TRY - a global database of plant traits

doi:10.1111/J.1365-2486.2011.02451.X

Abstract:

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.

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TL;DR: The findings suggest that the ecosystem disservices of tick-borne diseases, via the abundance of ticks, strongly depends on habitat properties and thus on how humans manage ecosystems from the scale of the microhabitat to the landscape.

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TL;DR: Variation in the modularity of trait networks suggests that trait connectivity is shaped by prevailing environmental conditions and demonstrates that plants of different growth forms use alternative strategies to cope with local conditions.

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TL;DR: The results highlighted that an acquisitive resource use strategy and relatively higher functional diversity of leaf traits prevail in the alpine S. acaulis community, optimizing a rapid carbon gain, which would help overcome the constraints exerted by the short growing season.

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TL;DR: It is described how Trait bank ingests and manages data in a way that leverages EOL's existing infrastructure and semantic annotations to facilitate reasoning across the TraitBank corpus and interoperability with other resources.

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Abstract: Traits are powerful predictors of ecosystem functions pointing to underlying physiological and ecological processes. Plant individual performance results from the coordinated operation of many processes, ranging from nutrient uptake over organ turnover to photosynthesis, thus requiring a large set of traits for its prediction. For plant performance on higher hierarchical levels, e.g. populations, additional traits important for plant-plant and trophic interactions may be required which should even enlarge the spectrum of relevant predictor traits.(2)The goal of this study was to assess the importance of plant functional traits to predict individual and population performance of grassland species with particular focus on the significance of root traits. We tested this for 59 grassland species using 35 traits divided into three trait clusters: leaf traits (16), stature traits (8) and root traits (11), using individual biomass of mesocosm plants as a measure of individual performance and population biomass of monocultures as a measure of population performance. We applied structural equation models to disentangle direct effects of single traits on population biomass and indirect effects via individual plant biomass or shoot density.We tested multivariate trait effects on individual and population biomass to analyze whether the importance of different trait clusters shifts with increasing hierarchical integration from individuals to populations.(3)Traits of all three clusters significantly correlated with individual and population biomass. However, in spite of a number of significant correlations, above-below-ground linkages were generally week, with few exceptions like N content.(4)Stature traits exclusively affected population biomass indirectly via their effect on individual biomass, whereas root and leaf traits showed also direct effects and partly indirect effects via density.(5)The inclusion of root traits in multiple regression models improved the prediction of individual biomass compared to models with only above-ground information only slightly (95% vs. 93% of variance prediction with and without root traits, respectively) but was crucial for the prediction of population biomass (77% and 49%, respectively). Root traits were more important for plant performance than leaf traits and were even the most important predictors at the population level(6)Synthesis: Upscaling from the individual to the population level reflects an increasing number of processes requiring traits from different trait clusters for their prediction. Our results emphasize the importance of root traits for trait-based studies especially at higher organizational levels. Our approach provides a comprehensive framework acknowledging the hierarchical nature of trait influences. This is one step towards a more process-oriented assessment of trait-based approaches

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TL;DR: Various aspects of the biochemistry of photosynthetic carbon assimilation in C3 plants are integrated into a form compatible with studies of gas exchange in leaves.

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TL;DR: Reliable quantification of the leaf economics spectrum and its interaction with climate will prove valuable for modelling nutrient fluxes and vegetation boundaries under changing land-use and climate.

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TL;DR: A triangular model based upon the three strategies of evolution in plants may be reconciled with the theory of r- and K-selection, provides an insight into the processes of vegetation succession and dominance, and appears to be capable of extension to fungi and to animals.

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TL;DR: It is asserted that community ecology should return to an emphasis on four themes that are tied together by a two-step process: how the fundamental niche is governed by functional traits within the context of abiotic environmental gradients; and how the interaction between traits and fundamental niches maps onto the realized niche in the context a biotic interaction milieu.

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TL;DR: In this paper, the Lagrange multiplier procedure is used to derive efficient joint tests for residual normality, homoscedasticity and serial independence, which are simple to compute and asymptotically distributed as χ2.

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TRY - a global database of plant traits

Citations

Environmental drivers of Ixodes ricinus abundance in forest fragments of rural European landscapes.

Robustness of trait connections across environmental gradients and growth forms

Functional composition and diversity of leaf traits in subalpine versus alpine vegetation in the Apennines

TraitBank: Practical semantics for organism attribute data

From pots to plots: Hierarchical trait-based prediction of plant

References

A Biochemical Model of Photosynthetic CO 2 Assimilation in Leaves of C 3 Species

The worldwide leaf economics spectrum

Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory

Rebuilding community ecology from functional traits.

Efficient tests for normality, homoscedasticity and serial independence of regression residuals

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