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Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally.

Global warming has significantly altered the distribution and productivity of vegetation owing to shifts in plant functional traits. However, chlorophyll adaptations—good representative of plant production—in grasslands have not been investigated on a large scale, hindering ecological predictions of climate change. Three grassland transects with a natural temperature gradient were designed in the Tibetan, Mongolian, and Loess Plateau to describe the changes in chlorophyll under different warming scenarios for 475 species. In the three plateaus, variations and distributions of species chlorophyll concentration and composition were compared. The results showed that the means of chlorophyll concentration and composition (chlorophyll a/b) increased with the mean annual temperature. Still, their distributions shifted in opposite manners: chlorophyll concentration was distributed in a broader but more differential manner, while chlorophyll composition was distributed in a narrower but more uniform manner. Compared to chlorophyll concentration, chlorophyll composition was more conservative, with a slight shift in distribution. At the regional level, the chlorophyll concentration and composition depend on the limitations of the local climate or resources. The results implied that warming might drive shifts in grassland chlorophyll distribution mainly by alternations in species composition. Large-scale chlorophyll investigations will be useful for developing prediction techniques.

The carbon budgets in terrestrial ecosystems in China are strongly coupled with climate changes. Over the past decade, China has experienced dramatic climate changes characterized by enhanced summer monsoon and decelerated warming. However, the changes in the trends of terrestrial net ecosystem production (NEP) in China under climate changes are not well documented. Here, we used three ecosystem models to simulate the spatiotemporal variations in China's NEP during 1982–2010 and quantify the contribution of the strengthened summer monsoon and warming hiatus to the NEP variations in four distinct climatic regions of the country. Our results revealed a decadal-scale shift in NEP from a downtrend of –5.95 Tg C/yr2 (reduced sink) during 1982–2000 to an uptrend of 14.22 Tg C/yr2 (enhanced sink) during 2000–10. This shift was essentially induced by the strengthened summer monsoon, which stimulated carbon uptake, and the warming hiatus, which lessened the decrease in the NEP trend. Compared to the contribution of 56.3% by the climate effect, atmospheric CO2 concentration and nitrogen deposition had relatively small contributions (8.6 and 11.3%, respectively) to the shift. In conclusion, within the context of the global-warming hiatus, the strengthening of the summer monsoon is a critical climate factor that enhances carbon uptake in China due to the asymmetric response of photosynthesis and respiration. Our study not only revealed the shift in ecosystem carbon sequestration in China in recent decades, but also provides some insight for understanding ecosystem carbon dynamics in other monsoonal areas.

Nitrogen (N) is an essential nutrient that is important for plant growth and productivity. How plants distribute N in different plant organs is aligned to the N use strategy of plants, and, in turn, provides an accurate way of assessing N storage in vegetation at the regional scale. Here, we analyzed variation in N concentrations across different organs and at different spatial scales. Specifically, we obtained 13,526 observations of plant N in China from consistent field measurements and from the published literature. The results showed that N concentration was significantly different across different plant organs (leaf, branch, trunk, and root), with more active organs having higher N. For forests, N concentration was ordered as: leaf (17.35 g kg−1) > root (6.66 g kg–1) > branch (6.47 g kg–1) > trunk (2.79 g kg–1). Similar trends were observed in grasslands, deserts, and wetlands. The N concentration of different plant organs significantly differed among different vegetation types [e.g., leaf N was ordered as: grassland (19.20 g kg–1) > desert (17.91 g kg–1) > forest (17.35 g kg–1) > wetland (14.58 g kg–1)]. Furthermore, N concentration in different plant organs significantly differed across various regions. With increasing latitude and decreasing mean annual temperature, the N concentration of different plant organs increased, to some extent. Our findings provide new insights about the differences in the N use strategy of plants across plant organs and at different spatial scales. In conclusion, the data assimilated here provide a systematic reference point for estimating vegetation N storage at different scales.

Soil stores a large amount of the terrestrial ecosystem carbon (C) and plays an important role in maintaining global C balance. However, very few studies have addressed the regional patterns of soil organic carbon (SOC) storage and the main factors influencing its changes in Chinese terrestrial ecosystems, especially using field measured data. In this study, we collected information on SOC storage in main types of ecosystems (including forest, grassland, cropland, and wetland) across 18 regions in China during the 1980s (from the Second National Soil Survey of China, SNSSC) and the 2010s (from studies published between 2004 and 2014), and evaluated its changing trends during these 30 years. The SOC storage (0–100 cm) in Chinese terrestrial ecosystems was 83.46 ± 11.89 Pg C in the 1980s and 86.50 ± 8.71 Pg C in the 2010s, and the net increase over the 30 years was 3.04 ± 1.65 Pg C, with an overall rate of 0.101 ± 0.055 Pg C yr–1. This increase was mainly observed in the topsoil (0–20 cm). Forests, grasslands, and croplands SOC storage increased 2.52 ± 0.77, 0.40 ± 0.78, and 0.07 ± 0.31 Pg C, respectively, which can be attributed to the several ecological restoration projects and agricultural practices implemented. On the other hand, SOC storage in wetlands declined 0.76 ± 0.29 Pg C, most likely because of the decrease of wetland area and SOC density. Combining these results with those of vegetation C sink (0.100 Pg C yr–1), the net C sink in Chinese terrestrial ecosystems was about 0.201 ± 0.061 Pg C yr–1, which can offset 14.85%–27.79% of the fossil fuel C emissions from the 1980s to the 2010s. These first estimates of soil C sink based on field measured data supported the premise that China’s terrestrial ecosystems have a large C sequestration potential, and further emphasized the importance of forest protection and reforestation to increase SOC storage capacity.

Chlorophyll is the molecular basis for the function of photosystems and is also a promising tool for ecological prediction. However, the large-scale patterns of chlorophyll variation in grasslands remain poorly understood. We performed consistent measurements of chlorophyll a, b, a+b, and the a:b ratio (chlorophyll a/b) for 421 species across northern hemisphere grassland transects, recorded their distributions, variations, and influencing factors, and examined their relationships with leaf nitrogen. The results showed that the distributional ranges were 0.52–28.33 (mean 5.49) mg·g−1 dry weight, 0.15–12.11 (mean 1.83) mg·g−1 dry weight, 0.67–39.29 (mean 7.32) mg·g−1 dry weight, and 1.28–7.84 (mean 3.02) for chlorophyll a, b, a+b, and a/b, respectively. The chlorophyll averages differed among regions (higher in the Loess Plateau and the Mongolian Plateau than in the Tibetan Plateau), grassland types (desert grasslands > meadow > typical grasslands), life forms, life spans, and taxonomies. In the entire northern hemisphere grassland, chlorophyll concentrations and chlorophyll a/b were negatively correlated to photosynthetically active radiation and the soil N:P ratio, and positively correlated to the mean annual temperatures. These results implied that chlorophyll in grasslands was shaped by the layered structure of grasses, distinct plateau environments, and phylogeny. The allocation patterns of leaf nitrogen to chlorophyll differed among regions and grassland types, showing that caution is required if simply relating single leaf N or chlorophyll to productivity separately. These findings enhance our understanding of chlorophyll in natural grasslands on a large scale, as well as providing information for ecological predictive models.

