TY - JOUR
T1 - A spatially explicit hierarchical model to characterize population viability
AU - Campbell, Steven P.
AU - Zylstra, Erin R.
AU - Darst, Catherine R.
AU - Averill-Murray, Roy C.
AU - Steidl, Robert J.
N1 - Publisher Copyright:
Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
PY - 2018/12
Y1 - 2018/12
N2 - 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 (ϕad), juvenile survival (ϕjuv), and juvenile-to-adult transition rates (ψ), 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 (λ), then use estimates of λ (and its uncertainty) to forecast changes in local abundance and produce spatially explicit estimates of viability (probability of extirpation, Pex). 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 (Formula presented.) (0.94–1.03), which reflected spatial variation in (Formula presented.) (0.85–0.95), (Formula presented.) (0.70–0.89), and (Formula presented.) (0.07–0.13). Recruitment data were too sparse for spatially explicit estimates; therefore, we used a range-wide estimate ((Formula presented.) = 0.32 1-yr-old females per female per year). Spatial patterns in demographic rates were complex, but (Formula presented.), (Formula presented.), and (Formula presented.) tended to be lower and (Formula presented.) higher in the northwestern portion of the range. Spatial patterns in Pex varied with local abundance. For local abundances >500, Pex was near zero (<0.05) across most of the range after 100 yr; as abundances decreased, however, Pex approached one in the northwestern portion of the range and remained low elsewhere. When local abundances were <50, western and southern populations were vulnerable (Pex > 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.
AB - 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 (ϕad), juvenile survival (ϕjuv), and juvenile-to-adult transition rates (ψ), 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 (λ), then use estimates of λ (and its uncertainty) to forecast changes in local abundance and produce spatially explicit estimates of viability (probability of extirpation, Pex). 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 (Formula presented.) (0.94–1.03), which reflected spatial variation in (Formula presented.) (0.85–0.95), (Formula presented.) (0.70–0.89), and (Formula presented.) (0.07–0.13). Recruitment data were too sparse for spatially explicit estimates; therefore, we used a range-wide estimate ((Formula presented.) = 0.32 1-yr-old females per female per year). Spatial patterns in demographic rates were complex, but (Formula presented.), (Formula presented.), and (Formula presented.) tended to be lower and (Formula presented.) higher in the northwestern portion of the range. Spatial patterns in Pex varied with local abundance. For local abundances >500, Pex was near zero (<0.05) across most of the range after 100 yr; as abundances decreased, however, Pex approached one in the northwestern portion of the range and remained low elsewhere. When local abundances were <50, western and southern populations were vulnerable (Pex > 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.
KW - CAR model
KW - Gopherus morafkai
KW - Sonoran desert tortoise
KW - capture–recapture
KW - demography
KW - multi-state model
KW - population viability analysis
KW - recruitment
KW - spatial autoregressive model
KW - spatial variation
KW - survival
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U2 - 10.1002/eap.1794
DO - 10.1002/eap.1794
M3 - Article
C2 - 30187584
AN - SCOPUS:85057851580
SN - 1051-0761
VL - 28
SP - 2055
EP - 2065
JO - Ecological Applications
JF - Ecological Applications
IS - 8
ER -