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A spatially explicit hierarchical model to characterize population viability.
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Campbell_et_al-2018-Ecological ...
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Final published version
Affiliation
Univ Arizona, Sch Nat Resources & EnvironmIssue Date
2018-12-01Keywords
Gopherus morafkaiCAR model
Sonoran desert tortoise
capture-recapture
demography
multi-state model
population viability analysis
recruitment
spatial autoregressive model
spatial variation
survival
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WILEYCitation
Campbell, S. P., Zylstra, E. R., Darst, C. R., Averill‐Murray, R. C. and Steidl, R. J. (2018), A spatially explicit hierarchical model to characterize population viability. Ecol Appl, 28: 2055-2065. doi:10.1002/eap.1794Journal
ECOLOGICAL APPLICATIONSRights
This article is a U.S. Government work and is in the public domain in the USA.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Many of the processes that govern the viability of animal populations vary spatially, yet population viability analyses (PVAs) that account explicitly for spatial variation are rare. We develop a PVA model that incorporates autocorrelation into the analysis of local demographic information to produce spatially explicit estimates of demography and viability at relatively fine spatial scales across a large spatial extent. We use a hierarchical, spatial, autoregressive model for capture-recapture data from multiple locations to obtain spatially explicit estimates of adult survival (phi(ad)), juvenile survival (phi(juv)), and juvenile-to-adult transition rates (psi), and a spatial autoregressive model for recruitment data from multiple locations to obtain spatially explicit estimates of recruitment (R). We combine local estimates of demographic rates in stage-structured population models to estimate the rate of population change (lambda), then use estimates of lambda (and its uncertainty) to forecast changes in local abundance and produce spatially explicit estimates of viability (probability of extirpation, P-ex). We apply the model to demographic data for the Sonoran desert tortoise (Gopherus morafkai) collected across its geographic range in Arizona. There was modest spatial variation in lambda<^> (0.94-1.03), which reflected spatial variation in phi<^>ad (0.85-0.95), phi<^>juv (0.70-0.89), and psi<^> (0.07-0.13). Recruitment data were too sparse for spatially explicit estimates; therefore, we used a range-wide estimate (R<^> = 0.32 1-yr-old females per female per year). Spatial patterns in demographic rates were complex, but phi<^>ad, phi<^>juv, and lambda<^> tended to be lower and psi<^> higher in the northwestern portion of the range. Spatial patterns in P-ex varied with local abundance. For local abundances >500, P-ex was near zero (<0.05) across most of the range after 100 yr; as abundances decreased, however, P-ex approached one in the northwestern portion of the range and remained low elsewhere. When local abundances were <50, western and southern populations were vulnerable (P-ex > 0.25). This approach to PVA offers the potential to reveal spatial patterns in demography and viability that can inform conservation and management at multiple spatial scales, provide insight into scale-related investigations in population ecology, and improve basic ecological knowledge of landscape-level phenomena.Note
This article is a U.S. Government work and is in the public domain in the USA.ISSN
1051-0761PubMed ID
30187584DOI
10.1002/eap.1794Version
Final published versionSponsors
U.S. Fish and Wildlife Service; Arizona Game and Fish Departmentae974a485f413a2113503eed53cd6c53
10.1002/eap.1794
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Except where otherwise noted, this item's license is described as This article is a U.S. Government work and is in the public domain in the USA.
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