioral differences related to body size. Diversity (measured as Fisher's alpha) of light tower catches decreased from clearings (22.4) and secondary forest (21.7) to mature forest (11.0), while in the traps, values increased in the same order (Fisher's alpha: 6.0, 12.0, and 14.2). Species composition of trap samples taken in clearings and secondary forest differed strongly from man- tal catches, while manual a automatic samples from mature forest were more similar to each other. Manual moth sampling at light towers proved superior to automatic light traps in many ways and is hence recommended as a very useful standard method to record nocturnal insects if sufficient man-power is available. Additional key words: Geometridae, sampling method, tropical mountain rainforest, diversity assessment. Nocturnal moths can easily be sampled by attracting portable traps, weak fluorescent tubes (8-15 W) are them to artificial light sources. Two strategies of commonly used. It therefore remains difficult to obtaining samples are frequently employed. Moths directly compare results from such studies. may be collected in light traps. Various types of these The aim of our study is to compare both manual traps are commonly used (Taylor & Brown 1972, sampling at a light tower and automatic sampling using Taylor & French 1974, Baker & Sadovy 1978, Bowden a portable type of light trap. To facilitate comparisons, 1982, Muirhead-Thomson 1991, Leinonen et al. identical lamps were used in light towers and traps. 1998). Many light traps are run stationarily, as they are Thus effects of different light spectra and intensities heavy, bulky and rely on permanent electric power on the insects (e.g. Taylor & French 1974, Bowden supply, but more recently, light, robust types relying 1982, Leinonen et al. 1998, Intachat & Woiwod 1999, on batteries for power supply have become more Southwood & Henderson 2000) were eliminated. widely available. Alternatively, moths may be collected Geometrid moths were selected as our study group manually from reflective sheets or gauze cylinders set since they have been often used as ecological up adjacent to a light (e.g. Beck et al. 2002, Chey 2002, indicators (Holloway 1985, Chey et al. 1997, Intachat Axmacher 2003, Brehm & Fiedler 2003, Schulze & et al. 1997, Intachat et al. 1999a, 1999b, Intachat & Fiedler 2003). Both collecting methods yield samples Woiwod 1999, Willott 1999, Kitching et al. 2000, Beck that are amenable to statistical analysis, provided that et al. 2002, Brehm et al. 2003). With about 21,000 proper measures are taken to standardize catches known species (Scoble et al. 1995, Scoble 1999), this (Schulze 2000). Such samples can be used for family is one of the most diverse in the order addressing various ecological questions, such as the Lepidoptera. response of moth communities to environmental MATERIAL AND METHODS gradients or change (for geometrid moths e.g. Intachat Study site. The study was conducted in the et al. 1997, Intachat et al. 1999a, 1999b, Beck et all. montane rainforest on the south western slopes of Mt. 2002, Thomas 2002, Axmacher 2003, Brehm & Kilimanjaro, Tanzania, in close vicinity to the Fiedler 2003). Machame route at altitudes of about 2100 to 2300 m. Few studies have attempted to critically compare Moths were caught in three different habitat types: sampling success and sample composition from the large clearings (> 2500 m2, 3 sites), secondary forest (3 same sites as a function of the sampling method. Many sites), and mature forest (6 sites). light trap studies employed strong (100-250 W) Moth sampling. A small, robust type of automatic stationary light sources, while for hand sampling and light trap (Fritz Weber, Germany, slightly modified, VOLUME 58, NUMBER 4 Fig. 1) was used. The automatic light trap was arranged with the sampling bag just above the soil surface in order to avoid intrusion of army ants (Dorylus spp.). A total of seven traps were operated during the whole night from dusk to dawn (~1900 h to 0600 h), with 29 catches performed on clearings, 26 catches at secondary forest sites and 39 catches in mature forest. Additionally, moths were sampled manually at three light towers (cylinder of reflective gauze, Fritz Weber, Germany, Fig. 2). On light towers, all geometrid moths were manually sampled from 1900 h to 2200 h. Twenty- two catches were performed on clearings, 16 in secondary forest and 1] in mature forest. Five nights before to four nights after full moon, sampling with both methods was stopped as the attractiveness of artificial light sources is reduced during this period (McGeachie 1989, Yela & Holyoak 1997, Schulze 2000, Brehm 2002). Photocell Plexiglas Blacklight tube Sylvania blacklight-blue SW GSW) Cable to the dry accumulator (12V) Storage-bag Fic. 1: Sketch of the light trap used in this study. Moths circle around the lamp until they collide with the Plexiglass and fall through the funnel into the storage bag below. For rain protection, a plastic bowl was fixed above the lamp, and the storage bag was put into a plastic bag (dotted lines). The storage bag was partly filled with leaves and twigs among which the moths could rest. A photoelectric element was used to ensure the operation