Extreme drought impacts ecosystem function and processes dramatically. However, a comprehensive understanding of how extreme drought affects root biomass at regional scales remains elusive. Here, we investigated the effects across six grasslands with extreme drought treatment replicated across a precipitation gradient in Inner Mongolia, China. We found the root biomass and belowground net primary productivity (BNPP) were significantly positively correlated with precipitation at the reginal scale. Extreme drought decreased the slope of this correlation in 0-10 cm and increased in 10-20 cm. Root biomass and BNPP increased by extreme drought in the four relatively arid sites and decreased in the two relatively mesic sites in 0-10 cm, and the reverse pattern showed in 10-20 cm. These shifts were driven by the response of soil moisture. Our findings suggest that including vertical responses of belowground primary productivity to extreme drought should improve models predictions of plant roots to future climate change.

Forest age serves as an essential factor in determining the accuracy of historical and future carbon (C) uptake quantifications, which is especially critical for China since the forest C stock dynamics are sensitive to the fast-growing, young-age plantations. However, a spatially explicit forest age maps with specific focus on forest plantations is not available yet. In this study, we developed a 1-km resolution age and type maps of forest plantations, and quantified their uncertainties spatially using field-measured data, national forest inventory data, digitalized forest maps, and remote sensing-based forest height maps. Simulation results showed forest plantations were 16.5 years old at national scale in 2005, which is close to the age of 16.6 years old derived from the 7th national inventory data using medium age in each forest plantation group with weighted area. Interestingly, we found that human management played an important role in forest age map reconstruction, which has not yet been considered in former studies. We also suggest that forest age and type maps should be used consistently in C stock simulations to avoid biases from mismatch information. Large uncertainty found in this study suggests further endeavors are required for improving the forest age and type maps.

Carbon use efficiency (CUE), one of the most important eco-physiological parameters, represents the capacity of plants to transform carbon into new biomass. Understanding the variations and controls of CUE is crucial for regional carbon assessment. Here, we used 15-years of continuous remote sensing data to examine the variations of CUE across broad geographic and climatic gradients in China. The results showed that the vegetation CUE was averaged to 0.54 ± 0.11 with minor interannual variation. However, the CUE greatly varied with geographic gradients and ecosystem types. Forests have a lower CUE than grasslands and croplands. Evergreen needleleaf forests have a higher CUE than other forest types. Climate factors (mean annual temperature (MAT), precipitation (MAP) and the index of water availability (IWA)) dominantly regulated the spatial variations of CUE. The CUE exhibited a linear decrease with enhanced MAT and MAP and a parabolic response to the IWA. Furthermore, the responses of CUE to environmental change varied with individual ecosystem type. In contrast, precipitation exerted strong control on CUE in grassland, while in forest and cropland, the CUE was mainly controlled by the available water. This study identifies the variations and response of CUE to environmental drivers in China, which will be valuable for the regional assessment of carbon cycling dynamics under future climate change.

Ecosystem carbon use efficiency (CUEe), one of the most important ecological indicators of ecosystem, represents the capacity of transferring carbon from atmosphere to potential carbon sink. Understanding the variation of CUEe and its controlling factors is paramount for regional carbon budget evaluation. In this study, we conducted a synthesis of 50 field measurements on CUEe to examine the variations of CUEe across China’s terrestrial ecosystems. The results showed that the CUEe values of China’s ecosystems varied from −0.44 to 0.53 with the mean value of 0.19. Grassland had a lower CUEe than forest, cropland and wetland. However, the apparent effects of vegetation types on CUEe were eliminated by accounting for the covariates of climate. Variations of CUEe were correlated with temperature (MAT), precipitation (MAP) and nitrogen deposition (Ndep) in different relationships depend on climate and Ndep condition. CUEe was increased with the augment in MAT only for wet and low Ndep ecosystems. Ndep facilitated the increase of CUEe for wet ecosystems while oppositely restrained the CUEe for dry ecosystems. The results clarify the integrated roles of climate and nitrogen deposition on variations of CUEe that would be valuable for regional ecosystem function evaluation.

The long-term stressful utilization of forests and grasslands has led to ecosystem degradation and C loss. Since the late 1970s China has launched six key national ecological restoration projects to protect its environment and restore degraded ecosystems. Here, we conducted a large-scale field investigation and a literature survey of biomass and soil C in China's forest, shrubland, and grassland ecosystems across the regions where the six projects were implemented (∼16% of the country's land area). We investigated the changes in the C stocks of these ecosystems to evaluate the contributions of the projects to the country's C sink between 2001 and 2010. Over this decade, we estimated that the total annual C sink in the project region was 132 Tg C per y (1 Tg = 1012 g), over half of which (74 Tg C per y, 56%) was attributed to the implementation of the projects. Our results demonstrate that these restoration projects have substantially contributed to CO2 mitigation in China.

Leaf carbon content (LCC) is widely used as an important parameter in estimating ecosystem carbon (C) storage, as well as for investigating the adaptation strategies of vegetation to their environment at a large scale. In this study, we used a dataset collected from forests (5119 plots) and shrublands (2564 plots) in China, 2011–2015. The plots were sampled following a consistent protocol, and we used the data to explore the spatial patterns of LCC at three scales: plot scale, eco-region scale (n = 24), and eco-region scale (n = 8). The average LCC of forests and shrublands combined was 45.3%, with the LCC of forests (45.5%) being slightly higher than that of shrublands (44.9%). Forest LCC ranged from 40.2% to 51.2% throughout the 24 eco-regions, while that of shrublands ranged from 35% to 50.1%. Forest LCC decreased with increasing latitude and longitude, whereas shrubland LCC decreased with increasing latitude, but increased with increasing longitude. The LCC increased, to some extent, with increasing temperature and precipitation. These results demonstrate the spatial patterns of LCC in the forests and shrublands at different scales based on field-measured data, providing a reference (or standard) for estimating carbon storage in vegetation at a regional scale.

Nitrogen (N) ammonification and nitrification are two primary microbial processes controlling the availability of soil ammonium (NH4+), a key nutrient for vegetative growth. The large-scale patterns of gross ammonification (GA) and gross nitrification (GN) rates represent soil microbial adaptations to different vegetative and environmental conditions. In this study, we investigated GA and GN rates in nine forest soils along a 3,700-km north–south transect in eastern China. We used 15N-labelling techniques, along with field experiments and laboratory incubations, to assess in situ and potential rates of the GA and GN. The mean in situ GA rate was 4.9 ± 0.5 mg N kg−1 day−1, whereas the mean potential rate of GA was 32.0 ± 8.6 mg N kg−1 day−1. The mean in situ GN rate was 1.7 ± 0.3 mg N kg−1 day−1 (potential GN rate: 3.2 ± 0.6 mg N kg−1 day−1). GA was significantly higher than GN along the transect, and there were high variations in GA and GN among different forests. Significant relationships were identified between meteorological factors (temperature and precipitation) and the GA and GN rates during the sampling month (August 2013). However, the mean GA rate in primary forest was significantly lower in the Huzhong (HZ), Dongling (DL), Taiyue (TY) and Dinghu (DH) sites compared with other sites, whereas with the exception of the Liangshui (LS) sampling site, the mean GN rate in primary and secondary forests showed the same trends. Significant differences in GA rates were found between primary and secondary forests at the LS and Changbai (CB) sites, and differences were detected in GN rate at the HZ, LS and Jiulian (JL) sites. Structural equation modelling analysis suggested that soil N contents, microbial biomass N pool sizes and bacterial abundance are the primary determinants of the in situ rates of GA and GN. The strong control of edaphic factors on GA and GN indicates a need to improve soil N models with more explicit representation of edaphic factors and their control on soil N transformations. A plain language summary is available for this article.

