Abstract

Summary 1. Functional traits are increasingly used to investigate community structure, ecosystem functioning or to classify species into functional groups. These functional traits are expected to be variable between and within species. Intraspecific functional variability is supposed to influence and modulate species responses to environmental changes and their effects on their environment. However, this hypothesis remains poorly tested and species are mostly described by mean trait values without any consideration of variability in individual trait values. 2. In this study, we quantify the extent of intraspecific plant functional trait variability, its spatial structure and its response to environmental factors. Using a sampling design structured along two direct and orthogonal climatic gradients in an alpine valley, we quantified and analysed the intraspecific variability for three functional traits (height, leaf dry matter content and leaf nitrogen content) measured on sixteen plant species with contrasting life histories. 3. Results showed a large variability of traits within species with large discrepancies between functional traits and species. This variability did not appear to be structured within populations. Between populations, the overall variability was partly explained by the selected gradients. Despite the strong effects of temperature and radiation on trait intraspecific variability, the response curves of traits along gradients were partly idiosyncratic. 4. Synthesis. Giving a comprehensive quantification of intraspecific functional variability through the analysis of an original data set, we report new evidence that using a single trait value to describe a given species can hide large functional variation for this species along environmental gradients. These findings suggest that intraspecific functional variability should be a concern for ecologists and its recognition opens new opportunities to better understand and predict ecological patterns in a changing environment. Further analyses are, however, required to compare inter‐ and intraspecific variability.

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