, Volume 32, Issue 2, pp 379–389 | Cite as

Estimating Occupancy in Large Landscapes: Evaluation of Amphibian Monitoring in the Greater Yellowstone Ecosystem

  • William R. Gould
  • Debra A. Patla
  • Rob Daley
  • Paul Stephen Corn
  • Blake R. Hossack
  • Robert Bennetts
  • Charles R. Peterson


Monitoring of natural resources is crucial to ecosystem conservation, and yet it can pose many challenges. Annual surveys for amphibian breeding occupancy were conducted in Yellowstone and Grand Teton National Parks over a 4-year period (2006–2009) at two scales: catchments (portions of watersheds) and individual wetland sites. Catchments were selected in a stratified random sample with habitat quality and ease of access serving as strata. All known wetland sites with suitable habitat were surveyed within selected catchments. Changes in breeding occurrence of tiger salamanders, boreal chorus frogs, and Columbia-spotted frogs were assessed using multi-season occupancy estimation. Numerous a priori models were considered within an information theoretic framework including those with catchment and site-level covariates. Habitat quality was the most important predictor of occupancy. Boreal chorus frogs demonstrated the greatest increase in breeding occupancy at the catchment level. Larger changes for all 3 species were detected at the finer site-level scale. Connectivity of sites explained occupancy rates more than other covariates, and may improve understanding of the dynamic processes occurring among wetlands within this ecosystem. Our results suggest monitoring occupancy at two spatial scales within large study areas is feasible and informative.


Colonization Conservation Detection Extinction Trend Wetlands 

Supplementary material

13157_2012_273_MOESM1_ESM.pdf (367 kb)
ESM 1(PDF 367 kb)


