TRY (plant trait database)

TRY (plant trait database)
Name	TRY
Title	TRY (plant trait database)
Discipline	Plant functional ecology
Country	Germany
Established	2007
Hosted by	Max Planck Institute for Biogeochemistry

Contents

TRY (plant trait database)

TRY is a global initiative aggregating plant trait data to enable synthesis across scales and disciplines. Founded to coordinate trait datasets, it supports comparative studies across biomes, floras, and ecosystems by bringing together contributors from institutions such as the Max Planck Society, German Centre for Integrative Biodiversity Research, University of Helsinki, University of Oxford, and Smithsonian Institution. The database underpins work used by programs like the Intergovernmental Panel on Climate Change, Convention on Biological Diversity, and initiatives within the World Wide Fund for Nature.

Overview

TRY compiles standardized measurements of plant functional traits drawn from published studies, museum collections, long‑term monitoring networks, and targeted campaigns involving organizations such as the Global Biodiversity Information Facility, International Union for Conservation of Nature, European Commission, Asian Development Bank, and national herbaria. The project integrates contributions from researchers affiliated with University of California, Berkeley, ETH Zurich, Stockholm University, University of Queensland, and Australian National University, facilitating synthesis across taxonomic and geographic scales. The platform is designed to interoperate with complementary resources like GBIF, Dryad Digital Repository, PANGAEA, Neotoma Paleoecology Database, and model frameworks used at institutions such as the National Center for Atmospheric Research and Lawrence Berkeley National Laboratory.

TRY stores quantitative and categorical trait records covering morphology, physiology, phenology, and allocation, with traits such as leaf area, specific leaf area, wood density, seed mass, and photosynthetic capacity. Metadata standards reference practices from the Global Terrestrial Observing System, International Plant Names Index, International Union for Conservation of Nature Red List, and taxonomic backbones like those maintained by the Royal Botanic Gardens, Kew and Missouri Botanical Garden. Quality control involves cross‑checking against datasets from laboratories and observatories including the Lamont–Doherty Earth Observatory, Wageningen University, French National Centre for Scientific Research, and the Max Planck Institute for Biogeochemistry. Controlled vocabularies and trait definitions align with conventions used by the Ecological Society of America, Society for Conservation Biology, European Space Agency programs, and data standards promoted by the Committee on Data (CODATA).

Data contributors range from individual researchers at institutions like Harvard University, University of Cape Town, Peking University, Universidad Nacional Autónoma de México, and Universidad de São Paulo to consortiums such as the International Long Term Ecological Research Network and the National Ecological Observatory Network. Submission protocols request detailed sampling methods, georeferencing, and taxonomic authority, often coordinating with curators at the Natural History Museum, London, Field Museum of Natural History, and regional herbaria. Data curation workflows employ data stewards and technicians trained under standards promoted by organizations including the Biodiversity Information Standards (TDWG), European Bioinformatics Institute, and funding bodies like the European Research Council.

Access models balance open science principles endorsed by Open Data Commons, Creative Commons, and institutional repositories while protecting contributor rights through negotiated licenses. Users from universities, NGOs such as Conservation International and The Nature Conservancy, and governmental agencies may access aggregated datasets subject to terms that reflect attribution policies used by the DataCite community and mandates from funders like the National Science Foundation and Horizon Europe. Analytical tools and APIs interface with computing environments at CERN openlab, statistical ecosystems maintained by the R Consortium, and workflow platforms including those at the European Grid Infrastructure and cloud services used by Amazon Web Services and Google Cloud Platform for scalable analyses.

TRY has enabled meta‑analyses and model benchmarking cited by teams at Princeton University, University of Leeds, University of Montreal, Imperial College London, and the University of Tokyo addressing trait‑based ecology, global vegetation models, and biodiversity–climate feedbacks. Its records inform policy assessments under the Intergovernmental Science‑Policy Platform on Biodiversity and Ecosystem Services, land‑use scenarios developed by the International Institute for Applied Systems Analysis, and restoration guidelines promoted by UNEP. Benchmarking with datasets from FLUXNET, MODIS, and the Copernicus Programme supports trait‑enabled Earth system modeling and conservation prioritization used by practitioners at BirdLife International and the World Resources Institute.

Governance combines an international scientific advisory board drawing members from institutions like the Max Planck Institute for Biogeochemistry, Swedish University of Agricultural Sciences, University of Vienna, and Chinese Academy of Sciences with data access committees that follow best practices promulgated by bodies such as the Research Data Alliance and Science Europe. Funding has come from agencies and programs including the European Union, German Research Foundation, Swedish Research Council, National Natural Science Foundation of China, and philanthropic donors; in‑kind support is provided by hosting institutions and partner organizations including the Max Planck Society and various national research councils.

Category:Databases Category:Plant ecology Category:Biodiversity databases