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Emerging infectious disease outbreaks are one of multiple stressors responsible for amphibian declines globally. In the northeastern United States, ranaviral diseases are prevalent in amphibians and other ectothermic species, but there is still uncertainty as to whether their presence is leading to population-level effects. Further, there is also uncertainty surrounding the potential interactions among disease infection prevalence in free-ranging animals and habitat degradation (co-occurrence of chemical stressors). The present study was designed to provide field-based estimates of the relationship between amphibian disease and chemical stressors. We visited 40 wetlands across three protected areas, estimated the prevalence of ranavirus among populations of larval wood frogs and spotted salamanders, and assessed chemical and biological stressors in wetland habitats and larval amphibians using a suite of selected bioassays, screening tools, and chemical analyses. Ranavirus was detected on larval amphibians from each protected area with an estimated occupancy ranging from 0.27 to 0.55. Considerable variation in ranavirus occupancy was also observed within and among each protected area. Of the stressors evaluated, ranavirus prevalence was strongly and positively related to concentrations of metalloestrogens (metals with the potential to bind to estrogen receptors) and total metals in wetland sediments and weakly and negatively related to total pesticide concentrations in larval amphibians. These results can be used by land managers to refine habitat assessments to include such environmental factors with the potential to influence disease susceptibility. Environ Toxicol Chem 2022;41:781-791. © 2022 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Comparative studies of mortality in the wild are necessary to understand the evolution of aging; yet, ectothermic tetrapods are underrepresented in this comparative landscape, despite their suitability for testing evolutionary hypotheses. We present a study of aging rates and longevity across wild tetrapod ectotherms, using data from 107 populations (77 species) of nonavian reptiles and amphibians. We test hypotheses of how thermoregulatory mode, environmental temperature, protective phenotypes, and pace of life history contribute to demographic aging. Controlling for phylogeny and body size, ectotherms display a higher diversity of aging rates compared with endotherms and include phylogenetically widespread evidence of negligible aging. Protective phenotypes and life-history strategies further explain macroevolutionary patterns of aging. Analyzing ectothermic tetrapods in a comparative context enhances our understanding of the evolution of aging.

We conducted a national-scale assessment of mercury (Hg) bioaccumulation in aquatic ecosystems, using dragonfly larvae as biosentinels, by developing a citizen-science network to facilitate biological sampling. Implementing a carefully designed sampling methodology for citizen scientists, we developed an effective framework for a landscape-level inquiry that might otherwise be resource limited. We assessed the variation in dragonfly Hg concentrations across >450 sites spanning 100 United States National Park Service units and examined intrinsic and extrinsic factors associated with the variation in Hg concentrations. Mercury concentrations ranged between 10.4 and 1411 ng/g dry weight across sites and varied among habitat types. Dragonfly total Hg (THg) concentrations were up to 1.8-fold higher in lotic habitats than in lentic habitats and 37% higher in waterbodies with abundant wetlands along their margins than those without wetlands. Mercury concentrations in dragonflies differed among families but were correlated (r2 > 0.80) with each other, enabling adjustment to a consistent family to facilitate spatial comparisons among sampling units. Dragonfly THg concentrations were positively correlated with THg concentrations in both fish and amphibians from the same locations, indicating that dragonfly larvae are effective indicators of Hg bioavailability in aquatic food webs. We used these relationships to develop an integrated impairment index of Hg risk to aquatic ecosytems and found that 12% of site-years exceeded high or severe benchmarks of fish, wildlife, or human health risk. Collectively, this continental-scale study demonstrates the utility of dragonfly larvae for estimating the potential mercury risk to fish and wildlife in aquatic ecosystems and provides a framework for engaging citizen science as a component of landscape Hg monitoring programs.