The karst critical zone is an essential component of the carbon (C) pool, constituting the global C cycle. It is referred to as one of the “residual land sink” that remains largely indeterminate. Karst area (2.2×107 km2) comprises 15% of the world’s land area, and karst area comprises 3.44×106 km2 of area in China. Due to the complexity of karst structure and its considerable heterogeneity, C sequestration rate estimations contain large inaccuracies, especially in relation to the different methods used in calculations. Therefore, we reevaluated rock weathering-related C sink estimations in China (approximately 4.74 Tg C yr–1), which we calibrated from previous studies. Additionally, we stipulated that more comprehensive research on rock-soil-biology-atmosphere continuum C migration is essential to better understand C conversion mechanisms based on uncertainty analyses of C sink estimations. Moreover, we stressed that a collective confirmation of chemical methods and simulated models through a combined research effort could at least partially eliminate such uncertainty. Furthermore, integrated C cycling research need a long-term observation of the carbon flux of multi-interfaces. The enhanced capacity of ecosystem C and soil C pools remains an effective way of increasing C sink. Karst ecosystem health and security is crucial to human social development, accordingly, it is critical that we understand thresholds or potential C sink capacities in karst critical zones now and in the future.

To explore the importance of the Eurasian steppe region (EASR) in global carbon cycling, we analyzed the spatiotemporal dynamics of the aboveground net primary productivity (ANPP) of the entire EASR from 1982 to 2013. The ANPP in the EASR was estimated from the Integrated ANPPNDVI model, which is an empirical model developed based on field‐observed ANPP and long‐term normalized difference vegetation index (NDVI) data. The optimal composite period of NDVI data was identified by considering spatial heterogeneities across the study area in the Integrated ANPPNDVI model. EASR's ANPP had apparent zonal patterns along hydrothermal gradients, and the mean annual value was 43.78 g C m−2 yr−1, which was lower than the global grasslands average. Compared to other important natural grasslands, EASR's ANPP was lower than the North American, South American, and African grasslands. The total aboveground net primary productivity (TANPP) was found to be 378.97 Tg C yr−1, which accounted for 8.18%–36.03% of the TANPP for all grasslands. In addition, EASR's TANPP was higher than that of the grasslands in North America, South America, and Africa. The EASR's TANPP increased in a fluctuating manner throughout the entire period of 1982–2013. The increasing trend was greater than that for North American and South American and was lower than that for African grasslands over the same period. The years 1995 and 2007 were two turning points at which trends in EASR's TANPP significantly changed. Our analysis demonstrated that the EASR has been playing a substantial and progressively more important role in global carbon sequestration. In addition, in the development of empirical NDVI‐based ANPP models, the early–middle growing season averaged NDVI, the middle–late growing season averaged NDVI and the annual maximum NDVI are recommended for use for semi‐humid regions, semi‐arid regions, and desert vegetation in semi‐arid regions, respectively.

How to assess the temperature sensitivity (Q10) of soil organic matter (SOM) decomposition and its regional variation with high accuracy is one of the largest uncertainties in determining the intensity and direction of the global carbon (C) cycle in response to climate change. In this study, we collected a series of soils from 22 forest sites and 30 grassland sites across China to explore regional variation in Q10 and its underlying mechanisms. We conducted a novel incubation experiment with periodically changing temperature (5–30 °C), while continuously measuring soil microbial respiration rates. The results showed that Q10 varied significantly across different ecosystems, ranging from 1.16 to 3.19 (mean 1.63). Q10 was ordered as follows: alpine grasslands (2.01) > temperate grasslands (1.81) > tropical forests (1.59) > temperate forests (1.55) > subtropical forests (1.52). The Q10 of grasslands (1.90) was significantly higher than that of forests (1.54). Furthermore, Q10 significantly increased with increasing altitude and decreased with increasing longitude. Environmental variables and substrate properties together explained 52% of total variation in Q10 across all sites. Overall, pH and soil electrical conductivity primarily explained spatial variation in Q10. The general negative relationships between Q10 and substrate quality among all ecosystem types supported the C quality temperature (CQT) hypothesis at a large scale, which indicated that soils with low quality should have higher temperature sensitivity. Furthermore, alpine grasslands, which had the highest Q10, were predicted to be more sensitive to climate change under the scenario of global warming. This article is protected by copyright. All rights reserved.

Nitrogen (N) is an essential element for plant growth and ecosystem productivity. Accurate estimation of N storage in terrestrial ecosystems is crucial because it is one of the most important N pools in the earth system; however, the spatial patterns of N storage and the main influencing factors remain unclear due to the limited data available, particularly on the N content in plant organs. Here we systematically estimated the N storage in China for the first time using 44,337 field-measured data. The total N storage was 10.43 Pg N, with 0.29 Pg N in vegetation and 10.14 Pg N in soil (0–100 cm); of these, approximately 62.07% (0.18 Pg N) of the vegetation N was stored in active plant organs (leaf and root). Furthermore, N storage in the forest, grassland, wetland, and cropland ecosystems (excluding vegetation) was 3.74, 3.15, 0.24, and 1.93 Pg N, respectively. The spatial patterns of N density were different in vegetation and soil. Redundancy analysis showed that the main factor influencing the spatial patterns in vegetation was climate, whereas the main factors influencing the spatial patterns in soil were climate and soil nutrient. Our study clarified the N pools of each subsystem (particularly for plant organs) and revealed the main influencing factors. In addition, we compiled N density datasets for different plant organs and soil depths across various climatic regions in China, which could provide parameters for regional N cycle models or serve as a reference for regional N management.

Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwide, playing an important role in global carbon cycling. Therefore, studying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppe, an important part of global grasslands, is the largest and relatively well preserved grassland in the world. In this study, we analyzed the spatial pattern of aboveground biomass (AGB), and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources (literature, global NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL), some data provided by other researchers). Our results demonstrated that: (1) as for the Eurasian steppe overall, the spatial variation in AGB exhibited significant horizontal and vertical zonality. In detail, AGB showed an inverted parabola curve with the latitude and with the elevation, while a parabola curve with the longitude. In addition, the spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregion, while horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion. (2) Of the examined environmental variables, the spatial variation of AGB was related to mean annual precipitation (MAP), mean annual temperature (MAT), mean annual solar radiation (MAR), soil Gravel content, soil pH and soil organic content (SOC) at the depth of 0–30 cm. Nevertheless, MAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions. (3) A Gaussian function was found between AGB and MAP in the Eurasian steppe overall, which was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion (elevation < 3000 m), the Mongolian Plateau steppe subregion (elevation < 3000 m) and the surface (elevation ≥ 4800 m) of the Tibetan Plateau. Nevertheless, the spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins (elevation < 4800 m) of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grassland, the Tibetan Plateau alpine grassland, etc.

The inter-annual variability (IAV) of net ecosystem productivity (NEP) may be caused by both climatic factors and ecosystem responses. In this study, we used eddy covariance (EC) measurements over three typical grasslands in China to investigate the dynamics of NEP and its two components − gross primary productivity (GPP) and ecosystem respiration (Re) and their driving forces. We found that climatic factors and ecosystem response simultaneously influence the IAV of ecosystem carbon fluxes, with a dominant effect arising from an ecosystem response. On a daily scale, carbon fluxes were driven primarily by climatic factors, but effects from an ecosystem response strengthened when the period of analysis was extended. On an annual scale, ecosystem responses weakened the effects of climatic variability on ecosystem carbon fluxes for the three grasslands. This negative feedback demonstrated that ecosystem acclimatization to climate variability can constrain the IAV of carbon fluxes induced by such variability.

