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Occupancy Models to Study Wildlife June When Salamanders Were Believed 2 unit. Sample units were near trails and Further Reading Caudata) populations: a twenty-year and dynamics of species occurance. located approximately 250 m apart study in the southern Appalachians. Academic Press. Glossary: Ash, A. N. 1997. Disappearance and to ensure independence among sites. Brimleyana 18: 59-64. return of salamanders to clearcut plots Thirty-nine sites were sampled once 1. State variable: variable used to characterize the status of the wild- O’Connell, A. F., N. W. Talancy, L. in the southern Blue Ridge Mountains. Hanski, I. 1992. Inferences from eco- L. Bailey, J. R. Sauer, R. Cook and every two weeks from April to mid- life system of interest; the system being studied. Conservation Biology 11: 983-989. logical incidence functions. American A. T. Gilbert. 2005. Estimating site Occupancy Models to Study Wildlife June when salamanders were believed 2. Occupancy: the proportion of sites, patches, or habitat units oc- Naturalist 139: 657-662. occupancy and detection probability to be most active and near the surface. Ash, A. N. and K. H. Pollock. 1999. cupied by a species. parameters for mammals in a coastal However, we detected no salaman- Clearcuts, salamanders and field stud- 3. Detectability: the probability of detecting a species during a single Kendall, W. L. 1999. Robustness of ecosystem. Journal of Wildlife Man- ders of the Desmognathus imitator ies. Conservation Biology 13: 206- Abstract areas and may be survey, given it is present at the site. closed capture–recapture methods to agement 69: in press. 208. violations of the closure assumption. appropriate for spe- Coverboards Many wildlife studies seek to 4. Confounded: an inability to separate multiple factors potentially Ecology 80: 2517–2525. Olson, G. A., R. G. Anthony, E. E. cies that exhibit wide Burnham, K. P. and D. R. Anderson. understand changes or differences in contributing to an observed pattern. Forsman, S. H. Ackers, P. J. Los- population fluctua- 2002. Model selection and multimodel the proportion of sites occupied by 5. Likelihood function: a functional expression of unknown param- MacKenzie, D. I., J. D. Nichols, G. B. chl, J. A. Reid, K. M. Dugger, E. tions over short time inference. Springer-Verlag, New York, Lachman, S. Droege, J. A. Royle and a species of interest. These studies eters, given observed data and an assumed model structure. M. Glenn and W. J. Ripple. 2005. periods. For example, New York, USA. C. A. Langtimm. 2002. Estimating site are hampered by imperfect detection Modeling of site occupancy dynam- occupancy has been 6. Parameters: quantities to be estimated, such as occupancy or de- occupancy rates when detection prob- of these species, which can result Corn, P. S., B. R. Hossack, E. Muths, ics for Northern Spotted Owls, with tectability, under an assumed model structure. abilities are less than one. Ecology 83: in some sites appearing to be unoc- the most influential D. A. Patla, C. R. Peterson and A. L. emphasis on the effects of Barred 2248-2255. cupied that are actually occupied. state variable in de- 7. Logit function: an equation that converts a sigmoid relationship Gallant. 2005. Status of amphibians Owls. Journal of Wildlife Manage- Occupancy models solve this problem scribing world-wide (logistic) between two factors to a linear relationship. The logit on the Continental Divide: surveys on ment 69: in press. MacKenzie, D. I., J. D. Nichols, J. and produce unbiased estimates of amphibian declines function involving detectability may be: logit(p)=ln(p/(1-p))= y. a transect from Montana to Colorado, E. Hines, M. G. Knutson and A. Petranka, J. W., M. E. Eldridge and K. (Green 1997). Imitator Salamander USA. Alytes 22: 85-94. occupancy and related parameters. complex during the first survey. Thus, 8. Heterogeneity: Often used synonymously with variation. Here, it is B. Franklin. 2003. Estimating site E. Haley. 1993. Effects of timber Required data (detection/non-detec- we eliminated this survey from the used to refer to unexplained variation in the parameters of interest. Dodd, C. K. 2003. Monitoring amphib- occupancy, colonization and local harvesting on southern Appalachian tion information) are relatively simple The Problem The Solution analysis because we assume the sala- extinction probabilities when a species 9. Probability-based sampling: a sampling scheme in which every ians in Great Smoky Mountains salamanders. Conservation Biology 7: and inexpensive to collect. Software Wildlife species are rarely de- manders had not emerged from their sample unit (site) has a known probability of being selected (see National Park. U.S. Geological Survey is detected imperfectly. Ecology 84: 363-377. is available free of charge to aid in- New classes of models, called 2200-2207. tected with perfect accuracy, regard- occupancy models, were developed to winter retreats and were unavailable Thompson et al. 1998). Circular 1258. 