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 - 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 - GEN 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 T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1178 KW - connectivity KW - conservation KW - dispersal KW - evolution KW - population dynamics KW - range dynamics Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-523979 SN - 1866-8372 IS - 10 ER - TY - JOUR A1 - de Oliveira-Silva, Anna Elizabeth A1 - Piratelli, Augusto João A1 - Zurell, Damaris A1 - da Silva, Fernando Rodrigues T1 - Vegetation cover restricts habitat suitability predictions of endemic Brazilian Atlantic Forest birds JF - Perspectives in Ecology and Conservation N2 - Ecological niche models (ENMs) are often used to investigate how climatic variables from known occurrence records can estimate potential species range distribution. Although climate-based ENMs provide critical baseline information, the inclusion of non-climatic predictors related to vegetation cover might generate more realistic scenarios. This assumption is particularly relevant for species with life-history traits related to forest habitats and sensitive to habitat loss and fragmentation. Here, we developed ENMs for 36 Atlantic Forest endemic birds considering two sets of predictor variables: (i) climatic variables only and (ii) climatic variables combined with the percentage of remaining native vegetation. We hypothesized that the inclusion of native vegetation data would decrease the potential range distribution of forest-dependent species by limiting their occurrence in regions harboring small areas of native vegetation habitats, despite otherwise favorable climatic conditions. We also expected that habitat restriction in the climate-vegetation models would be more pronounced for highly forest-dependent birds. The inclusion of vegetation data in the modeling procedures restricted the final distribution ranges of 22 out of 36 modeled species, while the 14 remaining presented an expansion of their ranges. We observed that species with high and medium forest dependency showed higher restriction in range size predictions between predictor sets than species with low forest dependency, which showed no alteration or range expansion. Overall, our results suggest that ENMs based on climatic and landscape variables may be a useful tool for conservationists to better understand the dynamic of bird species distributions in threatened and highly fragmented regions such as the Atlantic Forest hotspot.(c) 2021 Associacao Brasileira de Cie circumflex accent ncia Ecol ogica e Conservacao. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ ). KW - Conservation KW - Ecological niche modeling KW - Forest dependency KW - Fragmentation KW - Habitat loss KW - Landscape KW - Life-history traits Y1 - 2021 U6 - https://doi.org/10.1016/j.pecon.2021.09.002 SN - 2530-0644 VL - 20 IS - 1 SP - 1 EP - 8 PB - Elsevier CY - Oxford ER - TY - GEN 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 T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1243 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-549915 SN - 1866-8372 VL - 2022 SP - 1 EP - 16 PB - Universitätsverlag Potsdam CY - Potsdam ET - 4 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 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 - Zurell, Damaris A1 - von Wehrden, Henrik A1 - Rotics, Shay A1 - Kaatz, Michael A1 - Gross, Helge A1 - Schlag, Lena A1 - Schäfer, Merlin A1 - Sapir, Nir A1 - Turjeman, Sondra A1 - Wikelski, Martin A1 - Nathan, Ran A1 - Jeltsch, Florian T1 - Home range size and resource use of breeding and non-breeding white storks along a land use gradient JF - Frontiers in Ecology and Evolution N2 - Biotelemetry is increasingly used to study animal movement at high spatial and temporal resolution and guide conservation and resource management. Yet, limited sample sizes and variation in space and habitat use across regions and life stages may compromise robustness of behavioral analyses and subsequent conservation plans. Here, we assessed variation in (i) home range sizes, (ii) home range selection, and (iii) fine-scale resource selection of white storks across breeding status and regions and test model transferability. Three study areas were chosen within the Central German breeding grounds ranging from agricultural to fluvial and marshland. We monitored GPS-locations of 62 adult white storks equipped with solar-charged GPS/3D-acceleration (ACC) transmitters in 2013-2014. Home range sizes were estimated using minimum convex polygons. Generalized linear mixed models were used to assess home range selection and fine-scale resource selection by relating the home ranges and foraging sites to Corine habitat variables and normalized difference vegetation index in a presence/pseudo-absence design. We found strong variation in home range sizes across breeding stages with significantly larger home ranges in non-breeding compared to breeding white storks, but no variation between regions. Home range selection models had high explanatory power and well predicted overall density of Central German white stork breeding pairs. Also, they showed good transferability across regions and breeding status although variable importance varied considerably. Fine-scale resource selection models showed low explanatory power. Resource preferences differed both across breeding status and across regions, and model transferability was poor. Our results indicate that habitat selection of wild animals may vary considerably within and between populations, and is highly scale dependent. Thereby, home range scale analyses show higher robustness whereas fine-scale resource selection is not easily predictable and not transferable across life stages and regions. Such variation may compromise management decisions when based on data of limited sample size or limited regional coverage. We thus recommend home range scale analyses and sampling designs that cover diverse regional landscapes and ensure robust estimates of habitat suitability to conserve wild animal populations. KW - 3D-acceleration sensor KW - biotelemetry KW - Ciconia ciconia KW - home range selection KW - resource selection Y1 - 2018 U6 - https://doi.org/10.3389/fevo.2018.00079 SN - 2296-701X VL - 6 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Schäfer, Merlin A1 - Menz, Stephan A1 - Jeltsch, Florian A1 - Zurell, Damaris T1 - sOAR: a tool for modelling optimal animal life-history strategies in cyclic environments JF - Ecography : pattern and diversity in