Towards a Handshake of Ground-Based Measurements and Remote-Sensing of Vegetation Traits at Global Scale?

Thursday, 18 December 2014: 8:00 AM
Jens Kattge1, Sandra Díaz2, Sandra Lavorel3, Iain Colin Prentice4, Paul Leadley5, Peter B. Reich6, Arindam Banerjee7, Farideh Fazayeli7, Franziska I Schrodt1, Julia Joswig1, Miguel D Mahecha1 and Christian Wirth8, (1)Max Planck Institute for Biogeochemistry, Jena, Germany, (2)Universidad Nacionalde Córdoba, Instituto Multidisciplinario de Biología Vegetal, Córdoba, Argentina, (3)Laboratoire d’Ecologie Alpine (LECA), CNRS, Grenoble, France, (4)Imperial College London, Grantham Institute and Division of Biology, London, United Kingdom, (5)Université Paris-Sud, Laboratoire Ecologie, Systematique, Evolution, Orsay, France, (6)University of Minnesota Twin Cities, Department of Forest Resources, Minneapolis, MN, United States, (7)University of Minnesota Twin Cities, Department of Computer Science and Engineering, Minneapolis, MN, United States, (8)University of Leipzig, Institute for Special Botany and Functional Biodiversity, Leipzig, Germany
Plant traits determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services, and provide a link from species richness to ecosystem functional diversity. Plant traits thus are a key to understand and predict the adaptation of ecosystems to environmental changes. At the same time ground based measurements of plant trait data are dispersed over a wide range of databases, many of these not publicly available. To overcome this deficiency IGBP and DIVERSITAS have initiated the development of a joint database, called TRY, aiming at constructing a standard resource of ground based plant trait observations for the ecological community and for the development of global vegetation models.

So far the TRY initiative has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: about 250 trait databases have been contributed and the data repository currently contains about 5.6 million trait entries for 90,000 out of the world's 350,000 plant species. The database includes data for 1100 traits, characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence.

Based on advanced methods for gap-filling and spatial extrapolation currently being developed in applied statistics and machine learning and in combination with environmental information and species distribution ranges, the unprecedented availability of ground based trait measurements is expected to allow for up-scaling of trait observations from plant to ecosystem level and from point measurements to regional and global scales. These up-scaled data products are expected to provide a link from ground based trait measurements to remote sensing of vegetation function and traits with global coverage.