4.7 Article

A two-stage light-use efficiency model for improving gross primary production estimation in agroecosystems

Journal

ENVIRONMENTAL RESEARCH LETTERS
Volume 17, Issue 10, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/1748-9326/ac8b98

Keywords

gross primary production; maximum light-use efficiency; two-stage light-use efficiency model; seasonal fluctuations; agroecosystems

Funding

  1. National Natural Science Foundation of China [41922009, 42071332]
  2. National Key R&D Program of China [2018YFA0605401]

Ask authors/readers for more resources

This study proposes a new two-stage light-use efficiency model that can improve the estimation of gross primary production in agroecosystems and shows great potential at a global scale.
Accurate quantification of gross primary production (GPP) in agroecosystems not only improves our ability to understand the global carbon budget but also plays a critical role in human welfare and development. Light-use efficiency (LUE) models have been widely applied in estimating regional and global GPP due to their simple structure and clear physical basis. However, maximum LUE (epsilon(max)), a key photosynthetic parameter in LUE models, has generally been treated as a constant, leading to common overestimation and underestimation of low and high magnitudes of GPP, respectively. Here, we propose a parsimonious and practical two-stage LUE (TS-LUE) model to improve GPP estimates by (a) considering seasonal variations of epsilon(max), and (b) separately re-parameterizing epsilon(max) in the green-up and senescence stages. The TS-LUE model is inter-compared with state-of-the-art epsilon(max)-static moderate resolution imaging spectroradiometer-GPP, eddy-covariance-LUE, and vegetation production models. Validation results at 14 FLUXNET sites for five crop species showed that: (a) the TS-LUE model significantly reduced the large bias at high- and low-level GPP as produced by the three epsilon(max)-static LUE models for all crop types; and (b) the TS-LUE model generated daily GPP estimates in good agreement with in-situ measurements and was found to outperform the three epsilon(max)-static LUE models. Especially compared to the well-known moderate resolution imaging spectroradiometer-GPP, the TS-LUE model could remarkably decrease the root mean square error (in gC m(-2) d(-1)) by 24.2% and 35.4% (from 3.84 to 2.91 and 2.48) and could increase the coefficient of determination by 14.7% and 20% (from 0.75 to 0.86 and 0.9) when the leaf area index (LAI) and infrared reflectance of vegetation (NIRv) were used to re-parameterize the epsilon(max), respectively. The TS-LUE model provides a brand-new perspective on the re-parameterization of epsilon(max) and indicates great potential for improving daily agroecosystem GPP estimates at a global scale.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available