Quantitative tools for implementing the new definition of significant portion of the range in the U.S. Endangered Species Act

In 2014, the Fish and Wildlife Service (FWS) and National Marine Fisheries Service announced a new policy interpretation for the U.S. Endangered Species Act (ESA). According to the act, a species must be listed as threatened or endangered if it is determined to be threatened or endangered in a significant portion of its range (SPR). The 2014 policy seeks to provide consistency by establishing that a portion of the range should be considered significant if the associated individuals’ “removal would cause the entire species to become endangered or threatened.” We reviewed 20 quantitative techniques used to assess whether a portion of a species’ range is significant according to the new guidance. Our assessments are based on the 3R criteria—redundancy (i.e., buffering from catastrophe), resiliency (i.e., ability to withstand stochasticity), and representation (i.e., ability to evolve)—that the FWS uses to determine if a species merits listing. We identified data needs for each quantitative technique and considered which methods could be implemented given the data limitations typical of rare species. We also identified proxies for the 3Rs that may be used with limited data. To assess potential data availability, we evaluated 7 example species by accessing data in their species status assessments, which document all the information used during a listing decision. In all species, an SPR could be evaluated with at least one metric for each of the 3Rs robustly or with substantial assumptions. Resiliency assessments appeared most constrained by limited data, and many species lacked information on connectivity between subpopulations, genetic variation, and spatial variability in vital rates. These data gaps will likely make SPR assessments for species with complex life histories or that cross national boundaries difficult. Although we reviewed techniques for the ESA, other countries require identification of significant areas and could benefit from this research.     

Geography and Recovery under the U.S. Endangered Species Act

Abstract: The U.S. Endangered Species Act (ESA) defines an endangered species as one “at risk of extinction throughout all or a significant portion of its range.” The prevailing interpretation of this phrase, which focuses exclusively on the overall viability of listed species without regard to their geographic distribution, has led to development of listing and recovery criteria with fundamental conceptual, legal, and practical shortcomings. The ESA's concept of endangerment is broader than the biological concept of extinction risk in that the “esthetic, ecological, educational, historical, recreational, and scientific” values provided by species are not necessarily furthered by a species mere existence, but rather by a species presence across much of its former range. The concept of “significant portion of range” thus implies an additional geographic component to recovery that may enhance viability, but also offers independent benefits that Congress intended the act to achieve. Although the ESA differs from other major endangered‐species protection laws because it acknowledges the distinct contribution of geography to recovery, it resembles the “representation, resiliency, and redundancy” conservation‐planning framework commonly referenced in recovery plans. To address representation, listing and recovery standards should consider not only what proportion of its former range a species inhabits, but the types of habitats a species occupies and the ecological role it plays there. Recovery planning for formerly widely distributed species (e.g., the gray wolf [Canis lupus]) exemplifies how the geographic component implicit in the ESA's definition of endangerment should be considered in determining recovery goals through identification of ecologically significant types or niche variation within the extent of listed species, subspecies, or “distinct population segments.” By linking listing and recovery standards to niche and ecosystem concepts, the concept of ecologically significant type offers a scientific framework that promotes more coherent dialogue concerning the societal decisions surrounding recovery of endangered species.     

Incorporating Climate Science in Applications of the U.S. Endangered Species Act for Aquatic Species

Aquatic species are threatened by climate change but have received comparatively less attention than terrestrial species. We gleaned key strategies for scientists and managers seeking to address climate change in aquatic conservation planning from the literature and existing knowledge. We address 3 categories of conservation effort that rely on scientific analysis and have particular application under the U.S. Endangered Species Act (ESA): assessment of overall risk to a species; long‐term recovery planning; and evaluation of effects of specific actions or perturbations. Fewer data are available for aquatic species to support these analyses, and climate effects on aquatic systems are poorly characterized. Thus, we recommend scientists conducting analyses supporting ESA decisions develop a conceptual model that links climate, habitat, ecosystem, and species response to changing conditions and use this model to organize analyses and future research. We recommend that current climate conditions are not appropriate for projections used in ESA analyses and that long‐term projections of climate‐change effects provide temporal context as a species‐wide assessment provides spatial context. In these projections, climate change should not be discounted solely because the magnitude of projected change at a particular time is uncertain when directionality of climate change is clear. Identifying likely future habitat at the species scale will indicate key refuges and potential range shifts. However, the risks and benefits associated with errors in modeling future habitat are not equivalent. The ESA offers mechanisms for increasing the overall resilience and resistance of species to climate changes, including establishing recovery goals requiring increased genetic and phenotypic diversity, specifying critical habitat in areas not currently occupied but likely to become important, and using adaptive management. Incorporación de las Ciencias Climáticas en las Aplicaciones del Acta Estadunidense de Especies en Peligro para Especies Acuáticas     

A Framework for Developing Objective and Measurable Recovery Criteria for Threatened and Endangered Species

