19 research outputs found

    TRY plant trait database – enhanced coverage and open access

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    Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Towards a thesaurus of plant characteristics: an ecological contribution

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    International audienceEcological research produces a tremendous amount of data, but the diversity in scales and topics covered and the ways in which studies are carried out result in large numbers of small, idiosyncratic data sets using heterogeneous terminologies. Such heterogeneity can be attributed, in part, to a lack of standards for acquiring, organizing and describing data. Here, we propose a terminological resource, a Thesaurus Of Plant characteristics (TOP), whose aim is to harmonize and formalize concepts for plant characteristics widely used in ecology. TOP concentrates on two types of plant characteristics: traits and environmental associations. It builds on previous initiatives for several aspects: (i) characteristics are designed following the entity-quality (EQ) model (a characteristic is modelled as the ‘Quality’ of an ‘Entity’ ) used in the context of Open Biological Ontologies; (ii) whenever possible, the Entities and Qualities are taken from existing terminology standards, mainly the Plant Ontology (PO) and Phenotypic Quality Ontology (PATO) ontologies; and (iii) whenever a characteristic already has a definition, if appropriate, it is reused and referenced. The development of TOP, which complies with semantic web principles, was carried out through the involvement of experts from both the ecology and the semantics research communities. Regular updates of TOP are planned, based on community feedback and involvement. TOP provides names, definitions, units, synonyms and related terms for about 850 plant characteristics. TOP is available online (www.top-thesaurus.org), and can be browsed using an alphabetical list of characteristics, a hierarchical tree of characteristics, a faceted and a free-text search, and through an Application Programming Interface. Synthesis. Harmonizing definitions of concepts, as proposed by TOP, forms the basis for better integration of data across heterogeneous data sets and terminologies, thereby increasing the potential for data reuse. It also allows enhanced scientific synthesis. TOP therefore has the potential to improve research and communication not only within the field of ecology, but also in related fields with interest in plant functioning and distribution

    Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation

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    Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles

    Global relationships in tree functional traits

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    Due to massive energetic investments in woody support structures, trees are subject to unique physiological, mechanical, and ecological pressures not experienced by herbaceous plants. Despite a wealth of studies exploring trait relationships across the entire plant kingdom, the dominant traits underpinning these unique aspects of tree form and function remain unclear. Here, by considering 18 functional traits, encompassing leaf, seed, bark, wood, crown, and root characteristics, we quantify the multidimensional relationships in tree trait expression. We find that nearly half of trait variation is captured by two axes: one reflecting leaf economics, the other reflecting tree size and competition for light. Yet these orthogonal axes reveal strong environmental convergence, exhibiting correlated responses to temperature, moisture, and elevation. By subsequently exploring multidimensional trait relationships, we show that the full dimensionality of trait space is captured by eight distinct clusters, each reflecting a unique aspect of tree form and function. Collectively, this work identifies a core set of traits needed to quantify global patterns in functional biodiversity, and it contributes to our fundamental understanding of the functioning of forests worldwide.Understanding patterns in woody plant trait relationships and trade-offs is challenging. Here, by applying machine learning and data imputation methods to a global database of georeferenced trait measurements, the authors unravel key relationships in tree functional traits at the global scale

    Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation

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    Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles. The authors investigate the broad-scale climatological and soil properties that co-vary with major axes of plant functional traits. They find that variation in plant size is attributed to latitudinal gradients in water or energy limitation, while variation in leaf economics traits is attributed to both climate and soil fertility including their interaction

    A global method for calculating plant CSR ecological strategies applied across biomes world-wide

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    Agraïments: The study has been supported by the TRY initiative on plant traits (www.try-db.org). The TRY initiative and database is hosted, developed and maintained by J. Kattge and G. Bönisch (Max-Planck-Institute for Biogeochemistry, Jena, Germany). TRY is/has been supported by DIVERSITAS, IGBP, the Global Land Project, the UK Natural Environment Research Council (NERC) through its program QUEST (Quantifying and Understanding the Earth System), the French Foundation for Biodiversity Research (FRB), and GIS "Climat, Environnement et Société" France. We thank Daniel Laughlin, Frédérique Louault, Belinda Medlyn, Julie Messier, Juli Pausas and Ian Wright for contributing data. The authors declare no conflict of interest.1. Competitor, stress-tolerator, ruderal (CSR) theory is a prominent plant functional strategy scheme previously applied to local floras. Globally, the wide geographic and phylogenetic coverage of available values of leaf area (LA), leaf dry matter content (LDMC) and specific leaf area (SLA) (representing, respectively, interspecific variation in plant size and conservative vs. acquisitive resource economics) promises the general application of CSR strategies across biomes, including the tropical forests hosting a large proportion of Earth's diversity. - 2. We used trait variation for 3068 tracheophytes (representing 198 families, six continents and 14 biomes) to create a globally calibrated CSR strategy calculator tool and investigate strategy-environment relationships across biomes world-wide. - 3. Due to disparity in trait availability globally, co-inertia analysis was used to check correspondence between a 'wide geographic coverage, few traits' data set and a 'restricted coverage, many traits' subset of 371 species for which 14 whole-plant, flowering, seed and leaf traits (including leaf nitrogen content) were available. CSR strategy/environment relationships within biomes were investigated using fourth-corner and RLQ analyses to determine strategy/climate specializations. - 4. Strong, significant concordance (RV = 0·597; P < 0·0001) was evident between the 14 trait multivariate space and when only LA, LDMC and SLA were used. - 5. Biomes such as tropical moist broadleaf forests exhibited strategy convergence (i.e. clustered around a CS/CSR median; C:S:R = 43:42:15%), with CS-selection associated with warm, stable situations (lesser temperature seasonality), with greater annual precipitation and potential evapotranspiration. Other biomes were characterized by strategy divergence: for example, deserts varied between xeromorphic perennials such as Larrea divaricata, classified as S-selected (C:S:R = 1:99:0%) and broadly R-selected annual herbs (e.g. Claytonia perfoliata; R/CR-selected; C:S:R = 21:0:79%). Strategy convergence was evident for several growth habits (e.g. trees) but not others (forbs). - 6. The CSR strategies of vascular plants can now be compared quantitatively within and between biomes at the global scale. Through known linkages between underlying leaf traits and growth rates, herbivory and decomposition rates, this method and the strategy-environment relationships it elucidates will help to predict which kinds of species may assemble in response to changes in biogeochemical cycles, climate and land use
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