Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning.

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr-1 falling into the range of previous works. Considering the consistency between the generated AGPP and previous products, our optimal mapping way was suitable for mapping AGPP from site measurements. Our results provided a methodological support for mapping regional AGPP and other fluxes.

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Ecologically fragile areas account for more than 60% of land area in China. Global change and human activities are aggravating ecosystem degradation and reducing the carrying capacity of resources and environment. It is important to accurately quantify the carrying capacity of resources and environment in ecologically fragile areas to deal with the risk and challenge of global change and to speed up the construction of ecological civilization. How-ever, existing methods evaluating carrying capacity of resources and environment are difficult to reflect the transmission effect of ecosystem structures, processes and functions changes among resource, environment and carrying capacity. Therefore, it is essential to establish a field observation network and obtain the comprehensive data set of resource and environment elements-ecosystem structure, function and process-ecosystem carrying capacity for develo-ping the theory and evaluation method. We introduced the collaborative monitoring networks of flux and UAV photographing, including the thoughts, practice, and preliminary results in the study of ecosystem structure, process and function in the fragile ecosystems of China. Based on the achievements and progress, we proposed the application of collaborative monitoring networks in capacity evaluation.

Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China.

Understanding the dynamics and underlying mechanism of carbon exchange between terrestrial ecosystems and the atmosphere is one of the key issues in global change research. In this study, we quantified the carbon fluxes in different terrestrial ecosystems in China, and analyzed their spatial variation and environmental drivers based on the long-term observation data of ChinaFLUX sites and the published data from other flux sites in China. The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude. However, GEP, ER, and NEP did not present a clear longitudinal pattern. The carbon sink functional areas of terrestrial ecosystems in China were mainly located in the subtropical and temperate forests, coastal wetlands in eastern China, the temperate meadow steppe in the northeast China, and the alpine meadow in eastern edge of Qinghai-Tibetan Plateau. The forest ecosystems had stronger carbon sink than grassland ecosystems. The spatial patterns of GEP and ER in China were mainly determined by mean annual precipitation (MAP) and mean annual temperature (MAT), whereas the spatial variation in NEP was largely explained by MAT. The combined effects of MAT and MAP explained 79%, 62%, and 66% of the spatial variations in GEP, ER, and NEP, respectively. The GEP, ER, and NEP in different ecosystems in China exhibited 'positive coupling correlation' in their spatial patterns. Both ER and NEP were significantly correlated with GEP, with 68% of the per-unit GEP contributed to ER and 29% to NEP. MAT and MAP affected the spatial patterns of ER and NEP mainly by their direct effects on the spatial pattern of GEP.

[Characteristics of evapotranspiration in an alpine shrub meadow in Haibei, Qinghai of Northwest China].

Evapotranspiration (ET) is an important component of hydrological cycle of terrestrial ecosystem. To study the seasonal and interannual ET variation patterns of typical ecosystems is essential to better understand the water cycle process and to provide reference for the rational utilization of water resources. By using eddy covariance method, this paper studied the seasonal and interannual variation characteristics of ET and water budget in an alpine shrub meadow ecosystem in Haibei of Qinghai from 2003 to 2011. There was an obvious seasonal variation of ET in the study area in 2003-2011, with the maximum (4.4-5.7 mm x d(-1)) in the vigorous growth season (July-August) and the minimum (0.09 +/- 0.04 mm x d(-1)) in January or December. The annual ET varied greatly among the nine consecutive years, being 451.3 mm in 2010 and 681.3 mm in 2007. More than 70% of the annual ET occurred in the growth season from May to September. The average ratio of annual ET to annual precipitation was 1.06 +/- 0.17, indicating that the water budget of this ecosystem was nearly balanced at year scale, and almost all the precipitation was released into atmosphere by ET.

[Periodic fluctuation features of air temperature, precipitation, and aboveground net primary production of alpine meadow ecosystem on Qinghai-Tibetan Plateau].

With Mexican Hat function as mother function, a wavelet analysis was conducted on the periodic fluctuation features of air temperature, precipitation, and aboveground net primary production (ANPP) in the Alpine Meadow Ecosystem Research Station, Chinese Academy of Sciences from 1980 to 2007. The results showed that there was a main period of 13 years for the annual fluctuations of air temperature, precipitation, and ANPP. A secondary period of 2 years for the annual fluctuations of air temperature and ANPP had lesser influence, whereas that of 4 years for the annual fluctuation of precipitation had greater effect. Lagged correlation analysis indicated that the annual fluctuation of ANNP was mainly controlled by the air temperature in a 20 years scale and had a weak 5-9 years lag effect, but there was a less correlation between ANPP and precipitation.

[Comparison of eddy covariance and static chamber/gas chromatogram methods in measuring ecosystem respiration].

Based on the measurement of carbon flux by the methods of eddy covariance and static chamber/gas chromatogram, a comparison was made between the two methods in evaluating ecosystem respiration over winter wheat (Triticum aestivum)--summer maize (Zea mays) double cropland and Kobresia humilis alpine meadow. The results showed that under the conditions of obtained data having good quality, nighttime ecosystem respiration from eddy covariance measurement was significantly agreed with that from static chamber/gas chromatogram measurement, with the correlation coefficients ranging from 0.95 to 0.98, and the daytime ecosystem respiration from these two measurements also had a good consistency though the static chamber/gas chromatogram measurement often produced higher values. The daily mean value of ecosystem respiration was significantly different between these two measurements, but the seasonal pattern was similar. For winter wheat-summer maize double cropland, the difference of mean air temperature inside and outside the chamber was 1.8 degrees C, and the daily mean value of ecosystem respiration across the whole study period was 30.3% lower in eddy covariance measurement than in static chamber/gas chromatogram measurement; while for alpine meadow, the difference of the mean air temperature was 1.9 degrees C, and the daily mean value of ecosystem respiration was 31.4% lower in eddy covariance measurement than in static chamber/gas chromatogram measurement. The variance between the daily mean values of ecosystem respiration obtained from the two measurements was higher in growing season than in dormant season.

Spatial and temporal relationships between precipitation and ANPP of four types of grasslands in northern China.

Precipitation is considered to be the primary resource limiting terrestrial biological activity in water-limited regions. Its overriding effect on the production of grassland is complex. In this paper, field data of 48 sites (including temperate meadow steppe, temperate steppe, temperate desert steppe and alpine meadow) were gathered from 31 published papers and monographs to analyze the relationship between above-ground net primary productivity (ANPP) and precipitation by the method of regression analysis. The results indicated that there was a great difference between spatial pattern and temporal pattern by which precipitation influenced grassland ANPP. Mean annual precipitation (MAP) was the main factor determining spatial distribution of grassland ANPP (r(2) = 0.61, P < 0.01); while temporally, no significant relationship was found between the variance of ANPP and inter-annual precipitation for the four types of grassland. However, after dividing annual precipitation into monthly value and taking time lag effect into account, the study found significant relationships between ANPP and precipitation. For the temperate meadow stcppe, the key variable determining inter-annual change of ANPP was last August May precipitation (r(2) 0.47, P= 0.01); for the temperate steppe, the key variable was July precipitation (r(2)= 0.36, P= 0.02); for the temperate desert steppe, the key variable was April-June precipitation (r(2)=0.51, P< 0.01); for the alpine meadow, the key variable was last September-May precipitation (r(2)= 0.29, P < 0.05). In comparison with analogous research, the study demonstrated that the key factor determining inter-annual changes of grassland ANPP was the cumulative precipitation in certain periods of that year or the previous year.