| Grant number: | 13/50533-5 |
| Support Opportunities: | Regular Research Grants |
| Start date: | January 01, 2014 |
| End date: | December 31, 2016 |
| Field of knowledge: | Physical Sciences and Mathematics - Geosciences |
| Agreement: | GOAmazon Collaborative Research |
| Principal Investigator: | Luiz Eduardo Oliveira e Cruz de Aragão |
| Grantee: | Luiz Eduardo Oliveira e Cruz de Aragão |
| Principal researcher abroad: | Dennis Gene Dye |
| Institution abroad: | Southwest Geographic Science Team, Tucson , United States |
| Host Institution: | Instituto Nacional de Pesquisas Espaciais (INPE). São José dos Campos , SP, Brazil |
| City of the host institution: | São José dos Campos |
Abstract
We propose a study focused on the basic question: What controls the response of photosynthesis in Amazonian forests to seasonal variations in climate? This question, despite its apparent simplicity, remains difficult for modem earth system models to answer, and is also the subject of continuing controversy in the remote-sensing literature. For example, in the modeling arena, four cutting-edge earth system models (ESM's) show significant divergence in their seasonal pattems of photosynthesis from observed whole-system photosynthetic fluxes at two sites in the central Amazon. The overall objective of the project is to guide improvements in earth system models of tropical forest photosynthesis by collecting and integrating a suite of observations to 1) test several hypotheses (three core, conceptual hypotheses for explaining observed photosynthetic seasonality and a methodological hypotheses for scaling from leaves to canopy with hyperspectral cameras), and 2) perform a synthesis activity that applies our empirical work to earth system models of terrestrial carbon cycling. The project will provide an extensive suite of new and unique datasets that enable us to fill, through advanced modeling techniques and analysis, critical knowledge gaps in current understanding of what controls the response of canopy photosynthesis and related functions in Amazonian forests to seasonal variation in climate. Three major types of datasets and data products will be delivered: (1) in situ leaf and tree-scale measurements from intensive ecophysiological and ecohydological field campaigns, (2) time-series observations of leaf-to-crown scale forest reflectance properties and atmospheric radiation from two innovative, ground-based imaging sensors (respectively, the Hyperspectral Vegetation Imaging System and the High Dynamic Range AII-Sky Imaging System), and (3) results from state-of-the-art models of 3-dimensional canopy processes for radiative transfer and photosynthesis that integrate and link our observations to tropical forest processes. These data products and the improved knowledge we achieve with them will contribute to testing and improving the treatment of tropical forest processes in ESMs. They will contribute data to and leverage related data from ofthe GOAmazon campaign, and make significant contributions to support the overall goals of GOAmazon. This work will also help establish a foundation for the Next Generation Ecosystem Experiments (NGEE) in the Tropics. (AU)
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