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 - 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 - CHAP A1 - Sapir, N. A1 - Rotics, S. A1 - Kaatz, M. A1 - Davidson, S. A1 - Zurell, Damaris A1 - Eggers, U. A1 - Jeltsch, Florian A1 - Nathan, R. A1 - Wikelski, M. T1 - Multi-year tracking of white storks (Ciconia ciconia) how the environment shapes the movement and behavior of a soaring-gliding inter-continental migrant T2 - Integrative and comparative biology Y1 - 2013 SN - 1540-7063 VL - 53 IS - 3 SP - E189 EP - E189 PB - Oxford Univ. Press CY - Cary ER - TY - JOUR A1 - Zurell, Damaris A1 - Jeltsch, Florian A1 - Dormann, Carsten F. A1 - Schröder-Esselbach, Boris T1 - Static species distribution models in dynamically changing systems : how good can predictions really be? N2 - SDM performance varied for different range dynamics. Prediction accuracies decreased when abrupt range shifts occurred as species were outpaced by the rate of climate change, and increased again when a new equilibrium situation was realised. When ranges contracted, prediction accuracies increased as the absences were predicted well. Far- dispersing species were faster in tracking climate change, and were predicted more accurately by SDMs than short- dispersing species. BRTs mostly outperformed GLMs. The presence of a predator, and the inclusion of its incidence as an environmental predictor, made BRTs and GLMs perform similarly. Results are discussed in light of other studies dealing with effects of ecological traits and processes on SDM performance. Perspectives are given on further advancements of SDMs and for possible interfaces with more mechanistic approaches in order to improve predictions under environmental change. Y1 - 2009 UR - http://www3.interscience.wiley.com/journal/117966123/home?CRETRY=1&SRETRY=0 U6 - https://doi.org/10.1111/j.1600-0587.2009.05810.x SN - 0906-7590 ER - TY - JOUR A1 - Zurell, Damaris A1 - Berger, Uta A1 - Cabral, Juliano Sarmento A1 - Jeltsch, Florian A1 - Meynard, Christine N. A1 - Muenkemueller, Tamara A1 - Nehrbass, Nana A1 - Pagel, Jörn A1 - Reineking, Bjoern A1 - Schroeder, Boris A1 - Grimm, Volker T1 - The virtual ecologist approach : simulating data and observers N2 - Ecologists carry a well-stocked toolbox with a great variety of sampling methods, statistical analyses and modelling tools, and new methods are constantly appearing. Evaluation and optimisation of these methods is crucial to guide methodological choices. Simulating error-free data or taking high-quality data to qualify methods is common practice. Here, we emphasise the methodology of the 'virtual ecologist' (VE) approach where simulated data and observer models are used to mimic real species and how they are 'virtually' observed. This virtual data is then subjected to statistical analyses and modelling, and the results are evaluated against the 'true' simulated data. The VE approach is an intuitive and powerful evaluation framework that allows a quality assessment of sampling protocols, analyses and modelling tools. It works under controlled conditions as well as under consideration of confounding factors such as animal movement and biased observer behaviour. In this review, we promote the approach as a rigorous research tool, and demonstrate its capabilities and practical relevance. We explore past uses of VE in different ecological research fields, where it mainly has been used to test and improve sampling regimes as well as for testing and comparing models, for example species distribution models. We discuss its benefits as well as potential limitations, and provide some practical considerations for designing VE studies. Finally, research fields are identified for which the approach could be useful in the future. We conclude that VE could foster the integration of theoretical and empirical work and stimulate work that goes far beyond sampling methods, leading to new questions, theories, and better mechanistic understanding of ecological systems. Y1 - 2010 UR - http://www3.interscience.wiley.com/cgi-bin/issn?DESCRIPTOR=PRINTISSN&VALUE=0030-1299 U6 - https://doi.org/10.1111/j.1600-0706.2009.18284.x SN - 0030-1299 ER - TY - JOUR A1 - Thuiller, Wilfried A1 - Muenkemueller, Tamara A1 - Schiffers, Katja H. A1 - Georges, Damien A1 - Dullinger, Stefan A1 - Eckhart, Vincent M. A1 - Edwards, Thomas C. A1 - Gravel, Dominique A1 - Kunstler, Georges A1 - Merow, Cory A1 - Moore, Kara A1 - Piedallu, Christian A1 - Vissault, Steve A1 - Zimmermann, Niklaus E. A1 - Zurell, Damaris A1 - Schurr, Frank Martin T1 - Does probability of occurrence relate to population dynamics? JF - Ecography : pattern and diversity in ecology ; research papers forum N2 - Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with P-occ, while N, and for most regions K, was generally positively correlated with P-occ. Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models. Y1 - 2014 U6 - https://doi.org/10.1111/ecog.00836 SN - 0906-7590 SN - 1600-0587 VL - 37 IS - 12 SP - 1155 EP - 1166 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Dormann, Carsten F. A1 - Elith, Jane A1 - Bacher, Sven A1 - Buchmann, Carsten M. A1 - Carl, Gudrun A1 - Carre, Gabriel A1 - Garcia Marquez, Jaime R. A1 - Gruber, Bernd A1 - Lafourcade, Bruno A1 - Leitao, Pedro J. A1 - Münkemüller, Tamara A1 - McClean, Colin A1 - Osborne, Patrick E. A1 - Reineking, Bjoern A1 - Schröder-Esselbach, Boris A1 - Skidmore, Andrew K. A1 - Zurell, Damaris A1 - Lautenbach, Sven T1 - Collinearity a review of methods to deal with it and a simulation study evaluating their performance JF - Ecography : pattern and diversity in ecology ; research papers forum N2 - Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the folk lore'-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them. Y1 - 2013 U6 - https://doi.org/10.1111/j.1600-0587.2012.07348.x SN - 0906-7590 SN - 1600-0587 VL - 36 IS - 1 SP - 27 EP - 46 PB - Wiley-Blackwell CY - Hoboken ER -