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. Ecography, 36, 27-46.
FRIAS Project
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.