Habitat fragmentation can alter species distributions and lead to reduced diversity at multiple scales. Yet, the literature describing fragmentation effects on biodiversity patterns is contradictory, possibly because most studies fail to integrate spatial scale into experimental designs and statistical analyses. Thus, it is difficult to extrapolate the effects of fragmentation to large-scaled systems in which conservation management is of immediate importance. To examine the influence of fragmentation on biodiversity across scales, we (1) estimated the effects of habitat area, connectivity, and quality at both local (i.e. community) and regional (i.e. metacommunity) scales; and (2) evaluated the direction, magnitude, and precision of these estimates at both spatial scales. We developed a multi-region community occupancy model to analyze 13 years (2005–2017) of amphibian monitoring data within the National Capital Region, a network of U.S. National Parks. Overall, we found a positive effect of park size and a negative effect of isolation on species richness at the park-level (i.e. metacommunity), and generally positive effects of wetland area, connectivity, and quality on species richness at the wetland-level (i.e. community), although parameter estimates varied among species. Covariate effects were less precise, but effect sizes were larger, at the local wetland-level as compared to the park-level scale. Our analysis reveals how scale can mediate interpretation of results from scientific studies, which might help explain conflicting narratives concerning the impacts of fragmentation in the literature. Our hierarchical framework can help managers and policymakers elucidate the relevant spatial scale(s) to target conservation efforts.

The frog-killing fungus Batrachochytrium dendrobatidis (Bd) grows within the mucus-coated skin of amphibians. Each lifecycle, Bd transitions from its motile, dispersal form to its sessile growth form in a complex process called encystation. Although encystation is critical to Bd growth, whether and how this developmental transition is triggered by external signals was previously unknown. We discovered that exposure to amphibian mucus triggers rapid and reproducible encystation within minutes. This response can be recapitulated with purified mucin, the bulk component of mucus, but not by similarly-viscous methylcellulose or simple sugars. Mucin-induced encystation does not require gene expression, but does require surface adhesion, calcium signaling, and modulation of the actin cytoskeleton. Mucus-induced encystation may represent a key mechanism for synchronizing Bd development with arrival at the host.

Dedicated long-term monitoring at appropriate spatial and temporal scales is necessary to understand biodiversity losses and develop effective conservation plans. Wildlife monitoring is often achieved by obtaining data at a combination of spatial scales, ranging from local to broad, to understand the status, trends, and drivers of individual species or whole communities and their dynamics. However, limited resources for monitoring necessitates tradeoffs in the scope and scale of data collection. Careful consideration of the spatial and temporal allocation of finite sampling effort is crucial for monitoring programs that span multiple spatial scales. Here we evaluate the ability of five monitoring designs-stratified random, weighted effort, indicator unit, rotating panel, and split panel-to recover parameter values that describe the status (occupancy), trends (change in occupancy), and drivers (spatially varying covariate and an autologistic term) of wildlife communities at two spatial scales. Using an amphibian monitoring program that spans a network of US national parks as a motivating example, we conducted a simulation study for a regional community occupancy sampling program to compare the monitoring designs across varying levels of sampling effort (ranging from 10% to 50%). We found that the stratified random design outperformed the other designs for most parameters of interest at both scales and was thus generally preferable in balancing the estimation of status, trends, and drivers across scales. However, we found that other designs had improved performance in specific situations. For example, the rotating panel design performed best at estimating spatial drivers at a regional level. Thus, our results highlight the nuanced scenarios in which various design strategies may be preferred and offer guidance as to how managers can balance common tradeoffs in large-scale and long-term monitoring programs in terms of the specific knowledge gained. Monitoring designs that improve accuracy in parameter estimates are needed to guide conservation policy and management decisions in the face of broad-scale environmental challenges, but the preferred design is sensitive to the specific objectives of a monitoring program.

Delaying species management reduces the chance of successful recovery, increases the risk of extinction, and can be expensive. Acting before major declines are realized affords access to a greater suite of cost-effective management actions to sustain populations, reducing the likelihood of declines warranting protected status. It is clear that reactive management approaches are not sufficient for amphibian conservation and a successful path forward will require proactive approaches. We describe how conservation timelines and structured decision making can help evaluate management options available to species given current, and often limited, knowledge about populations or distributions. We illustrate this framework by highlighting science and management of common and widespread amphibians, as many species are in decline, including those found in protected conservation areas. Formal decision-making processes require the development of explicit management objectives, management triggers, and evaluation of the cost-effectiveness of actions before species' declines are observed. These steps guide the science needed to inform decisions.

