Performance of hierarchical abundance models on simulated bat capture data

• Autorzy: Womack-Bulliner K.M. , Amelon S.K. , Thompson III F.R. , Lebrun J.J.
• Języki publikacji: EN

Abstrakty

EN

The ability to accurately estimate abundance is crucial to ecologists, conservationists, and managers to provide insight on species status, population trends, and viability. Acoustic detection and occupancy modeling can provide an understanding of resource use for bats, but these methods do not estimate how many bats are in an area, or how these numbers change over time. In North America, there is a heightened need to estimate bat abundance and trends in response to white-nose syndrome (WNS) and other threats to bat populations. We assessed the performance of the N-mixture model for repeated count data and the general multinomial-Poisson model for removal sampling to estimate bat abundance from simulated mist-net capture data. We evaluated performance under varying numbers of sites and visits, detection probabilities (P), and population sizes. We simulated four scenarios with a total of 85 combinations of parameter values each containing 1,000 replications. We used the UNMARKED package in R to fit the N-mixture and removal models. We calculated relative bias (RB), mean absolute error (MAE), and mean absolute percent error (MA%E) from model estimates to evaluate model performance. Relative bias, MAE, and MA%E decreased as p and bat abundance increased for all models. The removal model outperformed the N-mixture model in all scenarios except when P = 0.05. The N-mixture model had low RB, MAE, and MA%E when bat abundance was ≥ 70 and P > 0.5, but in other scenarios, errors were large. The mean of estimates from the removal model were unbiased and RB, MAE, and MA%E were very low for most scenarios. Use of the removal model with data from repeated mist-net surveys may allow resource managers and conservationists to better quantify how resource management and landscape composition affect bat species abundance and overall populations.

• Wydawca: -
• Czasopismo: Acta Chiropterologica
• Rocznik: 2018
• Tom: 20
• Numer: 2
• Opis fizyczny: p.465-474,fig.,ref.

Twórcy

autor

Womack-Bulliner K.M.

• Missouri Department of Conservation, Northeast Regional Office, 3500 S. Baltimore Street, Kirksville, MO 63501, USA

autor

Amelon S.K.

• U.S.D.A. Forest Service, Northern Research Station, 202 Natural Resource Building, Columbia, MO 65211, USA

autor

Thompson III F.R.

• U.S.D.A. Forest Service, Northern Research Station, 202 Natural Resource Building, Columbia, MO 65211, USA

autor

Lebrun J.J.

• U.S. Fish and Wildlife Service, 5600 American Blvd. West, Suite 990, Bloomington, MN 55437, USA

