Functional Ecology

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The understanding of the functional basis of how organisms interact with each other and with their environment is a key research objective of our department. Trait approaches are used to characterize functional community structure, to quantify the effects of organisms on ecosystem functioning, and for the parameterization of models on species distribution and ecosystem carbon and water balance. A particularly strong research focus lies on the impact of global change factors such as increasing drought and land use change on biodiversity and ecosystem processes. Using field and laboratory experiments and modeling approaches, we study mainly terrestrial ecosystems with a focus on Mediterranean systems, but also including tropical ecosystems mainly in South America, and temperate and alpine ecosystems.


Head of the department: Stephan HÄTTENSCHWILER


Key words

Biogeochemical cycles | Climate change | Community structure | Functional diversity | Functional traits | Global change | Mechanistic modelling | Mediterranean ecosystems | Plant-soil interactions | Soil ecology | Terrestrial ecosystems | Water relations


New publication :

  • Journe V, Barnagaud J-Y, Bernard C, Crochet PA, Morin X (2020). Correlative climatic niche models predict real and virtual species distributions equally well. Ecology, e02912.10.1002/ecy.2912.


Climate is one of the main factors driving species distributions and global biodiversity patterns. Obtaining accurate predictions of species’ range shifts in response to ongoing climate change has thus become a key issue in ecology and conservation. Correlative species distribution models (cSDMs) have become a prominent tool to this aim in the last decade and have demonstrated good predictive abilities with current conditions, irrespective of the studied taxon. However, cSDMs rely on statistical association between species’ presence and environmental conditions and have rarely been challenged on their actual capacity to reflect causal relationships between species and climate. In this study, we question whether cSDMs can accurately identify if climate and species distributions are causally linked, a prerequisite for accurate prediction of range shift in relation to climate change. We compared the performance of cSDMs in predicting the distributions of 132 European terrestrial species, chosen randomly within five taxonomic groups (three vertebrate groups and two plant groups), and of 1,320 virtual species whose distribution is causally fully independent from climate. We found that (1) for real species, the performance of cSDMs varied principally with range size, rather than with taxonomic groups and (2) cSDMs did not predict the distributions of real species with a greater accuracy than the virtual ones. Our results unambiguously show that the high predictive power of cSDMs can be driven by spatial autocorrelation in climatic and distributional data and does not necessarily reflect causal relationships between climate and species distributions. Thus, high predictive performance of cSDMs does not ensure that they accurately depict the role of climate in shaping species distributions. Our findings therefore call for strong caution when using cSDMs to provide predictions on future range shifts in response to climate change.


Link to the full article


Press coverage of the article: short communication by INEE

« Prédire la répartition future des espèces avec des modèles corrélatifs est hasardeux »