Prof. Dr. Carsten F. Dormann

Telefon: +49 761 203-3749
Telefax: +49 761 203-3751
eMail: carsten.dormann@biom.uni-freiburg.de 




Frau Eva Meier

Telefon: +49 761 203-3749 
Telefax: +49 761 203-3751 
eMail: eva.meier@biom.uni-freiburg.de 




Biometrie und Umweltsystemanalyse

Albert-Ludwigs-Universität Freiburg

Tennenbacher Straße 4 
79106 Freiburg i. Br.


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Prof. Dr. Carsten Dormann

Image Dorman 

Carsten Dormann, Prof. Dr.

Department of Biometry and Environmental System Analysis

Tennenbacher Straße 4, 79106 Freiburg, Germany
Room 03.059

phone: ++ 49 761 203-3750
fax: ++ 49 761 203-3751  
email: carsten [DOT] dormann [AT] biom [DOT] uni-freiburg [DOT] de (to reduce spam)


(Full) Professor at the University of Freiburg (since 2011)

Habilitation (a somewhat anachronistic rung of the German academic career ladder) at the Agricultural Faculty of the University of Göttingen (2008)

PostDoc and Senior Research Scientist at the Helmholtz Center for Environmental Research-UFZ, Department Computational Landscape Ecology (2002-2011)

PhD in Plant Ecology, University of Aberdeen , under the guidance of Dr. Sarah Woodin and Prof. Dr. Steve Albon (2001)

Diploma (equivalent to an MSc) in Biology, University of Kiel (1996)



Full list of scientific publicationsParStatcover.jpg

For the lecture "Statistics" for BSc Environmental Sciences, Forestry and Environment, Geography the textbook (2nd edition 2017):          Daten zum Buch     |    Errata zur 2. Auflage

Apppendix with "a less mathematical introduction to Bayesian statistics".

eda cover


The English version of this book has a different title: Environmental Data Analysis: An Introduction with Examples in R | Data accompanying the book | Errata



marine ecology notes


A Wikipedia-based book for the course Marine Ecology: Marine Ecology Notes , edited by Dormann, CF & Schröder, A.



Defining Agroecology : A Festschrift for TejaTscharntke.         defining agroecology


An earlier piece of work for those switching to R:

Dormann, CF , I. Kühn. 2008. Statistical analysis of biological data (with the free program package R). 2nd edition.          download (2.7 MB)    |    Data for Dormann & Kühn 


Research Interests

    Comparing, challenging and improving the toolbox of statistical ecology.

    Ecological data sets are often very small (less than 100 data points), but the complexity of the system allows for dozens to hundreds of potential predictors and explanations of the data's origin. Some statistical approaches commonly employed fail to meet assumptions or are poorly tested - with unknown effect on our ecological knowledge. Formally testing such approaches (with simulated data) and reviewing challenging topics in ecological analyzes is important to my research (spatial autocorrelation, null models, collinearity, etc).

    Formal statistical integration of (ecological) models and data.

    Ecologists are often happy to get their research qualitatively right. For more faith in our understanding of the living world, I think we should strive for more rigour: a more formal representation of our ecological understanding (or what we think we know) in models, quantitative predictions to new conditions, and statistically explicit comparison with new data. Being more interested in the how-to than the specific system, such models may be forest growth models, community processes or population dynamics.

    Evidence focus of environmental science.

    The complexity of the environmental systems and the multitude of approaches used to study them has allowed for some slip in scientific rigor. In analogy to evidence-based medicine, a transparent quest for causal mechanisms and evaluation of published studies for their actual level of evidence are, in my humble opinion, unnegotiable.

    Lots of other things:

    species distribution modeling, plant-pollinator interactions, experimental climate change, statistical teaching, scientific credibility, patterns of biodiversity

    Blog posts (highly infrequent)

     Time to leave “species richness” behind, as it serves no scientific purpose on x- or y-axis (October 2023)

     The end of the bias-variance trade-off? (July 2023)

     The tail of application wagging the dog of knowledge: Is ecological science fit for policy? (October 2022)

    “Scientists in a war for a future of humanity” – I strongly disagree! (October 2022)

   On the tree species richness - productivity relationship (January 2019)

   On model averaging (May 2018)

   On joint species distribution modeling (resulting from a conference workshop; April 2018)

   On transitivity in plant competition (July 2016)

   On null models in ecology (June 2016)


Current PhD researchers (main/co-supervisor)


Past PhDs researchers


Benutzerspezifische Werkzeuge