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Title: Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations

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 modern 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 patterns 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 seasonalmore » 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 All-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 of the 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.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]
  1. Dept. of Civil and Environmental Engineering, the University of Michigan
  2. Dept. of Ecology and Evolutionary Biology, the University of Arizona
Publication Date:
Research Org.:
Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division
OSTI Identifier:
1530160
Report Number(s):
DOE-MICHIGAN-11078
DOE Contract Number:  
SC0011078
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; seasonality, photosynthesis, Amazon, ecosystem

Citation Formats

Ivanov, Valeriy, and Saleska, Scott. Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations. United States: N. p., 2019. Web. doi:10.2172/1530160.
Ivanov, Valeriy, & Saleska, Scott. Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations. United States. doi:10.2172/1530160.
Ivanov, Valeriy, and Saleska, Scott. Sun . "Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations". United States. doi:10.2172/1530160. https://www.osti.gov/servlets/purl/1530160.
@article{osti_1530160,
title = {Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations},
author = {Ivanov, Valeriy and Saleska, Scott},
abstractNote = {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 modern 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 patterns 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 All-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 of the 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.},
doi = {10.2172/1530160},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {6}
}