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

Squeezing more information out of time variable gravity data with a temporal decomposition approach

A measure of the Earth's gravity contains contributions from solid Earth as well as climate-related phenomena, that cannot be easily distinguished both in time and space. After more than 7. years, the GRACE gravity data available now support more elaborate analysis on the time series. We propose an explorative approach based on a suitable time series decomposition, which does not rely on predefined time signatures. The comparison and validation against the fitting approach commonly used in GRACE literature shows a very good agreement for what concerns trends and periodic signals on one side, and on the other it reveals where other behaviours can occur. Variations over frequency lower than the usual semi-annual or annual ones and variations in the rates of the secular trends indeed occur, related to geophysical phenomena, climate and even to human activities. A careful analysis of the residues allows to design a screening algorithm to identify regions where anomalous gravity variations deserve further investigations. It also allows to raise the amount of information one can obtain exclusively from gravity data, prior and preliminary to any subsequent specifically targeted study. This approach has been used to assess the possibility of finding evidence of meaningful geophysical signals different from hydrology over Africa in GRACE data. In this case we conclude that hydrological phenomena are dominant and so time variable gravity data in Africa can be directly used to calibrate hydrological models