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Using climate‐driven leaf phenology and growth to improve predictions of gross primary productivity in North American forests.

Authors :
Fang, Jing
Lutz, James A.
Wang, Leibin
Shugart, Herman H.
Yan, Xiaodong
Source :
Global Change Biology. Dec2020, Vol. 26 Issue 12, p6974-6988. 15p.
Publication Year :
2020

Abstract

Forest ecosystems are an important sink for terrestrial carbon sequestration. Hence, accurate modeling of the intra‐ and interannual variability of forest photosynthetic productivity remains a key objective in global biology. Applying climate‐driven leaf phenology and growth in models may improve predictions of the forest gross primary productivity (GPP). We used a dynamic non‐structural carbohydrates (NSC) model (FORCCHN2) that couples leaf development and phenology to investigate the relationships among photosynthesis and environmental factors. FORCCHN2 simulates spring and autumn phenological events from heat and chilling, respectively. Leaf area index data from satellites along with climate data estimated localized phenological parameters. NSC limitation, immediate temperature, accumulated heat, and growth potential comprised a daily leaf‐growth model. Functionally, leaf growth was decoupled from photosynthesis. Leaf biomass determined overall photosynthetic production. We compared this model with outputs of the other six terrestrial biospheric models and with observations from the North American Carbon Program Site Interim Synthesis in 18 forest sites. This model improved the predicted performance of yearly GPP with a 57%–210% increase in correlation (median) and up to a 102% reduction in biases (median), compared to three prognostic models and three prescribed models. At the North America continental scale, the model predicted the average annual GPP of 7.38 Pg C/year from forest ecosystems during 1985–2016. The results showed an increasing trend of GPP in North America (1.0 Pg C/decade). The inclusion of climate‐driven phenology and growth has a significant potential for improving dynamic vegetation models, and promotes a further understanding of the complex relationship between environment and photosynthesis. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13541013
Volume :
26
Issue :
12
Database :
Academic Search Index
Journal :
Global Change Biology
Publication Type :
Academic Journal
Accession number :
147132281
Full Text :
https://doi.org/10.1111/gcb.15349