Long-term effects of rewetting and drought on GPP in a temperate peatland based on satellite remote sensing data.

The Science of the total environment(2023)

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摘要
Rewetting previously drained peatlands restores the critical function of peatlands as long-term carbon storages and sinks currently threatened by climate change and additional human-induced disturbances. Understanding and projecting the restoration process by rewetting, however, currently face a pressing challenge, the lack of consistent and gap-free records of important carbon cycling indicators of peatlands such as the gross primary production (GPP) over long term. In this study, we reconstructed the GPP in a rewetted peatland called Zarnekow (Fluxnet-ID: DE-Zrk) in Germany from 2000 to 2020 by combining long-term satellite observations and limited-term tower-based eddy covariance (EC) measurements based on Random Forest regression models. The R between the reconstructed data and EC data was 0.6. The reasonable reconstruction of long-term GPP enabled trend analysis that identified two distinct periods of decreasing/increasing in GPP due to rewetting and droughts. Rewetting in the winter of 2004 and 2005 stabilized GPP after a decreasing period. A drought in 2018 significantly increased GPP, and GPP remained high over the following two years. Furthermore, the month-specific trends show significant seasonality at this site, specifically, an increasing trend over the 21 years in the growing-season months of June to August and a decreasing trend in the other months. The most important variables for satellite-based estimates of GPP at this site include total evapotranspiration, land surface temperature, enhanced vegetation index and near-infrared reflectance vegetation index. Long-term analyses of carbon fluxes through the combination of satellite observations and EC measurements provide crucial insights into the restoration of carbon sequestration functions in rewetted peatlands.
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关键词
Data reconstruction,Gross primary production,Peatland,Random Forest,Remote sensing retrieval
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