@article{ZurellKoenigMalchowetal.2022, author = {Zurell, Damaris and K{\"o}nig, Christian and Malchow, Anne-Kathleen and Kapitza, Simon and Bocedi, Greta and Travis, Justin M. J. and Fandos, Guillermo}, title = {Spatially explicit models for decision-making in animal conservation and restoration}, series = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, journal = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, number = {4}, publisher = {Wiley-Blackwell}, address = {Oxford}, issn = {1600-0587}, doi = {10.1111/ecog.05787}, pages = {1 -- 16}, year = {2022}, abstract = {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.}, language = {en} } @article{MalchowBocediPalmeretal.2021, author = {Malchow, Anne-Kathleen and Bocedi, Greta and Palmer, Stephen C. F. and Travis, Justin M. J. and Zurell, Damaris}, title = {RangeShiftR: an R package for individual-based simulation of spatial eco-evolutionary dynamics and speciesu0027 responses to environmental changes}, series = {Ecography}, volume = {44}, journal = {Ecography}, number = {10}, publisher = {John Wiley \& Sons, Inc.}, address = {New Jersey}, issn = {1600-0587}, pages = {10}, year = {2021}, abstract = {Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.}, language = {en} } @article{MalchowBocediPalmeretal.2021, author = {Malchow, Anne-Kathleen and Bocedi, Greta and Palmer, Stephen C. F. and Travis, Justin M. J. and Zurell, Damaris}, title = {RangeShiftR}, series = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, volume = {44}, journal = {Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos}, number = {10}, publisher = {Wiley-Blackwell}, address = {Oxford [u.a.]}, issn = {1600-0587}, doi = {10.1111/ecog.05689}, pages = {1443 -- 1452}, year = {2021}, abstract = {Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.}, language = {en} } @article{BocediZurellReinekingetal.2014, author = {Bocedi, Greta and Zurell, Damaris and Reineking, Bjoern and Travis, Justin M. J.}, title = {Mechanistic modelling of animal dispersal offers new insights into range expansion dynamics across fragmented landscapes}, series = {Ecography : pattern and diversity in ecology ; research papers forum}, volume = {37}, journal = {Ecography : pattern and diversity in ecology ; research papers forum}, number = {12}, publisher = {Wiley-Blackwell}, address = {Hoboken}, issn = {0906-7590}, doi = {10.1111/ecog.01041}, pages = {1240 -- 1253}, year = {2014}, language = {en} }