39 research outputs found

    The functional trait spectrum of European temperate grasslands

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    Questions: What is the functional trait variation of European temperate grasslands and how does this reflect global patterns of plant form and function? Do habitat specialists show trait differentiation across habitat types?. Location: Europe. Methods: We compiled 18 regeneration and non-regeneration traits for a continental species pool consisting of 645 species frequent in five grassland types. These grassland types are widely distributed in Europe but differentiated by altitude, soil bedrock and traditional long-term management and disturbance regimes. We evaluated the multivariate trait space of this entire species pool and compared multi-trait variation and mean trait values of habitat specialists grouped by grassland type. Results: The first dimension of the trait space accounted for 23% of variation and reflected a gradient between fast-growing and slow-growing plants. Plant height and SLA contributed to both the first and second ordination axes. Regeneration traits mainly contributed to the second and following dimensions to explain 56% of variation across the first five axes. Habitat specialists showed functional differences between grassland types mainly through non-regeneration traits. Conclusions: The trait spectrum of plants dominating European temperate grasslands is primarily explained by growth strategies which are analogous to the trait variation observed at the global scale, and secondly by regeneration strategies. Functional differentiation of habitat specialists across grassland types is mainly related to environmental filtering linked with altitude and disturbance. This filtering pattern is mainly observed in non-regeneration traits, while most regeneration traits demonstrate multiple strategies within the same habitat type.EL, BJA, MTI, AM, PI and CB acknowledge the research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007–2013 under REA grant agreement no. 607785, as a part of the NAtive Seed Science TEchnology and Conservation (NASSTEC) Initial Training Network (ITN). BJA was further funded by the Marie Curie Clarín‐COFUND program of the Principality of Asturias and the European Union (ACB17‐26). BJA and HB acknowledge support from the German Centre for Integrative Biodiversity Research (iDiv) Halle–Jena–Leipzig funded by the German Research Foundation (DFTG FZT 118) through the sPlot research platform. PI acknowledges support from the Rural & Environment Science & Analytical Services Division of the Scottish Government. KÖ thanks RO1567‐IBB03/2018 for financial support

    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

    A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements

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    In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I–VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers’ views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning

    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

    Tundra Trait Team: A database of plant traits spanning the tundra biome

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    Abstract Motivation: The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained: The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub-Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release

    Next-gen plant clonal ecology

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    Plants with clonal growth can produce multiple potentially independent units, termed ramets. Clonal growth can have important ecological and evolutionary consequences, such as by increasing probability of reproduction, space monopolization, and regeneration after injury; and by permitting physiological integration of connected ramets. Although clonal growth is widespread among species and habitats, it has received relatively little attention in plant ecology. To introduce this special issue on clonal plant ecology, we first provide a brief background on the topic, noting its importance in areas ranging from evolution to the impacts of climate change on plant communities. We then focus on a set of pressing questions, to highlight both the obstacles and opportunities to more explicitly incorporate clonal growth in research on plant ecology and evolution
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