Summary1. 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.
Summary1. The prevalence of phylogenetic niche conservatism (PNC) in nature is still a conflicting issue. Disagreement arises from confusion over its precise definition and the variety of approaches to measure its prevalence. Recent work highlighted that common measures of PNC strongly depend on the assumptions of the underlying model of niche evolution. However, this warning has not been well recognized in the applied literature and questionable approaches are still frequently applied. 2. The aim of this study is to draw attention to the assumptions underlying commonly applied simple measures of PNC. We used a series of simulations to illustrate how misleading results can be if assumptions of niche evolution are violated, that the violation of assumptions is a common phenomenon and that testing assumptions requires in-depth pretest. 3. We conclude that the seemingly simple measures of PNC, such as phylogenetic signal (PS) and evolutionary rate, are not so easy to apply if one accounts for the necessity to test model assumptions. In addition, these measures can be difficult to interpret. The common assumption that strong PS indicates PNC will be often invalid. In addition, the interpretation of some measures, for example the conclusion that evolutionary rate is slow enough to indicate PNC, requires a comparison with another clade, another trait or well-developed null model assumptions and thus additional data. 4. We suggest that studies investigating PNC should always compare alternative evolutionary models and that model comparisons should in particular include flexible niche evolution models such as multiple-optima OU models, although these are computational intensive. These models are directly inherited from the concept of macroevolutionary adaptive landscape and can indicate PNC either by relative few peak shifts or by narrow peaks in the adaptive landscape. A test of PNC thus requires comparing these parameters of the macroevolutionary landscape between clades or time periods. 5. The general prevalence of PNC in nature should be evaluated only based on studies keeping up to the high standards of communicating the used definition of PNC, testing the assumptions made in the modelling approaches and including newly developed models in a model comparison approach.
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