Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

doi:10.1016/j.gecco.2017.09.004

Cited by 64 publications

(32 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…, McGowan et al. ), aggregating spatially explicit estimates for this goal is beneficial only to the extent that incorporating spatial variation improves the reliability of species‐level estimates of viability. The greater utility of spatially explicit estimates for species conservation will likely come from understanding how viability and dynamics of populations vary geographically in relation to each other and to landscape features and threats.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A spatially explicit hierarchical model to characterize population viability

Campbell

Zylstra

Darst

et al. 2018

Ecological Applications

View full text Add to dashboard Cite

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 (ϕ ), juvenile survival (ϕ ), 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, P ). 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 (0.94-1.03), which reflected spatial variation in (0.85-0.95), (0.70-0.89), and (0.07-0.13). Recruitment data were too sparse for spatially explicit estimates; therefore, we used a range-wide estimate ( = 0.32 1-yr-old females per female per year). Spatial patterns in demographic rates were complex, but , , and tended to be lower and higher in the northwestern portion of the range. Spatial patterns in P varied with local abundance. For local abundances >500, P was near zero (<0.05) across most of the range after 100 yr; as abundances decreased, however, P 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 > 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.

show abstract

Section: Discussionmentioning

confidence: 99%

“…, McGowan et al. ). Although resulting viability estimates may be reasonable across all populations, important site‐specific differences in viability that can affect population dynamics locally and regionally are likely to be overlooked (e.g., source–sink dynamics; Pulliam ).…”

Section: Introductionmentioning

confidence: 99%

A spatially explicit hierarchical model to characterize population viability

Campbell

Zylstra

Darst

et al. 2018

Ecological Applications

View full text Add to dashboard Cite

show abstract

“…These studies should allow the processes increasing a species' vulnerability to be identified and assisting pre-emptive action to be undertaken. PVAs provide a mechanism to incorporate future risk into threat assessment when examining species which are currently not at high risk (McGowan et al 2017). Particular attention should be paid to species whose risk classification, while still low, has relatively quickly changed in the recent past (see Roberts et al 2016).…”

Section: Recommendationsmentioning

confidence: 99%

Population viability analyses in New Zealand: a review

Simpkins¹,

Lee²,

Powers³

et al. 2018

NZ J Ecol

View full text Add to dashboard Cite

Biodiversity assets often require conservation management, which, in turn, necessitates decisions about which ecosystem, community or species should be prioritised to receive resources. Population viability analysis (PVA) uses a suite of quantitative methods to estimate the likelihood of population decline and extinction for a given species, and can be used to assess a population's status, providing useful information to decision-makers. In New Zealand, a range of taxa have been analysed using the PVA approach, but the scope of its implementation has not previously been reviewed. We compiled a database of 78 published PVAs for New Zealand indigenous fauna and flora, along with details of the species considered, the data used to parametrise the model, and the technical details of their implementation. We assessed the taxa and threat status of the species for which PVA were conducted relative to the distribution of taxa across threat classes in the New Zealand Threat Classification System database. There were clear biases in the species selected for analysis, notably an over-representation of birds and threatened species in general, and an under-representation of invertebrates and plants. Model parameterisation and implementation were often not reported in a transparent or standardised way, which hinders model communication and reconstruction. To maximise the benefit of PVAs, we suggest that more attention should be given to the ecosystem-level importance of species, and to species whose threat status is changing rapidly or are not yet threatened. More clearly describing the parameterisation, underlying assumptions and implementation of PVAs will help to better contextualise their results and support reproducible ecological science and decision-making.

show abstract

“…The subdominant eigenvalues have received far less attention in theoretical and applied ecology than the dominant eigenvalue. The dominant eigenvalue, as the finite population growth rate and the ultimate indicator of a population’s fate, is a focus of endangered species management policy (McGowan, Allan, Servoss, Hedwall, & Wooldridge, ). As well, the dominant eigenvalue is accompanied by an entourage of important quantities in the form of the stable stage proportions (right eigenvector) and the net reproductive values (left eigenvector; Caswell, ).…”

Section: Introductionmentioning

confidence: 99%

Analytical expressions for the eigenvalues, demographic quantities, and extinction criteria arising from a three‐stage wildlife population matrix

Hanley

Dennis

2019

Natural Resource Modeling

View full text Add to dashboard Cite

We used the symbolic solution for the roots of a cubic polynomial to derive expressions for the eigenvalues of a three‐stage population projection matrix. As well, we obtained expressions for eigenvectors, moduli, damping ratios, sensitivities, and elasticities. The equations reveal the existence of “superparameters;” natural groupings of vital rates that drive population dynamics. We show that growth rates can be calculated using (at most) three superparameters in place of as many as nine original vital rates, potentially simplifying data collection. Necessary and sufficient conditions for extinction can be summarized equivalently by three superparameter inequalities. For a common life history (Noon & Biles, 1990, J Wildl Manag, 54, 18–27) four vital rate parameters are reduced to two superparameters. The results are applicable to population viability and recovery analysis and harvest planning. Two recommendations for resource managers Superparameters can be estimated to determine population growth rates. Superparameters can be used to conduct rapid assessments of extinction risk.

show abstract

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

Cited by 64 publications

References 29 publications

A spatially explicit hierarchical model to characterize population viability

A spatially explicit hierarchical model to characterize population viability

Population viability analyses in New Zealand: a review

Analytical expressions for the eigenvalues, demographic quantities, and extinction criteria arising from a three‐stage wildlife population matrix

Contact Info

Product

Resources

About