High prevalence of chigger mite infection in a forest-specialist frog with evidence of parasite-related granulomatous myositis.

Amphibians are hosts for a wide variety of micro- and macro-parasites. Chigger mites from the Hannemania genus are known to infect a wide variety of amphibian species across the Americas. In Chile, three species (H. pattoni, H. gonzaleacunae and H. ortizi) have been described infecting native anurans; however, neither impacts nor the microscopic lesions associated with these parasites have been described. Here, we document 70% prevalence of chigger mite infection in Eupsophus roseus and absence of infection in Rhinoderma darwinii in the Nahuelbuta Range, Chile. Additionally, we describe the macroscopic and microscopic lesions produced by H. ortizi in one of these species, documenting previously undescribed lesions (granulomatous myositis) within the host's musculature. These findings highlight that further research to better understand the impacts of chigger mite infection on amphibians is urgently required in Chile and elsewhere.

Cryptic disease-induced mortality may cause host extinction in an apparently stable host-parasite system.

The decline of wildlife populations due to emerging infectious disease often shows a common pattern: the parasite invades a naive host population, producing epidemic disease and a population decline, sometimes with extirpation. Some susceptible host populations can survive the epidemic phase and persist with endemic parasitic infection. Understanding host-parasite dynamics leading to persistence of the system is imperative to adequately inform conservation practice. Here we combine field data, statistical and mathematical modelling to explore the dynamics of the apparently stable Rhinoderma darwinii-Batrachochytrium dendrobatidis (Bd) system. Our results indicate that Bd-induced population extirpation may occur even in the absence of epidemics and where parasite prevalence is relatively low. These empirical findings are consistent with previous theoretical predictions showing that highly pathogenic parasites are able to regulate host populations even at extremely low prevalence, highlighting that disease threats should be investigated as a cause of population declines even in the absence of an overt increase in mortality.

Dispersal and extrapolation on the accuracy of temporal predictions from distribution models for the Darwin's frog.

Climate change is a major threat to biodiversity; the development of models that reliably predict its effects on species distributions is a priority for conservation biogeography. Two of the main issues for accurate temporal predictions from Species Distribution Models (SDM) are model extrapolation and unrealistic dispersal scenarios. We assessed the consequences of these issues on the accuracy of climate-driven SDM predictions for the dispersal-limited Darwin's frog Rhinoderma darwinii in South America. We calibrated models using historical data (1950-1975) and projected them across 40 yr to predict distribution under current climatic conditions, assessing predictive accuracy through the area under the ROC curve (AUC) and True Skill Statistics (TSS), contrasting binary model predictions against temporal-independent validation data set (i.e., current presences/absences). To assess the effects of incorporating dispersal processes we compared the predictive accuracy of dispersal constrained models with no dispersal limited SDMs; and to assess the effects of model extrapolation on the predictive accuracy of SDMs, we compared this between extrapolated and no extrapolated areas. The incorporation of dispersal processes enhanced predictive accuracy, mainly due to a decrease in the false presence rate of model predictions, which is consistent with discrimination of suitable but inaccessible habitat. This also had consequences on range size changes over time, which is the most used proxy for extinction risk from climate change. The area of current climatic conditions that was absent in the baseline conditions (i.e., extrapolated areas) represents 39% of the study area, leading to a significant decrease in predictive accuracy of model predictions for those areas. Our results highlight (1) incorporating dispersal processes can improve predictive accuracy of temporal transference of SDMs and reduce uncertainties of extinction risk assessments from global change; (2) as geographical areas subjected to novel climates are expected to arise, they must be reported as they show less accurate predictions under future climate scenarios. Consequently, environmental extrapolation and dispersal processes should be explicitly incorporated to report and reduce uncertainties in temporal predictions of SDMs, respectively. Doing so, we expect to improve the reliability of the information we provide for conservation decision makers under future climate change scenarios.