Bibliografia

• 1. Amelon, S. K. 2007. Multi-scale factors influencing detection, site occupancy and resource use by foraging bats in the Ozark Highlands of Missouri. Ph.D. Thesis, University of Missouri, Columbia, MO, xiv + 223 pp. Google Scholar
• 2. Berry, N., W. O'Connor, M. W. Holderied, and G. Jones. 2004. Detection and avoidance of harp traps by echolocating bats. Acta Chiropterologica, 6: 335–346. Google Scholar
• 3. Buckland, S. T., D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers, and L. Thomas. 2001. Introduction to distance sampling estimating abundance of biological populations. Oxford University Press, Oxford, 432 pp. Google Scholar
• 4. Carers, M. C., and R. M. R. Barclay. 2000. Myotis septentrionalis. Mammalian Species, 634: 1–4. Google Scholar
• 5. Dorazio, R. M., and J. A. Royle. 2003. Mixture models for estimating the size of a closed population when capture rates vary among individuals. Biometrics, 59: 351–364. Google Scholar
• 6. Dorazio, R. M., H. L. Jelks, and F. Jordan. 2005. Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations. Biometrics, 61: 1093–1101. Google Scholar
• 7. Drapeau, P., A. Leduc, and R. Mcneil. 1999. Refining the use of point counts at the scale of individual points in studies of bird-habitat relationships. Journal of Avian Biology, 30: 367–382. Google Scholar
• 8. Efford, M. G., and D. K. Dawson. 2009. Effect of distancerelated heterogeneity on population size estimates from point counts. The Auk, 126: 100–111. Google Scholar
• 9. Farnsworth, K. D., O. Lyashevska, and T. Fung. 2012. Functional complexity: the source of value in biodiversity. Ecological Complexity, 11: 46–52. Google Scholar
• 10. Fiske, I. J., and R. B. Chandler. 2011. Unmarked: an R package for fitting hierarchical models of wildlife occurrence and abundance. Journal of Statistical Software, 43: 1–23. Google Scholar
• 11. Johnson, D. H. 2008. In defense of indices: the case of bird surveys. The Journal of Wildlife Management, 72: 857–868. Google Scholar
• 12. Kery, M., J. A. Royle, and H. Schmidt. 2005. Modeling avian abundance from replicated counts using binomial mixture models. Ecological Applications, 15: 1450–1461. Google Scholar
• 13. Kunz, T. H., and E. L. Anthony. 1977. On the efficiency of the Tuttle bat trap. Journal of Mammalogy, 58: 309–315. Google Scholar
• 14. Kunz, T. H., and A. Kurta. 1988. Capture methods and holding devices. Pp. 1–29, in Ecological and behavioral methods for the study of bats ( T. H. Kunz, ed.). Smithsonian Institution Press, Washington, D.C., 533 pp. Google Scholar
• 15. Kunz, T. H., E. B. Arnett, W. P. Erickson, A. R. Hoar, G. D. Johnson, R. P. Larkin, M. D. Strickland, R. W. Thresher, and M. D. Tuttle. 2007. Ecological impacts of wind energy development on bats: questions, research needs, and hypotheses. Frontiers in Ecology and the Environment, 5: 315–324. Google Scholar
• 16. Larsen, R. J., K. A. Boegler, H. H. Genoways, W. P. Mase-Field, R. A. Kirsch, and S. C. Pedersen. 2007. Mist netting bias, species accumulation curves, and the rediscovery of two bats on Montserrat (Lesser Antilles). Acta Chiropterologica, 9: 423–435. Google Scholar
• 17. Legates, D. R., and G. J. McCabe, Jr . 1999. Evaluating the use of ‘goodness-of-fit’ measures in hydrologic and hydroclimatic model validation. Water Resources Research, 35: 233–241. Google Scholar
• 18. Mackenzie, D. I., J. D. Nichols, G. B. Lachman, S. Droege, A. J. Royle, and C. A. Langtimm. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology, 83: 2248–2255. Google Scholar
• 19. Marques, J. T., M. J. Ramos Pereira, T. A. Marques, C. D. Santos, J. Santana, P. Beja, and J. M. Palmeirim. 2013. Optimizing sampling design to deal with mist-net avoidance in Amazonian birds and bats. PLoS ONE, 8: e74505. Google Scholar
• 20. Mayer, D. G., and D. G. Butler. 1993. Statistical validation. Ecological Modelling, 68: 21– 32. Google Scholar
• 21. McCaffery, R., J. J. Nowak, and P. M. Lukacs. 2016. Improved analysis of lek count data using N-mixture models. Journal of Wildlife Management, 80: 1011–1021. Google Scholar
• 22. McIntyre, A. P., J. E. Jones, E. M. Lund, F. T. Waterstrat, J. N. Giovanini, S. D. Duke, M. P. Hayes, T. Quinn, and A. J. Kroll. 2012. Empirical and simulation evaluations of an abundance estimator using unmarked individuals of cryptic forest-dwelling taxa. Forest Ecology and Management, 286: 129–136. Google Scholar
