Reframing wildlife disease management problems with decision analysis.

Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade-offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision-making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision-making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision-making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white-nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision-making, including competing objectives, risks, prediction uncertainty, and limited resources.

Replanteamiento del manejo de problemas por enfermedades de fauna mediante el análisis de decisiones Resumen El manejo actual de las enfermedades de la fauna es complejo debido a que los gestores necesitan responder a una amplia gama de actores, varias incertidumbres y compensaciones difíciles que caracterizan los retos interconectados del día de hoy. A pesar de que en general se reconocen estas complejidades, el manejo de las enfermedades tiende a plantearse como un problema científico en el que el principal obstáculo es la falta de conocimiento. El proceso complejo y multifactorial de la toma decisiones está colapsado dentro de un esfuerzo científico para reducir la incertidumbre. Como resultado de esto, las decisiones contemporáneas pueden estar simplificadas en exceso, depender de métodos heurísticos simples y no considerar el contexto legal, social y económico más amplio en el que se toman las decisiones. De manera paralela, las investigaciones científicas sobre las enfermedades de la fauna pueden estar lejos de este contexto de decisiones, lo que deriva en información que puede no ser directamente relevante para las preguntas pertinentes de manejo. Proponemos replantear los obstáculos para el manejo de enfermedades de fauna como problemas de decisión y abordarlos con herramientas analíticas de decisión para dividir los problemas complejos en elementos más manejables de manera cognitiva. En particular, las decisiones estructuradas tienen el potencial de mejorar la calidad, el rigor y la transparencia de las decisiones sobre las enfermedades de la fauna en una variedad de sistemas. Ejemplos como el manejo del coronavirus del síndrome de respiración agudo tipo 2, el síndrome de nariz blanca, la influenza aviar y la quitridiomicosis ilustran los impedimentos más comunes para la toma de decisiones, incluyendo los objetivos en competencia, riesgos, incertidumbre en las predicciones y recursos limitados.

Updated range map of an endangered salamander and congeneric competitor reveals different niche preferences.

Estimating distributions for cryptic and highly range-restricted species induces unique challenges for species distribution modeling. In particular, bioclimatic covariates that are typically used to model species ranges at regional and continental scales may not show strong variation at scales of 100s and 10s of meters. This limits both the likelihood and usefulness of correlated occurrence to data typically used in distribution models. Here, we present analyses of species distributions, at 100 × 100 m resolution, for a highly range restricted salamander species (Shenandoah salamander, Plethodon shenandoah) and a closely related congener (red-backed salamander, Plethodon cinereus). We combined data across multiple survey types, account for seasonal variation in availability of our target species, and control for repeated surveys at locations- all typical challenges in range-scale monitoring datasets. We fit distribution models using generalized additive models that account for spatial covariates as well as unexplained spatial variation and spatial uncertainty. Our model accommodates different survey protocols using offsets and incorporates temporal variation in detection and availability resulting from survey-specific variation in temperature and precipitation. Our spatial random effect was crucial in identifying small-scale differences in the occurrence of each species and provides cell-specific estimates of uncertainty in the density of salamanders across the range. Counts of both species were seen to increase in the 3 days following a precipitation event. However, P. cinereus were observed even in extremely wet conditions, while surface activity of P. shenandoah was associated with a more narrow range. Our results demonstrate how a flexible analytical approach improves estimates of both distribution and uncertainty, and identify key abiotic relationships, even at small spatial scales and when scales of empirical data are mismatched. While our approach is especially valuable for species with small ranges, controlling for spatial autocorrelation, estimating spatial uncertainty, and incorporating survey-specific information in estimates can improve the reliability of distribution models in general.

A Dataset of Amphibian Species in U.S. National Parks.

National parks and other protected areas are important for preserving landscapes and biodiversity worldwide. An essential component of the mission of the United States (U.S.) National Park Service (NPS) requires understanding and maintaining accurate inventories of species on protected lands. We describe a new, national-scale synthesis of amphibian species occurrence in the NPS system. Many park units have a list of amphibian species observed within their borders compiled from various sources and available publicly through the NPSpecies platform. However, many of the observations in NPSpecies remain unverified and the lists are often outdated. We updated the amphibian dataset for each park unit by collating old and new park-level records and had them verified by regional experts. The new dataset contains occurrence records for 292 of the 424 NPS units and includes updated taxonomy, international and state conservation rankings, hyperlinks to a supporting reference for each record, specific notes, and related fields which can be used to better understand and manage amphibian biodiversity within a single park or group of parks.

Broad-Scale Assessment of Methylmercury in Adult Amphibians.

