LAUSR

Over the past decade, the use of future climate projections from the coupled model intercomparison project (CMIP) has become central in biodiversity science. Pre‐packaged datasets containing future projections of the widely used bioclimatic variables, for different times and socio‐economic pathways, have contributed immensely to the study of climate change implications for biodiversity. However, these datasets lack the flexibility to obtain projections to other target years, and the use of raw data requires coding and spatial information systems expertise. The Python tool, ‘chelsa‐cmip6', developed by Karger et al., provides the flexibility needed by allowing users to generate bioclimatic variables for the time of their choice provided the selected general circulation model and socioeconomic pathway combination exists. This is a fantastic step forward in bringing flexibility to the use of climate datasets in biodiversity and will allow for more widespread use of data provided by CMIP6. We hope it also will prompt the development of more user‐friendly tools for the study of the effects of climate change on biodiversity.