The C sequestration in coastal blue carbon (Cb) ecosystems, including mangroves, seagrasses and saltmarshes, was discovered to be useful in mitigating the increasing trend of carbon dioxide (CO2) emission due to climate change. In this study, we systematically estimate traditional Cb ecosystem distribution and the associated Cb sequestration rate, and then further quantify the Cb sinks fishery contribution to Cb ecosystem due to human activity in coastal ecosystem. The results show that the global Cb ecosystem is able to store 10.8 PgC, wherein biomass and soil are able to store 2.13 and 8.68 PgC, respectively. In China, the Cb pools are 162 TgC in mangroves, 67 TgC in saltmarshes and 75 TgC in seagrass. The human activity induced global Cb sink fishery on Cb ecosystem is about 26.58–37.6 TgC yr− 1, accounting for 30.7%–43.4% of the world's traditional Cb sequestration ecosystem.The global Cb sequestration potential reaches up to 86.59 Tg yr− 1, while China can explain 1.70% of the world's total Cb sequestration. However, in China, the Cb sequestration due to human activity reaches up to 6.32–7.89 TgC yr− 1, accounting for 20.9%–23.7% of global Cb sink fishery. Therefore, it is very important to build the Cb sink fisheries measure and monitor system to scientifically valuate Cb sink fisheries and associated development potential.

Nitrogen (N) and phosphorus (P), either individually or in combination, have been demonstrated to limit biomass production in terrestrial ecosystems. Field studies have been extensively synthesized to assess global patterns of N impacts on terrestrial ecosystem processes. However, to our knowledge, no synthesis has been done so far to reveal global patterns of P impacts on terrestrial ecosystems, especially under different nitrogen (N) levels. Here, we conducted a meta-analysis of impacts of P addition, either alone or with N addition, on aboveground (AGB) and belowground biomass production (BGB), plant and soil P concentrations, and N : P ratio in terrestrial ecosystems. Overall, our meta-analysis quantitatively confirmed existing notions: (i) colimitation of N and P on biomass production and (ii) more P limitation in tropical forest than other ecosystems. More importantly, our analysis revealed new findings: (i) P limitation on biomass production was aggravated by N enrichment and (ii) plant P concentration was a better indicator of P limitation than soil P availability. Specifically, P addition increased AGB and BGB by 34% and 13%, respectively. The effect size of P addition on biomass production was larger in tropical forest than grassland, wetland, and tundra and varied with P fertilizer forms, P addition rates, or experimental durations. The P-induced increase in biomass production and plant P concentration was larger under elevated than ambient N. Our findings suggest that the global limitation of P on biomass production will become severer under increasing N fertilizer and deposition in the future.

The impact of global climate change on precipitation regimes may bring about significant consequences to the productivity of grassland ecosystems. This study reports the effects of the characteristics of precipitation events (PEC, e.g., size, frequency, interval, and seasonal distribution of precipitation events) on gross primary productivity (GPP) based on long-term measurements of net ecosystem CO2 exchange and evapotranspiration by the eddy covariance technique in a water-limited temperate steppe in Inner Mongolia and a humid but temperature-limited alpine meadow in Tibet, China. We determined that the predominant characteristics of precipitation events that affected GPP differed remarkably between these two ecosystems. The number of heavy precipitation events (>10 mm day(-1)) was the most important PEC to impact GPP in the temperate steppe. Years with more frequent heavy precipitation events favored higher GPP. However, in contrast with the case in the temperate steppe, precipitation interval was the factor that affected GPP most in the alpine meadow. GPP was higher as the precipitation intervals lengthened or their distribution shifted to fewer but longer intervals (concentrated distribution). Additionally, the mechanisms for the effects of PEC on GPP also differed between these two ecosystems. Compared with small events, heavy precipitation events recharged deeper soil layers in the temperate steppe, which was biologically more meaningful for plant transpiration (i.e., an increase in the ratio of transpiration to evapotranspiration), relief from drought stress (an increase in the duration of high soil water content), and thereby higher GPP. In contrast, mean air temperature was higher in the alpine meadow when the precipitation intervals increased or their distribution was more concentrated, leading to a longer period of higher temperature that was favorable to higher GPP. Our results imply that soil water is not the exclusive means of revealing the mechanism of precipitation affecting productivity; the corresponding changes in temperature along with precipitation events may also play a substantial role in temperature-limited grasslands. (C) 2015 Elsevier B.V. All rights reserved.

The relationship between methane (CH4) and gross primary productivity (GPP) remains elusive and the underlying mechanism is even far from clear. To explore this relationship, we continually monitored CH4 flux and CO2 flux by eddy covariance technique in an alpine meadow on the Qinghai–Tibetan Plateau, China, during June 2015–December 2017. We found a parabolic-like relationship of net CH4 flux with GPP change in both the morning and afternoon at diurnal scale. However, with similar GPP, CH4 uptake was stronger in the morning than that in the afternoon, forming an anti-clockwise hysteretic relationship between CH4 and GPP in all the three years. Meanwhile, similar hysteresis loop was also observed between CH4 flux and photosynthetically active radiation (PAR), and between PAR and air temperature (Ta) during all the three years, with stronger CH4 uptake (or lower Ta) in the morning than that in the afternoon at the same PAR. Results from our study suggested that the hysteretic relationship between CH4 flux and GPP might be mainly induced by the hysteresis between PAR and Ta. The similar hysteresis pattern between CH4 flux (or Ta) and PAR in the non-growing season further confirmed our hypothesis. The findings provide new insights into the coupling of plant photosynthetic activity and net CH4 flux and help to improve model parameterization for simulating CO2–CH4 interaction processes.

Understanding ecosystem dynamics and predicting directional changes in ecosystem in response to global changes are ongoing challenges in ecology. Here we present a framework that links productivity dynamics and ecosystem state transitions based on a spatially continuous dataset of aboveground net primary productivity (ANPP) from the temperate grassland of China. Across a regional precipitation gradient, we quantified spatial patterns in ANPP dynamics (variability, asymmetry and sensitivity to rainfall) and related these to transitions from desert to semi-arid to mesic steppe. We show that these three indices of ANPP dynamics displayed distinct spatial patterns, with peaks signalling transitions between grassland types. Thus, monitoring shifts in ANPP dynamics has the potential for predicting ecosystem state transitions in the future. Current ecosystem models fail to capture these dynamics, highlighting the need to incorporate more nuanced ecological controls of productivity in models to forecast future ecosystem shifts.

