整合生物学期刊网

林业研究(英文版) ›› 2023, Vol. 34 ›› Issue (4): 915-927.DOI: 10.1007/s11676-022-01546-6

• • 上一篇    下一篇

Siyuan Chen1,2, Liangyun Liu2,b, Lichun Sui1, Xinjie Liu2   

  • 收稿日期:2022-01-29 接受日期:2022-04-04 出版日期:2024-10-16 发布日期:2024-10-16
  • 通讯作者: Liangyun Liu

Improving GPP estimates by partitioning green APAR from total APAR in two deciduous forest sites

Siyuan Chen1,2, Liangyun Liu2,b, Lichun Sui1, Xinjie Liu2   

  1. 1 College of Geological Engineering and Geomatics, Chang’an University, 710054, Xi’an, People’s Republic of China
    2 Aerospace Information Research Institute, Chinese Academy of Sciences, 100094, Beijing, People’s Republic of China
  • Received:2022-01-29 Accepted:2022-04-04 Online:2024-10-16 Published:2024-10-16
  • Contact: Liangyun Liu

Abstract:

Non-photosynthetic components within a forest ecosystem account for a large proportion of the canopy but are not involved in photosynthesis. Therefore, the accuracy of gross primary production (GPP) estimates is expected to improve by removing these components. However, their influence in GPP estimations has not been quantitatively evaluated for deciduous forests. Several vegetation indices have been used recently to estimate the fraction of photosynthetically active radiation absorbed by photosynthetic components (

FAPAR green
) for partitioning
APAR green
(photosynthetically active radiation absorbed by photosynthetic components). In this study, the enhanced vegetation index (EVI) estimated
FAPAR green
and to separate the photosynthetically active radiation absorbed by photosynthetic components (
APAR green
) from total APAR observations (
APAR total
) at two deciduous forest sites. The eddy covariance-light use efficiency (EC-LUE) algorithm was employed to evaluate the influence of non-photosynthetic components and to test the performance of
APAR green
in GPP estimation. The results show that the influence of non-photosynthetic components have a seasonal pattern at deciduous forest sites, large differences are observed with normalized root mean square error (RMSE*) values of
APAR green
-based GPP and
APAR total
-based GPP between tower-based GPP during the early and end stages, while slight differences occurred during peak growth seasons. In addition, daily GPP estimation was significantly improved using the
APAR green
-based method, giving a higher coefficient of determination and lower normalized root mean square error against the GPP estimated by the
APAR total
-based method. The results demonstrate the significance of partitioning
APAR green
from
APAR total
for accurate GPP estimation in deciduous forests.

Key words: Gross primary production, Absorbed photosynthetically active radiation, Photosynthetic component, Vegetation index, AmeriFlux, European fluxes database