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Optimal design of butterfly occupancy surveys and testing if occupancy converts to abundance for sparse populations

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Abstract

Occupancy has several important advantages over abundance methods and may be the best choice for monitoring sparse populations. Here we use simulations to evaluate competing designs (number of sites vs. number of surveys) for occupancy monitoring, with emphasis on sparse populations of the endangered Karner blue butterfly (Lycaeides melissa samuelis Nabokov). Because conservation planning is usually abundance-based, we also ask whether detection/non-detection data may reliably convert to abundance, hypothesizing that occupancy provides a more dependable shortcut when populations are sparse. Count-index and distance sampling were conducted across 50 habitat patches containing variably sparse Karner blue populations. We used occupancy-detection model estimates as simulation inputs to evaluate primary replication tradeoffs, and used peak counts and population densities to evaluate the occupancy-abundance relationship. Detection probability and therefore optimal design of occupancy monitoring was strongly temperature dependent. Assuming a quality threshold of 0.075 root-mean square error for the occupancy estimator, the minimum allowable effort was 360 (40 sites × 9 surveys) for spring generation and 200 (20 sites × 10 surveys) for summer generation. A mixture model abundance estimator for repeated detection/non-detection data was biased low for high-density and low-density populations, suggesting that occupancy may not provide a reliable shortcut in abundance-based conservation planning for sparse butterfly populations.

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References

  • Anderson DR (2001) The need to get the basics right in wildlife field studies. Wildlife Soc B 29:1294–1297

    Google Scholar 

  • Anderson DR (2003) Response to Engeman: index values rarely constitute reliable information. Wildlife Soc B 31:288–291

    Google Scholar 

  • Bailey LL, Simons TR, Pollock KH (2004) Estimating site occupancy and species detection probability parameters for terrestrial salamanders. Ecol Appl 14:692–702

    Article  Google Scholar 

  • Bailey LL, Hines JE, Nichols JD, MacKenzie DI (2007) Sampling design tradeoffs in occupancy studies with imperfect detection: examples and software. Ecol Appl 17:281–290

    Article  PubMed  Google Scholar 

  • Barnes JK (2003) Natural history of the Albany Pine Bush: Albany and Schenectady counties, New York. New York State Museum Bulletin #502, Albany, New York

  • Bart J, Droege S, Geissler P, Peterjohn B, Ralph CJ (2004) Density estimation in wildlife surveys. Wildlife Soc B 32:1242–1247

    Article  Google Scholar 

  • Bried JT (2009) Information costs of reduced-effort habitat monitoring in a butterfly recovery program. J Insect Conserv 13:615–626

    Article  Google Scholar 

  • Bried JT, Braun DP (2009) Restoration monitoring for Karner blue butterfly recovery in New York State. State Wildlife Grant Service Contract #C006028, Albany, New York

  • Bried JT, Langwig KE, DeWan AA, Gifford NA (2011) Habitat associations and survey effort for shrubland birds in an urban pine barrens preserve. Landscape Urban Plan 99:218–225

    Article  Google Scholar 

  • Brown JA, Boyce MS (1998) Line transect sampling of Karner blue butterflies (Lycaeides melissa samuelis). Environ Ecol Stat 5:81–91

    Article  Google Scholar 

  • Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2001) Introduction to distance sampling: estimating abundance of biological populations. Oxford University Press, Oxford

    Google Scholar 

  • Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach (revised edn). Springer, New York

    Google Scholar 

  • Collier N, MacKay DA, Benkendorff K (2008) Is relative abundance a good indicator of population size? Evidence from fragmented populations of a specialist butterfly (Lepidoptera: Lycaenidae). Popul Ecol 50:17–23

    Article  Google Scholar 

  • Cormont A, Malinowska AH, Kostenko O, Radchuk V, Hemerik L, Wallis-DeVries MF, Verboom J (2011) Effect of local weather on butterfly flight behavior, movement, and colonization: significance for dispersal under climate change. Biodivers Conserv 20:483–503

    Article  Google Scholar 

  • Dreitz VJ, Lukacs PM, Knopf FL (2006) Monitoring low density avian populations: an example using mountain plovers. Condor 108:700–706

    Article  Google Scholar 

  • Fuller SG (2008) Population dynamics of the endangered Karner blue butterfly (Lycaeides melissa samuelis Nabokov). Dissertation, State University of New York, College of Environmental Science and Forestry, Syracuse, New York

  • Gall LF (1984) The effects of capturing and marking on subsequent activity in Boloria acrocnema (Lepidoptera: Nymphalidae), with a comparison of different numerical models that estimate population size. Biol Conserv 28:139–154