Natural resource managers are increasingly faced with threats to managed ecosystems that are largely outside of their control. Examples include land development, climate change, invasive species, and emerging infectious diseases. All of these are characterized by large uncertainties in timing, magnitude, and effects on species. In many cases, the conservation of species will only be possible through concerted action on the limited elements of the system that managers can control. However, before an action is taken, a manager must decide how to act, which is, if done well, not easy. In addition to dealing with uncertainty, managers must balance multiple potentially competing objectives, often in cases when the management actions available to them are limited. Guidance in making these types of challenging decisions can be found in the practice known as decision analysis. We demonstrate how using a decision-analytic approach to frame decisions can help identify and address impediments to improved conservation decision making. We demonstrate the application of decision analysis to two high-elevation amphibian species. An inadequate focus on the decision-making process, and an assumption that scientific information is adequate to solve conservation problems, must be overcome to advance the conservation of amphibians and other highly threatened taxa.

Wood frogs, like other amphibian species worldwide, are experiencing population declines due to multiple stressors. In the northeastern United States, wood frog declines are thought to result from a reduction in successful metamorphosis in part due to climate change, disease (specifically ranavirus), and contaminant exposure. The presence of multiple stressors can increase uncertainty in characterizing the main effects of each stressor, as well as understanding the degree to which their effects interact (additively or synergistically) to impact populations. This uncertainty adds inherent challenges to selecting appropriate management actions for conserving populations. Finding solutions that are robust to these uncertainties can improve management amid absent or equivocal knowledge. We used a Bayesian Belief Network (BBN), a quantitative tool that allowed us to evaluate how potential management actions might mitigate the effects of increasingly frequent and severe droughts, ranavirus exposure, and methylmercury on wood frog populations in the northeastern U.S. In our system, successful wood frog recruitment was largely driven by hydroperiod regardless of other stressors. Our modelling indicated that increased hydroperiod lowered the probability of complete metamorphosis failure from 0.6 to 0.37, suggesting that under the conditions tested in the model, pond hydrology is more important for successful recruitment than either methylmercury or ranavirus exposure. As more information becomes available on stressor interactions, model scenarios could be re-evaluated, and management options reconsidered.

Research is necessary to identify patterns in nature, to understand how a system functions, and to make predictions about the future state of an ecosystem. Applied research in conservation biology can identify effective strategies to maintain biodiversity, though many papers end with the conclusion that more research is needed. However, more research does not necessarily lead to solutions. We use the ongoing global decline of amphibians as a salient example to highlight limitations in current conservation research, and to focus on finding solutions which are directly relevant for conservation. While research has been conducted since declines were first detected in the 1990s, outside a few specific examples, little progress in conservation has been achieved. We suggest that the case of amphibian declines is relevant to conservation science in general, as the current paradigm for conservation is that management is planned after research is completed; research and management are not effectively (and not directly) connected. This disconnect illustrates the knowledge-action divide which has been identified as a serious deficiency in conservation. Accordingly, we use this introductory paper to the Special Issue (Amphibian conservation in the Anthropocene: Progress and challenges) to describe amphibians as a conservation dilemma, and to make the case for a different, more pragmatic, and more solutions-focused view of conservation research.

Despite increasing interest in determining the population-level effects of emerging infectious diseases on wildlife, estimating effects of disease on survival rates remains difficult. Even for a well-studied disease such as amphibian chytridiomycosis (caused by the fungus Batrachochytrium dendrobatidis [Bd]), there are few estimates of how survival of wild hosts is affected. We applied hierarchical models to long-term capture-mark-recapture data (mean = 10.6 yrs, range = 6–15 yrs) from >5500 uniquely-marked individuals to estimate the effect of Bd on apparent survival of four threatened or endangered ranid frog species (Rana draytonii, R. muscosa, R. pretiosa, R. sierrae) at 14 study sites in California and Oregon (USA) and one bufonid toad (Anaxyrus boreas) at two study sites in Wyoming and Montana. Our models indicated that the presence of Bd on an individual reduced apparent survival of ranid frogs by ~6–15% depending on species and sex. The estimated difference between toads with and without Bd was 19% for the Montana population and 55% for the Wyoming population; however, the 95% Credible Interval of these estimates included zero. These results provide evidence for negative effects of Bd on survival in wild populations even in the absence of obvious die-offs. Determining what factors influence the magnitude of the effects of Bd on wildlife populations is an important next step toward identifying management actions. These estimates of Bd effects are important for understanding the extent and severity of disease, whether disease effects have changed over time, and for informing management actions.

