Empirical evidence for effects of invasive American Bullfrogs on occurrence of native amphibians and emerging pathogens.

Invasive species and emerging infectious diseases are two of the greatest threats to biodiversity. American Bullfrogs (Rana [Lithobates] catesbeiana), which have been introduced to many parts of the world, are often linked with declines in native amphibians via predation and the spread of emerging pathogens such as amphibian chytrid fungus (Batrachochytrium dendrobatidis [Bd]) and ranaviruses. Although many studies have investigated the potential role of bullfrogs in the decline of native amphibians, analyses that account for shared habitat affinities and imperfect detection have found limited support for clear effects. Similarly, the role of bullfrogs in shaping the patch-level distribution of pathogens is unclear. We used eDNA methods to sample 233 sites in the southwestern USA and Sonora, Mexico (2016-2018) to estimate how the presence of bullfrogs affects the occurrence of four native amphibians, Bd, and ranaviruses. Based on two-species, dominant-subordinate occupancy models fitted in a Bayesian context, federally threatened Chiricahua Leopard Frogs (Rana chiricahuensis) and Western Tiger Salamanders (Ambystoma mavortium) were eight times (32% vs. 4%) and two times (36% vs. 18%), respectively, less likely to occur at sites where bullfrogs occurred. Evidence for the negative effects of bullfrogs on Lowland Leopard Frogs (Rana yavapaiensis) and Northern Leopard Frogs (Rana pipiens) was less clear, possibly because of smaller numbers of sites where these native species still occurred and because bullfrogs often occur at lower densities in streams, the primary habitat for Lowland Leopard Frogs. At the community level, Bd was most likely to occur where bullfrogs co-occurred with native amphibians, which could increase the risk to native species. Ranaviruses were estimated to occur at 33% of bullfrog-only sites, 10% of sites where bullfrogs and native amphibians co-occurred, and only 3% of sites where only native amphibians occurred. Of the 85 sites where we did not detect any of the five target amphibian species, we also did not detect Bd or ranaviruses; this suggests other hosts do not drive the distribution of these pathogens in our study area. Our results provide landscape-scale evidence that bullfrogs reduce the occurrence of native amphibians and increase the occurrence of pathogens, information that can clarify risks and aid the prioritization of conservation actions.

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 statistical forecasting approach to metapopulation viability analysis.

Conservation of at-risk species is aided by reliable forecasts of the consequences of environmental change and management actions on population viability. Forecasts from conventional population viability analysis (PVA) are made using a two-step procedure in which parameters are estimated, or elicited from expert opinion, and then plugged into a stochastic population model without accounting for parameter uncertainty. Recently developed statistical PVAs differ because forecasts are made conditional on models fitted to empirical data. The statistical forecasting approach allows for uncertainty about parameters, but it has rarely been applied in metapopulation contexts where spatially explicit inference is needed about colonization and extinction dynamics and other forms of stochasticity that influence metapopulation viability. We conducted a statistical metapopulation viability analysis (MPVA) using 11 yr of data on the federally threatened Chiricahua leopard frog (Lithobates chiricahuensis) to forecast responses to landscape heterogeneity, drought, environmental stochasticity, and management. We evaluated several future environmental scenarios and pond restoration options designed to reduce extinction risk. Forecasts over a 50-yr time horizon indicated that metapopulation extinction risk was <4% for all scenarios, but uncertainty was high. Without pond restoration, extinction risk is forecasted to be 3.9% (95% CI 0-37%) by year 2066. Restoring six ponds by increasing their hydroperiod reduced extinction risk to <1% and greatly reduced uncertainty (95% CI 0-2%). Our results suggest that managers can mitigate the impacts of drought and environmental stochasticity on metapopulation viability by maintaining ponds that hold water throughout the year and keeping them free of invasive predators. Our study illustrates the utility of the spatially explicit statistical forecasting approach to MPVA in conservation planning efforts.

Quantifying climate sensitivity and climate-driven change in North American amphibian communities.

Changing climate will impact species' ranges only when environmental variability directly impacts the demography of local populations. However, measurement of demographic responses to climate change has largely been limited to single species and locations. Here we show that amphibian communities are responsive to climatic variability, using >500,000 time-series observations for 81 species across 86 North American study areas. The effect of climate on local colonization and persistence probabilities varies among eco-regions and depends on local climate, species life-histories, and taxonomic classification. We found that local species richness is most sensitive to changes in water availability during breeding and changes in winter conditions. Based on the relationships we measure, recent changes in climate cannot explain why local species richness of North American amphibians has rapidly declined. However, changing climate does explain why some populations are declining faster than others. Our results provide important insights into how amphibians respond to climate and a general framework for measuring climate impacts on species richness.

Increasing connectivity between metapopulation ecology and landscape ecology.

Metapopulation ecology and landscape ecology aim to understand how spatial structure influences ecological processes, yet these disciplines address the problem using fundamentally different modeling approaches. Metapopulation models describe how the spatial distribution of patches affects colonization and extinction, but often do not account for the heterogeneity in the landscape between patches. Models in landscape ecology use detailed descriptions of landscape structure, but often without considering colonization and extinction dynamics. We present a novel spatially explicit modeling framework for narrowing the divide between these disciplines to advance understanding of the effects of landscape structure on metapopulation dynamics. Unlike previous efforts, this framework allows for statistical inference on landscape resistance to colonization using empirical data. We demonstrate the approach using 11 yr of data on a threatened amphibian in a desert ecosystem. Occupancy data for Lithobates chiricahuensis (Chiricahua leopard frog) were collected on the Buenos Aires National Wildlife Refuge (BANWR), Arizona, USA from 2007 to 2017 following a reintroduction in 2003. Results indicated that colonization dynamics were influenced by both patch characteristics and landscape structure. Landscape resistance increased with increasing elevation and distance to the nearest streambed. Colonization rate was also influenced by patch quality, with semi-permanent and permanent ponds contributing substantially more to the colonization of neighboring ponds relative to intermittent ponds. Ponds that only hold water intermittently also had the highest extinction rate. Our modeling framework can be widely applied to understand metapopulation dynamics in complex landscapes, particularly in systems in which the environment between habitat patches influences the colonization process.