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Aim Species with deciduous and evergreen leaf habits typically differ in leaf life span (LLS). Yet quantification of the response of LLS, within each habit, to key environmental conditions is surprisingly lacking. The aim of this study is to quantify LLS strategies of the two leaf habits under varying temperature, moisture and nutrient conditions, using a global database. We hypothesize that deciduous LLS reflects the length of the growing season, avoiding unfavourable conditions regardless of the cause. Evergreen species adjust to unfavourable periods and amortize lower net carbon gains over several growing seasons, with increasing LLS associated with increasingly short favourable versus unfavourable season lengths. Location Global. Methods Data on LLS and environmental variables were compiled from global datasets for 189 deciduous and 506 evergreen species across 83 study locations. Individual and combined effects of measures of seasonality of temperature, water and nutrient availability on length of the growing season and on LLS were quantified using linear mixed models. The best models for predicting LLS were obtained using Akaike's information criterion (AIC) and ΔAIC. Results The LLS of deciduous and evergreen species showed opposite responses to changes in environmental conditions. Under unfavourable conditions, deciduous LLS decreases while evergreen LLS increases. A measure of temperature alone was the best predictor of the growing season. The LLS of deciduous species was independent of environmental conditions after expressing LLS in relation to the number of growing seasons. Evergreen species, on the other hand, adjusted to unfavourable conditions by increasing LLS up to four growing seasons. Contrary to expectations, variation in LLS was best explained solely by temperature, instead of by combined measures of temperature, moisture and nutrient availability. Shifts in the photosynthesis to respiration balance might provide a physiological explanation. Main conclusions Temperature, and not drought or nutrient availability, is the primary driver of contrasting responses of LLS for different leaf habit types. © 2011 Blackwell Publishing Ltd.

Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

Aim The drivers of species assembly, by limiting the possible range of functional trait values, can lead to either convergent or divergent distributions of traits in realized assemblages. Here, to evaluate the strengths of these species assembly drivers, we partition trait variance across global, regional and community scales. We then test the hypothesis that, from global to community scales, the outcome of co-occurring trait convergence and divergence is highly variable across biomes and communities. Location Global: nine biomes ranging from subarctic highland to tropical rain forest. Methods We analysed functional trait diversity at progressively finer spatial scales using a global, balanced, hierarchically structured dataset from 9 biomes, 58 communities and 652 species. Analyses were based on two key leaf traits (foliar nitrogen content and specific leaf area) that are known to drive biogeochemical cycling. Results While 35% of the global variance in these traits was between biomes, only 15% was between communities within biomes and as much as 50% occurred within communities. Despite this relatively high within-community variance in trait values, we found that trait convergence dominated over divergence at both global and regional scales through comparisons of functional trait diversity in regional and community assemblages against random (null) models of species assembly. Main conclusions We demonstrate that the convergence of traits occurring from global to regional assemblages can be twice as strong as that from regional to community assemblages, and argue that large differences in the nature and strength of abiotic and biotic drivers of dominant species assembly can, at least partly, explain the variable outcome of simultaneous trait convergence and divergence across sites. Ultimately, these findings stress the urgent need to extend species assembly research to address those scales where trait variance is the highest, i.e. between biomes and within communities. © 2011 Blackwell Publishing Ltd.