Estimating mangrove forest gross primary production by quantifying environmental stressors in the coastal area

Yuhan Zheng,Wataru Takeuchi

doi:10.1038/s41598-022-06231-6

Abstract

Mangrove ecosystems play an important role in global carbon budget, however, the quantitative relationships between environmental drivers and productivity in these forests remain poorly understood. This study presented a remote sensing (RS)-based productivity model to estimate the light use efficiency (LUE) and gross primary production (GPP) of mangrove forests in China. Firstly, LUE model considered the effects of tidal inundation and therefore involved sea surface temperature (SST) and salinity as environmental scalars. Secondly, the downscaling effect of photosynthetic active radiation (PAR) on the mangrove LUE was quantified according to different PAR values. Thirdly, the maximum LUE varied with temperature and was therefore determined based on the response of daytime net ecosystem exchange and PAR at different temperatures. Lastly, GPP was estimated by combining the LUE model with the fraction of absorbed photosynthetically active radiation from Sentinel-2 images. The results showed that the LUE model developed for mangrove forests has higher overall accuracy (RMSE = 0.0051, R2 = 0.64) than the terrestrial model (RMSE = 0.0220, R2 = 0.24). The main environmental stressor for the photosynthesis of mangrove forests in China was PAR. The estimated GPP was, in general, in agreement with the in-situ measurement from the two carbon flux towers. Compared to the MODIS GPP product, the derived GPP had higher accuracy, with RMSE improving from 39.09 to 19.05 g C/m2/8 days in 2012, and from 33.76 to 19.51 g C/m2/8 days in 2015. The spatiotemporal distributions of the mangrove GPP revealed that GPP was most strongly controlled by environmental conditions, especially temperature and PAR, as well as the distribution of mangroves. These results demonstrate the potential of the RS-based productivity model for scaling up GPP in mangrove forests, a key to explore the carbon cycle of mangrove ecosystems at national and global scales.

Highlights

Mangrove ecosystems play an important role in global carbon budget, the quantitative relationships between environmental drivers and productivity in these forests remain poorly understood
The model considered the environmental stresses induced by tidal inundation, involving sea surface temperature (SST), sea surface salinity, and photosynthetic active radiation (PAR) as environmental scalars to develop the light use efficiency (LUE) model
The mangrove gross primary production (GPP) was estimated based on the mangrove LUE model, fraction of absorbed photosynthetic active radiation (fAPAR) generated from Sentinel-2 images and reconstructed PAR from meteorological stations

Summary

Introduction

Mangrove ecosystems play an important role in global carbon budget, the quantitative relationships between environmental drivers and productivity in these forests remain poorly understood. The spatiotemporal distributions of the mangrove GPP revealed that GPP was most strongly controlled by environmental conditions, especially temperature and PAR, as well as the distribution of mangroves These results demonstrate the potential of the RS-based productivity model for scaling up GPP in mangrove forests, a key to explore the carbon cycle of mangrove ecosystems at national and global scales. Carbon flux data measured with eddy covariance (EC) techniques provide invaluable information on ecosystem productivities and can be used to establish productivity models[2] These models were limited to a 0.1–2 km spatial footprint around the towers, and applying them at other sites remains challenging due to the variation of GPP across species, structural features, and latitudinal locations. It is challenging to apply their models to other regions without continuous measurements

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