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Spatially explicit models for decision-making in animal conservation and restoration


Zurell, Damaris et al. (2021), Spatially explicit models for decision-making in animal conservation and restoration, Dryad, Dataset,


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 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.


We conducted a Web of Science search on 9th February 2021, searching for studies employing different model types (see Box 1 in main text) for specific management applications (see Box 2 in main text) in the period 1900-2021 (for a complete list of keywords cf. Appendix S1, Table S1). We initially identified 5179 papers, which we further refined to papers that fell under the Web of Science category “biodiversity conservation”, yielding a list of 650 papers. We screened these and only kept papers that had a clear management application (Box 2) and that provided some form of spatial planning and decision support. The latter requirement was met when at least a map of the status quo was derived from the model and presented. Papers that had potential implications for conservation but did not provide a basis for spatial planning and management decisions were excluded. The final list contained 217 research articles that met our inclusion criteria.


Deutsche Forschungsgemeinschaft, Award: ZU 361/1-1

Royal Society University Research Fellowship, Award: UF160614

Royal Society University Research Fellowship, Award: UF160614