Skip to main content

Advertisement

Log in

Abundance estimates to inform butterfly management: double-observer versus distance sampling

  • ORIGINAL PAPER
  • Published:
Journal of Insect Conservation Aims and scope Submit manuscript

Abstract

Abundance estimates are used to establish baselines, set recovery targets, and assess management actions, all of which are essential aspects of evidence-based natural resource management. For many rare butterflies, these estimates do not exist, and conservation decisions rely instead on expert opinion. Using Bartram’s scrub-hairstreak (Strymon acis bartrami, US Endangered) as a case study, we present a novel comparison of two methods that permit the incorporation of detection probabilities into abundance estimates, distance sampling and double-observer surveys. Additionally we provide a framework for establishing a systematic sampling scheme for monitoring very rare butterflies. We surveyed butterflies monthly in 2013, increasing intensity to weekly when butterflies were detected. We conducted 19 complete, island-wide surveys on Big Pine Key in the Florida Keys, detecting a total of 59 Bartram’s scrub-hairstreaks across all surveys. Peak daily abundances were similar as estimated with distance sampling, 156 butterflies (95 % CI 65–247), and double-observer, 169 butterflies (95 % CI 65–269). Selecting a method for estimating abundance of rare species involves evaluating trade-offs between methods. Distance sampling requires at least 40 detections, but only one observer, while double-observer requires only 10 detections, but two observers. Double-observer abundance estimates agreed with distance sampling estimates, which suggests that double-observer is a reasonable alternative method to use for estimating detection probability and abundance for rare species that cannot be surveyed with other, more commonly used methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  • Abbitt RJF, Scott JM (2001) Examining differences between recovered and declining endangered species. Conserv Biol 15:1274–1284

    Article  Google Scholar 

  • Alexander TR (1967) A tropical hardwood hammock on the Miami (Florida) limestone—a twenty five year study. Ecology 48:863–867

    Article  Google Scholar 

  • Alexander TR, Dickson JH III (1972) Vegetational changes in the NKDR II. Q J Fla Acad Sci 35:85–96

    Google Scholar 

  • Alldredge MW, Pollock KH, Simons TR (2006) Estimating detection probabilities from multiple-observer counts. Auk 123:1172–1182

    Google Scholar 

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

    Google Scholar 

  • Anderson CT, Henry EH (2014) Synthesis of research, monitoring, management of the Bartram’s Hairstreak in the National Key Deer Refuge 2009–2014. Report to U.S. Fish and Wildlife Service, Florida Keys Refuges Complex, Big Pine Key

  • Baggett HD (1982) Order Lepidoptera. In: Deyrup M, Franz R (eds) Rare and endangered biota of Florida: Invertebrates, vol 4. University Press of Florida, Gainesville, pp 78–81

    Google Scholar 

  • Bradley KA, Saha S (2009) Post-hurricane responses of rare plant species and vegetation of pine rocklands in the lower Florida Keys. Institute for Regional Conservation, Miami

    Google Scholar 

  • Bried JT, Pellet J (2012) Optimal design of butterfly occupancy surveys and testing if occupancy converts to abundance for sparse populations. J Insect Conserv 16:489–499

    Article  Google Scholar 

  • Bried JT, Murtaugh JE, Dillon AM (2012) Local distribution factors and sampling effort guidelines for the rare frosted elfin butterfly. Northeast Nat 19:673–684

    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 

  • Calabrese JM (2012) How emergence and death assumptions affect count-based estimates of butterfly abundance and lifespan. Popul Ecol 54:431–442

    Article  Google Scholar 

  • Carlson PC, Tanner GW, Wood JM, Humphrey SR (1993) Fires in Key deer habitat improves browse, prevents succession, and preserves endemic herbs. J Wildl Manag 57:914–928

    Article  Google Scholar 

  • Cayton H, Haddad NM, Gross K, Diamond SE, Ries L (2015) Do growing degree days predict phenology across butterfly species? Ecology 96:1473–1479

    Article  Google Scholar 

  • Clark JA, Hoekstra JM, Boersma PD, Kareiva P (2002) Improving US Endangered Species Act recovery plans: key findings and recommendations of the SCB recovery plan project. Conserv Biol 16:1510–1519