For species listed under the U.S. Endangered Species Act (ESA), the U.S. Fish and Wildlife Service and National Marine Fisheries Service are tasked with writing recovery plans that include “objective, measurable criteria” that define when a species is no longer at risk of extinction, but neither the act itself nor agency guidelines provide an explicit definition of objective, measurable criteria. Past reviews of recovery plans, including one published in 2012, show that many criteria lack quantitative metrics with clear biological rationale and are not meeting the measureable and objective mandate. I reviewed how objective, measureable criteria have been defined implicitly and explicitly in peer‐reviewed literature, the ESA, other U.S. statutes, and legal decisions. Based on a synthesis of these sources, I propose the following 6 standards be used as minimum requirements for objective, measurable criteria: contain a quantitative threshold with calculable units, stipulate a timeframe over which they must be met, explicitly define the spatial extent or population to which they apply, specify a sampling procedure that includes sample size, specify a statistical significance level, and include justification by providing scientific evidence that the criteria define a species whose extinction risk has been reduced to the desired level. To meet these 6 standards, I suggest that recovery plans be explicitly guided by and organized around a population viability modeling framework even if data or agency resources are too limited to complete a viability model. When data and resources are available, recovery criteria can be developed from the population viability model results, but when data and resources are insufficient for model implementation, extinction risk thresholds can be used as criteria. A recovery‐planning approach centered on viability modeling will also yield appropriately focused data‐acquisition and monitoring plans and will facilitate a seamless transition from recovery planning to delisting. Un Marco de Referencia para Desarrollar Criterios de Recuperación Objetivos y Medibles para Especies Amenazadas y en Peligro     

Climate Change,Marine Environments,and the U.S. Endangered Species Act

Climate change is expected to be a top driver of global biodiversity loss in the 21st century. It poses new challenges to conserving and managing imperiled species, particularly in marine and estuarine ecosystems. The use of climate‐related science in statutorily driven species management, such as under the U.S. Endangered Species Act (ESA), is in its early stages. This article provides an overview of ESA processes, with emphasis on the mandate to the National Marine Fisheries Service (NMFS) to manage listed marine, estuarine, and anadromous species. Although the ESA is specific to the United States, its requirements are broadly relevant to conservation planning. Under the ESA, species, subspecies, and “distinct population segments” may be listed as either endangered or threatened, and taking of most listed species (harassing, harming, pursuing, wounding, killing, or capturing) is prohibited unless specifically authorized via a case‐by‐case permit process. Government agencies, in addition to avoiding take, must ensure that actions they fund, authorize, or conduct are not likely to jeopardize a listed species’ continued existence or adversely affect designated critical habitat. Decisions for which climate change is likely to be a key factor include: determining whether a species should be listed under the ESA, designating critical habitat areas, developing species recovery plans, and predicting whether effects of proposed human activities will be compatible with ESA‐listed species’ survival and recovery. Scientific analyses that underlie these critical conservation decisions include risk assessment, long‐term recovery planning, defining environmental baselines, predicting distribution, and defining appropriate temporal and spatial scales. Although specific guidance is still evolving, it is clear that the unprecedented changes in global ecosystems brought about by climate change necessitate new information and approaches to conservation of imperiled species. El Cambio Climático, los Ecosistemas Marinos y el Acta Estadunidense de Especies en Peligro     

Importance of Habitat Quality and Landscape Connectivity for the Persistence of Endangered Natterjack Toads

Abstract: The natterjack toad (Bufo calamita) is endangered in several parts of its distribution, including Belgium, where it occurs mainly in artificial habitats. We parameterized a general model for natterjack population viability analysis (PVA) and tested its sensitivity to changes in the values of basic parameters. Then we assessed the relative efficiency of various conservation measures in 2 situations: a small isolated population and a system of 4 populations connected by rare dispersal movements. We based the population viability analysis on a stage‐structured model of natterjack population dynamics. We parameterized the model in the RAMAS GIS platform with vital rates obtained from our own field experience and from published studies. Simulated natterjack populations were highly sensitive to habitat quality (particularly pond drying), to dispersal from surrounding local populations, and to a lesser extent to values of fecundity and survival of terrestrial stages. Population trajectories were nearly insensitive to initial abundances, carrying capacities, and the frequency of extreme climatic conditions. The simulations showed that in habitats with highly ephemeral ponds, where premetamorphosis mortality was high, natterjack populations nearly always had a very high extinction risk. We also illustrated how low dispersal rates (<1 dispersing individual/generation) efficiently rescued declining local populations. Such source‐sink dynamics demonstrate that the identification and management of source populations should be a high priority.     

