Consistent Extinction Risk Assessment under the U.S. Endangered Species Act

Using life-history trait variation to inform ecological risk assessments for threatened and endangered plant species

Developing population models for assessing risks to terrestrial plant species listed as threatened or endangered under the Endangered Species Act (ESA) is challenging given a paucity of data on their life histories. The purpose of this study was to develop a novel approach for identifying relatively data-rich nonlisted species that could serve as representatives for species listed under the ESA in the development of population models to inform risk assessments. We used the USDA PLANTS Database, which provides data on plants present in the US territories, to create a list of herbaceous plants. A total of 8742 species was obtained, of which 344 were listed under the ESA. Using the most up-to-date phylogeny for vascular plants in combination with a database of matrix population models for plants (COMPADRE) and cluster analyses, we investigated how listed species were distributed across the plant phylogeny, grouped listed and nonlisted species according to their life history, and identified the traits distinguishing the clusters. We performed elasticity analyses to determine the relative sensitivity of population growth rate to perturbations of species' survival, growth, and reproduction and compared these across clusters and between listed and nonlisted species. We found that listed species were distributed widely across the plant phylogeny as well as clusters, suggesting that listed species do not share a common evolution or life-history characteristics that would make them uniquely vulnerable. Lifespan and age at maturity were more important for distinguishing clusters than were reproductive traits. For clusters that were intermediate in their lifespan, listed and nonlisted species responded similarly to perturbations of their life histories. However, for clusters at either extreme of lifespan, the response to survival perturbations varied depending on conservation status. These results can be used to guide the choice of representative species for population model development in the context of ecological risk assessment. Integr Environ Assess Manag 2023;19:213-223. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Global population trends in shorebirds: migratory behaviour makes species at risk

Linking population trends to species' traits is informative for the detection of the most important threatening factors and for assessing the effectiveness of conservation measures. Although some previous studies performed such an analysis at local to continental scales, the global-scale focus is the most relevant for conservation of the entire species. Here we evaluate information on global population trends of shorebirds, a widely distributed and ecologically diversified group, where some species connect different parts of the world by migration, while others are residents. Nowadays, shorebirds face rapid environmental changes caused by various human activities and climate change. Numerous signs of regional population declines have been recently reported in response to these threats. The aim of our study was to test whether breeding and non-breeding habitats, migratory behaviour (migrants vs. residents) and migration distance, breeding latitude, generation time and breeding range size mirror species' global population trends. We found that a majority of shorebird species have declined globally. After accounting for the influence of traits and species taxonomy, linear mixed-effects models showed that populations of migratory shorebirds decreased more than populations of residents. Besides that, declines were more frequent for species breeding at high latitudes of the Northern Hemisphere, but these patterns did not hold after excluding the non-migratory species. Our findings suggest that factors linked to migration, such as habitat loss as well as deterioration at stop-over or wintering sites and a pronounced climate change impact at high latitudes, are possible drivers of the observed worldwide population decreases.

Predictability of demographic rates based on phylogeny and biological similarity

Lack of demographic data for most of the world's threatened species is a widespread problem that precludes viability-based status assessments for species conservation. A commonly suggested solution is to use data from species that are closely related or biologically similar to the focal species. This approach assumes similar species and populations of the same species have similar demographic rates, an assumption that has yet to be thoroughly tested. We constructed a Bayesian hierarchical model with data on 425 plant species to predict demographic rates (intrinsic rate of population growth, recruit survival, juvenile survival, adult survival, and fecundity) based on biological traits and phylogenetic relatedness. Generally, we found small effects of species-level traits (except woody polycarpic species tended to have high adult survival rates that increased with plant height) and a weak phylogenetic signal for 4 of the 5 demographic parameters examined. Patterns were stronger in adult survival and fecundity than other demographic rates; however, the unexplained variances at both the species and population levels were high for all demographic rates. For species lacking demographic data, our model produced large, often inaccurate, prediction intervals that may not be useful in a management context. Our findings do not support the assumption that biologically similar or closely related species have similar demographic rates and provide further evidence that direct monitoring of focal species and populations is necessary for informing conservation status assessments.

Development of a Species Status Assessment Process for Decisions under the U.S. Endangered Species Act

Decisions under the U.S. Endangered Species Act (ESA) require scientific input on the risk that the species will become extinct. A series of critiques on the role of science in ESA decisions have called for improved consistency and transparency in species risk assessments and clear distinctions between science input and policy application. To address the critiques and document the emerging practice of the U.S. Fish and Wildlife Service (USFWS), we outline an assessment process based on principles and practices of risk and decision analyses that results in a scientific report on species status. The species status assessment (SSA) process has three successive stages: 1) document the life history and ecological relationships of the species in question to provide the foundation for the assessment, 2) describe and hypothesize causes for the current condition of the species, and 3) forecast the species' future condition. The future condition refers to the ability of a species to sustain populations in the wild under plausible future scenarios. The scenarios help explore the species' response to future environmental stressors and to assess the potential for conservation to intervene to improve its status. The SSA process incorporates modeling and scenario planning for prediction of extinction risk and applies the conservation biology principles of representation, resiliency, and redundancy to evaluate the current and future condition. The SSA results in a scientific report distinct from policy application, which contributes to streamlined, transparent, and consistent decision-making and allows for greater technical participation by experts outside of the USFWS, for example, by state natural resource agencies. We present two case studies based on assessments of the eastern massasauga rattlesnake Sistrurus catenatus and the Sonoran Desert tortoise Gopherus morafkai to illustrate the process. The SSA builds upon the past threat-focused assessment by including systematic and explicit analyses of a species' future response to stressors and conservation, and as a result, we believe it provides an improved scientific analysis for ESA decisions.