TY - JOUR A1 - Malchow, Anne-Kathleen A1 - Bocedi, Greta A1 - Palmer, Stephen C. F. A1 - Travis, Justin M. J. A1 - Zurell, Damaris T1 - RangeShiftR BT - an R package for individual-based simulation of spatial changes JF - Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos N2 - 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. KW - connectivity KW - conservation KW - dispersal KW - evolution KW - population dynamics KW - range dynamics Y1 - 2021 U6 - https://doi.org/10.1111/ecog.05689 SN - 1600-0587 VL - 44 IS - 10 SP - 1443 EP - 1452 PB - Wiley-Blackwell CY - Oxford [u.a.] ER - TY - JOUR A1 - Malchow, Anne-Kathleen A1 - Bocedi, Greta A1 - Palmer, Stephen C. F. A1 - Travis, Justin M. J. A1 - Zurell, Damaris T1 - RangeShiftR: an R package for individual-based simulation of spatial eco-evolutionary dynamics and speciesu0027 responses to environmental changes JF - Ecography N2 - 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. KW - connectivity KW - conservation KW - dispersal KW - evolution KW - population dynamics KW - range dynamics Y1 - 2021 SN - 1600-0587 VL - 44 IS - 10 PB - John Wiley & Sons, Inc. CY - New Jersey ER - TY - JOUR A1 - Zurell, Damaris A1 - König, Christian A1 - Malchow, Anne-Kathleen A1 - Kapitza, Simon A1 - Bocedi, Greta A1 - Travis, Justin M. J. A1 - Fandos, Guillermo T1 - Spatially explicit models for decision-making in animal conservation and restoration JF - Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos N2 - 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. KW - adaptive management KW - biodiversity conservation KW - cost optimisation KW - ecosystem restoration KW - global change KW - predictive models Y1 - 2021 U6 - https://doi.org/10.1111/ecog.05787 SN - 1600-0587 IS - 4 SP - 1 EP - 16 PB - Wiley-Blackwell CY - Oxford ER - TY - JOUR A1 - Emary, Clive A1 - Malchow, Anne-Kathleen T1 - Stability-instability transition in tripartite merged ecological networks JF - Journal of mathematical biology N2 - Although ecological networks are typically constructed based on a single type of interaction, e.g. trophic interactions in a food web, a more complete picture of ecosystem composition and functioning arises from merging networks of multiple interaction types. In this work, we consider tripartite networks constructed by merging two bipartite networks, one mutualistic and one antagonistic. Taking the interactions within each sub-network to be distributed randomly, we consider the stability of the dynamics of the network based on the spectrum of its community matrix. In the asymptotic limit of a large number of species, we show that the spectrum undergoes an eigenvalue phase transition, which leads to an abrupt destabilisation of the network as the ratio of mutualists to antagonists is increased. We also derive results that show how this transition is manifest in networks of finite size, as well as when disorder is introduced in the segregation of the two interaction types. Our random-matrix results will serve as a baseline for understanding the behaviour of merged networks with more realistic structures and/or more detailed dynamics. KW - Random matrices KW - Phase transition KW - Random eigenvalues KW - Population dynamics KW - Community matrix KW - Ecological network Y1 - 2022 U6 - https://doi.org/10.1007/s00285-022-01783-7 SN - 0303-6812 SN - 1432-1416 VL - 85 IS - 3 PB - Springer CY - Heidelberg ER -