Population-level variation in host responses to disease can be observed across a wide array of host-pathogen systems. Some host populations are extirpated, some persist at lower densities or abundances, and others rebound to pre-disease levels. Understanding the causes of this variation, and the mechanisms of successful persistence, can serve as vital information for species conservation. One such mechanism of population persistence that has gained support in the amphibian Batrachochytrium dendrobatidis (Bd) host-pathogen system is the demographic process of compensatory recruitment. Host populations may persist by increasing recruitment to compensate for reduced survival due to infection, thus limiting the negative effects of the disease on population trajectories. However, high-elevation amphibian populations are inherently vulnerable to stochastic processes and may be limited in their ability to exhibit compensatory recruitment relative to lower-elevation populations. We use long-term mark-recapture data from five populations of boreal toads (Anaxyrus boreas boreas), across an elevational gradient in Colorado, before and after pathogen arrival to assess whether populations can persist with Bd via compensatory recruitment. Prior to Bd arrival, we found a life history tradeoff between survival and recruitment across elevations, where high-elevation toads have high survival but lower recruitment and vice versa at lower elevations. Bd arrival had a strong negative effect on apparent annual survival and recruitment, and led to negative population growth rates and dramatically reduced host abundances. The data did not support the occurrence of compensatory recruitment. Synthesis and applications. Our unique dataset suggests that demographic responses to pathogens may be environmentally (i.e., elevationally) context-dependent and highlights the value of long-term monitoring. We recommend that practitioners verify that potential persistence mechanisms occur across multiple populations and relevant environmental gradients to counter any assumptions of the mechanism existing species-wide. Quantifying any variation in population responses to disease will aid in understanding the bounds of such persistence mechanisms, and identify particularly vulnerable populations where mechanisms are non-existent.

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.

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.