Reexamining the Minimum Viable Population Concept for Long‐Lived Species

For decades conservation biologists have proposed general rules of thumb for minimum viable population size (MVP); typically, they range from hundreds to thousands of individuals. These rules have shifted conservation resources away from small and fragmented populations. We examined whether iteroparous, long‐lived species might constitute an exception to general MVP guidelines. On the basis of results from a 10‐year capture‐recapture study in eastern New York (U.S.A.), we developed a comprehensive demographic model for the globally threatened bog turtle (Glyptemys muhlenbergii), which is designated as endangered by the IUCN in 2011. We assessed population viability across a wide range of initial abundances and carrying capacities. Not accounting for inbreeding, our results suggest that bog turtle colonies with as few as 15 breeding females have >90% probability of persisting for >100 years, provided vital rates and environmental variance remain at currently estimated levels. On the basis of our results, we suggest that MVP thresholds may be 1–2 orders of magnitude too high for many long‐lived organisms. Consequently, protection of small and fragmented populations may constitute a viable conservation option for such species, especially in a regional or metapopulation context. Reexaminando el Concepto de Población Mínima Viable para Especies Longevas Resumen     

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas     

Inferring the nature of anthropogenic threats from long‐term abundance records

Diagnosing the processes that threaten species persistence is critical for recovery planning and risk forecasting. Dominant threats are typically inferred by experts on the basis of a patchwork of informal methods. Transparent, quantitative diagnostic tools would contribute much‐needed consistency, objectivity, and rigor to the process of diagnosing anthropogenic threats. Long‐term census records, available for an increasingly large and diverse set of taxa, may exhibit characteristic signatures of specific threatening processes and thereby provide information for threat diagnosis. We developed a flexible Bayesian framework for diagnosing threats on the basis of long‐term census records and diverse ancillary sources of information. We tested this framework with simulated data from artificial populations subjected to varying degrees of exploitation and habitat loss and several real‐world abundance time series for which threatening processes are relatively well understood: bluefin tuna (Thunnus maccoyii) and Atlantic cod (Gadus morhua) (exploitation) and Red Grouse (Lagopus lagopus scotica) and Eurasian Skylark (Alauda arvensis) (habitat loss). Our method correctly identified the process driving population decline for over 90% of time series simulated under moderate to severe threat scenarios. Successful identification of threats approached 100% for severe exploitation and habitat loss scenarios. Our method identified threats less successfully when threatening processes were weak and when populations were simultaneously affected by multiple threats. Our method selected the presumed true threat model for all real‐world case studies, although results were somewhat ambiguous in the case of the Eurasian Skylark. In the latter case, incorporation of an ancillary source of information (records of land‐use change) increased the weight assigned to the presumed true model from 70% to 92%, illustrating the value of the proposed framework in bringing diverse sources of information into a common rigorous framework. Ultimately, our framework may greatly assist conservation organizations in documenting threatening processes and planning species recovery. Inferencia la Naturaleza de las Amenazas Antropogénicas para los Registros de Abundancia a Largo Plazo     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

Population Viability Analysis with Species Occurrence Data from Museum Collections

Abstract: The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi‐extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available.     

Paradigms for parasite conservation

Parasitic species, which depend directly on host species for their survival, represent a major regulatory force in ecosystems and a significant component of Earth's biodiversity. Yet the negative impacts of parasites observed at the host level have motivated a conservation paradigm of eradication, moving us farther from attainment of taxonomically unbiased conservation goals. Despite a growing body of literature highlighting the importance of parasite‐inclusive conservation, most parasite species remain understudied, underfunded, and underappreciated. We argue the protection of parasitic biodiversity requires a paradigm shift in the perception and valuation of their role as consumer species, similar to that of apex predators in the mid‐20th century. Beyond recognizing parasites as vital trophic regulators, existing tools available to conservation practitioners should explicitly account for the unique threats facing dependent species. We built upon concepts from epidemiology and economics (e.g., host‐density threshold and cost‐benefit analysis) to devise novel metrics of margin of error and minimum investment for parasite conservation. We define margin of error as the risk of accidental host extinction from misestimating equilibrium population sizes and predicted oscillations, while minimum investment represents the cost associated with conserving the additional hosts required to maintain viable parasite populations. This framework will aid in the identification of readily conserved parasites that present minimal health risks. To establish parasite conservation, we propose an extension of population viability analysis for host–parasite assemblages to assess extinction risk. In the direst cases, ex situ breeding programs for parasites should be evaluated to maximize success without undermining host protection. Though parasitic species pose a considerable conservation challenge, adaptations to conservation tools will help protect parasite biodiversity in the face of an uncertain environmental future.     

Setting population targets for mammals using body mass as a predictor of population persistence

Conservation planning and biodiversity assessments need quantitative targets to optimize planning options and assess the adequacy of current species protection. However, targets aiming at persistence require population‐specific data, which limit their use in favor of fixed and nonspecific targets, likely leading to unequal distribution of conservation efforts among species. We devised a method to derive equitable population targets; that is, quantitative targets of population size that ensure equal probabilities of persistence across a set of species and that can be easily inferred from species‐specific traits. In our method, we used models of population dynamics across a range of life‐history traits related to species’ body mass to estimate minimum viable population targets. We applied our method to a range of body masses of mammals, from 2 g to 3825 kg. The minimum viable population targets decreased asymptotically with increasing body mass and were on the same order of magnitude as minimum viable population estimates from species‐ and context‐specific studies. Our approach provides a compromise between pragmatic, nonspecific population targets and detailed context‐specific estimates of population viability for which only limited data are available. It enables a first estimation of species‐specific population targets based on a readily available trait and thus allows setting equitable targets for population persistence in large‐scale and multispecies conservation assessments and planning.