    Article  Google Scholar 

  • Dennis RLH, Shreeve TG, Van Dyck H (2003) Towards a functional resource-based concept for habitat: a butterfly biology viewpoint. Oikos 102:417–426

    Article  Google Scholar 

  • Dickson JD (1955) An ecological study of the Key deer. Technical bulletin of the Florida Game and Fresh Water Fish Commission, Pittman–Robertson Projects

  • Ehrlich PR, Davidson SE (1960) Techniques for capture-recapture studies of Lepidoptera populations. J Lepidopterists Soc 14:227–229

    Google Scholar 

  • Emmel TC, Worth RA, Schwarz K (1995) The relationships between host plant and habitat for the distribution of three potentially endangered south Florida butterfly species. Report to the National Biological Survey

  • Fiske I, Chandler R (2011) Unmarked: an R package for fitting hierarchical models of wildlife occurrence and abundance. J Stat Softw 43:1–23

    Article  Google Scholar 

  • Folk ML (1992) Habitat of the Key deer. Dissertation, Southern Illinois University at Carbondale

  • Franco AMA, Hill JK, Kitschke C, Collingham YC, Roy DB, Fox R, Huntley B, Thomas CD (2006) Impacts of climate warming and habitat loss on extinctions at species’ low-latitude range boundaries. Glob Change Biol 12:1545–1553

    Article  Google Scholar 

  • Ganey JL, White GC, Bowden DC, Franklin AB (2004) Evaluating methods for monitoring populations of Mexican spotted owls: a case study. In: Thompson WL (ed) Sampling rare or elusive species: concepts, designs, and techniques for estimating population parameters. Island Press, Washington, pp 337–385

    Google Scholar 

  • Gerber LR, Hatch LT (2002) Are we recovering? An evaluation of recovery criteria under the US Endangered Species Act. Ecol Appl 12:668–673

    Article  Google Scholar 

  • Grundel R (2015) A guide to the use of distance sampling to estimate abundance of Karner blue butterflies. U.S. Geological Survey, Great Lakes Science Center, Porter

  • 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 

  • Hamm CA (2013) Estimating abundance of the federally endangered Mitchell’s satyr butterfly using hierarchical distance sampling. Insect Conserv Divers 6:619–626

    Article  Google Scholar 

  • Harker RJ, Shreeve TJ (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 

  • Harley GL (2012) Tree growth dynamics, fire history, and fire-climate relationships in pine rocklands of the Florida Keys, USA. Disseration, University of Tennessee

  • Hennessey MK, Nigg HN, Habeck DH (1992) Mosquito (Diptera: Culicidae) adulticide drift into wildlife refuges of the Florida Keys. Environ Entomol 21:714–721

    Article  Google Scholar 

  • Henry EH, Haddad NM, Wilson J, Hughes P, Gardner B (2015) Point transect methods to monitor butterfly populations when traditional methods fail: a case study with Miami blue butterfly. J Insect Conserv 19:519–529

    Article  Google Scholar 

  • Hicks TL (2011) Monitoring and estimating Fender’s blue butterfly (Icaricia icarioides fenderi) populations. Unpublished report (January 2011). Washington State University, Vancouver

  • Issac 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. Methods Ecol Evol 2:585–594

    Article  Google Scholar 

  • Johnson DH (2008) In defense of indicies: the case of bird surveys. Wildl Manag 72:857–868

    Article  Google Scholar 

  • Kerry M, Royle JA (2016) Applied Hierarchical Modeling in Ecology: analysis of distribution, abundance and species richness in R and BUGS, vol 1. Academic Press, London

    Google Scholar 

  • Menendez R, González-Megías A, Hill JK, Braschler B, Willis SG, Collingham Y, Fox R, Roy DB, Thomas CD (2007) Species richness changes lag behind climate change. Proc R Soc Lond B Biol Sci 273:1465–1470

    Article  Google Scholar 

  • Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63:81–97

    Article  CAS  PubMed  Google Scholar 

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

    Google Scholar 

  • Nichols JD, Hines JE, Sauer JR, Fallon FW, Fallon JE, Heglund PJ (2000) A double-observer approach for estimating detection probability and abundance from point counts. Auk 117:393–408

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Oliver TH, Marshall HH, Morecroft MD, Brereton T, Prudhomme C, Huntingford C (2015) Interacting effects of climate change and habitat fragmentation on drought-sensitive butterflies. Nat Clim Change 5:941–945

