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.

[Semen quality of the men from six districts in Chongqing].

OBJECTIVE: To investigate the quality and spatial distribution features of semen and to evaluate the reproductive health of the males in the Chongqing section of the Three-Gorge Reservoir area. METHODS: We collected semen samples by masturbation after 2 -7 days of abstinence from the men in Nan'an, Shapingba, Zhongxian, Wanzhou, Yunyang and Wushan of Chongqing, which are geographically and demographically representative of the Three-Gorge Reservoir area. We analyzed the semen quality of all the samples and evaluated the reproductive health of the men. RESULTS: The mean value of the five semen parameters of the male subjects from the six districts was within the normal range, including semen volume, sperm concentration, total sperm count, rapid progressive motile sperm, and total motile sperm. Those from Shapingba, Yunyang and Zhongxian exhibited abnormal sperm motility. According to the WHO criteria, normal value of all the semen parameters was found in less than 50% of the semen samples from the six districts, in 47% of those from Yunyang, and only 16% of those from Wanzhou. Spatial distribution maps of the semen parameters revealed significant spatial differences in seminal quality among the six districts, the highest in Yunyang, and the lowest in Wanzhou and Wushan that are located in the middle and lower reaches of the Three-Gorge Reservoir area. CONCLUSION: The mean value of semen parameters was low in a large proportion of men in the Chongqing section of the Three-Gorge Reservoir area, with spatial differences along the Changjiang river.