Inference for Occupancy and Occupancy Dynamics

  • Allan F. O’Connell
  • Larissa L. Bailey


This chapter deals with the estimation of occupancy as a state variable to assess the status of, and track changes in, species distributions when sampling with camera traps. Much of the recent interest in occupancy estimation and modeling originated from the models developed by MacKenzie et al. (2002, 2003), although similar methods were developed independently (Azuma et al. 1990; Bayley and Petersen 2001; Nichols and Karanth, 2002; Tyre et al. 2003), all of which deal with species occurrence information and imperfect detection. Less than a decade after these publications, the modeling and estimation of species occurrence and occupancy dynamics have increased significantly. Special features of scientific journals have explored innovative uses of detection–nondetection data with occupancy models (Vojta 2005), and an entire volume has synthesized the use and application of occupancy estimation methods (MacKenzie et al. 2006). Reviews of the topical concepts, philosophical considerations, and various sampling designs that can be used for occupancy estimation are now readily available for a range of audiences (MacKenzie and Royle 2005; MacKenzie et al. 2006; Bailey et al. 2007; Royle and Dorazio 2008; Conroy and Carroll 2009; Kendall and White 2009; Hines et al. 2010; Link and Barker 2010). As a result, it would be pointless here to recast all that these publications have so eloquently articulated, but that said, a review of any scientific topic requires sufficient context and relevant background information, especially when relatively new methodologies and techniques such as occupancy estimation and camera traps are involved. This is especially critical in a digital age where new information is published at warp speed, making it increasingly difficult to stay abreast of theoretical advances and research developments.


Detection Probability Camera Trap Occupied Site Occupancy State Occupancy Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We would like to thank Jim Nichols and Ullas Karanth for comments that improved earlier drafts of this chapter, and Mathias Kobler for allowing us to examine and discuss his datasets.


