Niklaus E. Zimmermann

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Jane Elith*, Catherine H. Graham*, Robert P. Anderson, Miroslav Dudı́k, Simon Ferrier, Antoine Guisan, Robert J. Hijmans, Falk Huettmann, John R. Leathwick, Anthony Lehmann, Jin Li, Lucia G. Lohmann, Bette A. Loiselle, Glenn Manion, Craig Moritz, Miguel Nakamura, Yoshinori Nakazawa, Jacob McC. Overton, A. Townsend Peterson, Steven J. Phillips, Karen(More)
Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species’ range shifts, changes in phenology and species’ extinctions,(More)
Because data on rare species usually are sparse, it is important to have efficient ways to sample additional data. Traditional sampling approaches are of limited value for rare species because a very large proportion of randomly chosen sampling sites are unlikely to shelter the species. For these species, spatial predictions from niche-based distribution(More)
J. Lenoir (lenoir.john@gmail.com), The Ecoinformatics & Biodiversity Group, Dept of Biological Sciences, Aarhus Univ., Ny Munkegade 114, DK-8000 Aarhus C, Denmark and AgroParisTech, UMR1092 AgroParisTech-INRA, Laboratoire d’Etude des Ressources Forêt-Bois (LERFoB), 14 rue Girardet, FR-54000 Nancy, France. J.-C. Gégout, AgroParisTech, UMR1092(More)
Ecoinformatics & Biodiversity Group, Department of Bioscience, Aarhus University, DK-8000 Aarhus C, Denmark, Biometry and Environmental System Analysis, Faculty of Forest and Environmental Sciences, University of Freiburg, 79106 Freiburg, Germany, Helmholtz Centre for Environmental Research – UFZ, Department of Computational Landscape Ecology, 04318(More)
The current rate of warming due to increases in greenhouse gas (GHG) emissions is very likely unprecedented over the last 10,000 y. Although the majority of countries have adopted the view that global warming must be limited to <2 °C, current GHG emission rates and nonagreement at Copenhagen in December 2009 increase the likelihood of this limit being(More)
Data characteristics and species traits are expected to influence the accuracy with which species’ distributions can be modeled and predicted. We compare 10 modeling techniques in terms of predictive power and sensitivity to location error, change in map resolution, and sample size, and assess whether some species traits can explain variation in model(More)
The usefulness of species distribution models (SDMs) in predicting impacts of climate change on biodiversity is difficult to assess because changes in species ranges may take decades or centuries to occur. One alternative way to evaluate the predictive ability of SDMs across time is to compare their predictions with data on past species distributions. We(More)
1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial(More)