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 - TY - JOUR A1 - Gutt, Julian A1 - Zurell, Damaris A1 - Bracegridle, Thomas J. A1 - Cheung, William A1 - Clark, Melody S. A1 - Convey, Peter A1 - Danis, Bruno A1 - David, Bruno A1 - De Broyer, Claude A1 - di Prisco, Guido A1 - Griffiths, Huw A1 - Laffont, Remi A1 - Peck, Lloyd S. A1 - Pierrat, Benjamin A1 - Riddle, Martin J. A1 - Saucede, Thomas A1 - Turner, John A1 - Verde, Cinzia A1 - Wang, Zhaomin A1 - Grimm, Volker T1 - Correlative and dynamic species distribution modelling for ecological predictions in the Antarctic a cross-disciplinary concept JF - Polar research : a Norwegian journal of Polar research N2 - Developments of future scenarios of Antarctic ecosystems are still in their infancy, whilst predictions of the physical environment are recognized as being of global relevance and corresponding models are under continuous development. However, in the context of environmental change simulations of the future of the Antarctic biosphere are increasingly demanded by decision makers and the public, and are of fundamental scientific interest. This paper briefly reviews existing predictive models applied to Antarctic ecosystems before providing a conceptual framework for the further development of spatially and temporally explicit ecosystem models. The concept suggests how to improve approaches to relating species' habitat description to the physical environment, for which a case study on sea urchins is presented. In addition, the concept integrates existing and new ideas to consider dynamic components, particularly information on the natural history of key species, from physiological experiments and biomolecular analyses. Thereby, we identify and critically discuss gaps in knowledge and methodological limitations. These refer to process understanding of biological complexity, the need for high spatial resolution oceanographic data from the entire water column, and the use of data from biomolecular analyses in support of such ecological approaches. Our goal is to motivate the research community to contribute data and knowledge to a holistic, Antarctic-specific, macroecological framework. Such a framework will facilitate the integration of theoretical and empirical work in Antarctica, improving our mechanistic understanding of this globally influential ecoregion, and supporting actions to secure this biodiversity hotspot and its ecosystem services. KW - Environmental change KW - integrative modelling framework KW - spatially and temporally explicit modelling macroecology KW - biodiversity KW - habitat suitability models Y1 - 2012 U6 - https://doi.org/10.3402/polar.v31i0.11091 SN - 0800-0395 VL - 31 IS - 6 PB - Co-Action Publ. CY - Jarfalla 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 - 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 - Jeltsch, Florian A1 - Blaum, Niels A1 - Brose, Ulrich A1 - Chipperfield, Joseph D. A1 - Clough, Yann A1 - Farwig, Nina A1 - Geissler, Katja A1 - Graham, Catherine H. A1 - Grimm, Volker A1 - Hickler, Thomas A1 - Huth, Andreas A1 - May, Felix A1 - Meyer, Katrin M. A1 - Pagel, Jörn A1 - Reineking, Björn A1 - Rillig, Matthias C. A1 - Shea, Katriona A1 - Schurr, Frank Martin A1 - Schroeder, Boris A1 - Tielbörger, Katja A1 - Weiss, Lina A1 - Wiegand, Kerstin A1 - Wiegand, Thorsten A1 - Wirth, Christian A1 - Zurell, Damaris T1 - How can we bring together empiricists and modellers in functional biodiversity research? JF - Basic and applied ecology : Journal of the Gesellschaft für Ökologie N2 - Improving our understanding of biodiversity and ecosystem functioning and our capacity to inform ecosystem management requires an integrated framework for functional biodiversity research (FBR). However, adequate integration among empirical approaches (monitoring and experimental) and modelling has rarely been achieved in FBR. We offer an appraisal of the issues involved and chart a course towards enhanced integration. A major element of this path is the joint orientation towards the continuous refinement of a theoretical framework for FBR that links theory testing and generalization with applied research oriented towards the conservation of biodiversity and ecosystem functioning. We further emphasize existing decision-making frameworks as suitable instruments to practically merge these different aims of FBR and bring them into application. This integrated