Simulation of the Unexpected Photosynthetic Seasonality in Amazonian Evergreen Forests by Using an Improved Diffuse Fraction-Based Light Use Efficiency Model. Yan, H., Wang, S., Q., da Rocha, H., R., Rap, A., Bonal, D., Butt, N., Coupe, N., R., & Shugart, H., H. Journal of Geophysical Research: Biogeosciences, 122(11):3014-3030, 2017.
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©2017. American Geophysical Union. Understanding the mechanism of photosynthetic seasonality in Amazonian evergreen forests is critical for its formulation in global climate and carbon cycle models. However, the control of the unexpected photosynthetic seasonality is highly uncertain. Here we use eddy-covariance data across a network of Amazonian research sites and a novel evapotranspiration (E) and two-leaf-photosynthesis-coupled model to investigate links between photosynthetic seasonality and climate factors on monthly scales. It reproduces the GPP seasonality (R 2 = 0.45-0.69) with a root-mean-square error (RMSE) of 0.67-1.25 g C m -2 d -1 and a Bias of -0.03-1.04 g C m -2 d -1 for four evergreen forest sites. We find that the proportion of diffuse and direct sunlight governs the photosynthetic seasonality via their interaction with sunlit and shaded leaves, supported by a proof that canopy light use efficiency (LUE) has a strong linear relationship with the fraction of diffuse sunlight for Amazonian evergreen forests. In the transition from dry season to rainy season, incident total radiation (Q) decreased while LUE and diffuse fraction increased, which produced the large seasonal increase (~34%) in GPP of evergreen forests. We conclude that diffuse radiation is an important environmental driver of the photosynthetic seasonality in tropical Amazon forests yet depending on light utilization by sunlit and shaded leaves. Besides, the GPP model simulates the precipitation-dominated GPP seasonality (R 2 = 0.40-0.69) at pasture and savanna sites. These findings present an improved physiological method to relate light components with GPP in tropical Amazon.
@article{
 title = {Simulation of the Unexpected Photosynthetic Seasonality in Amazonian Evergreen Forests by Using an Improved Diffuse Fraction-Based Light Use Efficiency Model},
 type = {article},
 year = {2017},
 keywords = {GF_GUY},
 pages = {3014-3030},
 volume = {122},
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 last_modified = {2020-09-08T15:25:47.529Z},
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 abstract = {©2017. American Geophysical Union. Understanding the mechanism of photosynthetic seasonality in Amazonian evergreen forests is critical for its formulation in global climate and carbon cycle models. However, the control of the unexpected photosynthetic seasonality is highly uncertain. Here we use eddy-covariance data across a network of Amazonian research sites and a novel evapotranspiration (E) and two-leaf-photosynthesis-coupled model to investigate links between photosynthetic seasonality and climate factors on monthly scales. It reproduces the GPP seasonality (R 2 = 0.45-0.69) with a root-mean-square error (RMSE) of 0.67-1.25 g C m -2 d -1 and a Bias of -0.03-1.04 g C m -2 d -1 for four evergreen forest sites. We find that the proportion of diffuse and direct sunlight governs the photosynthetic seasonality via their interaction with sunlit and shaded leaves, supported by a proof that canopy light use efficiency (LUE) has a strong linear relationship with the fraction of diffuse sunlight for Amazonian evergreen forests. In the transition from dry season to rainy season, incident total radiation (Q) decreased while LUE and diffuse fraction increased, which produced the large seasonal increase (~34%) in GPP of evergreen forests. We conclude that diffuse radiation is an important environmental driver of the photosynthetic seasonality in tropical Amazon forests yet depending on light utilization by sunlit and shaded leaves. Besides, the GPP model simulates the precipitation-dominated GPP seasonality (R 2 = 0.40-0.69) at pasture and savanna sites. These findings present an improved physiological method to relate light components with GPP in tropical Amazon.},
 bibtype = {article},
 author = {Yan, Hao and Wang, Shao Qiang and da Rocha, Humberto R. and Rap, Alexandru and Bonal, Damien and Butt, Nathalie and Coupe, Natalia Restrepo and Shugart, Herman H.},
 doi = {10.1002/2017JG004008},
 journal = {Journal of Geophysical Research: Biogeosciences},
 number = {11}
}

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