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  - 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  - 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  - Grimm, Volker
A1  - Rossmanith, Eva
A1  - Zbinden, Niklaus
A1  - Zimmermann, Niklaus E.
A1  - Schröder-Esselbach, Boris
T1  - Uncertainty in predictions of range dynamics black grouse climbing the Swiss Alps
JF  - Ecography : pattern and diversity in ecology ; research papers forum
N2  - Empirical species distribution models (SDMs) constitute often the tool of choice for the assessment of rapid climate change effects on species vulnerability. Conclusions regarding extinction risks might be misleading, however, because SDMs do not explicitly incorporate dispersal or other demographic processes. Here, we supplement SDMs with a dynamic population model 1) to predict climate-induced range dynamics for black grouse in Switzerland, 2) to compare direct and indirect measures of extinction risks, and 3) to quantify uncertainty in predictions as well as the sources of that uncertainty. To this end, we linked models of habitat suitability to a spatially explicit, individual-based model. In an extensive sensitivity analysis, we quantified uncertainty in various model outputs introduced by different SDM algorithms, by different climate scenarios and by demographic model parameters. Potentially suitable habitats were predicted to shift uphill and eastwards. By the end of the 21st century, abrupt habitat losses were predicted in the western Prealps for some climate scenarios. In contrast, population size and occupied area were primarily controlled by currently negative population growth and gradually declined from the beginning of the century across all climate scenarios and SDM algorithms. However, predictions of population dynamic features were highly variable across simulations. Results indicate that inferring extinction probabilities simply from the quantity of suitable habitat may underestimate extinction risks because this may ignore important interactions between life history traits and available habitat. Also, in dynamic range predictions uncertainty in SDM algorithms and climate scenarios can become secondary to uncertainty in dynamic model components. Our study emphasises the need for principal evaluation tools like sensitivity analysis in order to assess uncertainty and robustness in dynamic range predictions. A more direct benefit of such robustness analysis is an improved mechanistic understanding of dynamic species responses to climate change.
Y1  - 2012
U6  - https://doi.org/10.1111/j.1600-0587.2011.07200.x
SN  - 0906-7590
VL  - 35
IS  - 7
SP  - 590
EP  - 603
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  - 
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  - 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  - 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  -