Does the thermal mismatch hypothesis predict disease outcomes in different morphs of a terrestrial salamander?

Many aspects of ectotherm physiology are temperature-dependent. The immune system of temperate-dwelling ectothermic host species is no exception and their immune function is often downregulated in cold temperatures. Likewise, species of ectothermic pathogens experience temperature-mediated effects on rates of transmission and/or virulence. Although seemingly straightforward, predicting the outcomes of ectothermic host-pathogen interactions is quite challenging. A recent hypothesis termed the thermal mismatch hypothesis posits that cool-adapted host species should be most susceptible to pathogen infection during warm temperature periods whereas warm-adapted host species should be most susceptible to pathogens during periods of cool temperatures. We explore this hypothesis using two ecologically and physiologically differentiated color morphs of the Eastern Red-backed Salamander (Plethodon cinereus) and a pathogenic chytrid fungus (Batrachochytrium dendrobatidis; hereafter "Bd") using a fully factorial laboratory experiment. At cool temperatures, unstriped salamanders (i.e., those that are tolerant of warm temperatures) had a significantly higher probability of Bd infection compared with cool-tolerant striped salamanders, consistent with the thermal mismatch hypothesis. However, we found no support for this hypothesis when salamanders were exposed to Bd at warm temperatures: the probability of Bd infection in the cool-tolerant striped salamanders was nearly identical in both cool and warm temperatures, opposite the predictions of the thermal mismatch hypothesis. Our results are most consistent with the fact that Bd grows poorly at warm temperatures. Alternatively, our data could indicate that the two color morphs do not differ in their tolerance to warm temperatures but that striped salamanders are more tolerant to cool temperatures than unstriped salamanders.

A demographic approach to understanding the effects of climate on population growth

Amphibian life history traits are affected by temperature and precipitation. Yet, connecting these relationships to population growth, especially for multiple populations within a species, is lacking and precludes our understanding of amphibian population dynamics and distributions. Therefore, we constructed integral projection models for five populations along an elevational gradient to determine how climate and season affect population growth of a terrestrial salamander Plethodon montanus and the importance of demographic vital rates to population growth under varying climate scenarios. We found that population growth was typically higher at the highest elevation compared to the lower elevations, whereas varying inactive season conditions, represented by the late fall, winter and early spring, produced a greater variation in population growth than varying active season conditions (late spring, summer, and early fall). Furthermore, survival and growth were consistently more important, as measured by elasticity, compared to fecundity, and large females had the greatest elasticity compared to all other body sizes. Our results suggest that changing inactive season conditions, especially those that would affect the survival of large individuals, may have the greatest impact on population growth. We recommend future experimental studies focus on the inactive season to better elucidate the mechanisms by which these conditions can affect survival.

Species distribution models throughout the invasion history of Palmer amaranth predict regions at risk of future invasion and reveal challenges with modeling rapidly shifting geographic ranges

Palmer amaranth (Amaranthus palmeri) is an annual plant native to the desert Southwest of the United States and Mexico and has become invasive and caused large economic losses across much of the United States. In order to examine the temporal and spatial dynamics of past invasion, and to predict future invasion, we developed a broad array of species distribution models (SDMs). In particular, we constructed sequential SDMs throughout the invasion history and asked how well those predicted future invasion (1970 to present). We showed that invasion occurred from a restricted set of environments in the native range to a diverse set in the invaded range. Spatial autocorrelation analyses indicated that rapid range expansion was facilitated by stochastic, long-distance dispersal events. Regardless of SDM approach, all SDMs built using datasets from early in the invasion (1970–2010) performed poorly and failed to predict most of the current invaded range. Together, these results suggest that climate is unlikely to have influenced early stages of range expansion. SDMs that incorporated data from the most recent sampling (2011–2017) performed considerably better, predicted high suitability in regions that have recently become invaded, and identified mean annual temperature as a key factor limiting northward range expansion. Under future climates, models predicted both further northward range expansion and significantly increased suitability across large portions of the U.S. Overall, our results indicate significant challenges for SDMs of invasive species far from climate equilibrium. However, our models based on recent data make more robust predictions for northward range expansion of A. palmeri with climate change.