  1. Anderson, D. R. and K. P. Burnham. 2002. Avoiding pitfalls when using information-theoretic methods. Journal of Wildlife Management 66:912–918CrossRefGoogle Scholar
  2. Anderson, D. R., W. A. Link, D. H. Johnson, and K. P. Burnham. 2001. Suggestions for presenting the results of data analyses. Journal of Wildlife Management 65:373–378CrossRefGoogle Scholar
  3. Azuma, D. L., J. A. Baldwin, and B. R. Noon. 1990. Estimating the occupancy of spotted owl habitat by sampling and adjusting for bias. USDA Technical Report PSW-124. Berkeley, CAGoogle Scholar
  4. Bailey, L. L., T. R. Simons, and K. H. Pollock. 2004. Estimating site occupancy and detection probability parameters for terrestrial salamanders. Ecological Applications 14:692–702CrossRefGoogle Scholar
  5. Bailey, L. L., J. E. Hines, J. D. Nichols, and D. I. MacKenzie. 2007. Sampling design trade-offs in occupancy studies with imperfect detection: examples and software. Ecological Applications 17:281–290PubMedCrossRefGoogle Scholar
  6. Bailey, L. L., J. A. Reid, E. D. Forsman, and J. D. Nichols. 2009. Modeling co-occurrence of northern spotted and barred owls: accounting for detection probability differences. Biological Conservation 142:2983–2989CrossRefGoogle Scholar
  7. Baldwin, R. A. and L. C. Bender. 2008. Distribution, occupancy, and habitat correlates of American marten (Martes americana) in Rocky Mountain National Park, Colorado. Journal of Mammalogy 89:419–427CrossRefGoogle Scholar
  8. Bayley, P. B. and Peterson, J. T. 2001. An approach to estimate presence and richness of fish species. Transactions of the American Fisheries Society 130:620–633CrossRefGoogle Scholar
  9. Buckland, S. T., A. E. Magurran, R. E. Green, and R. M. Fewster. 2005. Monitoring change in biodiversity through composite indices. Philosophical Transactions of the Royal Society B 360:243–254CrossRefGoogle Scholar
  10. Burnham, K. P. and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach, Second edition. Springer, New York, NY, USAGoogle Scholar
  11. Conroy, M. J. and J. P. Carroll. 2009. Quantitative conservation of vertebrates. Blackwell, West Sussex, UKCrossRefGoogle Scholar
  12. Gompper, M. E., R. W. Kays, J. C. Ray, S. D. LaPoint, D. A. Bogan, and R. J. Cryan. 2006. A comparison of noninvasive techniques to survey carnivore communities in Northeastern North America. Wildlife Society Bulletin 34:1142–1151CrossRefGoogle Scholar
  13. Gu, W. and R. K. Swihart. 2004. Absent or undetected? Effects of non-detection of species occurrence on wildlife-habitat models. Biological Conservation 116:195–203CrossRefGoogle Scholar
  14. Hines, J., J. D. Nichols, J. A. Royle, D. I. MacKenzie, A. M. Gopalaswamy, N. S. Kumar, and K. U. Karanth. 2010. Tigers on trails: occupancy modeling for cluster sampling. Ecological Applications 20:1456–1466Google Scholar
  15. Johnson, A., C. Vongkhamheng, and T. Saithongdam. 2009. The diversity, status and conservation of small carnivores in a montane tropical forest in Northern Laos. Oryx 43:626–633CrossRefGoogle Scholar
  16. Kendall, W. L. and G. C. White. 2009. A cautionary note on trading spatial for temporal sampling in studies of site occupancy. Journal of Applied Ecology 46:1182–1188Google Scholar
  17. Lancia, R. A., J. D. Nichols, and K. H. Pollock. 1994. Estimating the number of animals in wildlife populations. Pages 215–253 in T. A. Bookhout, editor. Research and management techniques for wildlife and habitats, Fifth edition. The Wildlife Society, Bethesda, MDGoogle Scholar
  18. Link, W. A. and R. J. Barker. 2010. Bayesian inference: with ecological applications. Academic, San Diego, CAGoogle Scholar
  19. Linkie, M., Y. Dinata, A. Nugroho, and I. A. Haidir. 2007. Estimating occupancy of a data deficient mammalian species living in tropical rainforests: sun bears in the Kerinci Seblat region, Sumatra. Biological Conservation 137:20–27CrossRefGoogle Scholar
  20. Long, R. A., T. M. Donovan, P. Mackay, W. J. Zielinski, and J. S. Buzas. 2007. Comparing scat detection dogs, cameras, and hair snares for surveying carnivores. Journal of Wildlife Management 71:2018–2025CrossRefGoogle Scholar
  21. MacKenzie, D. I. 2005. What are the issues with presence–absence data for wildlife managers? Journal of Wildlife Management 69:849–860CrossRefGoogle Scholar
  22. MacKenzie, D. I. and J. D. Nichols. 2004. Occupancy as a surrogate for abundance estimation. Animal Biodiversity and Conservation 27:461–467Google Scholar
  23. MacKenzie, D. I. and J. A. Royle. 2005. Designing efficient occupancy studies: general advice and tips on allocation of survey effort. Journal of Applied Ecology 42:1105–1114CrossRefGoogle Scholar
  24. MacKenzie, D. I., J. D. Nichols, G. B. Lachman, S. Droege, R. A. Royle, and C. A. Langtimm. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83:2248–2255CrossRefGoogle Scholar
  25. MacKenzie, D. I., J. D. Nichols, J. E. Hines, M. G. Knutson, and A. B. Franklin. 2003. Estimating site occupancy, colonization, and extinction when a species is detected imperfectly. Ecology 84:2200–2207CrossRefGoogle Scholar
  26. MacKenzie, D. I., L. L. Bailey, and J. D. Nichols. 2004. Investigating species co-occurrence patterns when species are detected imperfectly. Journal of Animal Ecology 73:546–555CrossRefGoogle Scholar
  27. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey, and J. E. Hines. 2006. Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic, New York, NYGoogle Scholar
  28. MacKenzie, D. I., J. D. Nichols, M. E. Seamans, and R. J Gutierrez. 2009. Modeling species occurrence dynamics with multiple states and imperfect detection. Ecology 90:823–835PubMedCrossRefGoogle Scholar
  29. Manley, P. N., W. J. Zielinski, M. D. Schlesinger, and S. R. Mori. 2004. Evaluation of a multiple-species approach to monitoring species at the ecoregional scale. Ecological Applications 14:296–310CrossRefGoogle Scholar
