18 research outputs found
TRY plant trait database â enhanced coverage and open access
Plant traitsâthe morphological, anatomical, physiological, biochemical and phenological characteristics of plantsâdetermine 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 traitâbased 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 traitsâalmost complete coverage for âplant growth formâ. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and traitâenvironmental 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
Microstructural refinement and deformation twinning during severe plastic deformation of 316L stainless steel at high temperatures
Toxicity in standard melphalan-prednisone therapy among myeloma patients with renal failure - a retrospective analysis and recommendations for dose adjustment
Cardiac Amyloidosis: Report of a Patient Heterozygous for the Transthyretin Isoleucine 122 Variant
Estimating Farm Productivity Differentials using Panel Data: The Hausman-Taylor Approach
This paper investigates the relation between unobserved farm productivity and other production factors in a system of netput equations for specialised pig breeding farms in the Netherlands. In order to estimate the system, a Hausman-Taylor panel data estimator is developed for a system of equations with unbalanced panel data. Tests on correlation between model variables and farm-effects are performed, yielding insight in the sources of differences in total factor productivity and its components (e.g. managerial ability and scale economies). Results indicate that specialised pig breeding farms that are characterised by high total factor productivity have more buildings and machinery than farms with low total factor productivity