China's terrestrial ecosystems have functioned as important carbon sinks. However, previous estimates of carbon budgets have included large uncertainties owing to the limitations of sample size, multiple data sources, and inconsistent methodologies. In this study, we conducted an intensive field campaign involving 14,371 field plots to investigate all sectors of carbon stocks in China's forests, shrublands, grasslands, and croplands to better estimate the regional and national carbon pools and to explore the biogeographical patterns and potential drivers of these pools. The total carbon pool in these four ecosystems was 79.24 ± 2.42 Pg C, of which 82.9% was stored in soil (to a depth of 1 m), 16.5% in biomass, and 0.60% in litter. Forests, shrublands, grasslands, and croplands contained 30.83 ± 1.57 Pg C, 6.69 ± 0.32 Pg C, 25.40 ± 1.49 Pg C, and 16.32 ± 0.41 Pg C, respectively. When all terrestrial ecosystems are taken into account, the country's total carbon pool is 89.27 ± 1.05 Pg C. The carbon density of the forests, shrublands, and grasslands exhibited a strong correlation with climate: it decreased with increasing temperature but increased with increasing precipitation. Our analysis also suggests a significant sequestration potential of 1.9-3.4 Pg C in forest biomass in the next 10-20 years assuming no removals, mainly because of forest growth. Our results update the estimates of carbon pools in China's terrestrial ecosystems based on direct field measurements, and these estimates are essential to the validation and parameterization of carbon models in China and globally.

The scale of economic growth in China during the past three decades is unprecedented in modern human history. China is now the world’s second largest economic entity, next to the United States. However, this fast economic growth puts China’s environment under increasing stresses. China can be viewed as a massive “laboratory” with complex interactions between socioeconomic and natural systems, providing an excellent opportunity to examine how environmental changes and intensive human economic activities influence natural systems. This special feature explores the impacts of climate change and human activities on the structure and functioning of ecosystems, with emphasis on quantifying the magnitude and distribution of carbon (C) pools and C sequestration in China’s terrestrial ecosystems. We also document how species diversity, species traits, and nitrogen (N) and phosphorus (P) stoichiometry mediate ecosystem C pool and vegetation production. This overview paper introduces the background and scientific significance of the research project, presents the underlying conceptual framework, and summarizes the major findings of each paper. Reducing CO2 emissions to mitigate regional and global climate change is one of the most challenging issues facing humanity (1). At present, China has the largest annual CO2 emissions in the world ( Upper graph in Fig. 1), placing it in the spotlight of efforts to manage global C emissions and design climate-change policy. It is therefore critical to improve our understanding of the C budget and its dynamics in China to mitigate climate change at both regional and global scales. Fig. 1. Evolution in total national GDP, population, and fossil fuel CO2 emissions, together with trajectory of the national policies in China between 1945 and 2015. ( Upper ) GDP, population, and CO2 emissions. The CO2 emissions data were from Oak Ridge National Laboratory (cdiac.ess-dive.lbl.gov/), and population and GDP data from the World Bank (https://data.worldbank.org/country/). ( Lower ) National … [↵][1]1To whom correspondence may be addressed. Email: jyfang{at}urban.pku.edu.cn, fangjingyun{at}ibcas.ac.cn, or terry.chapin{at}alaska.edu. [1]: #xref-corresp-1-1

It is important to accurately estimate terrestrial ecosystem carbon (C) storage. However, the spatial patterns of C storage and the driving factors remain unclear, owing to lack of data. Here, we collected data from literature published between 2004 and 2014 on C storage in China’s terrestrial ecosystems, to explore variation in C storage across different ecosystems and evaluate factors that influence them. We estimated that total C storage was 99.15 ± 8.71 PgC, with 14.60 ± 3.24 PgC in vegetation C (Veg-C) and 84.55 ± 8.09 PgC in soil organic C (SOC) storage. Furthermore, C storage in forest, grassland, wetland, shrub, and cropland ecosystems (excluding vegetation) was 34.08 ± 5.43, 25.69 ± 4.71, 3.62 ± 0.80, 7.42 ± 1.92, and 15.17 ± 2.20 PgC, respectively. In addition to soil nutrients and texture, climate was the main factor regulating the spatial patterns of C storage. Climate influenced the spatial patterns of Veg-C and SOC density via different approaches, Veg-C was mainly positively influenced by mean annual precipitation (MAP), whereas SOC was negatively dependent on mean annual temperature (MAT). This systematic estimate of C storage in China provides new insights about how climate constrains C sequestration, demonstrating the contrasting effects of MAP and MAT on Veg-C and SOC; thus, these parameters should be incorporated into future land management and C sequestration strategies.

It is important to accurately evaluate ecosystem respiration (RE) in the alpine grasslands of the Tibetan Plateau and the temperate grasslands of the Inner Mongolian Plateau, as it serves as a sensitivity indicator of regional and global carbon cycles. Here, we combined flux measurements taken between 2003 and 2013 from 16 grassland sites across northern China and the corresponding MODIS land surface temperature (LST), enhanced vegetation index (EVI), and land surface water index (LSWI) to build a satellite-based model to estimate RE at a regional scale. First, the dependencies of both spatial and temporal variations of RE on these biotic and climatic factors were examined explicitly. We found that plant productivity and moisture, but not temperature, can best explain the spatial pattern of RE in northern China’s grasslands; while temperature plays a major role in regulating the temporal variability of RE in the alpine grasslands, and moisture is equally as important as temperature in the temperate grasslands. However, the moisture effect on RE and the explicit representation of spatial variation process are often lacking in most of the existing satellite-based RE models. On this basis, we developed a model by comprehensively considering moisture, temperature, and productivity effects on both temporal and spatial processes of RE, and then, we evaluated the model performance. Our results showed that the model well explained the observed RE in both the alpine (R2 = 0.79, RMSE = 0.77 g C m−2 day−1) and temperate grasslands (R2 = 0.75, RMSE = 0.60 g C m−2 day−1). The inclusion of the LSWI as the water-limiting factor substantially improved the model performance in arid and semi-arid ecosystems, and the spatialized basal respiration rate as an indicator for spatial variation largely determined the regional pattern of RE. Finally, the model accurately reproduced the seasonal and inter-annual variations and spatial variability of RE, and it avoided overestimating RE in water-limited regions compared to the popular process-based model. These findings provide a better understanding of the biotic and climatic controls over spatiotemporal patterns of RE for two typical grasslands and a new alternative up-scaling method for large-scale RE evaluation in grassland ecosystems.

Changes in the sizes of precipitation events in the context of global climate change may have profound impacts on ecosystem productivity in arid and semiarid grasslands. However, we still have little knowledge about to what extent grassland productivity will respond to an individual precipitation event. In this study, we quantified the duration, the maximum, and the time-integrated amount of the response of daily gross primary productivity (GPP) to an individual precipitation event and their variations with different sizes of precipitation events in a typical temperate steppe in Inner Mongolia, China. Results showed that the duration of GPP-response (τR) and the maximum absolute GPP-response (GPPmax) increased linearly with the sizes of precipitation events (Pes), driving a corresponding increase in time-integrated amount of the GPP-response (GPPtotal) because variations of GPPtotal were largely explained by τR and GPPmax. The relative contributions of these two parameters to GPPtotal were strongly Pes-dependent. The GPPmax contributed more to the variations of GPPtotal when Pes was relatively small (

