Rain use efficiency changes and its effects on land surface phenology in the Songnen Plain, Northeast China

2018 ◽  
Author(s):  
Fang Huang ◽  
Ping Wang ◽  
Shuai Chang ◽  
Bo Li
Keyword(s):  
Land Surface ◽  
Northeast China ◽  
Songnen Plain ◽  
Land Surface Phenology ◽  
Use Efficiency ◽  
Rain Use Efficiency

scholarly journals Spatio-Temporal Variations of Carbon Use Efficiency in Natural Terrestrial Ecosystems and the Relationship with Climatic Factors in the Songnen Plain, China

2019 ◽  
Vol 11 (21) ◽  
pp. 2513 ◽  
Author(s):  
Bo Li ◽  
Fang Huang ◽  
Lijie Qin ◽  
Hang Qi ◽  
Ning Sun
Keyword(s):  
Primary Productivity ◽  
Land Surface ◽  
Climatic Factors ◽  
Transitional Region ◽  
Songnen Plain ◽  
Natural Ecosystems ◽  
Land Surface Phenology ◽  
Carbon Use Efficiency ◽  
Use Efficiency ◽  
The Impact

The Songnen Plain (SNP) is an important grain production base, and is designated as an ecological red-line as a protected area in China. Natural ecosystems such as the ecological protection barrier play an important role in maintaining the productivity and sustainability of farmland. Carbon use efficiency (CUE), defined as the ratio of net primary productivity (NPP) to gross primary productivity (GPP), represents the ecosystem capacity of transferring carbon from the atmosphere to terrestrial biomass. The understanding of the CUE of natural ecosystems in protected farmland areas is vital to predicting the impact of global change and human disturbances on carbon budgets and evaluating ecosystem functions. To date, the changes in CUE at different time scales and their relationships with climatic factors have yet to be fully understood. CUE and the response to land surface phenology are also deserving attention. In this study, variations in ecosystem CUE in the SNP during 2001–2015 were investigated using Moderate-Resolution Imaging Spectroradiometer (MODIS) GPP and NPP data products estimated using the Carnegie-Ames-Stanford approach (CASA) model. The relationships between CUE and phenological and climate factors were explored. The results showed that ecosystem CUE fluctuated over time in the SNP. The lowest and highest CUE values mainly occurred in May and October, respectively. At seasonal scale, average CUE followed a descending order of Autumn > Summer > Spring. The CUE of mixed forest was greater than that of other ecosystems at both monthly and seasonal scales. Land surface phenology plays an important role in the regulation of CUE. The earlier start (SOS), the later end (EOS) and longer length (LOS) of the growing season would contribute increasing of CUE. Precipitation and temperature affected CUE positively in most areas of the SNP. These findings help explain the CUE of natural ecosystems in the protected farmland areas and improve our understanding of ecosystem carbon allocation dynamics in temperate semi-humid to semi-arid transitional region under climate and phenological fluctuations.

Terrestrial CO2 Fluxes, Concentrations, Sources and Budget in Northeast China: Observational and Modeling Studies

2020 ◽  
Author(s):  
Xiaolan Li ◽  
Xiao-Ming Hu ◽  
Changjie Cai ◽  
Qingyu Jia ◽  
Yao Zhang ◽  
...  
Keyword(s):  
Land Surface ◽  
Northeast China ◽  
Ecosystem Respiration ◽  
Mixed Forest ◽  
Net Ecosystem Exchange ◽  
Growth Period ◽  
Rice Paddy ◽  
Light Use Efficiency ◽  
Maximum Light ◽  
Use Efficiency

<p>CO<sub>2</sub> fluxes and concentrations are not well understood in Northeast China, where dominant land surface types are mixed forest and cropland.  Here, we analyzed the CO<sub>2</sub> fluxes and concentrations using Eddy Covariance (EC) measurements, satellite observations, and the Weather Research and Forecasting model coupled with the Vegetation Photosynthesis and Respiration Model (WRF-VPRM).  We also used WRF-VPRM outputs to examine CO<sub>2</sub> transport/dispersion, and to quantify the biogenic and anthropogenic contributions to atmospheric CO<sub>2</sub> concentrations.  Finally, we investigated the uncertainties of simulating CO<sub>2</sub> fluxes related to four VPRM parameters (including maximum light use efficiency, photosynthetically active radiation half-saturation value, and two respiration parameters) using offline ensemble simulations with randomly selected parameter values.  The results indicated that mixed forests acted as a larger CO<sub>2</sub> source and sink than rice paddies on average in 2016 due to a longer growth period and stronger ecosystem respiration, although the minimum EC-measured daily mean net ecosystem exchange (NEE) was smaller at rice paddy (-10 μmol m<sup>-2</sup> s<sup>-1</sup>) than at mixed forest (-6.5 μmol m<sup>-2</sup> s<sup>-1</sup>) during the growing season (May through September).  The monthly fluctuation of column-averaged CO<sub>2</sub> concentrations (XCO<sub>2</sub>) exceeded 10 ppm in Northeast China during 2016.  Biogenic contribution (large negative in summer and insignificant in other months) offset about 70% of anthropogenic contribution of XCO<sub>2</sub> in this region.  WRF-VPRM modeling successfully captured seasonal and episodic variations of NEE and CO<sub>2</sub> concentrations, however, the NEE in mixed forest was overestimated during daytime, mainly due to the uncertainties of VPRM parameters, especially maximum light use efficiency.</p>

scholarly journals Investigation of Urbanization Effects on Land Surface Phenology in Northeast China during 2001–2015