    Article  Google Scholar 

  • Gaston KJ, Blackburn TM, Greenwood JJD, Gregory RD, Quinn RM, Lawton JH (2000) Abundance-occupancy relationships. J Appl Ecol 37:39–59

    Article  Google Scholar 

  • Gifford NA, O’Brien K (2010) Karner blue butterfly recovery plan for the Albany Pine Bush Meta-population Recovery Unit. Management Plan and Final Environmental Impact Statement for the Albany Pine Bush Preserve: Appendix D. Available at www.albanypinebush.org

  • Gross K, Kalendra EJ, Hudgens BR, Haddad NM (2007) Robustness and uncertainty in estimates of butterfly abundance from transect counts. Popul Ecol 49:191–200

    Article  Google Scholar 

  • Grundel R, Pavlovic NB (2007) Resource availability, matrix quality, microclimate, and spatial pattern as predictors of patch use by the Karner blue butterfly. Biol Conserv 135:135–144

    Article  Google Scholar 

  • Grundel R, Pavlovic NB, Sulzman CL (1998a) Habitat use by the endangered Karner blue butterfly in oak woodlands: the influence of canopy cover. Biol Conserv 85:47–53

    Article  Google Scholar 

  • Grundel R, Pavlovic NB, Sulzman CL (1998b) The effect of canopy cover and seasonal change on host plant quality for the endangered Karner blue butterfly (Lycaeides melissa samuelis). Oecologia 114:243–250

    Article  Google Scholar 

  • Guillera-Arroita G (2011) Impact of sampling with replacement in occupancy studies with spatial replication. Method Ecol Evol. doi:10.1111/j.2041-210X.2011.00089.x

  • Guillera-Arroita G, Ridout MS, Morgan BJT (2010) Design of occupancy studies with imperfect detection. Method Ecol Evol 1:131–139

    Article  Google Scholar 

  • Guiney MS, Andow DA, Wilder TT (2010) Metapopulation structure and dynamics of an endangered butterfly. Basic Appl Ecol 11:354–362

    Article  Google Scholar 

  • Haddad NM, Hudgens B, Damiani C, Gross K, Kuefler D, Pollock K (2008) Determining optimal population monitoring for rare butterflies. Conserv Biol 22:929–940

    Article  PubMed  Google Scholar 

  • Hanski IA, Gilpin ME (eds) (1997) Metapopulation biology: ecology, genetics, and evolution. Academic Press, San Diego

    Google Scholar 

  • Harker RJ, Shreeve TG (2008) How accurate are single site transect data for monitoring butterfly trends? Spatial and temporal issues identified in monitoring Lasiommata megera. J Insect Conserv 12:125–133

    Article  Google Scholar 

  • He F, Gaston KJ (2000) Estimating species abundance from occurrence. Am Nat 156:553–559

    Article  Google Scholar 

  • Hui C, McGeoch MA, Reyers B, Cle Roux P, Greve M, Chown SL (2009) Extrapolating population size from the occupancy-abundance relationship and the scaling pattern of occupancy. Ecol Appl 19:2038–2048

    Article  PubMed  Google Scholar 

  • Hwang W-H, He F (2011) Estimating abundance from presence/absence maps. Method Ecol Evol. doi:10.1111/j.2041-210X.2011.00105.x

  • Isaac NJB, Cruickshanks KL, Weddle AM, Rowcliffe JM, Brereton TM, Dennis RLH, Shuker DM, Thomas CD (2011) Distance sampling and the challenge of monitoring butterfly populations. Method Ecol Evol. doi:10.1111/j.2041-210X.2011.00109.x

  • Johnson DH (2008) In defense of indices: the case of bird surveys. J Wildlife Manage 72:857–868

    Google Scholar 

  • Joseph LN, Field SA, Wilcox C, Possingham HP (2006) Presence-absence versus abundance data for monitoring threatened species. Conserv Biol 20:1679–1687

    Article  PubMed  Google Scholar 

  • Joseph LN, Elkin C, Martin TG, Possingham HP (2009) Modeling abundance using N-mixture models: the importance of considering ecological mechanisms. Ecol Appl 19:631–642

    Article  PubMed  Google Scholar 

  • Kadlec T, Tropek R, Konvicka M (2011) Timed surveys and transect walks as comparable methods for monitoring butterflies in small plots. J Insect Conserv. doi:10.1007/s10841-011-9414-7

