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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.

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"White-nose syndrome is likely to extirpate the endangered Indiana bat over large parts of its range" (2013 a b s t r a c tWhite-nose syndrome, a novel fungal pathogen spreading quickly through cave-hibernating bat species in east and central North America, is responsible for killing millions of bats. We developed a stochastic, stage-based population model to forecast the population dynamics of the endangered Indiana bat (Myotis sodalis) subject to white-nose syndrome. Our population model explicitly incorporated environmentally imposed annual variability in survival and reproductive rates and demographic stochasticity in predictions of extinction. With observed rates of disease spread, >90% of wintering populations were predicted to experience white-nose syndrome within 20 years, causing the proportion of populations at the quasiextinction threshold of less than 250 females to increase by 33.9% over 50 years. At the species' lowest median population level, ca. year 2022, we predicted 13.7% of the initial population to remain, totaling 28,958 females (95% CI = 13,330; 92,335). By 2022, only 12 of the initial 52 wintering populations were expected to possess wintering populations of >250 females. If the species can acquire immunity to the disease, we predict 3.7% of wintering populations to be above 250 females after 50 years (year 2057) after a 69% decline in abundance (from 210,741 to 64,768 [95% CI = 49,386; 85,360] females). At the nadir of projections, we predicted regional quasi-extirpation of wintering populations in 2 of 4 Recovery Units while in a third region, where the species is currently most abundant, >95% of the wintering populations were predicted to be below 250 females. Our modeling suggests white-nose syndrome is capable of bringing about severe numerical reduction in population size and local and regional extirpation of the Indiana bat. Published by Elsevier Ltd.

ABSTRACT:Knowledge of current trends of quickly spreading infectious wildlife diseases is vital to efficient and effective management. We developed space-time mixed-effects logistic regressions to characterize a disease, white-nose syndrome (WNS), quickly spreading among endangered Indiana bats (Myotis sodalis) in eastern North America. Our goal was to calculate and map the risk probability faced by uninfected colonies of hibernating Indiana bats. Model covariates included annual distance from and direction to nearest sources of infection, geolocational information, size of the Indiana bat populations within each wintering population, and total annual size of populations known or suspected to be affected by WNS. We considered temporal, spatial, and spatiotemporal formulae through the use of random effects for year, complex (a collection of interacting hibernacula), and year3complex. Since first documented in 2006, WNS has spread across much of the range of the Indiana bat. No sizeable wintering population now occurs outside of the migrational distance of an infected source. Annual rates of newly affected wintering Indiana bat populations between winter 2007 to 2008 and 2010 to 2011 were 4, 6, 8, and 12%; this rate increased each year at a rate of 3%. If this increasing rate of newly affected populations continues, all wintering populations may be affected by 2016. Our models indicated the probability of a wintering population exhibiting infection was a linear function of proximity to affected Indiana bat populations and size of the at-risk population. Geographic location was also important, suggesting broad-scale influences. For every 50-km increase in distance from a WNS-affected population, risk of disease declined by 6% (95% CI55.2-5.7%); for every increase of 1,000 Indiana bats, there was an 8% (95% CI51-21%) increase in disease risk. The increasing rate of infection seems to be associated with the movement of this disease into the core of the Indiana bat range. Our spatially explicit estimates of disease risk may aid managers in prioritizing surveillance and management for wintering populations of Indiana bats and help understand the risk faced by other hibernating bat species.