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Changes in plant biomass induced by soil moisture variability drive interannual variation in the net ecosystem CO2 exchange over a reclaimed coastal wetland

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Abstract Changes in the timing and magnitude of precipitation is a threat to agricultural productivity and farmland carbon stocks. However, the relationship between inter-annual variations in precipitation and net ecosystem… Click to show full abstract

Abstract Changes in the timing and magnitude of precipitation is a threat to agricultural productivity and farmland carbon stocks. However, the relationship between inter-annual variations in precipitation and net ecosystem CO2 exchange (NEE) remains to be clarified, particularly when combined with water-salt transport in reclaimed coastal wetland. Here, based on the eddy-covariance technique, we investigated the interannual variation in carbon dioxide exchange and its control mechanism over a reclaimed coastal wetland of the Yellow River Delta from 2010 to 2014. The coastal wetland functioned as a strong sink for atmospheric CO2, with the annual NEE of −229, −175, −142, −92 and −80 g C m−2 in the 5 years from 2010 to 2014, respectively. Surprisingly, we find that large annual variation in net ecosystem exchange (NEE) can be predicted accurately using plant biomass. Plant biomass was driven by soil water content (SWC), with about 48%–80% seasonal variation of biomass attributed to SWC. During the early growing stage, high SWC accompanied with low salinity promoted plant biomass and NEE. While high SWC accompanied with increased waterlogged stress inhibited plant biomass and NEE during the middle growing stage. The same results were also observed in a field manipulation experiment over a nearby natural coastal wetland. Our study indicated that extreme climate accompanied with extreme drought and flooding may decrease carbon sequestration capacity of the reclaimed coastal wetland due to the increase in salinity.

Keywords: plant biomass; reclaimed coastal; wetland; coastal wetland

Journal Title: Agricultural and Forest Meteorology
Year Published: 2019

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