A species-level trait dataset of bats in Europe and beyond.

Knowledge of species' functional traits is essential for understanding biodiversity patterns, predicting the impacts of global environmental changes, and assessing the efficiency of conservation measures. Bats are major components of mammalian diversity and occupy a variety of ecological niches and geographic distributions. However, an extensive compilation of their functional traits and ecological attributes is still missing. Here we present EuroBaTrait 1.0, the most comprehensive and up-to-date trait dataset covering 47 European bat species. The dataset includes data on 118 traits including genetic composition, physiology, morphology, acoustic signature, climatic associations, foraging habitat, roost type, diet, spatial behaviour, life history, pathogens, phenology, and distribution. We compiled the bat trait data obtained from three main sources: (i) a systematic literature and dataset search, (ii) unpublished data from European bat experts, and (iii) observations from large-scale monitoring programs. EuroBaTrait is designed to provide an important data source for comparative and trait-based analyses at the species or community level. The dataset also exposes knowledge gaps in species, geographic and trait coverage, highlighting priorities for future data collection.

popharvest: An R package to assess the sustainability of harvesting regimes of bird populations.

Bird harvest for recreational purposes or as a source for food is an important activity worldwide. Assessing or mitigating the impact of these additional sources of mortality on bird populations is therefore crucial issue. The sustainability of harvest levels is however rarely documented, because knowledge of their population dynamics remains rudimentary for many bird species. Some helpful approaches using limited demographic data can be used to provide initial assessment of the sustainable use of harvested bird populations, and help adjusting harvest levels accordingly. The Demographic Invariant Method (DIM) is used to detect overharvesting. In complement, the Potential Take Level (PTL) approach may allow setting a level of take with regard to management objectives and/or to assess whether current harvest levels meet these objectives. Here, we present the R package popharvest that implements these two approaches in a simple and straightforward way. The package provides users with a set of flexible functions whose arguments can be adapted to existing knowledge about population dynamics. Also, popharvest enables users to test scenarios or propagate uncertainty in demographic parameters to the assessment of sustainability through easily programming Monte Carlo simulations. The simplicity of the package makes it a useful toolbox for wildlife managers or policymakers. This paper provides them with backgrounds about the DIM and PTL approaches and illustrates the use of popharvest's functionalities in this context.