ecology ; research papers forum N2 - Periodic environments determine the life cycle of many animals across the globe and the timing of important life history events, such as reproduction and migration. These adaptive behavioural strategies are complex and can only be fully understood (and predicted) within the framework of natural selection in which species adopt evolutionary stable strategies. We present sOAR, a powerful and user-friendly implementation of the well-established framework of optimal annual routine modelling. It allows determining optimal animal life history strategies under cyclic environmental conditions using stochastic dynamic programming. It further includes the simulation of population dynamics under the optimal strategy. sOAR provides an important tool for theoretical studies on the behavioural and evolutionary ecology of animals. It is especially suited for studying bird migration. In particular, we integrated options to differentiate between costs of active and passive flight into the optimal annual routine modelling framework, as well as options to consider periodic wind conditions affecting flight energetics. We provide an illustrative example of sOAR where food supply in the wintering habitat of migratory birds significantly alters the optimal timing of migration. sOAR helps improving our understanding of how complex behaviours evolve and how behavioural decisions are constrained by internal and external factors experienced by the animal. Such knowledge is crucial for anticipating potential species’ response to global environmental change. Y1 - 2017 U6 - https://doi.org/10.1111/ecog.03328 SN - 0906-7590 SN - 1600-0587 VL - 41 IS - 3 SP - 551 EP - 557 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Rotics, Shay A1 - Kaatz, Michael A1 - Resheff, Yehezkel S. A1 - Turjeman, Sondra Feldman A1 - Zurell, Damaris A1 - Sapir, Nir A1 - Eggers, Ute A1 - Flack, Andrea A1 - Fiedler, Wolfgang A1 - Jeltsch, Florian A1 - Wikelski, Martin A1 - Nathan, Ran T1 - The challenges of the first migration: movement and behaviour of juvenile vs. adult white storks with insights regarding juvenile mortality JF - Journal of animal ecology : a journal of the British Ecological Society N2 - 1. Migration conveys an immense challenge, especially for juvenile birds coping with enduring and risky journeys shortly after fledging. Accordingly, juveniles exhibit considerably lower survival rates compared to adults, particularly during migration. Juvenile white storks (Ciconia ciconia), which are known to rely on adults during their first fall migration presumably for navigational purposes, also display much lower annual survival than adults. 2. Using detailed GPS and body acceleration data, we examined the patterns and potential causes of age-related differences in fall migration properties of white storks by comparing first-year juveniles and adults. We compared juvenile and adult parameters of movement, behaviour and energy expenditure (estimated from overall dynamic body acceleration) and placed this in the context of the juveniles’ lower survival rate. 3. Juveniles used flapping flight vs. soaring flight 23% more than adults and were estimated to expend 14% more energy during flight. Juveniles did not compensate for their higher flight costs by increased refuelling or resting during migration. When juveniles and adults migrated together in the same flock, the juvenile flew mostly behind the adult and was left behind when they separated. Juveniles showed greater improvement in flight efficiency throughout migration compared to adults which appears crucial because juveniles exhibiting higher flight costs suffered increased mortality. 4. Our findings demonstrate the conflict between the juveniles’ inferior flight skills and their urge to keep up with mixed adult–juvenile flocks. We suggest that increased flight costs are an important proximate cause of juvenile mortality in white storks and likely in other soaring migrants and that natural selection is operating on juvenile variation in flight efficiency. KW - flight KW - flight efficiency KW - juvenile mortality KW - migration KW - white stork Y1 - 2016 U6 - https://doi.org/10.1111/1365-2656.12525 SN - 0021-8790 SN - 1365-2656 VL - 85 SP - 938 EP - 947 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Zurell, Damaris A1 - Eggers, Ute A1 - Kaatz, Michael A1 - Rotics, Shay A1 - Sapir, Nir A1 - Wikelski, Martin A1 - Nathan, Ran A1 - Jeltsch, Florian T1 - Individual-based modelling of resource competition to predict density-dependent population dynamics: a case study with white storks JF - Oikos N2 - Density regulation influences population dynamics through its effects on demographic rates and consequently constitutes a key mechanism explaining the response of organisms to environmental changes. Yet, it is difficult to establish the exact form of density dependence from empirical data. Here, we developed an individual-based model to explore how resource limitation and behavioural processes determine the spatial structure of white stork Ciconia ciconia populations and regulate reproductive rates. We found that the form of density dependence differed considerably between landscapes with the same overall resource availability and between home range selection strategies, highlighting the importance of fine-scale resource distribution in interaction with behaviour. In accordance with theories of density dependence, breeding output generally decreased with density but this effect was highly variable and strongly affected by optimal foraging strategy, resource detection probability and colonial behaviour. Moreover, our results uncovered an overlooked consequence of density dependence by showing that high early nestling mortality in storks, assumed to be the outcome of harsh weather, may actually result from density dependent effects on food provision. Our findings emphasize that accounting for interactive effects of individual behaviour and local environmental factors is crucial for understanding density-dependent processes within spatially structured populations. Enhanced understanding of the ways animal populations are regulated in general, and how habitat conditions and behaviour may dictate spatial population structure and demographic rates is critically needed for predicting the dynamics of populations, communities and ecosystems under changing environmental conditions. Y1 - 2015 U6 - https://doi.org/10.1111/oik.01294 SN - 0030-1299 SN - 1600-0706 VL - 124 IS - 3 SP - 319 EP - 330 PB - Wiley-Blackwell CY - Hoboken ER -