  1. Adams MJ, Pearl CA, Galvan S, McCreary B (2011) Non-native species impacts on pond occupancy by an anuran. Journal of Wildlife Management 75:30–35CrossRefGoogle Scholar
  2. Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov B, Czaki F (eds) Proceedings of the 2nd international symposium on information theory. Akademiai Kiado, Budapest, pp 267–281Google Scholar
  3. Bailey LL, Nichols JD (2009) Capture-mark-recapture, removal, and occupancy models. In: Dodd CK Jr (ed) Amphibian ecology and conservation: a handbook of techniques. Oxford University Press, New York, pp 447–463Google Scholar
  4. Burnham KP, Anderson DR (2002) Model selection and inference: a practical information-theoretic approach, 2nd edn. Springer, New YorkGoogle Scholar
  5. Bury BB, Corn PS, Dodd DK, McDiamid RW, Scott NJ (1995) Amphibians. In: Laroe ET, Farris GS, Pucket CE, Dorna PD, Mac MJ (eds) Our living resources: a report to the Nation on the distribution, abundance, and health of US plants, animals, and ecosystems. US Department of Interior, Washington, DC, pp 124–126Google Scholar
  6. Church DR (2008) Role of current versus historical hydrology in amphibian species turnover within local pond communities. Copeia 2008:115–125CrossRefGoogle Scholar
  7. Corn PS (2007) Amphibians and disease: implications for conservation in the Greater Yellowstone Ecosystem. Yellowstone Science 15:11–16Google Scholar
  8. Corn PS, Hossack BR, Muths E, Patla DA, Peterson CR, Gallant AL (2005a) Status of amphibians on the Continental Divide: surveys on a transect from Montana to Colorado, USA. Alytes 22:85–94Google Scholar
  9. Corn PS, Muths E, Adams MJ, Dodd CK (2005b) The United States geological survey’s amphibian research and monitoring initiative. Alytes 22:65–71Google Scholar
  10. Cowardin LM, Carter V, Golet FC, Laroe ET (1979) Classification of wetlands and deepwater habitats of the United States, U.S. Fish and Wildlife Service, Washington, DC.Google Scholar
  11. Crump ML, Scott NS Jr (1994) Visual encounter surveys. In: Heyer WR, Donnelly MA, McDiarmid RW, Hayek LAC, Foster MS (eds) Measuring and monitoring biological diversity: standard methods for amphibians. Smithsonian Institution Press, Washington, DC, pp 84–92Google Scholar
  12. Despain DG (1990) Yellowstone vegetation: consequences of environment and history in a natural setting. Roberts Rinehart, BoulderGoogle Scholar
  13. Drost CA, Fellers GM (1996) Collapse of a regional frog fauna in the Yosemite area of the California Sierra Nevada, USA. Conservation Biology 10:414–425CrossRefGoogle Scholar
  14. Elliott CR, Hektner MM (2000) Wetland resources of Yellowstone National Park. United States Fish and Wildlife Service, Yellowstone National Park, Wyoming, p 32Google Scholar
  15. Fancy SG, Gross JE, Carter SL (2009) Monitoring the condition of natural resources in US National Parks. Environmental Monitoring and Assessment 151:161–174PubMedCrossRefGoogle Scholar
  16. Gorman TA, Haas CA, Bishop DC (2009) Factors related to occupancy of breeding wetlands by flatwoods salamander larvae. Wetlands 29:323–329CrossRefGoogle Scholar
  17. Green DM (1997) Perspectives on amphibian population declines: defining the problem and searching for answers. In: Green GM (ed). Herpetological conservation, Vol. I: amphibians in decline. Canadian studies of a global problem, Society for the Study of Amphibians and Reptiles, St. Louis, pp 291–308Google Scholar
  18. Green DM (2005) Designatable units for status assessment of endangered species. Conservation Biology 19:1813–1820CrossRefGoogle Scholar
  19. Hamer AJ, Mahoney MJ (2010) Rapid turnover in site occupancy of a pond-breeding frog demonstrates the need for landscape-level management. Wetlands 30:287–299CrossRefGoogle Scholar
  20. Hanski I (1998) Metapopulation dynamics. Nature 396:41–49CrossRefGoogle Scholar
  21. Hartel T, Ollerer K (2009) Local turnover and factors influencing the persistence of amphibians in permanent ponds from the Saxon landscapes of Transylvania. Northwestern Journal of Zoology 5:40–52Google Scholar
  22. Hossack BR, Corn PS (2007) Responses of pond-breeding amphibians to wildfire: short-term patterns in occupancy and colonization. Ecological Applications 17:1403–1410PubMedCrossRefGoogle Scholar
  23. Koch ED, Peterson CR (1995) Amphibian and reptiles of Yellowstone and Grand Teton National Parks. University of Utah Press, Salt Lake CityGoogle Scholar
  24. MacArthur RH, Wilson EO (1967) The theory of island biogeography. Princeton University Press, PrincetonGoogle Scholar
  25. 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 83:2248–2255CrossRefGoogle Scholar
  26. MacKenzie DI, Nichols JD, Hines JE, Knutson MG, Franklin AD (2003) Estimating site occupancy, colonization and local extinction when a species is detected imperfectly. Ecology 84:2200–2207CrossRefGoogle Scholar