framework requires joint research planning, and should improve communication and stimulate collaboration between modellers and empiricists, thereby overcoming existing reservations and prejudices. The implementation of this integrative research agenda for FBR requires an adaptation in most national and international funding schemes in order to accommodate such joint teams and their more complex structures and data needs. KW - Biodiversity theory KW - Biodiversity experiments KW - Conservation management KW - Decision-making KW - Ecosystem functions and services KW - Forecasting KW - Functional traits KW - Global change KW - Monitoring programmes KW - Interdisciplinarity Y1 - 2013 U6 - https://doi.org/10.1016/j.baae.2013.01.001 SN - 1439-1791 VL - 14 IS - 2 SP - 93 EP - 101 PB - Elsevier CY - Jena 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 - THES A1 - Zurell, Damaris T1 - Integrating dynamic and statistical modelling approaches in order to improve predictions for scenarios of environmental change T1 - Integration dynamischer und statistischer Modellansätze zur Verbesserung von Arealvorhersagen für Szenarien globalen Wandels N2 - Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species’ occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species’ distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species’ distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this ‘virtual ecologist’ approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species’ response to altered environmental conditions and which should hence be considered when trying to project species’ distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species’ response to environmental change, identify key challenges for future research and discuss emerging developments. N2 - Das Vorkommen von Arten wird zunehmend bedroht durch Klima- und Landnutzungswandel. Robuste Vorhersagen der damit verbundenen Arealveränderungen sind ausschlaggebend für die Erarbeitung dynamischer und nachhaltiger Naturschutzstrategien. Habitateignungsmodelle erstellen statistische Zusammenhänge zwischen dem Vorkommen einer Art und relevanten Umweltvariablen und erlauben zügige Einschätzungen potentieller Arealveränderungen. Dabei werden jedoch transiente Dynamiken weitgehend ignoriert sowie demographische Prozesse und biotische Interaktionen. Daher wurden Vorschläge laut, diese statistischen Modelle mit mechanistischeren Ansätzen zu koppeln. In der vorliegenden Arbeit zeige ich zwei verschiedene Möglichkeiten solcher Kopplung auf. (i) Ich beschreibe den sogenannten ‚Virtuellen Ökologen’-Ansatz als mächtiges Validierungswerkzeug, in dem mechanistische Modelle virtuelle Testflächen bieten zur Erforschung verschiedener Probenahmedesigns oder statistischer Methoden sowie spezifischer Fragestellungen. Auch verwende ich diesen Ansatz, um systematisch zu untersuchen wie sich transiente Dynamiken sowie Arteigenschaften und ökologische Prozesse auf die Vorhersagegüte von Habitateignungsmodellen auswirken. So kann ich entscheidende Prozesse identifizieren welche in zukünftigen Modellen Berücksichtigung finden sollten. (ii) Darauf aufbauend koppele ich Vorhersagen von Habitateignungsmodellen mit einem individuen-basierten Populationsmodell, um die Entwicklung des Schweizer Birkhuhnbestandes unter Klimawandel vorherzusagen. Durch die explizite Berücksichtigung der Wechselwirkungen zwischen Habitat und demographischer Prozesse lassen sich direktere Aussagen über Populationsentwicklung und damit verbundener Extinktionsrisiken treffen. Allerdings führen verschiedene Simulationen auch zu hoher Variabilität zwischen Vorhersagen, was die Bedeutung von Sensitivitätsanalysen unterstreicht, um Unsicherheiten und Robustheit von Vorhersagen einzuschätzen. Außerdem identifiziere ich Restriktionen in der Datenabdeckung des Umweltraumes als möglichen Grund für kontrastierende Vorhersagen verschiedener Habitateignungsmodelle. Wenn die Nische einer Art nicht vollständig durch Daten beschrieben ist, kann dies zu unrealistischen Vorhersagen der Art-Habitat-Beziehung führen. Insgesamt trägt meine Arbeit erheblich bei zu einem besseren Verständnis der Auswirkung verschiedenster Unsicherheitsfaktoren auf Vorhersagen von Arealveränderungen und zeigt Wege auf, mit diesen umzugehen. Abschließend erstelle ich einen vorläufigen Leitfaden für Vorhersagemodelle und identifiziere Kernpunkte für weitere Forschung auf diesem