Ecosystem respiration (R-e) is rarely quantified from remote sensing data because satellite technique is incapable of observing the key processes associated with soil respiration. In this study, we develop a Remote Sensing Model for R-e (ReRSM) by assuming that one part of R-e is derived from current photosynthate with the respiratory rate coupling closely with gross primary production (GPP), and the other part of R-e is derived from reserved ecosystem organic matter (including plant biomass, plant residues and soil organic matter) with the respiratory rate responding strongly to temperature change. The ReRSM is solely driven by the Enhanced Vegetation Index (EVI), the Land Surface Water Index (LSWI) and the Land Surface Temperature (LST) from MODIS data. Multi-year eddy CO2 flux data of five vegetation types in Northern China and the Tibetan Plateau (including temperate mixed forest, temperate steppe, alpine shrubland, alpine marsh and alpine meadow-steppe) were used for model parameterization and validation. In most cases, the simulated R-e agreed well with the observed R-e in terms of seasonal and interannual variation irrespective of vegetation types. The ReRSM could explain approximately 93% of the variation in the observed R-e across five vegetation types, with the root mean square error (RMSE) of 0.04 mol Cm-2 d(-1) and the modeling efficiency (EF) of 0.93. Model comparison showed that the performance of the ReRSM was comparable with that of the RECO in the studied five vegetation types, while the former had much fewer parameters than the latter. The ReRSM parameters showed good linear relationships with the mean annual satellite indices. With these linear functions, the ReRSM could explain approximately 90% of the variation in the observed R-e across five vegetation types, with the RMSE of 0.05 mol Cm-2 d(-1) and the EF of 0.89. These analyses indicated that the ReRSM is a simple and alternative approach in Re estimation and has the potential of estimating spatial R-e. However, the performance of ReRSM in other vegetation types or regions still needs a further study. (C) 2015 Elsevier B.V. All rights reserved.

Both the amounts of data describing the site-scale carbon flux at a high temporal and spatial resolution collected in China and the number of eddy covariance flux towers have been increasing during the last decade. To correctly upscale these fluxes to the regional and global level, the representativeness of the current network of flux towers must be known. The present study quantifies the representativeness of the flux network for the regional carbon exchange. This analysis combined the total solar radiation, air temperature, vapor pressure and the enhanced vegetation index to indicate the environmental characteristics of each 1-km pixel cell and flux tower. Next, the Euclidean distance from each pixel to the tower was calculated to determine the representativeness of the existing flux towers. To improve the regional representativeness, additional tower locations were pinpointed by identifying and clustering the underrepresented areas. The existing network of flux towers performed well in representing the environmental conditions of the middle and the northeastern portions of China. The well-represented areas covered 60.9% of the total areas. The towers in croplands and grasslands represented the vegetation types well, but the wetlands and barelands were poorly represented. The representativeness of the flux network increased with the addition of nine towers located in forests, grasslands, wetlands and barelands. The representativeness of 27.5% of the land areas improved. In addition, the well-represented areas were enlarged by 15.2%. Substantial gains in representation were achieved by adding new towers on the Tibet Plateau. The representativeness of the northwest and southwest was improved less significantly, suggesting that more towers are required to capture certain ecosystem behaviors.

Aims The plasticity of ecosystem responses could buffer and postpone the effects of climates on ecosystem carbon fluxes, but this lagged effect is often ignored. In this study, we used carbon flux data collected from three typical grassland ecosystems in China, including a temperate semiarid steppe in Inner Mongolia (Neimeng site, NM), an alpine shrub-meadow in Qinghai (Haibei site, HB) and an alpine meadow steppe in Tibet (Dangxiong site, DX), to examine the time lagged effects of environmental factors on CO2 exchange. Methods Eddy covariance data were collected from three typical Chinese grasslands. In linking carbon fluxes with climatic factors, we used their averages or cumulative values within each 12-month period and we called them 'yearly' statistics in this study. To investigate the lagged effects of the climatic factors on the carbon fluxes, the climatic 'yearly' statistics were kept still and the 'yearly' statistics of the carbon fluxes were shifted backward 1 month at a time. Important Findings Soil moisture and precipitation was the main factor driving the annual variations of carbon fluxes at the alpine HB and DX, respectively, while the NM site was under a synthetic impact of each climatic factor. The time lagged effect analysis showed that temperature had several months, even half a year lag effects on CO2 exchange at the three studied sites, while moisture's effects were mostly exhibited as an immediate manner, except at NM. In general, the lagged climatic effects were relatively weak for the alpine ecosystem. Our results implied that it might be months or even 1 year before the variations of ecosystem carbon fluxes are adjusted to the current climate, so such lag effects could be resistant to more frequent climate extremes and should be a critical component to be considered in evaluating ecosystem stability. An improved knowledge on the lag effects could advance our understanding on the driving mechanisms of climate change effects on ecosystem carbon fluxes.

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.

Ecosystem restoration requires considering both above‐ground biomass (AGB) and soils, and the latter is even more essential due to the importance and restoration difficulty of soil organic matter (SOM). Remote sensing studies have shown that AGB has recovered in the grasslands of northern China, but the recovery of soil organic carbon (SOC) or SOM is still unclear. Here, based on the published data between the 1980s and 2014, we used the variation in carbon (C) density observed in the vegetation and soils of four regions across northern China as integrative indicator to explore grassland restoration. Overall, northern Chinese grasslands were a weak carbon source (−14 Tg C), although C density in AGB and below‐ground biomass increased on average by 0.019 and 0.224 kg C/m2, respectively, during the period considered in the present study. Unexpectedly, SOC density in the 0–20 cm soil layer decreased by 0.193 kg C/m2 on average, and all regions registered a decrease in SOC, although values differed among them. Our findings were consistent with previous evaluations using remote sensing and with the idea that vegetation in northern China has been restored. However, SOC has not been restored, and given its importance for sustaining nutrient supply and water conservation, as well as the high difficulty of SOC restoration, grassland restoration in northern China is still far from being achieved.

Nitrogen (N) has great ecological importance, but the biogeographic pattern across forest biomes in China has only recently been explored. Here we conducted a systematic census of leaf C and N following the same protocol to explore the variations of leaf traits, and their possible responses to plant functional types (PFTs) and environmental factors. Results showed that leaf traits varied substantially across biomes, and the relationships of PFTs to climatic factors were stronger than those of PFTs versus soil nutrient proxies, indicating that plant species composition might be a better predictor of plant species distribution with climate than leaf traits. Soil nutrient proxies explained more variation of leaf traits than climate, which demonstrates that leaf traits reflect important aspects of plant responses to soil nutrients. Importantly, partial general linear models analyses found that PFTs showed the greatest direct influence for leaf traits, and climate and soil affected leaf traits mainly through the change in plant species composition rather than having direct impacts. Hence, we concluded that leaf traits were largely controlled by PFTs rather than climate or soil at the biome scale. The results favored the species composition hypothesis, indicating that leaf nutrient concentration is mainly determined by PFTs.

It is widely accepted that excess nutrients change the dissolved inorganic carbon (DIC) system, which drives air–sea carbon dioxide (CO2) exchanges, so the changes in the DIC system will then affect the oceans’ carbon (C) biogeochemistry cycle. This study explores the impact of external nutrient input from 2006 to 2011 on the DIC system and air–sea CO2 exchanges in four largest coastal seas in China. The result demonstrates that external nutrient input significantly facilitates the biological uptake of DIC and promotes air–sea CO2 fluxes in coastal waters. The C sink caused by nitrogen (N) and phosphorus (P) input for the Bohai Sea, the Yellow Sea, the East China Sea, and the South China Sea account for 46, 45, 11, and 59 % of the total C sink, respectively. The excess nutrient input significantly changes the DIC system and C biogeochemistry cycle process in China Ocean. Up to a certain point, these effects are positive in increasing DIC levels and enhancing air–sea CO2 exchanges. However, the DIC levels may decrease if the nutrient increase is greater than the capacity of the oceanic C system. In addition, the other impact factors, including sea level, winds, water, and air temperatures, and various human activities, such as agriculture, industry, and domestic discharge, also affect N and P transport, air–sea CO2 fluxes, and C biogeochemistry cycles.

