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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.
  • Martínez-Sanz, Marta, et al. (författare)
  • Composition and rheological properties of microalgae suspensions : Impact of ultrasound processing
  • 2020
  • Ingår i: Algal Research. - : Elsevier B.V.. - 2211-9264. ; 49
  • Tidskriftsartikel (refereegranskat)abstract
    • In this study the rheological properties of aqueous suspensions of three microalgae species, Nannochloropsis gaditana, Scenedesmus almeriensis and Spirulina platensis, were investigated as a function of solids content, and related to their composition and microstructure. In addition, the impact of ultrasound processing on their structuring ability was also studied. The less rigid character of the Spirulina platensis cell walls (with very low carbohydrate contents) and the presence of extracellular components promoted cell-cell interactions, yielding suspensions which showed a shear thinning behaviour at lower concentrations than Nannochloropsis gaditana and Scenedesmus almeriensis. It is noteworthy that the three species showed different viscoelastic properties at 25 wt.% total solids. Spirulina platensis suspensions showed a more elastic behaviour and lower frequency dependence, characteristic of weak gels, whilst Nannochloropsis gaditana and Scenedesmus almeriensis behaved more like viscous liquids. The ultrasound treatment did not affect the cell wall integrity, but it promoted the release of intracellular components (some of which could have been partially degraded) and disrupted physical interparticle interactions in Nannochloropsis gaditana and Scenedesmus almeriensis. This has an impact on the rheological properties, increasing the viscosity of Nannochloropsis gaditana suspensions, whilst the viscosity of Scenedesmus almeriensis suspensions was reduced. The outcomes of this work give insights into the exploitation of these microalgae species in soft materials for food, pharma and other technological applications. 
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3.
  • 2017
  • swepub:Mat__t
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