• Energy Research

A central hypothesis of ecology states that regional diversity influences local diversity through species-pool effects. Species pools are supposedly shaped by large-scale factors and then filtered into ecological communities, but understanding these processes requires the analysis of large datasets across several regions. Here, we use a framework of community assembly at a continental scale to test the relative influence of historical and environmental drivers, in combination with regional or local species pools, on community species richness and community completeness. Using 42,173 vegetation plots sampled across European beech forests, we found that large-scale factors largely accounted for species pool sizes. At the regional scale, main predictors reflected historical contingencies related to post-glacial dispersal routes, whereas at the local scale, the influence of environmental filters was predominant. Proximity to Quaternary refugia and high precipitation were the main factors supporting community species richness, especially among beech forest specialist plants. Models for community completeness indicate the influence of large-scale factors, further suggesting community saturation as a result of dispersal limitation or biotic interactions. Our results empirically demonstrate how historical factors complement environmental gradients to provide a better understanding of biodiversity patterns across multiple regions.

AbstractMicroclimate research gained renewed interest over the last decade and its importance for many ecological processes is increasingly being recognized. Consequently, the call for high‐resolution microclimatic temperature grids across broad spatial extents is becoming more pressing to improve ecological models. Here, we provide a new set of open‐access bioclimatic variables for microclimate temperatures of European forests at 25 × 25 m2 resolution.

AbstractEcological research heavily relies on coarse‐gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub‐canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the assessment of climatic conditions and climate‐change‐related impacts on forest‐floor biodiversity and functioning, high‐resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near‐surface forest temperature with topographical, biological and macroclimatic variables in a machine learning model, we predicted the mean monthly offset between sub‐canopy temperature at 15 cm above the surface and free‐air temperature over the period 2000–2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub‐canopy air temperatures differ substantially from free‐air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high‐resolution maps expose considerable microclimatic variation within landscapes, not captured by the gridded macroclimatic products. The provided forest sub‐canopy temperature maps will enable future research to model below‐canopy biological processes and patterns, as well as species distributions more accurately.