  27. MacKenzie DI, Nichols JD, Royle JA, Pollock KH, Bailey LL, Hines JE (2006) Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic, San DiegoGoogle Scholar
  28. Mazerolle MJ, Bailey LL, Kendall WL, Royle JA, Converse SJ, Nichols JD (2007) Making great leaps: accounting for detectability in herpetological field studies. Journal of Herpetology 41:672–689CrossRefGoogle Scholar
  29. McMenamin SK, Hadly EA, Wright CK (2008) Climatic change and wetland desiccation cause amphibian decline in Yellowstone National Park. Proceedings of the National Academy of Sciences (USA) 105:16988–16993CrossRefGoogle Scholar
  30. Muths E, Corn PS, Pessier AP, Green DE (2003) Evidence for disease related amphibian decline in Colorado. Biological Conservation 110:357–365CrossRefGoogle Scholar
  31. Noss RF, Carroll C, Vance-Borland K, Wuerthner G (2002) A multicriteria assessment of the irreplaceability and vulnerability of sites in the Greater Yellowstone Ecosystem. Conservation Biology 16:895–908CrossRefGoogle Scholar
  32. Patla DA, Peterson CR, Corn PS (2009) Amphibian decline in Yellowstone National Park. Proceedings of the National Academy of Sciences (USA) 106(9):E22CrossRefGoogle Scholar
  33. Pechmann JHK, Wilbur HM (1994) Putting declining amphibian populations in perspective: natural fluctuations and human impacts. Herpetologica 60:55–84Google Scholar
  34. Pederson GT, Gray ST, Woodhouse CA, Betancourt JL, Fagre DB, Littell JS, Watson E, Luckman BH, Graumlich LJ (2011) The unusual nature of recent snowpack declines in the North American Cordillera. Science 333:332–335PubMedCrossRefGoogle Scholar
  35. Petranka JW, Smith CK, Scott AF (2004) Identifying the minimal demographic unit for monitoring pond-breeding amphibians. Ecological Applications 14:1065–1078CrossRefGoogle Scholar
  36. Prugh LR, Hodges KE, Sinclair ARE, Brashares JS (2009) Effect of habitat area and isolation on fragmented animal populations. Proceedings of the National Academy of Sciences (USA) 105:20770–20775CrossRefGoogle Scholar
  37. Schmidt BR (2005) Monitoring the distribution of pond-breeding amphibians when species are detected imperfectly. Aquatic Conservation of Marine and Freshwater Ecosystems 15:681–692CrossRefGoogle Scholar
  38. Stebbins RC, Cohen NW (1995) A natural history of amphibians. Princeton University Press, PrincetonGoogle Scholar
  39. Stuart SN, Chanson JS, Cox NA, Young BE, Rodrigues ASL, Fischman DL, Waller RW (2004) Status and trends of amphibian declines and extinctions worldwide. Science 306:1783–1786PubMedCrossRefGoogle Scholar
  40. Thompson SK (1992) Sampling. Wiley, New YorkGoogle Scholar
  41. Thoms C, Corkran CC, Olson DH (1997) Basic amphibian survey for inventory and monitoring in lentic habitats. In: Olson DH, Leonard WP, Bury RB (eds) Sampling amphibians in lentic habitats. Northwest Fauna 4, Society for Northwestern Vertebrate Biology, Olympia, pp 35–46Google Scholar
  42. Van Buskirk J (2005) Local and landscape influence on amphibian occurrence and abundance. Ecology 86:1936–1947CrossRefGoogle Scholar
  43. Vredenburg VT, Knapp RA, Tunstall TS, Briggs CJ (2010) Dynamics of an emerging disease drive large-scale amphibian population extinctions. Proceedings of the National Academy of Sciences (USA) 107:9689–9694CrossRefGoogle Scholar
  44. Werner EE, Yurewicz KL, Skelly DK, Relyea RA (2007) Turnover in an amphibian metacommunity: the role of local and regional factors. Oikos 116:1713–1725CrossRefGoogle Scholar
  45. Werner EE, Relyea RA, Yurewicz KL, Skelly DK, Davis CJ (2009) Comparative landscape dynamics of two anuran species: climate-driven interaction of local and regional processes. Ecological Monographs 79:503–521CrossRefGoogle Scholar
  46. White GC, Burnham KP (1999) Program MARK: survival estimation from populations of marked animals. Bird Study 46 Supplement:120–138CrossRefGoogle Scholar
  47. Wright C, Gallant A (2007) Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data. Remote Sensing of the Environment 107:582–60CrossRefGoogle Scholar

Copyright information

© US Government 2012

Authors and Affiliations

  • William R. Gould
    • 1
  • Debra A. Patla
    • 2
  • Rob Daley
    • 3
  • Paul Stephen Corn
    • 4
  • Blake R. Hossack
    • 4
    • 5
  • Robert Bennetts
    • 3
  • Charles R. Peterson
    • 2
  1. 1.Applied Statistics ProgramNew Mexico State UniversityLas CrucesUSA
  2. 2.Department of Biological SciencesIdaho State UniversityPocatelloUSA
  3. 3.National Park Service, Greater Yellowstone NetworkBozemanUSA
  4. 4.U.S. Geological Survey, Northern Rocky Mountain Science CenterAldo Leopold Wilderness Research InstituteMissoulaUSA
  5. 5.Wildlife Biology ProgramUniversity of MontanaMissoulaUSA

Personalised recommendations