of the lamp from dusk until dawn. 197 Steel ring Gauze cylinder 170 Blacklight tube = Sylvania blacklight- blue (15W) Soil surface Cable to the dry accumulator (12V) Fic. 2: Sketch of the light tower. Moths settle on the reflective gauze cylinder where they can be easily and selectively sampled. Automatic light traps and light towers were equipped with a 15W-blacklight tube each (Sylvania Blacklight- Blue, F 15 W/ BLB-TB) run on a 12V dry battery pack. This weak light source was aimed to ensure that moths were only attracted from a short radius, so that habitat- specific sampling was possible also in habitat mosaics. Earlier studies with the same equipment revealed that indeed such moth samples have a high spatial resolution (Schulze & Fiedler 2003, Fiedler & Schulze in press). To avoid possible effects of seasonality on the comparison of the sampling techniques, for both methods only catches from the rainy seasons (1st March to 30th May and Ist -26th November) are considered in this study. Furthermore, samples were generally taken simultaneously at all three habitat types to make results more easily comparable. Site selection within the same habitat type was performed at random. To allow for meaningful statistical analyses, samples from different sites belonging to the same habitat type were pooled. Moths were sorted to morphospecies level and further determined as far as possible at the Zoologische Staatssammlung, Munich, where vouchers of all species will be deposited. A complete list of our specimens has been published (Axmacher 2003) and can also be obtained directly from the corresponding author. Statistical analysis. y7-tests were employed to compare the effect of the sampling technique on the proportion of the subfamilies in the overall catches. Fisher's alpha (Fisher et al. 1943) was used to assess the 198 diversity of moths in different habitat types (with pooled samples exceeding 150 individuals in all cases) according to sampling methods. To the similarity between the pooled samples for each habitat type and for each sampling method, the chord- normalized expected species shared (CNESS) index (Trueblood et al. 1994) was employed. This index gives an approximation of the expected similarity of samples evaluate of an equal sample size (m) which can be varied from 1 to the smallest common maximal sample size. Setting m=l1 strongly emphasises the most dominant species, while an intermediate level (m=50) and high values (m=100) give an increasingly strong emphasis to rare species. Based on the CNESS dissimilarity matrices, samples were ordinated using non-metric two- dimensional scaling for different values of the sample size parameter m (Brehm & Fiedler 2004). The software packages EstimateS 6.5 (Colwell 2000), COMPAH 96 (Gallagher 1999) and STATISTICA (Statsoft, Tulsa, UK) were used for analyses. RESULTS Effectiveness of methods. In the study area, 49 nightly manual catches at the light tower resulted in 2123 specimens representing 109 species of geometrid moths, while 94 nights of automatic light trapping yielded a total of 372 specimens representing 49 species. The average number of individuals caught in light traps was 4.0 specimens/night, whereas the light towers yielded approximately 43 specimens/3 h period (Table 1). Thus, manual samples of moths at light towers were on average more than ten times larger than trap catches. The maximum number of individuals found in a single trap was 20, while the minimum was 1. At the tower, recorded in a single, 3 h period was 239, the minimum the maximum number of geometrids 6. While between-habitat variation for sampling success of light traps was negligible, the effectiveness of light towers strongly increased from clearings and secondary to mature forest. A comparison of species caught with the two methods showed that 42 species (36%) were present in both samples from light towers and light traps. Sixty-seven species (57%) were only found at fhe light towers, while 8 species (7%) were exclusively recorded in traps. Subfamilial sample composition. Depending on the collecting method, samples differed strongly with regard to subfamily composition (Fig. 3 (A)). Larentiinae comprised 68% of all individuals caught at the light tower, compared to only 44% in the traps (¥°=79.1; p<0.01; df=1). Conversely, the proportion of Ennominae specimens was 30% at the tower and 51% in the traps (y?=62.8; p<0.01; df=1). Geometrinae JOURNAL OF THE LEPIDOPTERISTS’ SOCIETY accounted for a slightly higher proportion in the traps than at the tower, while Sterrhinae occurred rarely at the light tower as well as in the traps. Desmobathrinae (overall very rare on the study sites) were never caught in the traps. When comparing the number of species belonging to different subfamilies (Fig. 3 (B)), the differences were much less pronounced. Larentiinae in both cases accounted for slightly more than half of the species, while Ennominae had a higher proportion in the traps, and there were proportionally more species of Geometrinae encountered at the light towers. Two species of Larentiinae (Mimoclystia corticearia Aurivillius and Chloroclystis derasata Bastelberger) and the Ennomine Darisodes oritropha Fletcher were the three most