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- 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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| 2. |
- Lau, Danny C. P., et al.
(author)
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Multitrophic biodiversity patterns and environmental descriptors of sub‐Arctic lakes in northern Europe
- 2022
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In: Freshwater Biology. - : John Wiley & Sons. - 0046-5070 .- 1365-2427. ; 67:1, s. 30-48
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Journal article (peer-reviewed)abstract
- 1. Arctic and sub‐Arctic lakes in northern Europe are increasingly threatened by climate change, which can affect their biodiversity directly by shifting thermal and hydrological regimes, and indirectly by altering landscape processes and catchment vegetation. Most previous studies of northern lake biodiversity responses to environmental changes have focused on only a single organismal group. Investigations at whole‐lake scales that integrate different habitats and trophic levels are currently rare, but highly necessary for future lake monitoring and management.2. We analysed spatial biodiversity patterns of 74 sub‐Arctic lakes in Norway, Sweden, Finland, and the Faroe Islands with monitoring data for at least three biological focal ecosystem components (FECs)—benthic diatoms, macrophytes, phytoplankton, littoral benthic macroinvertebrates, zooplankton, and fish—that covered both pelagic and benthic habitats and multiple trophic levels.3. We calculated the richnessrelative (i.e. taxon richness of a FEC in the lake divided by the total richness of that FEC in all 74 lakes) and the biodiversity metrics (i.e. taxon richness, inverse Simpson index (diversity), and taxon evenness) of individual FECs using presence–absence and abundance data, respectively. We then investigated whether the FEC richnessrelative and biodiversity metrics were correlated with lake abiotic and geospatial variables. We hypothesised that (1) individual FECs would be more diverse in a warmer and wetter climate (e.g. at lower latitudes and/or elevations), and in hydrobasins with greater forest cover that could enhance the supply of terrestrial organic matter and nutrients that stimulated lake productivity; and (2) patterns in FEC responses would be coupled among trophic levels.4. Results from redundancy analyses showed that the richnessrelative of phytoplankton, macrophytes, and fish decreased, but those of the intermediate trophic levels (i.e. macroinvertebrates and zooplankton) increased with decreasing latitude and/or elevation. Fish richnessrelative and diversity increased with increasing temporal variation in climate (temperature and/or precipitation), ambient nutrient concentrations (e.g. total nitrogen) in lakes, and woody vegetation (e.g. taiga forest) cover in hydrobasins, whereas taxon richness of macroinvertebrates and zooplankton decreased with increasing temporal variation in climate.5. The similar patterns detected for richnessrelative of fish, macrophytes, and phytoplankton could be caused by similar responses to the environmental descriptors, and/or the beneficial effects of macrophytes as habitat structure. By creating habitat, macrophytes may increase fish diversity and production, which in turn may promote higher densities and probably more diverse assemblages of phytoplankton through trophic cascades. Lakes with greater fish richnessrelative tended to have greater average richnessrelative among FECs, suggesting that fish are a potential indicator for overall lake biodiversity.6. Overall, the biodiversity patterns observed along the environmental gradients were trophic‐level specific, indicating that an integrated food‐web perspective may lead to a more holistic understanding of ecosystem biodiversity in future monitoring and management of high‐latitude lakes. In future, monitoring should also focus on collecting more abundance data for fish and lower trophic levels in both benthic and pelagic habitats. This may require more concentrated sampling effort on fewer lakes at smaller spatial scales, while continuing to sample lakes distributed along environmental gradients.
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