Details

Autor(en) / Beteiligte

• Tucker, A. M.
• McGowan, C. P.
• Mulero Oliveras, E. S.
• Angeli, N. F.
• Zegarra, J. P.

Titel

A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data

Ist Teil von

• Animal conservation, 2021-04, Vol.24 (2), p.292-302

Ort / Verlag

London: Wiley Subscription Services, Inc

Erscheinungsjahr

2021

Quelle

Wiley-Blackwell Journals

Beschreibungen/Notizen

• Conservation planning for rare and threatened species is often made more difficult by a lack of research and monitoring data. In such cases, managers may rely on qualitative assessments of species risk that lack explicit acknowledgement of uncertainty. Snakes are a group of conservation concern that are also notoriously difficult to monitor. Here, we demonstrate a quantitative population projection for a data‐deficient species, the Puerto Rican boa (Chilabothrus inornatus) using expert knowledge and published information about species life history and threats to persistence. Using this model, we simulated population dynamics over 30 years under four scenarios of future urbanization and found that there was an increased probability of population decline as urbanization rates increased. We conduct a sensitivity analysis to evaluate the sensitivity of outcomes to model inputs, a practice that may also be useful in recovery planning. The sensitivity analyses also provide insight into how the future trajectories would change if the elicited demographic rates are incorrect. Even when data are sparse, quantitative methods can often be used to produce rigorous and reproducible estimates of future status with quantifiable uncertainty. In this paper, we develop a demographic projection model for a data‐deficient and endangered snake, the Puerto Rican boa (Chilabothrus inornatus), using habitat suitability models and expert judgment to develop a population viability analysis. We also demonstrate model sensitivity analyses to evaluate the influence of various model parameters on estimates of quasi‐extinction risk and population growth rate, which are useful at evaluating model outcomes and developing recovery targets. This work presents a quantitative, reproducible, and transparent projection model that can be used to support decisions regarding future protection status of this species. (Photo credit: J.P. Zegarra)