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Journal articles
How many dimensions are needed to accurately assess functional diversity? A pragmatic approach for assessing the quality of functional spaces
Abstract : Aim Functional diversity is a key facet of biodiversity that is increasingly being measured to quantify its changes following disturbance and to understand its effects on ecosystem functioning. Assessing the functional diversity of assemblages based on species traits requires the building of a functional space (dendrogram or multidimensional space) where indices will be computed. However, there is still no consensus on the best method for measuring the quality of functional spaces. Innovation Here we propose a framework for evaluating the quality of a functional space (i.e. the extent to which it is a faithful representation of the initial functional trait values). Using simulated datasets, we analysed the influence of the number and type of functional traits used and of the number of species studied on the identity and quality of the best functional space. We also tested whether the quality of the functional space affects functional diversity patterns in local assemblages, using simulated datasets and a real study case. Main conclusions The quality of functional space strongly varied between situations. Spaces having at least four dimensions had the highest quality, while functional dendrograms and two-dimensional functional spaces always had a low quality. Importantly, we showed that using a poor-quality functional space could led to a biased assessment of functional diversity and false ecological conclusions. Therefore, we advise a pragmatic approach consisting of computing all the possible functional spaces and selecting the most parsimonious one.
https://hal.umontpellier.fr/hal-01919339
Contributor : Anthony Herrada <>
Submitted on : Monday, November 12, 2018 - 12:58:18 PM
Last modification on : Tuesday, December 29, 2020 - 2:08:04 PM
Contributor : Anthony Herrada <>
Submitted on : Monday, November 12, 2018 - 12:58:18 PM
Last modification on : Tuesday, December 29, 2020 - 2:08:04 PM
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