Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment

Abstract

The US Fish and Wildlife Service (USFWS) has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of the current and predicted future status of a species. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, and recovery planning. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting conservation decisions in current data and cutting edge analytical and modeling techniques. Here, we describe a novel analysis of available data to assess the current condition of eastern black rail Laterallus jamaicensis jamaicensis across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future status under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units, and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With the results of these data analyses and predictive models, the USFWS concluded that protections of the Endangered Species Act were warranted for this subspecies.

Breeding Dynamics of Gopher Frog Metapopulations Over 10 Years

“…It is our experience that State and Federal agencies and other partners often collect data sets for pond-breeding amphibians and other species of concern within their separate jurisdictions that may be compatible for unified analyses similar to those undertaken in this study. Recent efforts have successfully coordinated partners and developed appropriate modeling frameworks for these contexts (e.g., Ahrestani et al 2017;Crawford et al 2020b;McGowan et al 2020). Our study also advanced previous work on gopher frogs by estimating the influence of climatic and wetland-specific factors on breeding dynamics over a 10y period and across the species' range, which can directly inform site-level management and future models predicting persistence of gopher frog metapopulations.…”

Land cover habitat associations of breeding marsh birds and priority waterfowl differ in eastern Canada

“…Favorable precipitation in key regions since the 1990s, particularly in the Prairies, has also helped boost productivity, and in turn, populations of many waterfowl species (US Fish & Wildlife Service 2020). By contrast, population trends and range for many marsh birds are declining (Correll et al 2016, Tozer 2016, Stevens and Conway 2020, McGowan et al 2020, prompting the question of why wetland conservation efforts have not had an equally positive impact on all wetland-dependent birds. The answer likely lies in differences in key habitat associations between these guilds.…”

Stability of patch‐turnover relationships under equilibrium and nonequilibrium metapopulation dynamics driven by biogeography

“…In comparison, the decline of the California black rail in the Sierra Foothills averaged 5% per year over the same time period. Nearly all surveys for the eastern black rail (McGowan et al, 2020 ) began after the arrival of WNV on the east coast of the US in 1999 and its rapid spread across the continent (Kramer et al, 2019 ). Wetland creation has been recommended for recovering the eastern black rail but could produce sink habitats unless the research is undertaken to understand the complex factors affecting the prevalence of WNV and its vectors (Kovach & Kilpatrick, 2018 ; Paull et al, 2017 ).…”