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You are here: FRIAS Fellows Fellows 2021/22 Prof. Dr. Carsten Dormann

Prof. Dr. Carsten Dormann

Source: private
University of Freiburg
Biometry and Environmental System Analysis
Internal Senior Fellow
October 2019 - July 2020

Room 01 026
Phone +49 (0) 761-203 97344
Fax +49 (0) 761-203 97451


Carsten Dormann studied Biology, with specialisation in botany but also marine science, at the University of Kiel, Germany and did his early research on herbivory in natural systems (the saltmarshes in the Netherlands, and the high arctic tundra of Spitsbergen). After earning his PhD at the University of Aberdeen, UK, in 2001 and a brief spell as PostDoc on invasive plants on Crete, he transitioned more and more towards statistical ecology and macroecology. During his PostDoc at the Helmholtz Centre for Environmental Research UFZ in Leipzig in the Department of Computational Landscape Ecology he established his own Junior Research Group on biotic ecosystem services, in collaboration with the University of Göttingen, where he also habilitated (an anachronistic step akin to a higher-level PhD) in 2008. Since 2011 he holds a full professorship for Biometry and Environmental System Analysis at the University of Freiburg. His main research focus remains statistical ecology, but with a stronger focus on marrying statistics and process-based environmental models.


Selected Publications

  • Dormann, C. F.; Bobrowski, M.; Dehling, D. M.; Harris, D. J.; Hartig, F.; Lischke, H.; Moretti, M.; Pagel, J.; Pinkert, S.; Schleuning, M.; Schmidt, S. I.; Sheppard, C. S.; Steinbauer, M. J.; Zeuss, D. & Kraan, C. (2018) Biotic interactions in species distribution modelling: ten questions to guide interpretation and avoid false conclusions. Global Ecology and Biogeography 27, 14-116.
  • Dormann, C. F., Guillera-Arroita, G., Calabrese, J. M., Matechou, E., Bahn, V., Bartón, K., … Hartig, F. (2018). Model averaging in ecology: a review of Bayesian, information-theoretic and tactical approaches for predictive inference. Ecological Monographs 88, 485-504.
  • Dormann, C.F., Fründ, J. & Schaefer, H.M. (2017) Opportunities and limitations for identifying the underlying causes of patterns in ecological networks. Annual Review of Ecology, Evolution, and Systematics, 48, 559-584.
  • Roberts, D.R., Bahn, V., Ciuti, S., Boyce, M.S., Elith, J., Guillera-Arroita, G., Severin Hauenstein, Lahoz-Monfort, J.J., Schröder, B., Thuiller, W., Warton, D.I., Wintle, B.A., Hartig, F. & Dormann, C.F. 2017. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40, 913-929.
  • Dormann, C.F., Elith, J, Bacher, S., Buchmann, C.M., Carl, G., Carré, G., Diekötter, T., Marquéz, J.R.G., Gruber, B., Lafourcade, B., Leitão, P.J., Münkemüller, T., McClean, C., Osborne, P., Reineking, B., Schröder, B., Skidmore, A., Zurell, D. & Lautenbach, S. 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography36, 27-46.



FRIAS Research Focus Environmental Forecasting

Environmental models are the main tool through which our understanding of natural processes is transferred into practice in a human-dominated world: weather forecasts, flood warnings, carbon balances of forests, landslides, recycling budgets are computed using environmental models along a range of complexity. Such environmental models comprise representations of the natural processes as well as human impacts, and include economic models, such as those simulating trade and environmental impacts at local to global scales.

Environmental disciplines have evolved strikingly divergent modelling cultures, of different scientific credibility. The aim of the Research Focus at the FRIAS is to understand modelling cultures as reflecting distinct goals, distil a best practice from disciplinary experiences that makes environmental forecasts credible across environmental disciplines, and to formulate a research agenda for those areas where we can identify deficits without an existing solution.