| Forest ecosystem carbon and water fluxes modeling is one of the main directions of the forest carbon cycle monitoring research. This research is helpful to accurately assess the contribution of forest ecosystem to global carbon and water balance and to make forest carbon planning for mediating climate change. Forest disturbances by extreme weather events cause large uncertainties in carbon and water flux estimates and become an important part of forest carbon and water fluxes modeling. Compared with other forest types, bamboo forest has significant transpiration and carbon sequestration potential and its biological characteristics are special. It is intensively managed by farmers. Due to the lack of long-term observation site in bamboo forest ecosystem, bamboo forest ecosystem carbon and water cycle in the canopy scale was rarely reported. Therefore, combined the flux observation tower of Moso bamboo forest ecosystem in Anji county, Landsat Thematic Mapper (TM), MODerate resolution Imaging Spectroradiometer (MODIS) data, and Modern Era Retrospective-Analysis for Research and Applications (MERRA), this study quantitatively analyzed variations of Moso bamboo(Phyllostachys edulis) forest ecosystem carbon and water fluxes and their correlations with environmental and biological factors; Models for carbon and water fluxes were built and used to scale site-based fluxes up to regional-based fluxes; Effects of snow damages and drought on Moso bamboo forest ecosystem carbon and water fluxes were also analyzed. Results from this study were a reference for evaluating the contribution of Moso bamboo forest ecosystem to the regional carbon and water balance, provided methods for accurately estimating carbon and water fluxes in regional scale, and presented reference data for making Moso bamboo forest carbon planning for mediating climate change. Results and conclusions are mainly included in the following aspects:(1) Quality of turbulent flux measurements of Moso bamboo forest flux tower was evaluated using steady state test, Monin-Obukhov similarity function, and energy balance closure. Results showed that:COt flux measurements are met with the constant flux layer hypothesis and basic requirements of eddy covariance technique; Standard deviates of vertical wind speed and temperature normalized by a scaling velocity or temperature are universal functions of atmospheric stability; Minimum values of friction velocity for each seasonal nocturnal flux are between0.24and0.33m s-1; Energy balance closure is relatively low with value of71%due to precipitation and heterogeneous terrain, especially for nocturnal period.(2) Correction, gap-filling and flux partitioning were implemented to carbon flux measurements of Moso bamboo forest in2011. Results showed that, for the ecosystem respiration (Re), there is significant difference between night-based method and daytime-based method, implying huge uncertainty in Re; Net ecosystem exchange (NEE), gross primary productivity (GPP) and Re in2011were417.5g C m-2y-1,1899.7g C m-2y-1, and-1482.2g C m-2y-1. NEE reaches its peak at10:00-11:00, and it is slightly lower in the afternoon than in the morning. Moso bamboo forest has strong ability in carbon sequestration and is a carbon sink in each season.(3) The eddy covariance (EC) data collected from the Anji flux tower were used in this study to calibrate and validate the remote sensing-driven Penman-Monteith (RS-PM) and Eddy Covariance Light Use Efficiency (EC-LUE) models, and the models driven by the MODIS and MERRA datasets were used to estimate the evapotranspiration (ET) and GPP of Moso bamboo forest in Anji county. Results showed that the relative root mean square error of ET and GPP estimates were22.35%and17.96%compared with measurements, respectively; The saturation effect of GPP was taken into account in the EC-LUE model, which played an important role in improving the model performance with relative root mean square error reduced from32.79%to17.96%.(4) Correlation analysis between carbon flux components and environmental and biological factors showed that the correlation between GPP and temperature (T) was the highest (P<0.01), followed by Leaf Area Index (LAI)> Normalized Difference Vegetation Index (NDVI)> Vapor Pressure Deficit (VPD)> Photosynthetically Active Radiation (PAR)> Soil Volumetric Water Content (SVWC); PAR, LAI, and VPD were main control factors for NEE (P<0.01); Correlation between Re and T was the highest, followed by NDVI, LAI (P<0.01). LAI and NDVI can serve as inputs to model for estimating regional Re.(5) The whole drought period was divided into beginning phase, drought phase and recovery phase. The influences of drought on NEE, GPP and Re were analyzed. Results showed that the correlations between environmental factors and GPP, NEE and Re were significantly changed due to drought effect; Key control factors for the carbon flux were different in each phase of drought; Combined VPD and soil moisture content can be used to well describe occurrence and influence of drought; Simulation results from the dynamic linear regression model showed that the decreases in GPP and NEE caused by drought were12.7%and44.8%, respectively. Sensitivity of Re to drought was lower than those of GPP and NEE. Re did not decrease during drought period. The accuracy of GPP estimates during drought period was improved when VPD and SVWC were inputted into the EC-LUE model.(6) The impacts of ice storm on GPP and ET of Moso bamboo forests and their relationships with terrain factors were analyzed based on ET, GPP and digital elevation data from2004to2011. Results showed that the early2008ice storm caused a slight decrease in annual ET and GPP, and this ice storm decreased annual mean GPP by0.17g C m-2d-1; Ice storm damage effects on ET and GPP for the off-year were slightly greater than those for the on-year; Relationships between decreases in GPP and terrain factors were more significant than those between decreases in ET and terrain factors. The correlations between decreases in GPP and altitude and slope were positive. |
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