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- Biurrun, Idoia, et al.
(author)
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Benchmarking plant diversity of Palaearctic grasslands and other open habitats
- 2021
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In: Journal of Vegetation Science. - Oxford : John Wiley & Sons. - 1100-9233 .- 1654-1103. ; 32:4
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Journal article (peer-reviewed)abstract
- Journal of Vegetation Science published by John Wiley & Sons Ltd on behalf of International Association for Vegetation Science.Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology. © 2021 The Authors.
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- Dengler, Jürgen, et al.
(author)
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Ecological Indicator Values for Europe (EIVE) 1.0
- 2023
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In: Vegetation Classification and Survey. - 2683-0671. ; 4, s. 7-29
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Journal article (peer-reviewed)abstract
- Aims: To develop a consistent ecological indicator value system for Europe for five of the main plant niche dimensions: soil moisture (M), soil nitrogen (N), soil reaction (R), light (L) and temperature (T). Study area: Europe (and closely adjacent regions). Methods: We identified 31 indicator value systems for vascular plants in Europe that contained assessments on at least one of the five aforementioned niche dimensions. We rescaled the indicator values of each dimension to a continuous scale, in which 0 represents the minimum and 10 the maximum value present in Europe. Taxon names were harmonised to the Euro+Med Plantbase. For each of the five dimensions, we calculated European values for niche position and niche width by combining the values from the individual EIV systems. Using T values as an example, we externally validated our European indicator values against the median of bioclimatic conditions for global occurrence data of the taxa. Results: In total, we derived European indicator values of niche position and niche width for 14,835 taxa (14,714 for M, 13,748 for N, 14,254 for R, 14,054 for L, 14,496 for T). Relating the obtained values for temperature niche position to the bioclimatic data of species yielded a higher correlation than any of the original EIV systems (r = 0.859). The database: The newly developed Ecological Indicator Values for Europe (EIVE) 1.0, together with all source systems, is available in a flexible, harmonised open access database. Conclusions: EIVE is the most comprehensive ecological indicator value system for European vascular plants to date. The uniform interval scales for niche position and niche width provide new possibilities for ecological and macroecological analyses of vegetation patterns. The developed workflow and documentation will facilitate the future release of updated and expanded versions of EIVE, which may for example include the addition of further taxonomic groups, additional niche dimensions, external validation or regionalisation.
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3. |
- Kattge, Jens, et al.
(author)
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TRY plant trait database - enhanced coverage and open access
- 2020
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In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Journal article (peer-reviewed)abstract
- 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.
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