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Recent increases in wildlife cause negative impacts on humans through both economic and ecological damage, as well as the spread of pathogens. Understanding the population dynamics of wildlife is crucial to develop effective management strategies. However, it is difficult to estimate accurate and precise population size over large spatial and temporal scales because of the limited data availability. We addressed these issues by first fitting a random encounter and staying time (REST) model based on camera trap data to construct an informative prior distribution for a capture rate parameter in a harvest‐based Bayesian state‐space model. We constructed a Bayesian state‐space model that integrated administration data on the number of captured wild boar with the prior distribution of capture efficiency estimated by camera trap data. The model with informative prior distribution from the REST model successfully estimated population dynamics, whereas the model using only the administration data did not, owing to a lack of parameter convergence. We identified areas where (1) wild boars exhibit a high potential population growth rate and a high carrying capacity, (2) current trapping efforts are effectively suppressing local populations, and (3) trapping reinforcement is required to control populations in the whole region. The model could be used to predict future trends in populations under the assumptions of ongoing trapping pressure. This will help identify spatially explicit trapping efforts to achieve target population levels. [ABSTRACT FROM AUTHOR]

Studying the interaction between evolutionary and ecological processes (i.e. eco-evolutionary dynamics) has great potential to improve our understanding of biological processes such as species interactions, community assembly and ecosystem functions. However, most experimental studies have been conducted under controlled laboratory or mesocosm conditions, and the importance of these interactions in natural field communities has not been evaluated. In this study, we focused on the contemporary divergence of a competitive trait (the height-width ratio) of an annual grass Eleusine indica between urban and farmland populations and investigated how trait evolution affects ecological processes by transplanting E. indica individuals from lineages with different trait values into semi-natural grassland. The competitive trait of the transplanted individuals not only affected their own growth and fitness, but also affected the vegetative growth of the competing species and the species diversity. These results indicate that the evolution of competitive traits, even in a single species, can influence the community species diversity through changes in interspecific interactions. Eco-evolutionary interactions therefore play a crucial role in natural field environments. Our results suggest that understanding intraspecific variation in competitive traits driven by rapid evolution is essential for understanding interspecific competitive interactions, community assembly and species diversity.

Land abandonment may decrease biodiversity but also provides an opportunity for rewilding. It is therefore necessary to identify areas that may benefit from traditional land management practices and those that may benefit from a lack of human intervention. In this study, we conducted comparative field surveys of butterfly occurrence in abandoned and inhabited settlements in 18 regions of diverse climatic zones in Japan to test the hypotheses that species-specific responses to land abandonment correlate with climatic niches and habitat preferences. Hierarchical models that unified species occurrence and habitat preferences revealed that negative responses to land abandonment were associated with species that have cold climatic niches and use open habitats, suggesting that species negatively impacted by land abandonment will decline more due to future climate warming. Maps representing species gains and losses due to land abandonment, which were created from the model estimates, showed similar geographical patterns, but some areas exhibited high species losses relative to gains. Our hierarchical modelling approach was useful for scaling up local-scale effects of land abandonment to a macro-scale assessment, which is crucial to developing spatial conservation strategies in the era of depopulation.