A demographic projection model to support conservation decision making for an endangered snake with limited monitoring data. (28th September 2020)

• Record Type: Journal Article
• Authors: Tucker, A. M.; McGowan, C. P.; Mulero Oliveras, E. S.; Angeli, N. F.; Zegarra, J. P.
• Is Part Of: Animal conservation. Volume 24:Number 2(2021)
• Page Start: 291
• Page End: 301
• Publication Date: 2020-09-28
• Subjects: population viability analysis -- matrix population model -- endangered species -- conservation planning -- data‐deficient species -- urbanization -- snakes; Conservation biology -- Periodicals; Wildlife conservation -- Periodicals; Conservation de la biodiversité; Conservation de la faune; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 333.95416
• DOI: 10.1111/acv.12641
• Languages: English
• ISSNs: 1367-9430

Abstract

Abstract: 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. Abstract : 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)