117p. vestigators in occupancy estimation. for capture during this survey occa- Petranka, J. W. 1999. Recovery of less of the technique employed. solve the problems created by imper- MacKenzie, D. I., L. L. Bailey and J. D. sion. This left a total of four surveys 10.Biased: describes an estimator that, over repeated trials, exhibits Green, D. M. 1997. Perspectives on salamanders after clearcutting in the Non-detection does not necessarily fect detectability (MacKenzie et al. a non-random (directional) difference from the true value being Nichols. 2004. Investigating species southern Appalachians: a critique of Response Variables in Wildlife mean that a species was absent unless for the analysis. amphibian population decline: defin- 2002, 2003, 2004). These models use estimated. co-occurrence patterns when species Ash’s estimates. Conservation Biology Studies Analysis, Model Selection, and ing the problem and searching for the probability of detecting the spe- information from repeated observa- answers. In: Green D. M. (ed.) Am- are detected imperfectly. Journal of 13: 203-205. 3 Interpretation: Salamanders of the 11.Parsimonious model selection: given a set of candidate models, Studies of wildlife populations cies (detectability ) was 100%. This tions at each site to estimate detect- phibians in decline: Canadian studies Animal Ecology 73: 546-555. Desmognathus imitator complex selecting those model(s) that describe the information content of Scott, J. M., P. J. Heglund, M. L. Mor- often attempt to understand patterns leads to a fundamental problem: the ability. Detectability may vary with of a global problem. Herpetological were detected at 10 of the 39 sites, the data adequately with the fewest number of parameters pos- MacKenzie, D. I. and L. L. Bailey. 2004. rison, J. B. Haufler, M. G. Raphael, W. of distribution and abundance. Es- measure of occupancy (presence/ab- site characteristics (e.g., habitat vari- Conservation 1: 291-308. 4 yielding a naïve occupancy estimate sible. Assessing the fit of site occupancy A. Wall and F. B. Samson (eds). 2002. timating abundance can be a costly sence at a set of sites) is confounded ables) or survey characteristics (e.g., 1 of 0.26; however, we suspected that 12.Weighted average: an average where the contribution of the values Gu, W. and R. K. Swihart. 2004. Absent models. Journal of Agricultural, Bio- Predicting species occurrence: issues endeavor, and other state variables with the detectability of the spe- weather conditions), whereas occu- 2 salamanders may be more likely to being averaged is unequal. For example, the unweighted average or undetected? Effects of non-detec- logical and Environmental Statistics 9: of accuracy and scale. Island Press, like species richness or occupancy cies. More specifically, an observed pancy relates only to site characteris- occupy undisturbed sites compared of 5, 3, and 9 is (5+3+9)/3=(0.33(5)+0.33(3)+0.33(9))=5.7. How- tion of species occurrence on wildlife- 300-318. Washington, D.C. may be more appropriate and less “absence” occurs if either the species tics. Repeated observations can take to disturbed sites. In addition, we habitat models. Biological Conserva- expensive. Occupancy is an alterna- was present at the site but not detect- many forms, but the most obvious is ever, if we wanted the contribution of those three values to be 0.1, MacKenzie, D. I., J. D. Nichols, J. A. Ro- Thompson, W. L., G. C. White and C. thought detectability might vary tion 116: 195-203. tive that has a long history of use in ed, or the species was truly absent. simply surveying each site repeatedly. 0.4, and 0.5 respectively, we would calculate a weighted average yle, K. H. Pollock, L. L. Bailey and J. Gowan. 1998. Monitoring vertebrate ecological and wildlife studies. Two Detectability may vary among study In some cases, traps, coverboards, among surveys due to environmental of (0.1(5)+0.4(3)+0.5(9))=6.2. Hairston, N. G. and R. H. Wiley. 1993. E. Hines. In press. Occupancy estima- populations. Academic Press, San of the most noticeable areas where oc- sites and may be related to character- transects, and surveys by independent conditions such as rainfall or temper- No decline in salamander (Amphibia: tion and modeling: inferring patterns Diego, CA. ature. Thus, we consider all combina- cupancy information is used include: istics of a survey on a particular day, observers can be treated as repeated tions of models in which occupancy (1) studies of species distribution and such as weather conditions. Because observations for a local sample area probability is assumed to be constant ous process of model selection,11 but indeed differs between
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