Emerging infectious diseases (EIDs) of wildlife have characteristics that make them difficult to manage, leading to reactive and often ineffective management strategies. Currently, two fungal patho...

Species with narrow environmental tolerances are often distributed within fragmented patches of suitable habitat, and dispersal among these subpopulations can be difficult to directly observe. Genetic data can help quantify gene flow between localities, which is especially important for vulnerable species with a disjunct range. The Shenandoah salamander (Plethodon shenandoah) is a federally endangered species known only from three mountaintops in Virginia, USA. To reconstruct the evolutionary history and population connectivity of this species, we generated both mitochondrial and nuclear data using sequence capture from individuals collected across all three mountaintops. Applying population and landscape genetic methods, we found strong population structure that was independent of geographic distance. Both the nuclear markers and mitochondrial genomes indicated a deep split between the most southern population and the genetically similar central and northern populations. Although there was some mitochondrial haplotype-splitting between the central and northern populations, there was admixture in nuclear markers. This is indicative of either a recent split or current male-biased dispersal among mountain isolates. Models of landscape resistance found that dispersal across north-facing slopes at mid-elevation levels best explain the observed genetic structure among populations. These unexpected results highlight the importance of incorporating landscape features in understanding and predicting the movement and fragmentation of this range-restricted salamander species across space.

Roadside amphibian citizen science (CS) programmes bring together volunteers focused on collecting scientific data while working to mitigate population declines by reducing road mortality of pond‐breeding amphibians. Despite the international popularity of these movement‐based, roadside conservation efforts (i.e. “big nights,” “bucket brigades” and “toad patrols”), direct benefits to conservation have rarely been quantified or evaluated. As a case study, we used a population simulation approach to evaluate how volunteer intensity, frequency and distribution influence three conservation outcomes (minimum population size, population growth rate and years to extinction) of the spotted salamander (Ambystoma maculatum), often a focal pond‐breeding amphibian of CS and conservation programmes in the United States. Sensitivity analysis supported the expectation that spotted salamander populations were primarily recruitment‐driven. Thus, conservation outcomes were highest when volunteers focused on metamorph outmigration as opposed to adult in‐migration—contrary to the typical timing of such volunteer events. Almost every volunteer strategy resulted in increased conservation outcomes compared to a no‐volunteer strategy. Specifically, volunteer frequency during metamorph migration increased outcomes more than the same increases in volunteer effort during adult migration. Small population sizes resulted in a negligible effect of volunteer intensity. Volunteers during the first adult in‐migration had a relatively small effect compared to most other strategies. Synthesis and applications. Although citizen science (CS)‐focused conservation actions could directly benefit declining populations, additional conservation measures are needed to halt or reverse local amphibian declines. This study demonstrates a need to evaluate the effectiveness of focusing CS mitigation efforts on the metamorph stage, as opposed to the adult stage. This may be challenging, compared to other management actions such as road‐crossing infrastructure. Current amphibian CS programmes will be challenged to balance implementing evidence‐based conservation measures on the most limiting life stage, while retaining social and community benefits for volunteers.

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.

The Dragonfly Mercury Project (DMP) is a dynamic national scale program coupling scientific efforts to understand mercury pollution risks to protected areas with citizen engagement and education. W...

This research was funded by the National Institute of Food and Agriculture, accession 1009581. This is a contribution of the Salamander Population and Adaptation Network (SPARCnet) and contribution #767 of the U.S. Geological Survey’s Amphibian Research and Monitoring Initiative (ARMI). A principal challenge impeding strong inference in analyses of wild populations is the lack of robust and long-term data sets. Recent advancements in analytical tools used in wildlife science may increase our ability to integrate smaller data sets and enhance the statistical power of population estimates. One such advancement, the development of spatial capture-recapture (SCR) methods, explicitly accounts for differences in spatial study designs, making it possible to equate multiple study designs in one analysis. SCR has been shown to be robust to variation in design as long as minimal sampling guidance is adhered to. However, these expectations are based on simulation and have yet to be evaluated in wild populations. Here we conduct a rigorously designed field experiment by manipulating the arrangement of artificial cover objects (ACOs) used to collect data on red-backed salamanders (Plethodon cinereus) to empirically evaluate the effects of design configuration on inference made using SCR. Our results suggest that, using SCR, estimates of space use and detectability are sensitive to study design configuration, namely the spacing and extent of the array, and that caution is warranted when assigning biological interpretation to these parameters. However, estimates of population density remain robust to design except when the configuration of detectors grossly violates existing recommendations. Publisher PDF