    Article  Google Scholar 

  • Pfitsch WA, Williams EH (2009) Habitat restoration for lupine and specialist butterflies. Restor Ecol 17:226–233

    Article  Google Scholar 

  • Pollard E, Yates TJ (1993) Monitoring butterflies for ecology and conservation: the British butterfly monitoring scheme. Chapman and Hall, London

    Google Scholar 

  • Salvato MH (1999) Factors influencing the declining populations of three threatened butterflies in south Florida and the Florida Keys. Master’s Thesis, University of Florida

  • Salvato MH (2003) Butterfly conservation and hostplant fluctuations: the relationship between Strymon acis bartrami and Anaea troglodyta foridalis on Croton linearis in Florida (Lepidtoptera: Lycaenidae and Nymphalidae). Holarct Lepidoptera 8:53–75

    Google Scholar 

  • Salvato MH, Hennessey MK (2004) Notes on the status and fire-related ecology of Strymon acis bartrami. J Lepidopterists Soc 58:223–227

    Google Scholar 

  • Salvato MH, Salvato HL (2010) Notes on the Status and Ecology of Strymon acis bartrami (Lycaenidae) in Everglades National Park. J Lepidopterists Soc 64:154–160

    Article  Google Scholar 

  • Schultz CB, Hammond PC (2003) Using population viability analysis to develop recovery criteria for endangered insects: case study of the Fender’s blue butterfly. Conserv Biol 17:1372–1385

    Article  Google Scholar 

  • Schwartz A (1987) The butterflies of the Lower Florida Keys. Milwaukee Public Museum, Contributions in Biology and Geology vol 73, pp 1–34

  • Simons TR, Alldredge MW, Pollock KH et al (2007) Experimental analysis of the auditory detection process on avian point counts. Auk 124:986–999

    Article  Google Scholar 

  • Smith DS, Miller LD, Miller JY (1994) The butterflies of the West Indies and South Florida. Oxford University Press, New York

    Google Scholar 

  • Thomas JA (1983) A quick method for estimating butterfly numbers during surveys. Biol Conserv 27:195–211

    Article  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  • U.S. Fish and Wildlife Service (2013) Endangered and Threatened Wildlife and Plants; Threatened Status for Dakota Skipper and Endangered Status for Powesheik Skipperling; Proposed Rule. Federal Register vol 78, pp 63574–63625

  • U.S. Fish and Wildlife Service (2014a) Endangered and Threatened Wildlife and Plants; Designation of Critical Habitat for the Florida Leafwing and Bartram’s Scrub-Hairstreak Butterflies; Final Rule. Federal Register vol 79, pp 47179–47220

  • U.S. Fish and Wildlife Service (2014b) Endangered and Threatened Wildlife and Plants; Endangered Status for the Florida Leafwing and Bartram’s Scrub-Hairstreak Butterflies; Final Rule. Federal Register vol 79, pp 47221–47244

  • Williams BK, Nichols JD, Conroy MJ (2002) Analysis and management of animal populations. Academic Press, Waltham

    Google Scholar 

  • Worth RA, Schwarz KA, Emmel TC (1996) Notes on the biology of Strymon acis bartrami and Anaea troglodyta floridalis in south Florida. Holarct Lepidoptera 3:62–65

    Google Scholar 

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

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank the U.S. Fish and Wildlife Service and North Carolina State University for making this study possible. We thank Nick Haddad, Mike Cove, Tyson Wepprich, Anne Morkill, Mark Salvato, Jennifer Anderson, Phillip Hughes and Nancy Finley for thoughtful comments, support, and guidance in the formation and implementation of the project. This work benefited from the field assistance of Camille Knight, Jessica Padilla, and Kate Cardenas. We also thank two anonymous reviewers for constructive comments. Use of trade, product, or firm names does not imply endorsement by the United States Government. The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the U.S. Fish and Wildlife Service.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Erica H. Henry.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Henry, E.H., Anderson, C.T. Abundance estimates to inform butterfly management: double-observer versus distance sampling. J Insect Conserv 20, 505–514 (2016). https://doi.org/10.1007/s10841-016-9883-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10841-016-9883-9

Keywords