Nice weather for bettongs: using weather events,not climate means,in species distribution models

Current applications of species distribution models (SDM) are typically static, in that they are based on correlations between where a species has been observed (ignoring the date of the observation) and environmental features, such as long‐term climate means, that are assumed to be constant for each site. Because of this SDMs do not account for temporal variation in the distribution of suitable habitat across the range of a species. Here, we demonstrate the temporal variability in the potential geographic distributions of an endangered marsupial, the northern bettong Bettongia tropica as a case study. Models of the species distribution using temporally matched observations of the species with weather data (including extreme weather events) at the time of species observations, were better able to define habitat suitability, identify range edges and uncover competitive interactions than models based on static long‐term climate means. Droughts and variable temperature are implicated in low densities and local extinctions of northern bettong populations close to range edges. Further, we show how variable weather can influence the results of competition with the common rufous bettong Aepyprymnus rufescens. Because traditional SDMs do not account for temporal variability of suitable habitat, static SDMs may underestimate the impacts of climate change particularly as the incidence of extreme weather events is likely to rise.     

Experience Does Not Equal Expertise in Recognizing Infrequent Incoming Gunfire: Neural Markers for Experience and Task Expertise at Peak Behavioral Performance

For a soldier, decisions to use force can happen rapidly and sometimes lead to undesired consequences. In many of these situations, there is a rapid assessment by the shooter that recognizes a threat and responds to it with return fire. But the neural processes underlying these rapid decisions are largely unknown, especially amongst those with extensive weapons experience and expertise. In this paper, we investigate differences in weapons experts and non-experts during an incoming gunfire detection task. Specifically, we analyzed the electroencephalography (EEG) of eleven expert marksmen/soldiers and eleven non-experts while they listened to an audio scene consisting of a sequence of incoming and non-incoming gunfire events. Subjects were tasked with identifying each event as quickly as possible and committing their choice via a motor response. Contrary to our hypothesis, experts did not have significantly better behavioral performance or faster response time than novices. Rather, novices indicated trends of better behavioral performance than experts. These group differences were more dramatic in the EEG correlates of incoming gunfire detection. Using machine learning, we found condition-discriminating EEG activity among novices showing greater magnitude and covering longer periods than those found in experts. We also compared group-level source reconstruction on the maximum discriminating neural correlates and found that each group uses different neural structures to perform the task. From condition-discriminating EEG and source localization, we found that experts perceive more categorical overlap between incoming and non-incoming gunfire. Consequently, the experts did not perform as well behaviorally as the novices. We explain these unexpected group differences as a consequence of experience with gunfire not being equivalent to expertise in recognizing incoming gunfire.     

Seasonal dietary niche contraction in coexisting Neotropical frugivorous bats (Stenodermatinae)

Tropical dry forests are characterized by punctuated seasonal precipitation patterns that drive primary production and the availability of fruits, seeds, flowers, and insects throughout the year. In environments in which the quantity and quality of food resources varies seasonally, consumers should adjust their foraging behavior to maximize energy intake while minimizing overlap with competitors during periods of low food availability. Here, we investigated how the diets of frugivorous bats in tropical dry forests of NW Mexico varied in response to seasonal availability and how this affected dietary overlap of morphologically similar species. We performed stable isotope analyses to understand temporal and interspecific patterns of overall isotopic niche breadth, trophic position, and niche overlap in the diet of six frugivorous species of closely related New World leaf-nosed bats (family Phyllostomidae, subfamily Stenodermatinae). We estimated seasonal changes in resource abundance in two complementary ways: (a) vegetative phenology based on long-term remote sensing data and (b) observational data on food availability from previously published insect and plant fruiting surveys. In all species, there was a consistent pattern of reduced isotopic niche breadth during periods of low food availability. However, patterns of niche overlap varied between morphologically similar species. Overall, results from our study and others suggest that seasonal food availability likely determines overall dietary niche breadth in Phyllostomidae and that despite morphological specialization, it is likely that other mechanisms, such as opportunistic foraging and spatiotemporal niche segregation, may play a role in maintaining coexistence rather than simply dietary displacement.