1. Current modelling approaches to predict spatially explicit biodiversity responses to climate change mainly focus on the direct effects of climate on species. Integration of spatiotemporal land-cover scenarios is still limited. Current approaches either regard land cover as constant boundary conditions, or rely on general, typically globally defined land-use scenarios. This is problematic as it disregards the complex synergistic effects of climate and land use on biodiversity at the regional scale, as biophysical, economic, and social issues important for regional land-use decisions are also affected by climate change. To realistically predict climate impacts on biodiversity, it is therefore necessary to consider both, the direct effect of climate change on biodiversity, and its indirect effect on biodiversity via land-use change. 2. In this review and perspective paper, we outline how biodiversity models could be better integrated with regional, climate-driven land-use models. We provide an overview of empirical and modelling approaches to both land-use (LU) and biodiversity (BD) change, focusing on how integration has been attempted. We then analyse how LU and BD model properties, such as scales, inputs, and outputs, can be matched and identify potential integration challenges and opportunities. 3. We found LU integration in BD models has been frequently attempted. By contrast, integrating the role of BD in models of LU decisions is largely lacking. As a result, bi-directional effects remain largely understudied. Only few integrated LU-BD socio-ecological models have assessed climate change effects on LU and no study has yet investigated the relative contribution of direct vs. indirect effects of climate change on BD. 4. There is a large potential for model integration given the overlap on spatial scales, although challenges remain with respect to spatial scale, temporal dynamics, investigation of indirect effects, and bi-directionality, including feeding back to climate models. Efforts to better understand human decisions, eco-evolutionary dynamics, connection between terrestrial and aquatic systems, and format standardization of modelling outputs and empirical data should improve future models. Integrating biodiversity feedbacks into land-use and climate models requires modelling innovations, but should be feasible.

The abandonment of historical land‐use forms within forests, such as grazing or coppicing, and atmospheric nitrogen deposition, has led to an increasing overgrowth of forest gaps and canopy closure in forest ecosystems of Central Europe. From 1945 to 2015, 81% of the forest gaps greater than 150 m2 within the study area transitioned into a closed forest. This study investigated how the overgrowth process affects flower supply, flower visitors, and reproduction of Campanula species. Six native Campanula species with different light requirements were used as phytometers. The forest gaps in the studied area are a feature of the historical European cultural landscape. We compared large gaps caused by human activities, small gaps caused by habitat conditions, and closed forests. In eight blocked replicates, each with the three habitat categories, we recorded the flower cover and number of indigenous flowering species in the immediate surroundings, and, of six Campanula species, flower visitors and seed production. Forest gaps and their size positively affected the number of flowering plant species in the surrounding area, the number of all flower visitor groups, and the number of seeds produced by all six Campanula species. Flower cover in the surrounding area was higher in large gaps, but there was no difference between small gaps and closed forests. Among flower visitors, small bees varied the most between the three habitat categories, and flies varied the least. The effect on the number of seeds produced was particularly strong for three light‐demanding Campanula species. The overgrowth of forest gaps negatively affected flower supply, flower‐visiting insects, and seed sets of six Campanula species. Forest gaps should be managed to maintain the reproduction of open forest plants and their pollinators.

Current approaches to project spatial biodiversity responses to climate change mainly focus on the direct effects of climate on species while regarding land use and land cover as constant or prescribed by global land‐use scenarios. However, local land‐use decisions are often affected by climate change and biodiversity on top of socioeconomic and policy drivers. To realistically understand and predict climate impacts on biodiversity, it is, therefore, necessary to integrate both direct and indirect effects (via climate‐driven land‐use change) of climate change on biodiversity. In this perspective paper, we outline how biodiversity models could be better integrated with regional, climate‐driven land‐use models. We initially provide a short, non‐exhaustive review of empirical and modelling approaches to land‐use and land‐cover change (LU) and biodiversity (BD) change at regional scales, which forms the base for our perspective about improved integration of LU and BD models. We consider a diversity of approaches, with a special emphasis on mechanistic models. We also look at current levels of integration and at model properties, such as scales, inputs and outputs, to further identify integration challenges and opportunities. We find that LU integration in BD models is more frequent than the other way around and has been achieved at different levels: from overlapping predictions to simultaneously coupled simulations (i.e. bidirectional effects). Of the integrated LU‐BD socio‐ecological models, some studies included climate change effects on LU, but the relative contribution of direct vs. indirect effects of climate change on BD remains a key research challenge. Important research avenues include concerted efforts in harmonizing spatial and temporal resolution, disentangling direct and indirect effects of climate change on biodiversity, explicitly accounting for bidirectional feedbacks, and ultimately feeding socio‐ecological systems back into climate predictions. These avenues can be navigated by matching models, plugins for format and resolution conversion, and increasing the land‐use forecast horizon with adequate uncertainty. Recent developments of coupled models show that such integration is achievable and can lead to novel insights into climate–land use–biodiversity relations. Read the free Plain Language Summary for this article on the Journal blog.

Globally, biodiversity declines, threatening over 82,000 species (Maxwell et al., 2016). Apart from land-use change and the direct exploitation of species, anthropogenic climate change is now among the most important drivers of biodiversity decline (IPBES, 2019;Newbold et al., 2020). It alters the environmental conditions to such an extent that many ecoregions will be put under substantial survival