The virus that causes COVID‐19 likely evolved in a mammalian host, possibly Old‐World bats, before adapting to humans, raising the question of whether reverse zoonotic transmission to bats is possible. Wildlife management agencies in North America are concerned that the activities they authorize could lead to transmission of SARS‐CoV‐2 to bats from humans. A rapid risk assessment conducted in April 2020 suggested that there was a small but significant possibility that SARS‐CoV‐2 could be transmitted from humans to bats during summer fieldwork, absent precautions. Subsequent challenge studies in a laboratory setting have shed new information on these risks, as has more detailed information on human epidemiology and transmission. This inquiry focuses on the risk to bats from winter fieldwork, specifically surveys of winter roosts and handling of bats to test for white‐nose syndrome or other research needs. We use an aerosol transmission model, with parameter estimates both from the literature and from formal expert judgment, to estimate the risk to three species of North American bats, as a function of several factors. We find that risks of transmission are lower than in the previous assessment and are notably affected by chamber volume and local prevalence of COVID‐19. Use of facemasks with high filtration efficiency or a negative COVID‐19 test before field surveys can reduce zoonotic risk by 65 to 88%.

First-order dynamic occupancy models (FODOMs) are a class of state-space model in which the true state (occurrence) is observed imperfectly. An important assumption of FODOMs is that site dynamics only depend on the current state and that variations in dynamic processes are adequately captured with covariates or random effects. However, it is often difficult to understand and/or measure the covariates that generate ecological data, which are typically spatio-temporally correlated. Consequently, the non-independent error structure of correlated data causes underestimation of parameter uncertainty and poor ecological inference. Here, we extend the FODOM framework with a second-order Markov process to accommodate site memory when covariates are not available. Our modeling framework can be used to make reliable inference about site occupancy, colonization, extinction, turnover, and detection probabilities. We present a series of simulations to illustrate the data requirements and model performance. We then applied our modeling framework to 13 years of data from an amphibian community in southern Arizona, USA. In this analysis, we found residual temporal autocorrelation of population processes for most species, even after accounting for long-term drought dynamics. Our approach represents a valuable advance in obtaining inference on population dynamics, especially as they relate to metapopulations.

Emerging infectious diseases can result in species declines and hamper recovery efforts for at-risk populations. Generalizing recommendations for reducing the risk of pathogen introduction and mitigating the effects of disease remains challenging and inhibits our ability to provide guidance for species recovery planning. Given the growing rates of emerging pathogens globally, we identify key principles and mechanisms for maintaining sustainable populations in the face of emerging diseases (including minimizing the risk of pathogen introductions and their future impacts on hosts). Our synthesis serves as a reference for minimizing the risk of future disease outbreaks, mitigating the deleterious effects of future disease outbreaks on species extinction risk, and a review of the theoretical and/or empirical examples supporting these recommendations.

