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Sökning: WFRF:(Suarez Ana) > Stockholms universitet

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1.
  • Kattge, Jens, et al. (författare)
  • TRY plant trait database - enhanced coverage and open access
  • 2020
  • Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
  • 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.
  • 2019
  • Tidskriftsartikel (refereegranskat)
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3.
  • Jin, Hongxiao, et al. (författare)
  • Drone-Based Hyperspectral and Thermal Imagery for Quantifying Upland Rice Productivity and Water Use Efficiency after Biochar Application
  • 2021
  • Ingår i: Remote Sensing. - : MDPI AG. - 2072-4292. ; 13:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Miniature hyperspectral and thermal cameras onboard lightweight unmanned aerial vehicles (UAV) bring new opportunities for monitoring land surface variables at unprecedented fine spatial resolution with acceptable accuracy. This research applies hyperspectral and thermal imagery from a drone to quantify upland rice productivity and water use efficiency (WUE) after biochar application in Costa Rica. The field flights were conducted over two experimental groups with bamboo biochar (BC1) and sugarcane biochar (BC2) amendments and one control (C) group without biochar application. Rice canopy biophysical variables were estimated by inverting a canopy radiative transfer model on hyperspectral reflectance. Variations in gross primary productivity (GPP) and WUE across treatments were estimated using light-use efficiency and WUE models respectively from the normalized difference vegetation index (NDVI), canopy chlorophyll content (CCC), and evapotranspiration rate. We found that GPP was increased by 41.9 +/- 3.4% in BC1 and 17.5 +/- 3.4% in BC2 versus C, which may be explained by higher soil moisture after biochar application, and consequently significantly higher WUEs by 40.8 +/- 3.5% in BC1 and 13.4 +/- 3.5% in BC2 compared to C. This study demonstrated the use of hyperspectral and thermal imagery from a drone to quantify biochar effects on dry cropland by integrating ground measurements and physical models.
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