Gebiet. KW - species distribution models KW - dynamic population models KW - climate change KW - prediction KW - uncertainty KW - Habitatmodelle KW - dynamische Populationsmodelle KW - Klimawandel KW - Vorhersage KW - Unsicherheit Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-56845 ER - TY - GEN A1 - Jeltsch, Florian A1 - Bonte, Dries A1 - Pe'er, Guy A1 - Reineking, Björn A1 - Leimgruber, Peter A1 - Balkenhol, Niko A1 - Schröder-Esselbach, Boris A1 - Buchmann, Carsten M. A1 - Müller, Thomas A1 - Blaum, Niels A1 - Zurell, Damaris A1 - Böhning-Gaese, Katrin A1 - Wiegand, Thorsten A1 - Eccard, Jana A1 - Hofer, Heribert A1 - Reeg, Jette A1 - Eggers, Ute A1 - Bauer, Silke T1 - Integrating movement ecology with biodiversity research BT - exploring new avenues to address spatiotemporal biodiversity dynamics N2 - Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of ‘movement ecology’. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide ‘mobile links’ between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through ‘equalizing’ and ‘stabilizing’ mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 401 KW - mobile links KW - species coexistence KW - community dynamics KW - biodiversity conservation KW - long distance movement KW - landscape genetics KW - individual based modeling Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-401177 ER - TY - JOUR A1 - Jeltsch, Florian A1 - Bonte, Dries A1 - Peer, Guy A1 - Reineking, Björn A1 - Leimgruber, Peter A1 - Balkenhol, Niko A1 - Schröder-Esselbach, Boris A1 - Buchmann, Carsten M. A1 - Müller, Thomas A1 - Blaum, Niels A1 - Zurell, Damaris A1 - Böhning-Gaese, Katrin A1 - Wiegand, Thorsten A1 - Eccard, Jana A1 - Hofer, Heribert A1 - Reeg, Jette A1 - Eggers, Ute A1 - Bauer, Silke T1 - Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics Y1 - 2013 UR - http://download.springer.com/static/pdf/827/art%253A10.1186%252F2051-3933-1- 6.pdf?auth66=1394891271_f1a4cb74d6be42ee3f8872ef2ca22c24&ext=.pdf U6 - https://doi.org/10.1186/2051-3933-1-6 ER - TY - JOUR A1 - Bocedi, Greta A1 - Zurell, Damaris A1 - Reineking, Bjoern A1 - Travis, Justin M. J. T1 - Mechanistic modelling of animal dispersal offers new insights into range expansion dynamics across fragmented landscapes JF - Ecography : pattern and diversity in ecology ; research papers forum Y1 - 2014 U6 - https://doi.org/10.1111/ecog.01041 SN - 0906-7590 SN - 1600-0587 VL - 37 IS - 12 SP - 1240 EP - 1253 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 - Günther, Oliver A1 - Schüle, Manja A1 - Zurell, Damaris A1 - Jeltsch, Florian A1 - Roeleke, Manuel A1 - Kampe, Heike A1 - Zimmermann, Matthias A1 - Scholz, Jana A1 - Mikulla, Stefanie A1 - Engbert, Ralf A1 - Elsner, Birgit A1 - Schlangen, David A1 - Agrofylax, Luisa A1 - Georgi, Doreen A1 - Weymar, Mathias A1 - Wagener, Thorsten A1 - Bookhagen, Bodo A1 - Eibl, Eva P. S. A1 - Korup, Oliver A1 - Oswald, Sascha Eric A1 - Thieken, Annegret A1 - van der Beek, Peter T1 - Portal Wissen = Excellence JF - Portal Wissen: The research magazine of the University of Potsdam N2 - When something is not just good or very good, we often call it excellent. But what does that really mean? Coming from the Latin word “excellere,” it describes things, persons, or actions that are outstanding or superior and distinguish themselves from others. It cannot get any better. Excellence is the top choice for being the first or the best. Research is no exception. At the university, you will find numerous exceptional researchers, outstanding projects, and, time and again, sensational findings, publications, and results. But is the University of Potsdam also excellent? A question that will certainly create a different stir in 2023 than it did perhaps 20 years ago. Since the launch of the Excellence Initiative in 2005, universities that succeed in winning the most comprehensive funding program for research in Germany have been considered – literally – excellent. Whether in the form of graduate schools, research clusters, or – since the program was continued in 2019 under the title “Excellence Strategy” – entire universities of excellence: Anyone who wants to be among the best research universities needs the seal of excellence. The University of Potsdam is applying for funding with three cluster proposals in the recently launched new round of the “Excellence Strategy of the German Federal and State Governments.” One proposal