• 23. Menzel, J. M., W. M. Ford, M. A. Menzel, T. C. Carter, J. E. Gardner, J. D. Garner, and J. E. Hofmann. 2005. Summer habitat use and home-range analysis of the endangered Indiana bat. Journal of Wildlife Management, 69: 430–436. Google Scholar
• 24. Puechmaille, S. J., G. Wibbelt, V. Korn, H. Fuller, F. Forget, K. Mühldorfer, A. Kurth, W. Bogdanowicz, C. Borel, T. Bosch, et al. 2011. Pan-European distribution of white-nose syndrome fungus (Geomyces destructans) not associated with mass mortality. PLoS ONE, 6: e19167. Google Scholar
• 25. Reidy, J. L., F. R. Thompson, and S. W. Kendrick. 2014. Breeding bird response to habitat and landscape factors across a gradient of savanna, woodland, and forest in the Missouri Ozarks. Forest Ecology and Management, 313: 34–46. Google Scholar
• 26. Rigby, E. A. 2016. Simulating effects of imperfect detectability in bird surveys. Ph.D. Thesis, University of Minnesota, Minnea polis, MN, x + 324 pp. Google Scholar
• 27. Roach, M. C. 2016. Breeding bird response to pine-savanna and woodland restoration in the Ozark-Ouachita Interior Highlands. M.Sci. Thesis, University of Missouri, Columbia, MO, ix + 126 pp. Google Scholar
• 28. Rosenstock, S. S., D. R. Anderson, K. M. Giesen, T. Leukering, and M. F. Carter. 2002. Landbird counting techniques: current practices and an alternative. The Auk, 119: 46–53. Google Scholar
• 29. Royle, J. A. 2004a. Generalized estimators of avian abundance from count survey data. Animal Biodiversity and Conservation, 27: 375–386. Google Scholar
• 30. Royle, J. A. 2004b. N-mixture models for estimating population size from spatially replicated counts. Biometrics, 60: 108–115. Google Scholar
• 31. Royle, J. A., D. K. Dawson, and S. Bates. 2004. Modeling abundance effects in distance sampling. Ecology, 85: 1591–1597. Google Scholar
• 32. Ruiz, Gutiérrez V., E. F. Zipkin, and A. A. Dhondt. 2010. Occupancy dynamics in a tropical bird community: unexpectedly high forest use by birds classified as non-forest species. Journal of Applied Ecology, 47: 621–630. Google Scholar
• 33. Schwartz, C. W., and E. R. Schwartz. 2001. The wild mammals of Missouri. University of Missouri Press. Columbia, MO, , 368 pp. Google Scholar
• 34. Starbuck, C. A., S. K. Amelon, and F. R. Thompson. 2015. Relationships between bat occupancy and habitat and landscape structure along a savanna, woodland, forest gradient in the Missouri Ozarks. Wildlife Society Bulletin, 39: 20–30. Google Scholar
• 35. Turner, G. G., D. M. Reeder, and J. T. H. Coleman. 2011. A five-year assessment of mortality and geographic spread of white-nose syndrome in North American bats and a look to the future. Bat Research News, 52: 13–27. Google Scholar
• 36. USFWS (United States Fish And Wildlife Service). 2018. Range-wide Indiana bat summer survey guidelines. Endangered species, Midwest Region, US Fish and Wildlife Service. Last updated April 2018, 61 pp. Google Scholar
• 37. Veilleux, J. P., and S. L. Veilleux. 2004. Intra-annual and inter annual fidelity to summer roost areas by female eastern pipistrelles, Pipistrellus subflavus. The American Midland Naturalist, 152: 196–200. Google Scholar
• 38. Walters, C., A. Collen, T. Lucas, K. Mroz, C. Sayer, and K. E. Jones. 2013. Challenges of using bioacoustics to globally monitor bats. Pp. 479–500, in Bat evolution, ecology, and conservation ( R. A. Adams and S. C. Pedersen, eds.). Springer, New York, 547 pp. Google Scholar
• 39. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Analysis and management of animal populations: modeling, estimation, and decision making. Academic Press, San Diego, CA, 817 pp. Google Scholar
• 40. Womack, K. W. 2017. Multi-scale factors related to abundance of bats and insect prey in savannas, woodlands, and forest in the Ozark Highlands, USA. Ph.D. Thesis, University of Mis souri, Columbia, MO, 177 pp. Google Scholar
• 41. Yamaura, Y. 2013. Confronting imperfect detection: behavior of binomial mixture models under varying circumstances of visits, sampling sites, detectability, and abundance, in smallsample situations. Ornithological Science, 12: 73–88. Google Scholar
• 42. Yamaura, Y., M. Kery, and J. A. Royle. 2016. Study of biological communities' subject to imperfect detection: bias and precision of community N-mixture abundance models in small-sample situations. Ecological Research, 31: 289–305. Google Scholar
• 43. Yates, M. D. and R. M. Muzika. 2006. Effect of forest structure and fragmentation on site occupancy of bat species in Missouri Ozark forests. Journal of Wildlife Management, 70: 1238–1248. Google Scholar

Identyfikatory

DOI

10.3161/15081109ACC2018.20.2.016