Mercury (Hg) is a toxic contaminant that has been mobilized and distributed worldwide and is a threat to many wildlife species. Amphibians are facing unprecedented global declines due to many threats including contaminants. While the biphasic life history of many amphibians creates a potential nexus for methylmercury (MeHg) exposure in aquatic habitats and subsequent health effects, the broad-scale distribution of MeHg exposure in amphibians remains unknown. We used nonlethal sampling to assess MeHg bioaccumulation in 3,241 juvenile and adult amphibians during 2017-2021. We sampled 26 populations (14 species) across 11 states in the United States, including several imperiled species that could not have been sampled by traditional lethal methods. We examined whether life history traits of species and whether the concentration of total mercury in sediment or dragonflies could be used as indicators of MeHg bioaccumulation in amphibians. Methylmercury contamination was widespread, with a 33-fold difference in concentrations across sites. Variation among years and clustered subsites was less than variation across sites. Life history characteristics such as size, sex, and whether the amphibian was a frog, toad, newt, or other salamander were the factors most strongly associated with bioaccumulation. Total Hg in dragonflies was a reliable indicator of bioaccumulation of MeHg in amphibians (R2 ≥ 0.67), whereas total Hg in sediment was not (R2 ≤ 0.04). Our study, the largest broad-scale assessment of MeHg bioaccumulation in amphibians, highlights methodological advances that allow for nonlethal sampling of rare species and reveals immense variation among species, life histories, and sites. Our findings can help identify sensitive populations and provide environmentally relevant concentrations for future studies to better quantify the potential threats of MeHg to amphibians.

"It's a Living Experience": Bereavement by Suicide in Later Life.

Bereavement by suicide for people in later life is significantly under-researched. Research on ageing and suicide has yet to address the experiences of those bereaved by suicide and how such a devastating loss affects the ageing experience. Objectives: We explored the substantive issues involved in bereavement by suicide and its impact on later life. Methods: This was a co-produced qualitative study. Peer researchers with lived experience conducted in-depth interviews with twenty-four people aged 60-92 years. A phenomenological approach informed the data analysis. Main Findings: Themes described included (1) moral injury and trauma; (2) the rippling effect on wider family and networks; (3) transitions and adaptations of bereaved people and how their 'living experience' impacted on ageing. Conclusions: It is important to understand how individual experiences of suicide intersect with ageing and the significance of targeted assessment and intervention for those bereaved by suicide in ageing policies and support.

Amphibian mucus triggers a developmental transition in the frog-killing chytrid fungus.

The frog-killing chytrid fungus Batrachochytrium dendrobatidis (Bd) is decimating amphibian populations around the world.1-4Bd has a biphasic life cycle, alternating between motile zoospores that disperse within aquatic environments and sessile sporangia that grow within the mucus-coated skin of amphibians.5,6 Zoospores lack cell walls and swim rapidly through aquatic environments using a posterior flagellum and crawl across solid surfaces using actin structures similar to those of human cells.7,8Bd transitions from this motile dispersal form to its reproductive form by absorbing its flagellum, rearranging its actin cytoskeleton, and rapidly building a chitin-based cell wall-a process called "encystation."5-7 The resulting sporangium increases in volume by two or three orders of magnitude while undergoing rounds of mitosis without cytokinesis to form a large ceonocyte. The sporangium then cellurizes by dividing its cytoplasm into dozens of new zoospores. After exiting the sporangium through a discharge tube onto the amphibian skin, daughter zoospores can then reinfect the same individual or find a new host.5 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 the arrival at the host.

A comparison of monitoring designs to assess wildlife community parameters across spatial scales.

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.

Geographic variation and thermal plasticity shape salamander metabolic rates under current and future climates.

Predicted changes in global temperature are expected to increase extinction risk for ectotherms, primarily through increased metabolic rates. Higher metabolic rates generate increased maintenance energy costs which are a major component of energy budgets. Organisms often employ plastic or evolutionary (e.g., local adaptation) mechanisms to optimize metabolic rate with respect to their environment. We examined relationships between temperature and standard metabolic rate across four populations of a widespread amphibian species to determine if populations vary in metabolic response and if their metabolic rates are plastic to seasonal thermal cues. Populations from warmer climates lowered metabolic rates when acclimating to summer temperatures as compared to spring temperatures. This may act as an energy saving mechanism during the warmest time of the year. No such plasticity was evident in populations from cooler climates. Both juvenile and adult salamanders exhibited metabolic plasticity. Although some populations responded to historic climate thermal cues, no populations showed plastic metabolic rate responses to future climate temperatures, indicating there are constraints on plastic responses. We postulate that impacts of warming will likely impact the energy budgets of salamanders, potentially affecting key demographic rates, such as individual growth and investment in reproduction.

Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty.

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 (λmean = 0.952, 95% CI: 0.87-1.01) could not be used to unequivocally reject the hypotheses of a rapidly declining population nor the hypothesis of a stable, or even slightly growing population, whereas our results for the expert-elicited estimates supported the hypothesis that the wood turtle population will decline over time. Our results showed that the aggregation techniques used had an impact on model estimates, suggesting that the choice of techniques should be carefully considered. We discuss the benefits and limitations associated with each method and their relevance to the population status assessment. We note a difference in the temporal scope or inference between the literature-based estimates that provided insights about historical changes, whereas the expert-based estimates were forward looking. Therefore, conducting an expert-elicitation in addition to using parameter estimates from the literature improved our understanding of our species of interest.

Site- and Individual-Level Contaminations Affect Infection Prevalence of an Emerging Infectious Disease of Amphibians.

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.

Metal accumulation varies with life history, size, and development of larval amphibians.

