Assessing land‐use effects on European plant diversity using a biome‐specific countryside species–area model

AIM: Land‐use change is considered a major threat to biodiversity. Species–area relationships (SARs), which are often used to assess biodiversity changes, assume that land use leads to the loss of natural habitats. Yet, in regions with long land‐use histories, such as Europe, many species have persisted in, or even depend on, landscapes heavily influenced by land use (i.e., countryside landscapes). Here, we develop a SAR model that considers the conservation value of such landscapes, and we assess how land use affects plant‐species richness at broad spatial scales. LOCATION: Countries in the European Union (EU‐27). METHODS: We first predicted species richness at a 50 × 50 km resolution using a biome‐specific SAR and used these predictions as a baseline estimate for (semi‐)natural vegetation. Then, we parameterized a countryside SAR (sensu Pereira & Daily, 2006) with habitat affinities derived from a meta‐analysis. We estimated changes in species richness as the difference in predictions between the two SAR models. RESULTS: At a 50 × 50 km resolution, predicted species richness has increased by up to 184 species due to land use in 73% of all cells across Europe compared to the (semi‐)natural baseline. However, our model also highlights regions with dramatic species losses (in 25% of cells, losses of up to 900 species) due to an unfavourable combination of land‐use changes. Averaged across all cells, we predict a loss of 26 plant species (SD = 119, median = 49). MAIN CONCLUSIONS: Adopting the countryside SAR model to broader spatial scales overcomes the unrealistic assumptions of previous approaches about generally negative effects of land use. Our approach predicts how local‐scale land‐use effects translate to biodiversity changes at broader geographic scales. Thus, it allows land‐use scenarios being studied in relation to their trade‐offs with biodiversity and can be used to target conservation efforts across large areas.