comes from ecology and biodiversity research. The aim is to paint a comprehensive picture of ecological processes by examining the role of single individuals as well as the interactions among many species in an ecosystem to precisely determine the function of biodiversity. A second proposal has been submitted by the cognitive sciences. Here, the complex coexistence of language and cognition, development and learning, as well as motivation and behavior will be researched as a dynamic interrelation. The projects will include cooperation with the educational sciences to constantly consider linked learning and educational processes. The third proposal from the geo and environmental sciences concentrates on extreme and particularly devastating natural hazards and processes such as floods and droughts. The researchers examine these extreme events, focusing on their interaction with society, to be able to better assess the risks and damages they might involve and to initiate timely measures in the future. “All three proposals highlight the excellence of our performance,” emphasizes University President Prof. Oliver Günther, Ph.D. “The outlines impressively document our commitment, existing research excellence, and the potential of the University of Potsdam as a whole. The fact that three powerful consortia have come together in different subject areas shows that we have taken a good step forward on our way to becoming one of the top German universities.” In this issue, we are looking at what is in and behind these proposals: We talked to the researchers who wrote them. We asked them about their plans in case their proposals are successful and they bring a cluster of excellence to the university. But we also looked at the research that has led to the proposals, has long shaped the university’s profile, and earned it national and international recognition. We present a small selection of projects, methods, and researchers to illustrate why there really is excellent research in these proposals! By the way, “excellence” is also not the end of the flagpole. After all, the adjective “excellent” even has a comparative and a superlative. With this in mind, I wish you the most excellent pleasure reading this issue! T3 - Portal Wissen: The research magazine of the University of Potsdam [Englische Ausgabe] - 02/2023 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-611456 SN - 2198-9974 IS - 02/2023 ER - TY - JOUR A1 - Günther, Oliver A1 - Schüle, Manja A1 - Zurell, Damaris A1 - Jeltsch, Florian A1 - Roeleke, Manuel A1 - Kampe, Heike A1 - Zimmermann, Matthias A1 - Scholz, Jana A1 - Engbert, Ralf A1 - Elsner, Birgit A1 - Schlangen, David A1 - Agrofylax, Luisa A1 - Georgi, Doreen A1 - Weymar, Mathias A1 - Wagener, Thorsten A1 - Bookhagen, Bodo A1 - Eibl, Eva P. S. A1 - Korup, Oliver A1 - Oswald, Sascha Eric A1 - Thieken, Annegret A1 - van der Beek, Peter T1 - Portal Wissen = Exzellenz JF - Portal Wissen: Das Forschungsmagazin der Universität Potsdam N2 - Was nicht nur gut oder sehr gut ist, nennen wir gern exzellent. Aber was meint das eigentlich? Vom lateinischen „excellere“ kommend, beschreibt es Dinge, Personen oder Handlungen, die „hervor-“ oder „herausragen“ aus der Menge, sich „auszeichnen“ gegenüber anderen. Mehr geht nicht. Exzellenz ist das Mittel der Wahl, wenn es darum geht, der Erste oder Beste zu sein. Und das macht auch vor der Forschung nicht halt. Wer auf die Universität Potsdam schaut, findet zahlreiche ausgezeichnete Forschende, hervorragende Projekte und immer wieder auch aufsehenerregende Erkenntnisse, Veröffentlichungen und Ergebnisse. Aber ist die UP auch exzellent? Eine Frage, die 2023 ganz sicher andere Wellen schlägt als vielleicht vor 20 Jahren. Denn seit dem Start der Exzellenzinitiative 2005 gelten als – wörtlich – exzellent jene Hochschulen, denen es gelingt, in dem umfangreichsten Förderprogramm für Wissenschaft in Deutschland einen Zuschlag zu erhalten. Egal ob in Form von Graduiertenschulen, Forschungsclustern oder – seit Fortsetzung des Programms ab 2019 unter dem Titel „Exzellenzstrategie“ – ganzen Exzellenzuniversitäten: Wer im Kreis der Forschungsuniversitäten zu den Besten gehören will, braucht das Siegel der Exzellenz. In der gerade eingeläuteten neuen Wettbewerbsrunde der „Exzellenzstrategie des Bundes und der Länder“ bewirbt sich die Universität Potsdam mit drei Clusterskizzen um Förderung. Ein Antrag kommt aus der