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Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision‐making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene‐to‐individual level and the community‐to‐ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision‐making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier‐to‐use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best‐practise guidelines for applying these models. Further, more robust decision‐making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long‐term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes. [ABSTRACT FROM AUTHOR]

Global biodiversity is under high and rising anthropogenic pressure. Yet, how the taxonomic, phylogenetic, and functional facets of biodiversity are affected by different threats over time is unclear. This is particularly true for the two main drivers of the current biodiversity crisis: habitat destruction and overexploitation. We provide the first long‐term assessment of multifaceted biodiversity changes caused by these threats for any tropical region. Focussing on larger mammals in South America's 1.1 million km2 Gran Chaco region, we assessed changes in multiple biodiversity facets between 1985 and 2015, determined which threats drive those changes, and identified remaining key areas for all biodiversity facets. Using habitat and threat maps, we found, first, that between 1985 and 2015 taxonomic (TD), phylogenetic (PD) and functional (FD) diversity all declined drastically across over half of the area assessed. FD declined about 50% faster than TD and PD, and these declines were mainly driven by species loss, rather than species turnover. Second, habitat destruction, hunting, and both threats together contributed ~57%, ~37%, and ~6% to overall facet declines, respectively. However, hunting pressure increased where TD and PD declined most strongly, whereas habitat destruction disproportionally contributed to FD declines. Third, just 23% of the Chaco would have to be protected to safeguard the top 17% of all three facets. Our findings uncover a widespread impoverishment of mammal species richness, evolutionary history, and ecological functions across broad areas of the Chaco due to increasing habitat destruction and hunting. Moreover, our results pinpoint key areas that should be preserved and managed to maintain all facets of mammalian diversity across the Chaco. More generally, our work highlights how long‐term changes in biodiversity facets can be assessed and attributed to specific threats, to better understand human impacts on biodiversity and to guide conservation planning to mitigate them. [ABSTRACT FROM AUTHOR]