Amphibian larvae are commonly used as indicators of aquatic ecosystem health because they are susceptible to contaminants. However, there is limited information on how species characteristics and trophic position influence contaminant loads in larval amphibians. Importantly, there remains a need to understand whether grazers (frogs and toads [anurans]) and predators (salamanders) provide comparable information on contaminant accumulation or if they are each indicative of unique environmental processes and risks. To better understand the role of trophic position in contaminant accumulation, we analyzed composite tissues for 10 metals from larvae of multiple co-occurring anuran and salamander species from 20 wetlands across the United States. We examined how metal concentrations varied with body size (anurans and salamanders) and developmental stage (anurans) and how the digestive tract (gut) influenced observed metal concentrations. Across all wetlands, metal concentrations were greater in anurans than salamanders for all metals tested except mercury (Hg), selenium (Se), and zinc (Zn). Concentrations of individual metals in anurans decreased with increasing weight and developmental stage. In salamanders, metal concentrations were less correlated with weight, indicating diet played a role in contaminant accumulation. Based on batches of similarly sized whole-body larvae compared to larvae with their digestive tracts removed, our results indicated that tissue type strongly affected perceived concentrations, especially for anurans (gut represented an estimated 46-97% of all metals except Se and Zn). This suggests the reliability of results based on whole-body sampling could be biased by metal, larval size, and development. Overall, our data shows that metal concentrations differs between anurans and salamanders, which suggests that metal accumulation is unique to feeding behavior and potentially trophic position. To truly characterize exposure risk in wetlands, species of different life histories, sizes and developmental stages should be included in biomonitoring efforts.

Experimental evaluation of spatial capture-recapture study design.

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.

Risks posed by SARS-CoV-2 to North American bats during winter fieldwork.

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%.

Accommodating the role of site memory in dynamic species distribution models.

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 spatiotemporally 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 yr 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.

Batrachochytrium salamandrivorans (Bsal) not detected in an intensive survey of wild North American amphibians.

The salamander chytrid fungus (Batrachochytrium salamandrivorans [Bsal]) is causing massive mortality of salamanders in Europe. The potential for spread via international trade into North America and the high diversity of salamanders has catalyzed concern about Bsal in the U.S. Surveillance programs for invading pathogens must initially meet challenges that include low rates of occurrence on the landscape, low prevalence at a site, and imperfect detection of the diagnostic tests. We implemented a large-scale survey to determine if Bsal was present in North America designed to target taxa and localities where Bsal was determined highest risk to be present based on species susceptibility and geography. Our analysis included a Bayesian model to estimate the probability of occurrence of Bsal given our prior knowledge of the occurrence and prevalence of the pathogen. We failed to detect Bsal in any of 11,189 samples from 594 sites in 223 counties within 35 U.S. states and one site in Mexico. Our modeling indicates that Bsal is highly unlikely to occur within wild amphibians in the U.S. and suggests that the best proactive response is to continue mitigation efforts against the introduction and establishment of the disease and to develop plans to reduce impacts should Bsal establish.

A National-Scale Assessment of Mercury Bioaccumulation in United States National Parks Using Dragonfly Larvae As Biosentinels through a Citizen-Science Framework.

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.

North-facing slopes and elevation shape asymmetric genetic structure in the range-restricted salamander Plethodon shenandoah.

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.

Functional variation at an expressed MHC class IIß locus associates with Ranavirus infection intensity in larval anuran populations.

Infectious diseases are causing catastrophic losses to global biodiversity. Iridoviruses in the genus Ranavirus are among the leading causes of amphibian disease-related mortality. Polymorphisms in major histocompatibility complex (MHC) genes are significantly associated with variation in amphibian pathogen susceptibility. MHC genes encode two classes of polymorphic cell-surface molecules that can recognize and bind to diverse pathogen peptides. While MHC class I genes are the classic mediators of viral-acquired immunity, larval amphibians do not express them. Consequently, MHC class II gene diversity may be an important predictor of Ranavirus susceptibility in larval amphibians, the life stage most susceptible to Ranavirus. We surveyed natural populations of larval wood frogs (Rana sylvatica), which are highly susceptible to Ranavirus, across 17 ponds and 2 years in Maryland, USA. We sequenced the peptide-binding region of an expressed MHC class IIß locus and assessed allelic and genetic diversity. We converted alleles to functional supertypes and determined if supertypes or alleles influenced host responses to Ranavirus. Among 381 sampled individuals, 26% were infected with Ranavirus. We recovered 20 unique MHC class IIß alleles that fell into two deeply diverged clades and seven supertypes. MHC genotypes were associated with Ranavirus infection intensity, but not prevalence. Specifically, MHC heterozygotes and supertype ST1/ST7 had significantly lower Ranavirus infection intensity compared to homozygotes and other supertypes. We conclude that MHC class IIß functional genetic variation is an important component of Ranavirus susceptibility. Identifying immunogenetic signatures linked to variation in disease susceptibility can inform mitigation strategies for combatting global amphibian declines.

Disease-structured N-mixture models: A practical guide to model disease dynamics using count data.

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.