Ökologie- und Biodiversitätsforschung. Ziel ist es, ein komplexes Bild ökologischer Prozesse zu zeichnen – und dabei die Rolle von einzelnen Individuen ebenso zu betrachten wie das Zusammenwirken vieler Arten in einem Ökosystem, um die Funktion der Artenvielfalt genauer zu bestimmen. Eine zweite Skizze haben die Kognitionswissenschaften eingereicht. Hier soll das komplexe Nebeneinander von Sprache und Kognition, Entwicklung und Lernen sowie Motivation und Verhalten als dynamisches Miteinander erforscht werden – wobei auch mit den Erziehungswissenschaften kooperiert wird, um verknüpfte Lernund Bildungsprozesse stets mitzudenken. Der dritte Antrag aus den Geo- und Umweltwissenschaften nimmt extreme und besonders folgenschwere Naturgefahren und -prozesse wie Überschwemmungen und Dürren in den Blick. Die Forschenden untersuchen die Extremereignisse mit besonderem Fokus auf deren Wechselwirkung mit der Gesellschaft, um mit ihnen einhergehende Risiken und Schäden besser einschätzen sowie künftig rechtzeitig Maßnahmen einleiten zu können. „Alle drei Anträge zeichnen ein hervorragendes Bild unserer Leistungsfähigkeit“, betont der Präsident der Universität, Prof. Oliver Günther, Ph.D. „Die Skizzen dokumentieren eindrucksvoll unser Engagement, vorhandene Forschungsexzellenz sowie die Potenziale der Universität Potsdam insgesamt. Allein die Tatsache, dass sich drei schlagkräftige Konsortien in ganz unterschiedlichen Themenbereichen zusammengefunden haben, zeigt, dass wir auf unserem Weg in die Spitzengruppe der deutschen Universitäten einen guten Schritt vorangekommen sind.“ In diesem Heft schauen wir, was sich in und hinter diesen Anträgen verbirgt: Wir haben mit den Wissenschaftlerinnen und Wissenschaftlern gesprochen, die sie geschrieben haben, und sie gefragt, was sie sich vornehmen, sollten sie den Zuschlag erhalten und ein Cluster an die Universität holen. Wir haben aber auch auf die Forschung geschaut, die zu den Anträgen geführt hat und die schon länger das Profil der Universität prägt und ihr national wie international Anerkennung eingebracht hat. Wir stellen eine kleine Auswahl an Projekten, Methoden und Forschenden vor, um zu zeigen, warum in diesen Anträgen tatsächlich exzellente Forschung steckt! Übrigens: Auch „Exzellenz“ ist nicht das Ende der Fahnenstange. Immerhin lässt sich das Adjektiv exzellent sogar steigern. In diesem Sinne wünschen wir exzellentestes Vergnügen beim Lesen! T3 - Portal Wissen: Das Forschungsmagazin der Universität Potsdam [Deutsche Ausgabe] - 02/2023 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-611440 SN - 2194-4245 IS - 02/2023 ER - TY - GEN A1 - Zurell, Damaris A1 - Elith, Jane A1 - Schröder-Esselbach, Boris T1 - Predicting to new environments tools for visualizing model behaviour and impacts on mapped distributions T2 - Diversity & distributions : a journal of biological invasions and biodiversity N2 - Data limitations can lead to unrealistic fits of predictive species distribution models (SDMs) and spurious extrapolation to novel environments. Here, we want to draw attention to novel combinations of environmental predictors that are within the sampled range of individual predictors but are nevertheless outside the sample space. These tend to be overlooked when visualizing model behaviour. They may be a cause of differing model transferability and environmental change predictions between methods, a problem described in some studies but generally not well understood. We here use a simple simulated data example to illustrate the problem and provide new and complementary visualization techniques to explore model behaviour and predictions to novel environments. We then apply these in a more complex real-world example. Our results underscore the necessity of scrutinizing model fits, ecological theory and environmental novelty. KW - Environmental niche KW - extrapolation KW - inflated response curves KW - novel environment KW - sampling space KW - species distribution models Y1 - 2012 U6 - https://doi.org/10.1111/j.1472-4642.2012.00887.x SN - 1366-9516 VL - 18 IS - 6 SP - 628 EP - 634 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 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 - 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 - 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 - 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 - 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 -