The novel beta-coronavirus, SARS-CoV-2, may pose a threat to North American bat populations if bats are exposed to the virus through interaction with humans, if the virus can subsequently infect bats and be transmitted among them, and if the virus causes morbidity or mortality in bats Further, if SARS-CoV-2 became established in bat populations, it could possibly serve as a source for new infection in humans, domesticated animals, or other wild animals Wildlife management agencies in the United States are concerned about these potential risks and have begun to issue guidance regarding work that brings humans into contact with bats, but decision making is difficult because of the high degree of uncertainty about many of the relevant processes that could lead to virus transmission and establishment The risk assessment described in this report was undertaken to provide management agencies with an understanding of the likelihood that the various steps in the causal pathways would lead to SARS-CoV-2 infection of North American bats from people This assessment focused on the active season for bats in the temperate zone of North America (April 15 through November 15), and used Myotis lucifugus (little brown bats) as a surrogate species At the time of this work (April 2020), no empirical data about the effects of SARS-CoV-2 on North American bats were available, so a formal process of expert judgment was used to elicit estimates of the underlying parameters Twelve experts in bat ecology, epidemiology, virology, and wildlife disease from the United States, United Kingdom, and Australia participated in the elicitation A Monte Carlo simulation model was used to integrate the parameter estimates elicited from the experts and to predict the likelihood of exposure and infection in bats through a series of transmission pathways, with particular attention to capturing uncertainty in the predictions Given the current state of knowledge as expressed by the expert panel, the results of this assessment indicate that there is a non-negligible risk of transmission of SARS-CoV-2 from humans to bats For example, if a research scientist were shedding SARS-CoV-2 virus while handling bats under the field protocols used in North America prior to the COVID-19 pandemic, the risk model indicates that 50 percent (uncertainty, 15-84 percent) of those bats could be exposed to virus, and 17 percent (uncertainty, 3-51 percent) could become infected Use of personal protective equipment, especially a respirator, is expected to reduce the exposure risk The expert panel estimated that exposure risk from research scientists could be reduced 94-96 percent (uncertainty, 86-99 percent) through proper use of appropriate N95 respirators (a type of mechanical filter worn over the nose and mouth), dedicated clothing (such as Tyvek coveralls), and gloves Should any North American bats become infected with SARS-CoV-2, the expert panel estimated that there is an approximately 33-percent chance the virus could spread within a bat population This study, conducted by the U S Geological Survey in cooperation with the U S Fish and Wildlife Service, identified several critical uncertainties that could affect the estimate of risks associated with SARS-CoV-2 entering bat populations- notably, the underlying probability that a human would be shedding virus while working with bats, the likelihood of the virus replicating in bat tissue, and the likelihood of transmission of the virus within bat populations Ongoing empirical work during May-October 2020 may shed light on these issues Follow-up work is needed to better understand the probability of transmission of SARS-CoV-2 to bats from the general public;the manner in which the probabilities of exposure, infection, and transmission would differ during hibernation compared to the breeding season;and the likelihood of important effects, like morbidity and mortality in bats, the possibility of zoonosis from a North American bat reservoir, and effects of and on other wildlife

Population projection models are important tools for conservation and management. They are often used for population status assessments, for threat analyses, and to predict the consequences of conservation actions. Although conservation decisions should be informed by science, critical decisions are often made with very little information to support decision-making. Conversely, postponing decisions until better information is available may reduce the benefit of a conservation decision. When empirical data are limited or lacking, expert elicitation can be used to supplement existing data and inform model parameter estimates. The use of rigorous techniques for expert elicitation that account for uncertainty can improve the quality of the expert elicited values and therefore the accuracy of the projection models. One recurring challenge for summarizing expert elicited values is how to aggregate them. Here, we illustrate a process for population status assessment using a combination of expert elicitation and data from the ecological literature. We discuss the importance of considering various aggregation techniques, and illustrate this process using matrix population models for the wood turtle (Glyptemys insculpta) to assist U.S. Fish and Wildlife Service decision-makers with their Species Status Assessment. We compare estimates of population growth using data from the ecological literature and four alternative aggregation techniques for the expert-elicited values. The estimate of population growth rate based on estimates from the literature (λ

Temporary wetlands have value to both ecological and social systems. Interactions between local climate and the surrounding landscape result in patterns of hydrology that are unique to temporary wetlands. These seasonal and annual fluctuations in wetland inundation contribute to community composition and richness. Thus, predicting wetland community responses to environmental change is tied to the ability to predict wetland hydroregime. Detailed monitoring of wetland hydroregime is resource-intensive, limiting the scope and scale of forecasting. As an alternative, we determine which freely available measures of water availability best predict one component of wetland hydroregime, habitat suitability (i.e., the predictability of water in a wetland) within and among geographic regions. We used data from three North American regions to determine the climate index that best explained year-to-year variation in habitat suitability during a key phenological period—amphibian breeding. We demonstrate that simple, short-term climate indices based solely on precipitation data best predict habitat suitability in vernal pools in the northeast, montane wetlands in the west and coastal plain wetlands in the southeast. These relationships can help understand how changes in short-term precipitation patterns as a result of climate change may influence the overall hydroregime, and resulting biodiversity, of temporary wetlands across disparate biomes.