Understanding the climatic and biotic controls of interannual variability (IAV) in net ecosystem exchange (NEE) is important for projecting future uptake of CO2 in terrestrial ecosystems. In this study, a statistical modeling approach was used to partition climatic and biotic effects on the IAV in NEE, gross primary productivity (GPP) and ecosystem respiration (RE) at a subtropical evergreen plantation in China (QYZ), a deciduous forest (MOZ), and a grassland (DK1) in the USA. The climatic effects in the study are defined as the interannual anomalies in carbon (C) fluxes directly caused by climatic variations, whereas the biotic effects are those caused by the IAV in photosynthetic and respiratory traits. The results showed that the contribution of biotic effects to the IAV in NEE increased significantly as the temporal scale got longer from daily to annual scales. At the annual scale, the contribution of biotic effects to the IAV in NEE was 47, 69, and 77% at QYZ, MOZ, and DK1, respectively. However, the IAV in NEE was mainly controlled by GPP at QYZ, and by RE at DK1, whereas the contributions of GPP and RE to the IAV in NEE were similar at MOZ, indicating different mechanisms regulating the IAV in NEE among ecosystems. Interestingly, there was a strong negative correlation between the climatic and biotic effects at the annual scale from 2003 to 2009 at QYZ (r 2 = 0.80, P

Accurate quantification of the spatio-temporal variation of gross primary production (GPP) for terrestrial ecosystems is significant for ecosystem management and the study of the global carbon cycle. In this study, we propose a MODIS-based Photosynthetic Capacity Model (PCM) to estimate GPP in Northern China and the Tibetan Plateau. The PCM follows the logic of the light use efficiency model and is only driven by the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI). Multi-year eddy CO2 flux data from five vegetation types in North China (temperate mixed forest, temperate steppe) and the Tibetan Plateau (alpine shrubland, alpine marsh and alpine meadow-steppe) were used for model parameterization and validation. In most cases, the seasonal and interannual variation in the simulated GPP agreed well with the observed GPP. Model comparisons showed that the predictive accuracy of the PCM was higher than that of the MODIS GPP products and was comparable with that of the Vegetation Photosynthesis Model (VPM) and the potential PAR-based GPP models. The model parameter (PCmax) of the PCM represents the maximum photosynthetic capacity, which showed a good linear relationship with the mean annual nighttime Land Surface Temperature (LSTan). With this linear function, the PCM-simulated GPP can explain approximately 93% of the variation in the flux-observed GPP across all five vegetation types. These analyses demonstrated the potential of the PCM as an alternative tool for regional GPP estimation.

Temperate- and high-latitude forests have been shown to contribute a carbon sink in the Northern Hemisphere, but fewer studies have addressed the carbon balance of the subtropical forests. In the present study, we integrated eddy covariance observations established in the 1990s and 2000s to show that East Asian monsoon subtropical forests between 20 degrees N and 40 degrees N represent an average net ecosystem productivity (NEP) of 362 +/- 39 g C m(-2) yr(-1) (mean +/- 1 SE). This average forest NEP value is higher than that of Asian tropical and temperate forests and is also higher than that of forests at the same latitudes in Europe-Africa and North America. East Asian monsoon subtropical forests have comparable NEP to that of subtropical forests of the southeastern United States and intensively managed Western European forests. The total NEP of East Asian monsoon subtropical forests was estimated to be 0.72 +/- 0.08 Pg C yr(-1), which accounts for 8% of the global forest NEP. This result indicates that the role of subtropical forests in the current global carbon cycle cannot be ignored and that the regional distributions of the Northern Hemisphere's terrestrial carbon sinks are needed to be reevaluated. The young stand ages and high nitrogen deposition, coupled with sufficient and synchronous water and heat availability, may be the primary reasons for the high NEP of this region, and further studies are needed to quantify the contribution of each underlying factor.

Old-growth forests can accumulate carbon. However, what controls the rate of net carbon accumulation in those old-growth forests is still poorly understood. Using eddy flux measurements from two old-growth evergreen broadleaf forests (subtropical forest and tropical forest) in southern China, we compared the seasonal and inter-annual variations in the carbon fluxes of those two forests and quantified the major drivers for these temporal variations. The measured flux data showed that the annual net carbon uptake of the subtropical forest was generally much larger than that for the tropical forest. The mean net ecosystem exchange (NEE) over 6 years was -397 +/- 94 g C m(-2) yr(-1) for the subtropical forest and -166 +/- 49 g Cm-2 yr(-1) for the tropical forest with different seasonal variations. The subtropical forest was a carbon sink for most months in a year, while the tropical forest was a carbon source in wet seasons (positive NEE) and a carbon sink in dry seasons (negative NEE). Both forests were stronger carbon sink in dry years, because of much larger reduction in ER than in wet years. At the seasonal scale, GPP in wet seasons was 37.1% higher than that for dry seasons in the subtropical forest, and was only 12.4% higher in the tropical forest. The amplitude of seasonal GPP variation in the tropical forest was much weaker than in the subtropical forest, but the amplitude of the seasonal variation in ER was much larger than in the subtropical forest. The seasonal variation in NEE was largely driven by the variation in monthly ER of the tropical forest, and by both seasonal variations in monthly GPP and ER of the subtropical forest. At inter-annual scale, annual NEE varied tightly with annual rainfall from year to year. Therefore annual rainfall was suggested a fundamental driver of annual carbon sequestration in the subtropical and tropical forests in southern China. (C) 2013 Elsevier B.V. All rights reserved.

Carbon exchange between terrestrial ecosystems and the atmosphere is one of the most important processes in the global carbon cycle. Understanding the spatial variation and controlling factors of carbon exchange fluxes is helpful for accurately predicting and evaluating the global carbon budget. In this study, we quantified the carbon exchange fluxes of different terrestrial ecosystems in the Asian region, and analyzed their spatial variation and controlling factors based on long-term observation data from ChinaFLUX (19 sites) and published data from AsiaFlux (37 sites) and 32 other sites in Asia. The results indicated that the majority of Asian terrestrial ecosystems are currently large carbon sinks. The average net ecosystem production (NEP) values were 325+/-187, 274+/-207, 236+/-260, 89+/-134g C m(-2) yr(-1) in cropland, forest, wetland and grassland ecosystems, respectively. The spatial variation of gross primary production (GPP) and ecosystem respiration (Re) were mainly controlled by the mean annual temperature (MAT) and the mean annual precipitation (MAP) in the Asian region. There was a clear linear relationship between GPP and MAT, and a strong sigmoid relationship between GPP and MAP. Re was exponentially related to MAT and linearly related to MAP. Interestingly, those response modes were consistent across different ecosystem types. The different responses of GPP and Re to MAT and MAP determined the spatial variation of NEP. The combined effects of MAT and MAP contributed 85%, 81% and 36% to the spatial variations of GPP, Re and NEP, respectively. Our findings confirmed that the spatial variation of carbon exchange fluxes was mainly controlled by climatic factors, which further strongly supports the use of the climate-driven theory in the Asian region. (C) 2013 Elsevier B.V. All rights reserved.

