TRY plant trait database – enhanced coverage and open access

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

Presencia de Epilobium brachicarpum C. Presl. como infestante en los frutales de Extremadura

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A first record of bulk atmospheric deposition patterns of major ions in southern South America

Despite the importance of long-term atmospheric deposition of ions for vegetation productivity and biogeochemistry, southern South America lacks long-term deposition records. We report a 6-year-long record of atmospheric deposition measurements of Mg2+, Ca2+, Na+, K+, Cl−, SO42−, NO3− and NH4+ in the plains of southern South America, which encompass one of the most important agricultural basins and urban clusters of the continent. After establishing a deposition measurement network across four sites in Argentina and Uruguay, we collected bulk atmospheric deposition monthly form January 2007 through December 2012 in an east–west transect of 700 km. Spatial changes in the sea-salt component of atmospheric deposition were primarily associated with proximity to the sea—as observed in other regions of the world—whereas non-sea-salt components of atmospheric deposition of terrestrial origin were primarily associated with the size of the human population surrounding collection sites. Atmospheric deposition showed a strong interannual variability (CV 50%) mainly associated with variations in the non-sea salt components of terrestrial origin and were within observed values for other relatively unpolluted sites of South America and globally. However, atmospheric deposition appears to be increasing in the region, particularly for SO42− and other ions around Buenos Aires, Argentina, which may represent an early warning of increased air pollution in the area. Average annual regional deposition of sulfate (SO42−) was 12.7 kg S hectare−1 and nitrate (NO3−) was 9.2 kg N hectare−1. Weighted average concentrations of base cations (sum of Mg2+, Ca2+, Na+ and K+) was 0.27 mg L−1, and weighted average concentrations of SO42−, NO3− and NH4+ were 0.094, 0.018 and 0.046 mg L−1, respectively. Our work highlights the need for long-term networks recording atmospheric deposition in the region, increasing knowledge of nutrient cycling and establishing a baseline for future atmospheric pollution measurements.EEA PergaminoFil: Carnelos, D.A. Universidad de Buenos Aires Facultad de Agronomía, Catedra de Climatología y Fenología Agrícolas; Argentina. LART- Laboratorio de Análisis Regional y Teledetección; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Catedra de Ecología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas-Universidad de Buenos Aires (CONICET-UBA). Instituto de Investigaciones Fisiológicas y Ecológicas vinculadas a la Agricultura (IFEVA); ArgentinaFil: Portela, Silvina Isabel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Sección Laboratorio Suelos; ArgentinaFil: Jobbágy, E.G. Universidad Nacional de San Luis. Instituto de Matemática Aplicada San Luis (IMASL). Grupo de Estudio Ambiental; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Grupo de Estudio Ambiental; ArgentinaFil: Jackson, R.B. Stanford University. Woods Institute for the Environment, and Precourt Institute for Energy. Department of Earth System Science; Estados UnidosFil: Di Bella, Carlos Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaFil: Panario, D. Universidad de la República (Montevideo). Facultad de Ciencias. Instituto de Ecología y Ciencias Ambientales (IECA); UruguayFil: Fagúndez, C. Universidad de la República (Rocha). Centro Universitario Regional del Este (CURE); UruguayFil: Piñeiro-Guerra, J.M. LART- Laboratorio de Análisis Regional y Teledetección; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Catedra de Ecología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas-Universidad de Buenos Aires (CONICET-UBA). Instituto de Investigaciones Fisiológicas y Ecológicas vinculadas a la Agricultura (IFEVA); ArgentinaFil: Grion, L. LART- Laboratorio de Análisis Regional y Teledetección; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Catedra de Ecología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas-Universidad de Buenos Aires (CONICET-UBA). Instituto de Investigaciones Fisiológicas y Ecológicas vinculadas a la Agricultura (IFEVA); ArgentinaFil: Piñeiro, G. LART- Laboratorio de Análisis Regional y Teledetección; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Recursos Naturales y Ambiente. Catedra de Ecología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas-Universidad de Buenos Aires (CONICET-UBA). Instituto de Investigaciones Fisiológicas y Ecológicas vinculadas a la Agricultura (IFEVA); Argentina. Universidad de la Republica Montevideo. Facultad de Agronomía. Departamento de Sistemas Ambientales. Grupo de Ecología; Urugua

TRY plant trait database, enhanced coverage and open access

Plant traits-the morphological, ahawnatomical, 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