2017 ◽  
Vol 9 (1) ◽  
pp. 66 ◽  
Author(s):  
Rui Yao ◽  
Lunche Wang ◽  
Xin Huang ◽  
Xian Guo ◽  
Zigeng Niu ◽  
...  
Keyword(s):  
Land Surface ◽  
Northeast China ◽  
Land Surface Phenology

scholarly journals The Variations of Land Surface Phenology in Northeast China and Its Responses to Climate Change from 1982 to 2013

2016 ◽  
Vol 8 (5) ◽  
pp. 400 ◽  
Author(s):  
Jianjun Zhao ◽  
Yanying Wang ◽  
Zhengxiang Zhang ◽  
Hongyan Zhang ◽  
Xiaoyi Guo ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Northeast China ◽  
Land Surface Phenology

scholarly journals Investigation of Urbanization Effects on Land Surface Phenology in Northeast China during 2001–2015

2017 ◽  
Author(s):  
Rui Yao ◽  
Lunche Wang ◽  
Xin Huang ◽  
Xian Guo ◽  
Zigeng Niu ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Rural Area ◽  
Land Surface ◽  
Northeast China ◽  
Growing Season ◽  
Temporal Variations ◽  
Urban Heat Island Intensity ◽  
Heat Island ◽  
Land Surface Phenology ◽  
Urban Heat

The urbanization effects on land surface phenology (LSP) have been investigated by many studies, but few studies focused on the temporal variations of urbanization effects on LSP. In this study, we used the MODIS EVI, MODIS LST data and China’s Land Use/Cover Datasets (CLUDs) to investigate the temporal variations of urban heat island intensity and urbanization effects on LSP in Northeast China during 2001–2015. Land surface temperature (LST) and phenology differences between urban and rural areas represented the urban heat island intensity and urbanization effects on LSP, respectively. Mann-kendall nonparametric test and Sen's slope were used to evaluating the trends of urbanization effects on LSP and urban heat island intensity. The results indicated that the average land surface phenology (LSP) during 2001–2015 was characterized by high spatial heterogeneity. The start of the growing season (SOS) in old urban area had become earlier and earlier than rural area and the differences of SOS between urbanized area and the rural area changed greatly during 2001–2015 (−0.79 days/year, p < 0.01). Meanwhile, the length of the growing season (LOS) in urban and adjacent areas had become increasingly longer than rural area especially in urbanized area (0.92 days/year, p < 0.01), but the differences of the end of the growing season (EOS) between urban and adjacent areas did not change significantly. Next, the UHII increased in spring and autumn during the whole study period. Moreover, the correlation analysis indicated that the increasing urban heat island intensity in spring contributed greatly to the increases of urbanization effects on SOS, but the increasing urban heat island intensity in autumn did not lead to the increases of urbanization effects on EOS in Northeast China.

Evaluation of the CERES-Rice Model for Precision Nitrogen Management for Rice in Northeast China

2017 ◽  
Vol 8 (2) ◽  
pp. 328-332
Author(s):  
J. Zhang ◽  
Y. Miao ◽  
W.D. Batchelor
Keyword(s):  
Northeast China ◽  
Weather Data ◽  
Cool Season ◽  
Use Efficiency ◽  
Optimum N Rate ◽  
Management Recommendations ◽  
N Management ◽  
N Rates ◽  
N Use

Over-application of nitrogen (N) in rice (Oryza sativaL.) production in China is common, leading to low N use efficiency (NUE) and high environmental risks. The objective of this work was to evaluate the ability of the CERES-Rice crop growth model to simulate N response in the cool climate of Northeast China, with the long term goal of using the model to develop optimum N management recommendations. Nitrogen experiments were conducted from 2011–2015 in Jiansanjiang, Heilongjiang Province in Northeast China. The CERES-Rice model was calibrated for 2014 and 2015 and evaluated for 2011 and 2013 experiments. Overall, the model gave good estimations of yield across N rates for the calibration years (R2=0.89) and evaluation years (R2=0.73). The calibrated model was then run using weather data from 2001–2015 for 20 different N rates to determine the N rate that maximized the long term marginal net return (MNR) for different N prices. The model results indicated that the optimum mean N rate was 120–130 kg N ha–1, but that the simulated optimum N rate varied each year, ranging from 100 to 200 kg N ha–1. Results of this study indicated that the CERES-Rice model was able to simulate cool season rice growth and provide estimates of optimum regional N rates that were consistent with field observations for the area.

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