The TRY Plant Trait Database - enhanced coverage and open access

Global Change Biology, 2019

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 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.

Journal of Vegetation Science

Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

Methods in Ecology and Evolution

1. Human activities exert stress on and create disturbances to ecosystems, decreasing their diversity, resilience and ultimately the health of ecosystems and their vegetation. In environments with rapid changes in vegetation health (VH), progress is needed when it comes to monitoring these changes and underlying causes. How to cite this article: Lausch A, Bastian O, Klotz S, et al. Understanding and assessing vegetation health by in situ species and remote-sensing approaches.

New Phytologist, 2021

Rising to meet global, interconnected challenges, such as food security and ecosystem resilience to global change, requires insights from across the Earth. This is especially true for belowground terrestrial ecological processes. Soil ecologists have answered this call: like mushrooms, large global datasets and databases on soil physics, chemistry and ecology are sprouting up everywhere (e.g. Fine-Root Ecology Database (Iversen et al., 2018), FunFun (Zanne et al., 2020), GlobalFungi (V
etrovsky et al., 2020), COntinuous SOil REspiration (Jian et al., 2020), Global distribution of earthworm diversity (Philips et al., 2019) etc.). It is now time to leverage synergies among these datasets to link the continuum of belowground processes to ecosystem functions (e.g. decomposition, nutrient cycling and soil respiration). Built on interdisciplinary and international collaborations, data synthesis that leads to a holistic understanding is one of the best ways of predicting the future of terrestrial ecosystems and for preserving ecosystem services under global change.

Methods in Ecology and Evolution

Measuring plant species properties is challenging, yet an essential task in support of biodiversity and ecosystem function monitoring (Oliver et al., 2015). Because in situ trait measurements are costly and labour-intensive, hyperspectral remote sensing observations are increasingly considered a promising complementary data source (Jetz et al., 2016). The biochemical and morphological properties of leaves, as well as the 3D structure of vegetation, actually determine how light is reflected, transmitted and absorbed, and as such shape the spectral response of vegetation (Ollinger, 2011). A variety of plant traits can be estimated from hyperspectral observations

Journal od Applied Ecology

Social networks offer communication channels through which people share huge amounts of primary data that can be used for scientific analyses, including biodiversity research. To understand to what extent data extracted from social networks could complement data collected for scientific purposes, it is necessary to quantify the bias of such data. We analysed which plant traits increased the probability of a wild-growing plant species to be photographed and posted to a social network based on the data from an unstructured citizen science tool; a Facebook group focused on the vascular flora of Sicily (Italy). Then, we compared botanical data collected by this Facebook group members with data collected by scientists in 6,366 vegetation plots sampled across Sicily, stored in the EVA database. Our results suggested that data proceeding from the analysed Facebook group were affected by various sampling biases, which differed from the biases inherent to other types of biodiversity data such as those from vegetation plots. Facebook users recorded a higher proportion of red-listed and alien species than vegetation scientists. Therefore, social networks can provide a valuable complement to the data collected by scientists for research purposes. Synthesis and applications. Despite Facebook does not support geotagging and interface for data access and analysis, it is an invaluable source of biodiversity data that could complement those collected by professional researchers. The main advantage of data from social networks is their high dynamism, as they report large amounts of species occurrences in almost real time. Therefore, citizen science data from a Facebook group where the records are curated by expert volunteers can be used (a) for monitoring population dynamics of threatened and alien species; (b) as a source of additional data on rare species occurrences, particularly for plants that are attractive for amateur botanists, such as orchids; (c) for early warning systems of potential new invasions; and (4) for phenological studies, especially at the beginning of the flowering season.

Ecology and Evolution, 2021

1. Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations. 2. We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.

Global Ecology and Biogeography

This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Philosophical Transactions of the Royal Society B, 2018

Cite this article: Perez TM et al. 2018 Botanic gardens are an untapped resource for studying the functional ecology of tropical plants. Phil. Trans. R. Soc. B 374: 20170390. http://dx.One contribution of 16 to a theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.