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

Patterns of Early Gut Colonization Shape Future Immune Responses of the Host

The most important trigger for immune system development is the exposure to microbial components immediately after birth. Moreover, targeted manipulation of the microbiota can be used to change host susceptibility to immune-mediated diseases. Our aim was to analyze how differences in early gut colonization patterns change the composition of the resident microbiota and future immune system reactivity. Germ-free (GF) mice were either inoculated by single oral gavage of caecal content or let colonized by co-housing with specific pathogen-free (SPF) mice at different time points in the postnatal period. The microbiota composition was analyzed by denaturing gradient gel electrophoresis for 16S rRNA gene followed by principal component analysis. Furthermore, immune functions and cytokine concentrations were analyzed using flow cytometry, ELISA or multiplex bead assay. We found that a single oral inoculation of GF mice at three weeks of age permanently changed the gut microbiota composition, which was not possible to achieve at one week of age. Interestingly, the ex-GF mice inoculated at three weeks of age were also the only mice with an increased pro-inflammatory immune response. In contrast, the composition of the gut microbiota of ex-GF mice that were co-housed with SPF mice at different time points was similar to the gut microbiota in the barrier maintained SPF mice. The existence of a short GF postnatal period permanently changed levels of systemic regulatory T cells, NK and NKT cells, and cytokine production. In conclusion, a time window exists that enables the artificial colonization of GF mice by a single oral dose of caecal content, which may modify the future immune phenotype of the host. Moreover, delayed microbial colonization of the gut causes permanent changes in the immune system

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

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

Plant functional traits in studies of vegetation changes in response to grazing and mowing: towards a use of more specific traits

International audiencePlants' abilities to function are difficult to evaluate directly in the field. Therefore, a number of attempts have been made to determine easily measurable surrogates - plant functional traits (PFTs), In particular, the value of PFTs as tools for predicting vegetation responses to management (i.e., grazing and mowing) is the focus of a large number of studies. However, recent Studies using PFTs to predict the effect of pasture management in different regions did not give consistent predictions for the same set of PFTs. This lead to the suggestion that more specific traits better suited for a specific region be used in the future. We consider the identification of the roost adaptative traits for surviving grazing and mowing in different biomes an important goal. Using temperate grasslands in Europe as an example, we show that (i) plant height, often considered as the best predictor of species response to grassland management, is coupled with other more relevant functional traits, and that (ii) clonal traits have important, often neglected functions in the response of species to grassland management. We conclude that single traits cannot be the only basis for predicting vegetation changes under pasture management and, therefore, a functional analysis of the trade-off between key traits is needed

Plant functional traits in studies of vegetation changes in response to grazing and mowing: towards a use of more specific traits

International audiencePlants' abilities to function are difficult to evaluate directly in the field. Therefore, a number of attempts have been made to determine easily measurable surrogates - plant functional traits (PFTs), In particular, the value of PFTs as tools for predicting vegetation responses to management (i.e., grazing and mowing) is the focus of a large number of studies. However, recent Studies using PFTs to predict the effect of pasture management in different regions did not give consistent predictions for the same set of PFTs. This lead to the suggestion that more specific traits better suited for a specific region be used in the future. We consider the identification of the roost adaptative traits for surviving grazing and mowing in different biomes an important goal. Using temperate grasslands in Europe as an example, we show that (i) plant height, often considered as the best predictor of species response to grassland management, is coupled with other more relevant functional traits, and that (ii) clonal traits have important, often neglected functions in the response of species to grassland management. We conclude that single traits cannot be the only basis for predicting vegetation changes under pasture management and, therefore, a functional analysis of the trade-off between key traits is needed

Wait or escape? Contrasting submergence tolerance strategies of rorippa amphibia, rorippa sylvestris and their hybrid

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