AimTo understand: (1) how temperature, precipitation and stand age control the above-ground biomass carbon density (BCDa) of mature forests and its macroecology patterns across latitudes; (2) the age threshold for old-growth forests at a global scale. LocationGlobal forests. MethodsWe compiled a database (897 sites) of mature forests between 80 and 1200 years old. The site data include latitude, longitude, mean annual temperature, mean annual precipitation, forest type, stand age, BCDa, living biomass (above- and below-ground biomass) carbon density and total (living plus dead) biomass carbon density. Based on the site data, we performed regression analyses to show how BCDa changes with climate and forest stand age. ResultsAt a global scale, the highest BCDa of mature forests occurred mainly in the mid-latitude regions where mean annual temperatures were 8-10 degrees C and mean annual precipitation was between 1000 and 2500mm. The average BCDa of forests in the stand age class of 450-500 years was higher than those in the other stand age classes. For forests between 80 and 450 years old, which form the majority of mature forests, carbon accumulation was faster in dead biomass than in living biomass. Main conclusionsThe highest BCDa of mature forests is located in mid-latitude regions with cool temperatures and moderate precipitation. The age threshold for old-growth forests at a global scale should be 450-500 years, which is much older than the previously documented age of 100-200 years. This older age threshold for old-growth forests is probably one of the primary reasons why recent works have concluded that old-growth forests are still carbon sinks.

It is critical to study how different forest management practices affect forest carbon sequestration under global climate change regime. Previous researches focused on the stand-level forest carbon sequestration with rare investigation of forest carbon stocks influenced by forest management practices and climate change at regional scale. In this study, a general integrative approach was used to simulate spatial and temporal variations of woody biomass and harvested biomass of forest in China during the 21st century under different scenarios of climate and CO2 concentration changes and management tasks by coupling Integrated Terrestrial Ecosystem Carbon budget (InTEC) model with Global Forest Model (G4M). The results showed that forest management practices have more predominant effects on forest stem stocking biomass than climate and CO2 concentration change. Meanwhile, the concurrent future changes in climate and CO2 concentration will enhance the amounts of stem stocking biomass in forests of China by 12%–23% during 2001–2100 relative to that with climate change only. The task for maximizing stem stocking biomass will dramatically enhance the stem stocking biomass from 2001–2100, while the task for maximum average increment will result in an increment of stem stocking biomass before 2050 then decline. The difference of woody biomass responding to forest management tasks was owing to the current age structure of forests in China. Meanwhile, the sensitivity of long-term woody biomass to management practices for different forest types (coniferous forest, mixed forest and deciduous forest) under changing climate and CO2 concentration was also analyzed. In addition, longer rotation length under future climate change and rising CO2 concentration scenario will dramatically increase the woody biomass of China during 2001–2100. Therefore, our estimation indicated that taking the role of forest management in the carbon cycle into the consideration at regional or national level is very important to project the forest carbon sequestration under future climate change and rising atmospheric CO2 concentration.

Our Earth is facing the challenge of accelerating climate change, which imposes a great threat to biodiversity. Many published studies suggest that climate warming may cause a dramatic decline in biodiversity, especially in colder and drier regions. In this study, we investigated the effects of temperature, precipitation and a normalized difference vegetation index on biodiversity indices of rodent communities in the current or previous year for both detrended and nondetrended data in semi-arid grassland of Inner Mongolia during 1982-2006. Our results demonstrate that temperature showed predominantly positive effects on the biodiversity of small rodents; precipitation showed both positive and negative effects; a normalized difference vegetation index showed positive effects; and cross-correlation function values between rodent abundance and temperature were negatively correlated with rodent abundance. Our results suggest that recent climate warming increased the biodiversity of small rodents by providing more benefits to population growth of rare or less abundant species than that of more abundant species in Inner Mongolia grassland, which does not support the popular view that global warming would decrease biodiversity in colder and drier regions. We hypothesized that higher temperatures might benefit rare or less abundant species (with smaller populations and more folivorous diets) by reducing the probability of local extinction and/or by increasing herbaceous food resources.

Prior to ~1880 AD locust swarms periodically raged across both the North American Plains (NAP) and East Asian Plains (EAP). After this date, locust outbreaks almost never recurred on the NAP but have continued to cause problems on the EAP. The large quantities of pesticides used in the major agriculture regions of the NAP in the late 1870s have been suggested as a possible reason for the disappearance of locust outbreaks in this area. Extensive applications of modern, i.e. more effective, chemical pesticides were also used in the granary regions of the EAP in the 1950s in an effort to reduce pest outbreaks. However, locust swarms returned again in many areas of China in the 1960s. Therefore, locust extinction on the NAP still remains a puzzle. Frequent locust outbreaks on the EAP over the past 130 yr may offer clues to the key factors that control the disappearance of locust outbreaks on the NAP. This study analysed the climate extremes and monthly temperature–precipitation combinations for the NAP and EAP, and found that differences in the frequencies of these climate combinations resulted in the contrasting locust fates in the two regions: restricting locust outbreaks in the NAP but inducing such events in the EAP. Validation shows that severe EAP locust outbreak years were coincidental with extreme climate-combination years. Therefore, we suggest that changes in frequency, extremes and trends in climate can explain why the fate of locust outbreaks in the EAP was different from that in the NAP. The results also suggest that, with present global warming trends, precautionary measures should be taken to make sure other similar pest infestations do not occur in either region.

A number of continuous eddy covariance measurements and long-term biomass inventories had proved that old-growth forests are carbon sinks worldwide. The present study estimated the net ecosystem productivity (NEP) for an old-growth subtropical forest at the Dinghushan Biosphere Reserve in South China to investigate the temporal pattern of carbon sequestration, both seasonally and annually. The measured NEP over 7years (from 2003 to 2009) showed that this forest was a net carbon sink, ranging from 230 (in 2008) to 489gCm-2year-1 (in 2004). The greatest value of NEP was found in the driest year and the lowest value in the wettest year during the study period. Within a year, NEP during the dry season was about 81.4% higher than for the wet season. Accordingly, the dry season at seasonal scale and dry years at interannual scale are key periods for carbon sequestration in this forest. The strong seasonality of ecosystem or soil respiration (ER or SR) compared with gross primary productivity (GPP) resulted in substantial amounts of carbon being sequestered during dry seasons. A decrease of GPP and an increase of ER or SR demonstrated the lower carbon uptake in rainy years. From this study, we conclude that GPP and living biomass carbon increment are not overriding parameters controlling NEP. The variations in ER or SR driven by the rainfall scheme were the dominant factor determining the magnitude of NEP in this forest in South China. 2012 The Japanese Forest Society and Springer.

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.

Predicted future shifts in the magnitude and frequency (larger but fewer) of precipitation events and enhanced nitrogen (N) deposition may interact to affect grassland productivity, but the effects of N enrichment on the productivity response to individual precipitation events remain unclear. In this study, we quantified the effects of N addition on the response patterns of gross primary productivity (GPP) to individual precipitation events of different sizes (Psize) in a temperate grassland in China. The results showed that N enrichment significantly increased the time-integrated amount of GPP in response to an individual precipitation event (GPPtotal) and the N-induced stimulation of GPP increased with increasing Psize. N enrichment rarely affected the duration of the GPP response, but it significantly stimulated the maximum absolute GPP response. Higher foliar N content might play an important role in the N-induced stimulation of GPP. GPPtotal in both the N-addition and control treatments increased linearly with Psize with similar Psize intercepts (approximately 5 mm, indicating a similar lower Psize threshold to stimulate the GPP response) but had a steeper slope under N addition. Our work indicates that the projected larger precipitation events will stimulate grassland productivity and this stimulation might be amplified by increasing N deposition.