  • Knutson RL, Kwilosz JR, Grundel R (1999) Movement patterns and population characteristics of the Karner blue butterfly (Lycaeides melissa samuelis) at Indiana Dunes National Lakeshore. Nat Areas J 19:109–120

    Google Scholar 

  • Lane CP, Andow DA (2003) Oak savanna subhabitat variation and the population biology of Lycaeides melissa samuelis (Lepidoptera: Lycaenidae). Ann Entomol Soc Am 96:799–809

    Article  Google Scholar 

  • Longcore T, Lam CS, Kobernus P, Polk E, Wilson JP (2010) Extracting useful data from imperfect monitoring schemes: endangered butterflies at San Bruno Mountain, San Mateo County, California (1982–2000) and implications for habitat management. J Insect Conserv 14:335–346

    Article  Google Scholar 

  • Lopez JE, Pfister CA (2001) Local population dynamics in metapopulation models: implications for conservation. Conserv Biol 15:1700–1709

    Article  Google Scholar 

  • MacKenzie DI, Royle JA (2005) Designing occupancy studies: general advice and allocating survey effort. J Appl Ecol 42:1105–1114

    Article  Google Scholar 

  • MacKenzie DI, Nichols JD, Lachman GB, Droege S, Royle JA, Langtimm CA (2002) Estimating site occupancy rates when detection probabilities are less than one. Ecology 83:2248–2255

    Article  Google Scholar 

  • MacKenzie DI, Nichols JD, Hines JE, Knutson MG, Franklin AB (2003) Estimating site occupancy, colonization, and local extinction when a species is detected imperfectly. Ecology 84:2200–2207

    Article  Google Scholar 

  • MacKenzie DI, Nichols JD, Royle JA, Pollock KH, Bailey LL, Hines JE (2006) Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Elsevier, Burlington

    Google Scholar 

  • Marsh DM, Trenham PC (2008) Current trends in plant and animal population monitoring. Conserv Biol 22:647–655

    Article  PubMed  Google Scholar 

  • Mattoni R, Longcore T, Zonneveld C, Novotny V (2001) Analysis of transect counts to monitor population size in endangered insects. J Insect Conserv 5:197–206

    Article  Google Scholar 

  • Murphy DD (1987) Are we studying our endangered butterflies to death? J Res Lepidoptera 26:236–239

    Google Scholar 

  • Nowicki P, Richter A, Glinka U, Holzschuh A, Toelke U, Henle K, Woyciechowski M, Settele J (2005) Less input same output: simplified approach for population size assessment in Lepidoptera. Popul Ecol 47:203–212

    Article  Google Scholar 

  • Nowicki P, Settele J, Henry P-Y, Woyciechowski M (2008) Butterfly monitoring methods: the ideal and the real world. Israel J Ecol Evol 54:69–88

    Article  Google Scholar 

  • Parietti D (2009) Optimal monitoring strategy for endangered short-lived butterflies. Thesis, University of Lausanne, Switzerland

  • Pellet J (2008) Seasonal variation in detectability of butterflies surveyed with Pollard walks. J Insect Conserv 12:155–162

    Article  Google Scholar 

  • Pellet J, Fleishman E, Dobkin DS, Gander A, Murphy DD (2007) An empirical evaluation of the area and isolation paradigm of metapopulation dynamics. Biol Conserv 136:483–495

    Article  Google Scholar 

  • Pickens BA (2007) Understanding the population dynamics of a rare, polyvoltine butterfly. J Zool 273:229–236

    Article  Google Scholar 

  • Pickens BA, Root KV (2008) Factors affecting host-plant quality and nectar use for the Karner blue butterfly: implications for oak savanna restoration. Nat Areas J 28:210–217

    Article  Google Scholar 

  • Pickens BA, Root KV (2009) Behavior as a tool for assessing a managed landscape: a case study of the Karner blue butterfly. Landscape Ecol 24:243–251

    Article  Google Scholar 

  • Pocewicz A, Morgan P, Eigenbrode SD (2010) Local and landscape effects on butterfly density in northern Idaho grasslands and forests. J Insect Conserv 13:593–601

    Article  Google Scholar 

  • Pollard E, Yates TJ (1993) Monitoring butterflies for ecology and conservation. Chapman and Hall, London

    Google Scholar 

  • Pollard E, van Swaay CAM, Yates TJ (1993) Changes in butterfly numbers in Britain and the Netherlands, 1990–91. Ecol Entomol 18:93–94

    Article  Google Scholar 

  • Pollock JF (2006) Detecting population declines over large areas with presence-absence, time-to-encounter, and count survey methods. Conserv Biol 20:882–892

