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Bio
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 rigour. 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 modelling, plant-pollinator interactions, experimental climate change, statistical teaching, scientific credibility, patterns of biodiversity
Research Interests
Papers共 261 篇Author StatisticsCo-AuthorSimilar Experts
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crossref(2024)
Christiane Werner,Ulrike Wallrabe,Andreas Christen, Laura Comella,Carsten Dormann, Anna Göritz,Rüdiger Grote,Simon Haberstroh,Mazin Jouda,Ralf Kiese,Barbara Koch,Jan Korvink,
Research Ideas and Outcomes (2024): 1-54
Trends in ecology & evolutionno. 5 (2024): 494-505
METHODS IN ECOLOGY AND EVOLUTIONno. 2 (2024): 439-451
OIKOS (2024)
BMC Ecology and Evolutionno. 1 (2024): 1-13
Applied Network Scienceno. 1 (2024): 1-12
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