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One of the major challenges in ecology is to understand how ecosystems respond to changes inenvironmental conditions, and how taxonomic and functional diversity mediate these changes. Inthis study, we use a trait-spectra and individual-based model, to analyse variation in forest primaryproductivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accuratelypredicted the magnitude and trends in forest productivity with elevation, with solar radiation andplant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, andwood density) collectively accounting for productivity variation. Remarkably, explicit representationof temperature variation with elevation was not required to achieve accurate predictions offorest productivity, as trait variation driven by species turnover appears to capture the effect oftemperature. Our semi-mechanistic model suggests that spatial variation in traits can potentiallybe used to estimate spatial variation in productivity at the landscape scale. Fil: Fyllas, Nikolaos M.. University of Oxford; Reino Unido Fil: Patrick Bentley, Lisa. University of Oxford; Reino Unido Fil: Shenkin, Alexander. University of Oxford; Reino Unido Fil: Asner, Gregory P.. Carnegie Institution for Science. Department of Global Ecology; Reino Unido Fil: Atkin, Owen K.. The Australian National University. ARC Centre of Excellence in Plant Energy Biology. Research School of Biology; Australia Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enquist, Brian J.. Arizona State University; Estados Unidos Fil: Farfan Rios, William. University Wake Forest; Estados Unidos Fil: Gloor, Emanuel. University of Leeds; Reino Unido Fil: Guerrieri, Rossella. Universitat Autònoma de Barcelona; España. University of Edinburgh; Reino Unido Fil: Huaraca Huasco, Walter. Universidad Nacional de San Antonio Abad del Cusco; Perú Fil: Ishida, Yoko. James Cook University; Australia Fil: Martin, Roberta E.. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Meir, Patrick. University of Edinburgh; Reino Unido. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia Fil: Phillips, Oliver. University of Leeds; Reino Unido Fil: Salinas, Norma. University of Oxford; Reino Unido. Pontificia Universidad Católica de Perú; Perú Fil: Silman, Miles. University Wake Forest; Estados Unidos Fil: Weerasinghe, Lasantha K.. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia Fil: Zaragoza Castells, Joana. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia. University of Exeter; Reino Unido Fil: Malhi, Yadvinder. University of Oxford; Reino Unido

Terrestrial and marine ecosystems provide essential goods and services to human societies. In the last several decades, however, anthropogenic pressures are causing serious threats to ecosystem integrity, functions, and processes. In turn, ecosystem degradation and loss of ecosystem services can seriously affect human well-being and climate processes on local and regional scales, potentially amplifying the negative effects of global change. Knowledgebased conservation, management, and restoration policies are thus urgently needed in order to ensure the delivery of ecosystem benefits in the face of increasing anthropogenic pressures. The Group on Earth Observations Global Ecosystem Initiative (GEO ECO) uses newly available monitoring methodologies that combine approaches in geosciences and biosciences, remotely sensed data, and in situ observations to provide open-access information on the state and ongoing changes of ecosystems and ecosystem services. The best use is made of existing and future earth observations and field monitoring data, complemented by appropriate interpretation tools and data services, as well as ecosystem models able to use these data. The GEO ECO combines new activities developed in the framework of the European H2020 ECOPOTENTIAL and Satellite-Based Wetland Observation Service projects, with continuing global ecosystem mapping activities carried forward from the former GEO ecosystems task from the first decade of GEO and Global Earth Observation System of Systems (GEOSS), in collaboration with the U.S. Geological Survey, Esri, and a number of international ecosystems experts. In these endeavors, all data, scientific results, models, and information will be made accessible and available through a system of cloud-based open platforms implementing virtual laboratories. Such platforms will be a major contribution to the GEOSS common infrastructure, reinforcing the GEOSS Data Collection of Open Resources for Everyone and in harmony with the Open Data global vision.