  30. Martin, J. S., S. Chahamaillé-Jaames, J. D. Nichols, H. Fritz, J. E. Hines, C. J. Fonnesbeck, D. I. MacKenzie, and L. L. Bailey. 2010. Simultaneous modeling of habitat suitability, occupancy, and relative abundance: African elephants in Zimbabwe. Ecological Applications 20:1173–1182Google Scholar
  31. Mattfeldt, S. D., L. L. Bailey, and E. H. Campbell Grant. 2009. Monitoring multiple species: estimating state variables and exploring the efficacy of a monitoring program. Biological Conservation 142:720–737CrossRefGoogle Scholar
  32. McShea, W. J., C. Stewart, L. Peterson, P. Erb, R. Stuebing, and B. Giman. 2009. The importance of secondary forest blocks for terrestrial mammals within an acacia/secondary forest matrix in Sarawak, Malaysia. Biological Conservation 142:3108–3119CrossRefGoogle Scholar
  33. Nichols, J. D. and K. U. Karanth. 2002. Statistical concepts; assessing spatial distribution. Pages 29–38 in K. U. Karanth and J. D. Nichols, editors. Monitoring tigers and their prey. A manual for managers, researchers, and conservationists. Centre for Wildlife Studies, Bangalore, IndiaGoogle Scholar
  34. Nichols, J. D. and B. K. Williams. 2006. Monitoring for conservation. Trends in Ecology and Evolution 21:668–673PubMedCrossRefGoogle Scholar
  35. Nichols, J. D., J. E. Hines, D. I. MacKenzie, M. E. Seamans, and R. J. Gutiérrez. 2007. Occupancy estimation and modeling with multiple states and state uncertainty. Ecology 88:1395–1400PubMedCrossRefGoogle Scholar
  36. Nichols, J. D., L. L. Bailey, A. F. O’Connell, Jr., N. W. Talancy, E. H. Campbell, E. H. C. Grant, A. T. Gilbert, E. M. Annand, T. P. Husband, and J. E. Hines. 2008. Multi-scale occupancy estimation and modeling using multiple detection methods. Journal of Applied Ecology 45:1321–1329CrossRefGoogle Scholar
  37. Nomani, S. Z., R. R. Carthy, and M. K. Oli. 2008. Comparison of methods for estimating abundance of gopher tortoises. Applied Herpetology 5:13–31CrossRefGoogle Scholar
  38. O’Brien, T. G., J. E. M. Baille, and M. Cuke. 2010. The wildlife picture index: monitoring top trophic levels. Animal Conservation. doi: 10.1111/j.1469-1795.201000357.xGoogle Scholar
  39. O’Connell, A. F. Jr., N. W. Talancy, L. L. Bailey, J. R. Sauer, R. Cook, and A. T. Gilbert. 2006. Estimating site occupancy and detection probability parameters for mammals in a coastal ecosystem. Journal of Wildlife Management 70:1625–1633CrossRefGoogle Scholar
  40. Pollock, K. H. 1982. A capture–recapture design robust to unequal probability of capture. Journal of Wildlife Management 46:752–757CrossRefGoogle Scholar
  41. Pollock, K. H., J. D. Nichols, T. R. Simons, G. L. Farnsworth, L. L. Bailey, and J. R. Sauer. 2002. Large scale wildlife monitoring studies: statistical methods for design and analysis. Environmetrics 13:105–119CrossRefGoogle Scholar
  42. Rhodes, J. R., D. Lunney, C. Moon, A. Matthews, and C. A. McAlpine. 2010. The consequence of using indirect sign that decay to determine species’ occupancy. Ecography (in press)Google Scholar
  43. Royle, J. A. 2004. Modeling abundance index data from anuran calling surveys. Conservation Biology 18:1378–1385Google Scholar
  44. Royle, J. A. 2005. Site occupancy models with heterogeneous detection probabilities. Biometrics 62:97–102CrossRefGoogle Scholar
  45. Royle, J. A. and R. M. Dorazio. 2008. Hierarchical modeling and inference in ecology. The analysis of data form from populations, metapopulations, and communities. Academic, San Diego, CAGoogle Scholar
  46. Royle, J. A. and W. A. Link. 2005. A general class of multinomial mixture models for anuran calling survey data. Ecology 86:2505–2512Google Scholar
  47. Royle, J. A. and J. D. Nichols. 2003. Estimating abundance from repeated presence–absence data or point counts. Ecology 84:777–790CrossRefGoogle Scholar
  48. Terborgh, J., L. Lopez, P. Nuñez, M. Rao, G. Shahabuddin, G. Orihuela, M. Riveros, R. Ascanio, G. H. Adler, T. D. Lambert, and L. Balbas. 2001. Ecological meltdown in predator-free forest fragments. Science 294:1923–1926CrossRefGoogle Scholar
  49. Tobler, M. W., S. E. Carrillo-Percastegui, and G. Powell. 2009. Habitat use, activity patterns and use of mineral licks by five species of ungulate in south-eastern Peru. Journal of Tropical Ecology 25:261–270CrossRefGoogle Scholar
  50. Thompson, S. K. 2002. Sampling, Second edition. Wiley, New York, NYGoogle Scholar
  51. Tyre, A. J., B. Tenhumberg, S. A. Field, D. Niejalke, K. Parris, and H. P. Possingham. 2003. Improving precision and reducing bias in biological surveys by estimating false negative error rates in presence–absence data. Ecological Applications 13:1790–1801CrossRefGoogle Scholar
  52. Vojta, C. 2005. Old dog new tricks: innovations with presence–absence information. Journal of Wildlife Management 69:845–848CrossRefGoogle Scholar
  53. Wenger, S. J. and M. C. Freeman. 2008. Estimating species occurrence, abundance, and detection probability using zero-inflated distributions. Ecology 89:2953–2959CrossRefGoogle Scholar
  54. White, G. C. and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46:120–139CrossRefGoogle Scholar
  55. Winarni, N. L., T. G. O’Brien, J. P. Carroll, and M. F. Kinnaird. 2009. Movements, distribution, and abundance of Great Argus Pheasants (Argusianus Argus) in a Sumatran rainforest. Auk 126(2):341–350CrossRefGoogle Scholar
  56. Zielinski, W. J., K. M. Slauson, and A. E. Bowles. 2008. Effects of off-highway vehicle use on the American marten. Journal of Wildlife Management 72:1558–1571Google Scholar

Copyright information

© Springer 2011

Authors and Affiliations

  1. 1.U.S. Geological SurveyPatuxent Wildlife Research CenterBeltsvilleUSA
  2. 2.Department of Fish, Wildlife, and Conservation BiologyColorado State UniversityFort CollinsUSA

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