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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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Annual gross primary productivity (AGPP) serves as the basis for forming biomass and carbon sinks. Analysing the effects of ecosystem types on AGPP spatial variations would be beneficial for clarifying the spatial variability in AGPP, which would serve ecological management practices such as ensuring regional food security. Based on published eddy covariance measurements in China, we collected AGPP data from 128 ecosystems and analysed the effects of ecosystem types on the spatial variations in AGPP to reveal the AGPP spatial variability and its influencing factors over terrestrial ecosystems of China. The results showed that AGPP significantly differed among ecosystem types and vegetation regions, with the lowest AGPP appearing in grasslands, while different ecosystem types had comparable AGPP within the same vegetation region. The AGPP of all ecosystem types showed a decreasing latitudinal trend but slight longitudinal and altitudinal trends. Mean annual air temperature (MAT) and mean annual precipitation (MAP) were found to affect the spatial variations in AGPP over most ecosystem types, while other factors played little role. The mean annual leaf area index (LAI) and the maximum leaf area index (MLAI) were also found to affect the spatial variations in AGPP over most ecosystem types. Factors influencing the AGPP spatial variations differed among ecosystem types, but all included climatic and biotic factors. Therefore, climate inducing spatial distribution of ecosystem types and the non-zonal water supply made AGPP values and factors affecting the spatial variations in AGPP differ among ecosystem types, while different ecosystem types within the same vegetation region had comparable AGPP values. The spatial variation in AGPP over terrestrial ecosystems of China resulted from the integrated effects of climatic and biotic factors. Our study provided data support for improving the understanding of global AGPP spatial variability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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., (© 2012 Blackwell Publishing Ltd.)

Accurate quantifying the magnitudes and distributions of carbon budgets is helpful for strategies in mitigating global climate change. Based on spatial patterns of carbon fluxes (gross ecosystem productivity (GEP), ecosystem respiration (ER) and net ecosystem productivity (NEP)) and their drivers, we constructed geographical statistical assessment schemes and quantified the magnitudes of carbon fluxes in China. The optimal assessment scheme was then validated with observed eddy covariance data to analyze the spatial distributions of carbon fluxes. Using climate-based geographical statistical assessment schemes, our estimates of GEP, ER and NEP in China during 2000s were 7.51±0.51, 5.82±0.16 and 1.91±0.15PgCyr−1, corresponding to 4.29%–6.80%, 5.65%–6.06% and 9.10%–12.73% of global annual carbon fluxes, respectively. The spatial distributions of GEP, ER and NEP, generated from the optimal scheme, were similar, following a southeast–northwest decreasing gradient. The maximum values for GEP, ER and NEP were 1790, 1300 and 490gCm−2 yr−1, respectively, which occurred in Central subtropics and Southern subtropics. Climate-based geographical statistical assessment schemes provided an independent dataset for the regional carbon budget assessment, which can be deemed as the potential carbon fluxes. Meanwhile, most areas in China were potential carbon sink especially Eastern China and the largest potential carbon sink appeared in Central subtropics and Southern subtropics. [ABSTRACT FROM AUTHOR]

Abstract: As a weather element, clouds can affect CO2 exchange between terrestrial ecosystems and the atmosphere by altering environmental conditions, such as solar radiation received on the ground surface, temperature, and moisture. Based on the flux data measured at five typical ecosystems of China during mid-growing season (June–August) from 2003 to 2006, we analyzed the responses of net ecosystem exchange of carbon dioxide (NEE), light use efficiency (LUE, defined as Gross ecosystem photosynthesis (GEP)/Photosynthetically active radiation (PAR)), and water use efficiency (WUE, defined as GEP/Evapotranspiration (ET)) to the changes in cloudiness. The five ecological sites included Changbaishan temperate mixed forest (CBS), Dinghushan subtropical evergreen broad-leaved forest (DHS), Xishuangbanna tropical rainforest (XSBN), Inner Mongolia semi-arid Leymus chinensis steppe (NMG), and Haibei alpine frigid Potentilla fruticosa shrub (HB). Our analyses show that cloudy sky conditions with cloud index (k t) values between 0.4 and 0.6 increased NEE, LUE, and WUE of the ecosystems at CBS, DHS, NMG and HB from June to August. The LUE of tropical rainforest at XSBN was higher under cloudy than under clear sky conditions, but NEE and WUE did not decrease significantly under clear sky conditions from June to August. The increase in GEP with increasing diffuse radiation received by ecosystems under cloudy skies was the main reason that caused the increases in LUE and net carbon uptake in forest ecosystem at CBS, DHS, and alpine shrub ecosystem at HB, compared with clear skies. Moreover, for the ecosystem at CBS, DHS, and HB, when sky condition became from clear to cloudy, GEP increased and ET decreased with decreasing VPD, leading to the increase in WUE and NEE under cloudy sky conditions. The decrease in R e with decreasing temperature and increase in GEP with decreasing VPD under cloudy skies led to the increase in LUE, WUE, and net carbon uptake of semi-arid steppe at NMG, compared to clear skies. These different responses among the five ecosystems are attributable to the differences in canopy characteristics and water conditions. From June to August, the peaks of the k t frequency distribution in temperate ecosystems (e.g., CBS, NMG, and HB) were larger than 0.5, but they were smaller than 0.4 in subtropical/tropical forest ecosystems (e.g., DHS and XSBN). These results suggest that the pattern of cloudiness during the years from 2003 to 2006 in the five ecosystems was not the best condition for their net carbon uptake. This study highlights the importance of cloudiness factor in the prediction of net carbon absorption in the Asia monsoon region under climate change. [Copyright &y& Elsevier]