dominant species at the light towers. These species were also among the four most dominant species in the traps, but they accounted for smaller proportions in the traps (17%, 10% and 9% respectively), than in the manual catches (26%, 9% and 20% respectively). In the trap catches, the Ennominae Rhodophthitus — arichannaria Fletcher reached abundance rank two (44 individuals) whereas it was rarely encountered at light towers (12 individuals, rank 20). Within-habitat diversity. Values of Fisher's alpha for different habitats differed significantly for both sampling methods, but the trends diverged strongly relative to the sampling method (Fig. 4). On clearings, samples attained at light towers showed the highest values for Fisher's alpha, whereas trap samples had the lowest values of all habitats investigated. Diversity was intermediate in secondary forest for both methods and peaked in mature forest when evaluated with light traps, while there was an overall decrease in diversity from clearings across secondary forest to mature Rorzest for the catches at light towers. Species composition. Ordinations using CNESS distances were performed for three different values of the sample size parameter m (Fig. 5). There is a general division between trap samples from secondary forest and clearings, and the remaining samples along the first dimension. Only trap catches in mature forest show a stronger similarity with the respective tower catches. This dissimilarity increases with an increasing sample size parameter m. The stress value of the ordinations as a measure of goodness of fit was <<0.01 in all cases, indicating that the ordinations precisely depict the original dissimilarity matrices. DISCUSSION Comparisons of samples attained with sampling at light towers and with light traps show that there are selboterntiall differences in “abunaanes and composition of VOLUME 58, NUMBER 4 199 TABLE 1: Average number of Geometridae individuals, species, and individuals per catch recorded by nightly automatic light trap catches and manual 3 h catches in the different habitat types on Mt. Kilimanjaro, Tanzania. Individuals per Light trap Catches Individuals Species ‘styl *aATCh clearing 29 139 19 4.79 secondary forest 26 102 27 3.92 mature forest 39 131 33 3.45 all habitats 94 372 49 3.96 ¢ < oF re Si Individuals per Light tower Catches Individuals Species catch clearing 29, 534 72 9A.O7 secondary forest 16 578 71 36.13 mature forest 1] 1011 50 91.91 all habitats 49 9123 109 43.33 A 1% 1% 3% 2% 44% Individuals caught at the light tower Individuals caught in the light trap 1% 6% 54% Species caught at the light tower Species caught in the light trap @Larentiinae @Ennominae ~Geometrinae gmSterrhinae ~Desmobathrinae Fic. 3: Comparison of sampling methods with regard to subfamily spectra of (A) individuals and (B) species. 200 X light tower : A automatic light trap Fisher's alpha i Clearing secondary forest mature forest Fic. 4: Values of Fisher's alpha for the different habitats attained with light traps and at light towers. Whiskers show the 95% confidence interval. Pooled sample sizes exceed 100 individuals for each habitat. such catches, even when identical light sources are used in the same habitats. Manual samples taken at light towers over 3 h intervals were on average ten times larger than automatic trap samples assembled over 11 h. Overall, diversity and abundance of geometrid moths on Mt. Kilimanjaro is very low in comparison to other tropical forest ecosystems (Axmacher et al. 1994, in press). Nevertheless, the same tendency is obvious in other geographical regions. In Southeast Asia, light trap catches - mostly employing powerful types of lamps (125-250 W) - ranged from 10 to 31 geometrid moths per night (Barlow & Woiwod 1989, Intachat et al. 1997, Intachat & Woiwod 1999, Intachat & Holloway 2000). Trap catches in Australian tropical rainforest (8 W lamp) yielded an even lower average of only 6 geometrid moths per night (Kitching et al. 2000), which is in the same range as the catches on Mt. Kilimanjaro. In contrast, at light towers equipped with the same weak type of blacklight lamp as employed on Mt. Kilimanjaro, an average of 34 geometrid moths were caught on Borneo during 2 2.5 im nightly sampling periods (Beck et al. 2002). In the Ecuadorian Andes, the average number of geometrid individuals caught at light towers (with 2 x 15 W tubes) even exceeded 200 individuals during 3 h nightly catches (Brehm & Fiedler 2003). Quantitative samples from temperate regions reveal the same differences. Here, the number of individuals caught in traps varies from less than 5 to 27 (Usher & Keiller 1998, Ricketts et al. 2002, Thomas 2002), whereas at light towers, an average of 50 geometrid moths were caught during h sampling periods (Miihlenberg 1999). It can therefore be concluded that manual catches using light towers, albeit more laborious, generally result in a higher number of specimens caught per unit time than comparable light traps. In our study, the number of moths arriving on the gauze of the tower decreased strongly after 2100 h. It is JOURNAL OF THE LEPIDOPTERISTS’ SOCIETY A. 1 Stress: 0,004 N < 2 wo c ® a= a 2 A tt) 1 2 Dimension 1 B. 1 TrMF Stress: 0.004 N c ‘2 7) i