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Portal Wissen = Excellence
(2023)
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!
Portal Wissen = Exzellenz
(2023)
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!
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.
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.
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.
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.