| 1. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)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. |
- Blonder, Benjamin, et al.
(författare)
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Low predictability of energy balance traits and leaf temperature metrics in desert, montane and alpine plant communities
- 2020
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Ingår i: Functional Ecology. - : Wiley. - 0269-8463 .- 1365-2435. ; 34, s. 1882-1897
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Tidskriftsartikel (refereegranskat)abstract
- 1. Leaf energy balance may influence plant performance and community composition. While biophysical theory can link leaf energy balance to many traits and environment variables, predicting leaf temperature and key driver traits with incomplete parameterizations remains challenging. Predicting thermal offsets (δ, Tleaf − Tair difference) or thermal coupling strengths (β, Tleaf vs. Tair slope) is challenging.2. We ask: (a) whether environmental gradients predict variation in energy balance traits (absorptance, leaf angle, stomatal distribution, maximum stomatal conductance, leaf area, leaf height); (b) whether commonly measured leaf functional traits (dry matter content, mass per area, nitrogen fraction, δ13C, height above ground) predict energy balance traits; and (c) how traits and environmental variables predict δ and β among species.3. We address these questions with diurnal measurements of 41 species co‐occurring along a 1,100 m elevation gradient spanning desert to alpine biomes. We show that (a) energy balance traits are only weakly associated with environmental gradients and (b) are not well predicted by common functional traits. We also show that (c) δ and β can be partially approximated using interactions among site environment and traits, with a much larger role for environment than traits. The heterogeneity in leaf temperature metrics and energy balance traits challenges larger‐scale predictive models of plant performance under environmental change
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| 3. |
- Geange, Sonya R., et al.
(författare)
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Next-generation field courses : Integrating Open Science and online learning
- 2021
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Ingår i: Ecology and Evolution. - : Wiley. - 2045-7758. ; 11:8, s. 3577-3587
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Tidskriftsartikel (refereegranskat)abstract
- As Open Science practices become more commonplace, there is a need for the next generation of scientists to be well versed in these aspects of scientific research. Yet, many training opportunities for early career researchers (ECRs) could better emphasize or integrate Open Science elements. Field courses provide opportunities for ECRs to apply theoretical knowledge, practice new methodological approaches, and gain an appreciation for the challenges of real-life research, and could provide an excellent platform for integrating training in Open Science practices. Our recent experience, as primarily ECRs engaged in a field course interrupted by COVID-19, led us to reflect on the potential to enhance learning outcomes in field courses by integrating Open Science practices and online learning components. Specifically, we highlight the opportunity for field courses to align teaching activities with the recent developments and trends in how we conduct research, including training in: publishing registered reports, collecting data using standardized methods, adopting high-quality data documentation, managing data through reproducible workflows, and sharing and publishing data through appropriate channels. We also discuss how field courses can use online tools to optimize time in the field, develop open access resources, and cultivate collaborations. By integrating these elements, we suggest that the next generation of field courses will offer excellent arenas for participants to adopt Open Science practices.
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| 4. |
- Halbritter, Aud H., et al.
(författare)
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Plant trait and vegetation data along a 1314 m elevation gradient with fire history in Puna grasslands, Perú
- 2024
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Ingår i: SCIENTIFIC DATA. - 2052-4463. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Alpine grassland vegetation supports globally important biodiversity and ecosystems that are increasingly threatened by climate warming and other environmental changes. Trait-based approaches can support understanding of vegetation responses to global change drivers and consequences for ecosystem functioning. In six sites along a 1314 m elevational gradient in Puna grasslands in the Peruvian Andes, we collected datasets on vascular plant composition, plant functional traits, biomass, ecosystem fluxes, and climate data over three years. The data were collected in the wet and dry season and from plots with different fire histories. We selected traits associated with plant resource use, growth, and life history strategies (leaf area, leaf dry/wet mass, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N, P content, C and N isotopes). The trait dataset contains 3,665 plant records from 145 taxa, 54,036 trait measurements (increasing the trait data coverage of the regional flora by 420%) covering 14 traits and 121 plant taxa (ca. 40% of which have no previous publicly available trait data) across 33 families.
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| 5. |
- Vandvik, Vigdis, et al.
(författare)
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Plant traits and associated data from a warming experiment, a seabird colony, and along elevation in Svalbard
- 2023
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Ingår i: Scientific Data. - 2052-4463. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- The Arctic is warming at a rate four times the global average, while also being exposed to other global environmental changes, resulting in widespread vegetation and ecosystem change. Integrating functional trait-based approaches with multi-level vegetation, ecosystem, and landscape data enables a holistic understanding of the drivers and consequences of these changes. In two High Arctic study systems near Longyearbyen, Svalbard, a 20-year ITEX warming experiment and elevational gradients with and without nutrient input from nesting seabirds, we collected data on vegetation composition and structure, plant functional traits, ecosystem fluxes, multispectral remote sensing, and microclimate. The dataset contains 1,962 plant records and 16,160 trait measurements from 34 vascular plant taxa, for 9 of which these are the first published trait data. By integrating these comprehensive data, we bridge knowledge gaps and expand trait data coverage, including on intraspecific trait variation. These data can offer insights into ecosystem functioning and provide baselines to assess climate and environmental change impacts. Such knowledge is crucial for effective conservation and management in these vulnerable regions.
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