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- Dornelas, M., et al.
(författare)
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BioTIME: A database of biodiversity time series for the Anthropocene
- 2018
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Ingår i: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 27:7, s. 760-786
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
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- Cumming, Graeme S., et al.
(författare)
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Research priorities for the sustainability of coral-rich western Pacific seascapes
- 2023
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Ingår i: Regional Environmental Change. - 1436-3798 .- 1436-378X. ; 23:2
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Tidskriftsartikel (refereegranskat)abstract
- Nearly a billion people depend on tropical seascapes. The need to ensure sustainable use of these vital areas is recognised, as one of 17 policy commitments made by world leaders, in Sustainable Development Goal (SDG) 14 (‘Life below Water’) of the United Nations. SDG 14 seeks to secure marine sustainability by 2030. In a time of increasing social-ecological unpredictability and risk, scientists and policymakers working towards SDG 14 in the Asia–Pacific region need to know: (1) How are seascapes changing? (2) What can global society do about these changes? and (3) How can science and society together achieve sustainable seascape futures? Through a horizon scan, we identified nine emerging research priorities that clarify potential research contributions to marine sustainability in locations with high coral reef abundance. They include research on seascape geological and biological evolution and adaptation; elucidating drivers and mechanisms of change; understanding how seascape functions and services are produced, and how people depend on them; costs, benefits, and trade-offs to people in changing seascapes; improving seascape technologies and practices; learning to govern and manage seascapes for all; sustainable use, justice, and human well-being; bridging communities and epistemologies for innovative, equitable, and scale-crossing solutions; and informing resilient seascape futures through modelling and synthesis. Researchers can contribute to the sustainability of tropical seascapes by co-developing transdisciplinary understandings of people and ecosystems, emphasising the importance of equity and justice, and improving knowledge of key cross-scale and cross-level processes, feedbacks, and thresholds.
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- D H, Fleisher, et al.
(författare)
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Yield Response of an Ensemble of Potato Crop Models to Elevated CO2 in Continental Europe
- 2021
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Ingår i: European Journal of Agronomy. - : Elsevier BV. - 1161-0301. ; 126
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Tidskriftsartikel (refereegranskat)abstract
- A multi-model inter-comparison study was conducted to evaluate the performance of ten potato crop models to accurately predict potato yield in response to elevated CO2 (Ce) when calibrated with ambient CO2 data (Ca). Experimental data from seven open-top chambers (OTC) and free-air CO2-enrichment (FACE) facilities across continental Europe were used. Model ensemble percent errors averaged over all datasets for simulated yields were 26.5 % for Ca and 27.2 % Ce data. Metrics such as Wilmott’s index of agreement (IA) and root mean square relative error (RMSRE) ranged broadly among individual models and locations, such that four of the ten models outperformed the median or mean of the ensemble for about half of the Ce datasets. These top performing models were representative of three different model structural groups, including radiation use efficiency, transpiration efficiency, or leaf-level based approaches. Relative response to an increase in CO2 was more accurately modeled than absolute yield responses when averaged across all locations, and within 3.3 kg ppm 1 (or 5%) of observed values. Specific targets in the model structure needed for improvement were not identified due to large and inconsistent variation in the accuracy of yield predictions across locations. However, models with the lowest calibration errors tended to be top performers for Ce predictions as well. Such results suggest calibration is at least as important as model structure. Where possible, modelers using potato models to estimate Ce responses should use Ce calibration data to improve confidence in such predictions.
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