A Global Atlas of Specific Leaf Area Under Climate Change

ABSTRACT Motivation Specific leaf area (SLA) is a key plant functional trait linked to plant structural, physiological and resource‐use strategies. Despite its importance, spatially continuous data sets capturing SLA variation across global biomes remain scarce, particularly under future climate scenarios. Here, we compile and model a comprehensive global dataset of SLA to assess its current distribution and project responses to climate change. This resource provides critical support for exploring trait–environment relationships, plant community assembly and vegetation‐climate feedbacks at broad spatial and temporal scales. Main Types of Variables Contained The dataset consists of a single standardised table containing 24,237 SLA measurements, each linked to geographic coordinates. Observations span 5687 vascular plant species across 282 families and were compiled from peer‐reviewed literature, the TRY database and new field collections. Spatial Location and Grain The dataset has global coverage, with SLA predictions provided at a spatial resolution of 1 km 2 . Spatial layers include both present‐day environmental conditions and projections under future climate scenarios. Time Period and Grain The data represent current climatic conditions and future projections for the following intervals: 2020–2040, 2040–2060, 2060–2080 and 2080–2100 under multiple emissions scenarios. Major Taxa and Level of Measurement Trait data were collected at the species level for vascular plants, with particular emphasis on grasses and trees. These SLA values were measured excluding petioles and were georeferenced to 2437 sampling sites worldwide, enabling consistent cross‐biome analyses of functional trait variation. Software Format The raw trait data are provided in comma‐separated value (.csv) format. Model outputs, including global SLA predictions, are available as Geotiff (.tif) files suitable for integration into GIS platforms and Earth system models.