Contribution of local rarity and climatic suitability to local extinction and colonization varies with species traits

Local colonisations and extinctions of European birds are poorly explained by changes in climate suitability

Climate change has been associated with both latitudinal and elevational shifts in species' ranges. The extent, however, to which climate change has driven recent range shifts alongside other putative drivers remains uncertain. Here, we use the changing distributions of 378 European breeding bird species over 30 years to explore the putative drivers of recent range dynamics, considering the effects of climate, land cover, other environmental variables, and species' traits on the probability of local colonisation and extinction. On average, species shifted their ranges by 2.4 km/year. These shifts, however, were significantly different from expectations due to changing climate and land cover. We found that local colonisation and extinction events were influenced primarily by initial climate conditions and by species' range traits. By contrast, changes in climate suitability over the period were less important. This highlights the limitations of using only climate and land cover when projecting future changes in species' ranges and emphasises the need for integrative, multi-predictor approaches for more robust forecasting.

Is scat marking a reliable tool for otter census and surveys at the landscape scale?

Biological significance of scat marking by otters has been a controversial subject among scientists. Using multiyear (2014-2017) data of otter spraint counts in South Korea, this study aimed to test whether the observed pattern of spraint presence/absence is driven by detection error and if/how scat counts can be a proxy for otter abundance at the landscape scale. To test the first hypothesis, spraint presence/absence was analyzed through occupancy models, which relied on environmental variables related to otter detectability and presence. Spraint count models were used to test the second hypothesis against resource-related covariates in combination with landscape, anthropogenic, and climate variables through machine learning algorithms (MLAs). The detection probability has specifically decreased in areas characterized by high rainfall and human population densities, whereas the probability has increased near food-rich sites, characterized by high marking frequencies. The temporal trends of spraint count predictions were in line with changes in the diversity of fish communities in 2014-2017 instead of fish biomass, suggesting that the availability of feeding resources is higher where fish communities are more diverse. Because diverse fish communities can attract otters, fish diversity conservation is critical for preserving this mammal's populations. This fine scale four-year monitoring has contributed to the disentanglement of the role of spraint presence/absence and spraint counts in detectability and population trends. This will assist in identifying key resource areas and planning strategies to promote otter conservation and dispersal dynamics.

The effects of weather variability on patterns of genetic diversity in Tasmanian bettongs

While the effects of climate (long-term, prevailing weather) on species abundance, range and genetic diversity have been widely studied, short-term, localized variations in atmospheric conditions (i.e., weather) can also rapidly alter species' geographical ranges and population sizes, but little is known about how they affect genetic diversity. We investigated the relationship between weather and range-wide genetic diversity in a marsupial, Bettongia gaimardi, using dynamic species distribution models (SDMs). Genetic diversity was lower in parts of the range where the weather-based SDM predicted high variability in probability of B. gaimardi occurrence during 1950-2009. This is probably an effect of lower population sizes and extinction-recolonization cycles in places with highly variable weather. Spatial variation in genetic diversity was also better predicted by mean probabilities of B. gaimardi occurrence from weather- than climate-based SDMs. Our results illustrate the importance of weather in driving population dynamics and species distributions on decadal timescales and thereby in affecting genetic diversity. Modelling the links between changing weather patterns, species distributions and genetic diversity will allow researchers to better forecast biological impacts of climate change.