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The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.

Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.

Vegetation is a key driver of ecosystem functioning (e.g. productivity and stability) and of the maintenance of biodiversity (e.g. creating habitats for other species groups). While vegetation sensitivity to climate change has been widely investigated, its spatio-temporally response to the dual effects of land management and climate change has been ignored at landscape scale. Here we use a dynamic vegetation model called FATE-HD, which describes the dominant vegetation dynamics and associated functional diversity, in order to anticipate vegetation response to climate and landuse changes in both short and long-term perspectives. Using three contrasted management scenarios for the Ecrins National Park (French Alps) developed in collaboration with the park managers, and one regional climate change scenario, we tracked the dynamics of vegetation structure (forest expansion) and functional diversity over 100 yr of climate change and a further 400 additional years of stabilization. As expected, we observed a slow upward shift in forest cover distribution, which appears to be severely impacted by pasture management (i.e. maintenance or abandonment). The time lag before observing changes in vegetation cover was the result of demographic and seed dispersal processes. However, plant diversity response to environmental changes was rapid. After land abandonment, local diversity increased and spatial turnover was reduced, whereas local diversity decreased following land use intensification. Interestingly, in the long term, as both climate and management scenarios interacted, the regional diversity declined. Our innovative spatio-temporally explicit framework demonstrates that the vegetation may have contrasting responses to changes in the short and the long term. Moreover, climate and land-abandonment interact extensively leading to a decrease in both regional diversity and turnover in the long term. Based on our simulations we therefore suggest a continuing moderate intensity pasturing to maintain high levels of plant diversity in this system.

Aim Alpine habitats support unique biodiversity confined to high‐elevation areas in the current interglacial. Plant diversity in these habitats may respond to area, environment, connectivity and isolation, yet these factors have been rarely evaluated in concert. Here we investigate major determinants of regional species pools in alpine grasslands, and the responses of their constituent species groups. Location European mountains below 50° N. Time period Between 1928 and 2019. Major taxa studied Vascular plants. Methods We compiled species pools from alpine grasslands in 23 regions, including 794 alpine species and 2,094 non‐alpines. We used species–area relationships to test the influence of the extent of alpine areas on regional richness, and mixed‐effects models to compare the effects of 12 spatial and environmental predictors. Variation in species composition was addressed by generalized dissimilarity models and by a coefficient of dispersal direction to assess historical links among regions. Results Pool sizes were partially explained by current alpine areas, but the other predictors largely contributed to regional differences. The number of alpine species was influenced by area, calcareous bedrock, topographic heterogeneity and regional isolation, while non‐alpines responded better to connectivity and climate. Regional dissimilarity of alpine species was explained by isolation and precipitation, but non‐alpines only responded to isolation. Past dispersal routes were correlated with latitude, with alpine species showing stronger connections among regions. Main conclusions Besides area effects, edaphic, topographic and spatio‐temporal determinants are important to understand the organization of regional species pools in alpine habitats. The number of alpine species is especially linked to refugia and isolation, but their composition is explained by past dispersal and post‐glacial environmental filtering, while non‐alpines are generally influenced by regional floras. New research on the dynamics of alpine biodiversity should contextualize the determinants of regional species pools and the responses of species with different ecological profiles.