@article{2b16a42f555a425a85fe41db44a46283,
title = "Informing trait-based ecology by assessing remotely sensed functional diversity across a broad tropical temperature gradient",
abstract = "Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotely sensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivity could be predicted by remotely sensed functional diversity. Functional richness of the community decreased with increasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play an important role in explaining the range of trait variation within each site and along elevation. Single- and multitrait remotely sensed measures of functional diversity were important predictors of variation in rates of net and gross primary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.",
author = "Dur{\'a}n, {Sandra M.} and Martin, {Roberta E.} and Sandra D{\'i}az and Maitner, {Brian S.} and Yadvinder Malhi and Norma Salinas and Alexander Shenkin and Silman, {Miles R.} and Wieczynski, {Daniel J.} and Asner, {Gregory P.} and Bentley, {Lisa Patrick} and Savage, {Van M.} and Enquist, {Brian J.}",
note = "Funding Information: We thank two anonymous referees for constructive comments on earlier drafts. This work is a product of the Global Ecosystems Monitoring (GEM) network (gem.tropicalforests.ox.ac.uk), the Andes Biodiversity and Ecosystem Research Group (andesresearch.org), the Amazon Forest Inventory Network RAINFOR (www.rainfor.org), and the Carnegie Spectranomics Project (spectranomics.carnegiescience.edu) research consortia. Funding: Field campaigns were funded by grants to Y.M. from the UK Natural Environment Research Council (grants NE/J023418/1, NE/J023531/1, and NE/F002149/1), the European Research Council Advanced Investigator (grant GEM-TRAITS 321131), and the Gordon and Betty Moore Foundation to Y.M., M.R.S., and G.P.A. Carnegie Airborne Observatory (CAO) flights, data processing, and analyses were supported by a grant to G.P.A. from the John D. and Catherine T. MacArthur Foundation. The CAO is made possible by grants and donations to G.P.A. from the Avatar Alliance Foundation, Margaret A. Cargill Foundation, David and Lucile Packard Foundation, Gordon and Betty Moore Foundation, Grantham Foundation for the Protection of the Environment, W. M. Keck Foundation, John D. and Catherine T. MacArthur Foundation, Andrew Mellon Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr., and William R. Hearst III. This work was supported by NSF grant DEB1457812 (to B.J.E., L.P.B., G.P.A., and V.M.S.) and NSF grant DEB (LTREB) 1754647 (to M.R.S.). Publisher Copyright: Copyright {\textcopyright} 2019 The Authors.",
year = "2019",
month = dec,
day = "4",
doi = "10.1126/sciadv.aaw8114",
language = "English (US)",
volume = "5",
journal = "Science advances",
issn = "2375-2548",
publisher = "American Association for the Advancement of Science",
number = "12",
}