    Article  PubMed  Google Scholar 

  • Powell AFLA, Busby WH, Kindscher K (2007) Status of the regal fritillary (Speyeria idalia) and effects of fire management on its abundance in northeastern Kansas, USA. J Insect Conserv 11:299–308

    Article  Google Scholar 

  • Roy DB, Rothery P, Brereton T (2007) Reduced-effort schemes for monitoring butterfly populations. J Appl Ecol 44:993–1000

    Article  Google Scholar 

  • Royle JA, Nichols JD (2003) Estimating abundance from repeated presence-absence data or point counts. Ecology 84:777–790

    Article  Google Scholar 

  • Singer MC, Wedlake P (1981) Capture does affect probability of recapture in a butterfly species. Ecol Entomol 6:215–216

    Article  Google Scholar 

  • Strayer DL (1999) Statistical power of presence-absence data to detect population declines. Conserv Biol 13:1034–1038

    Article  Google Scholar 

  • Thomas JA (2005) Monitoring change in the abundance and distribution of insects using butterflies and other indicator groups. Philos Trans R Soc B 360:339–357

    Article  CAS  Google Scholar 

  • Thomas L, Buckland ST, Rexstad EA, Laake JL, Strindberg S, Hedley SL, Bishop JRB, Marques TA, Burnham KP (2010) Distance software: design and analysis of distance sampling surveys for estimating population size. J Appl Ecol 47:5–14

    Article  PubMed  Google Scholar 

  • [USFWS] U.S. Fish, Wildlife Service (2003) Final recovery plan for the Karner blue butterfly (Lycaeides melissa samuelis). U.S. Fish & Wildlife Service, Fort Snelling

    Google Scholar 

  • van Strien AJ, de Pavert RV, Moss D, Yates TJ, van Swaay CAM, Vos P (1997) The statistical power of two butterfly monitoring schemes to detect trends. J Appl Ecol 34:817–828

    Article  Google Scholar 

  • van Swaay CAM, Nowicki P, Settele J, van Strien AJ (2008) Butterfly monitoring in Europe: methods, applications and perspectives. Biodivers Conserv 17:3455–3469

    Article  Google Scholar 

  • Webb L (2010) Propagation handbook for the Karner blue butterfly, Lycaeides melissa samuelis, 1st edn. New Hampshire Fish and Game Department. Nongame Endangered Wildlife Program, Concord

    Google Scholar 

  • Wenger SJ, Freeman MC (2008) Estimating species occurrence, abundance, and detection probability using zero-inflated distributions. Ecology 89:2953–2959

    Article  PubMed  Google Scholar 

  • Wikstrom L, Milberg P, Bergman KO (2009) Monitoring butterflies in semi-natural grasslands: diurnal variation and weather effects. J Insect Conserv 13:203–211

    Article  Google Scholar 

  • Yoccoz NG, Nichols JD, Boulinier T (2001) Monitoring of biological diversity in space and time. Trends Ecol Evol 16:446–453

    Article  Google Scholar 

  • Zhou S, Griffiths SP (2007) Estimating abundance from detection-nondetection data for randomly distributed or aggregated elusive populations. Ecography 30:537–549

    Google Scholar 

  • Zonneveld C (1991) Estimating death rates from transect counts. Ecol Entomol 16:115–121

    Article  Google Scholar 

  • Zonneveld C, Longcore T, Mulder C (2003) Optimal schemes to detect the presence of insect species. Conserv Biol 17:476–487

    Article  Google Scholar 

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Acknowledgments

This project was enabled by the Environmental Protection Fund, New York State Department of Environmental Conservation. Stephen Bence, Beth Cooper, Amanda Dillon, Brandon Ferns, Garrett Grilli, Ashley Rathman, and Joanna Thompson conducted the butterfly surveys, and Amielle DeWan, Rebecca Shirer, and several anonymous reviewers offered valuable comments on earlier versions of the manuscript.

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  1. Albany Pine Bush Preserve Commission, 195 New Karner Road, Albany, NY, 12205-4605, USA

    Jason T. Bried

  2. A. Maibach Sàrl, CP 99, Ch. de la Poya 10, 1610, Oron-la-Ville, Switzerland

    Jérôme Pellet

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  1. Jason T. Bried
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Correspondence to Jason T. Bried.

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Bried, J.T., Pellet, J. Optimal design of butterfly occupancy surveys and testing if occupancy converts to abundance for sparse populations. J Insect Conserv 16, 489–499 (2012). https://doi.org/10.1007/s10841-011-9435-2

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