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Carbon (C) and nitrogen (N) are the primary elements involved in the growth and development of plants. The C:N ratio is an indicator of nitrogen use efficiency (NUE) and an input parameter for some ecological and ecosystem models. However, knowledge remains limited about the convergent or divergent variation in the C:N ratios among different plant organs (e.g., leaf, branch, trunk, and root) and how evolution and environment affect the coefficient shifts. Using systematic measurements of the leaf-branch-trunk-root of 2,139 species from tropical to cold-temperate forests, we comprehensively evaluated variation in C:N ratio in different organs in different taxa and forest types. The ratios showed convergence in the direction of change but divergence in the rate of change. Plants evolved toward lower C:N ratios in the leaf and branch, with N playing a more important role than C. The C:N ratio of plant organs (except for the leaf) was constrained by phylogeny, but not strongly. Both the change of C:N during evolution and its spatial variation (lower C:N ratio at midlatitudes) help develop the adaptive growth hypothesis. That is, plants with a higher C:N ratio promote NUE under strong N-limited conditions to ensure survival priority, whereas plants with a lower C:N ratio under less N-limited environments benefit growth priority. In nature, larger proportion of species with a high C:N ratio enabled communities to inhabit more N-limited conditions. Our results provide new insights on the evolution and drivers of C:N ratio among different plant organs, as well as provide a quantitative basis to optimize land surface process models.

Nitrogen (N) deposition is a component of global change that has considerable impact on belowground carbon (C) dynamics. Plant growth stimulation and alterations of fungal community composition and functions are the main mechanisms driving soil C gains following N deposition in N-limited temperate forests. In N-rich tropical forests, however, N deposition generally has minor effects on plant growth; consequently, C storage in soil may strongly depend on the microbial processes that drive litter and soil organic matter decomposition. Here, we investigated how microbial functions in old-growth tropical forest soil responded to 13 years of N addition at four rates: 0 (Control), 50 (Low-N), 100 (Medium-N), and 150 (High-N) kg N ha-1 year-1 . Soil organic carbon (SOC) content increased under High-N, corresponding to a 33% decrease in CO2 efflux, and reductions in relative abundances of bacteria as well as genes responsible for cellulose and chitin degradation. A 113% increase in N2 O emission was positively correlated with soil acidification and an increase in the relative abundances of denitrification genes (narG and norB). Soil acidification induced by N addition decreased available P concentrations, and was associated with reductions in the relative abundance of phytase. The decreased relative abundance of bacteria and key functional gene groups for C degradation were related to slower SOC decomposition, indicating the key mechanisms driving SOC accumulation in the tropical forest soil subjected to High-N addition. However, changes in microbial functional groups associated with N and P cycling led to coincidentally large increases in N2 O emissions, and exacerbated soil P deficiency. These two factors partially offset the perceived beneficial effects of N addition on SOC storage in tropical forest soils. These findings suggest a potential to incorporate microbial community and functions into Earth system models considering their effects on greenhouse gas emission, biogeochemical processes, and biodiversity of tropical ecosystems.

It is critical to accurately estimate carbon (C) turnover time as it dominates the uncertainty in ecosystem C sinks and their response to future climate change. In the absence of direct observations of ecosystem C losses, C turnover times are commonly estimated under the steady state assumption (SSA), which has been applied across a large range of temporal and spatial scales including many at which the validity of the assumption is likely to be violated. However, the errors associated with improperly applying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestrations have yet to be fully quantified. Here, we developed a novel model‐data fusion framework and systematically analyzed the SSA‐induced biases using time‐series data collected from 10 permanent forest plots in the eastern China monsoon region. The results showed that (a) the SSA significantly underestimated mean turnover times (MTTs) by 29%, thereby leading to a 4.83‐fold underestimation of the net ecosystem productivity (NEP) in these forest ecosystems, a major C sink globally; (b) the SSA‐induced bias in MTT and NEP correlates negatively with forest age, which provides a significant caveat for applying the SSA to young‐aged ecosystems; and (c) the sensitivity of MTT to temperature and precipitation was 22% and 42% lower, respectively, under the SSA. Thus, under the expected climate change, spatiotemporal changes in MTT are likely to be underestimated, thereby resulting in large errors in the variability of predicted global NEP. With the development of observation technology and the accumulation of spatiotemporal data, we suggest estimating MTTs at the disequilibrium state via long‐term data assimilation, thereby effectively reducing the uncertainty in ecosystem C sequestration estimations and providing a better understanding of regional or global C cycle dynamics and C‐climate feedback.

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.

Forests store a large part of the terrestrial vegetation carbon (C) and have high C sequestration potential. Here, we developed a new forest C sequestration (FCS) model based on the secondary succession theory, to estimate vegetation C sequestration capacity in China's forest vegetation. The model used the field measurement data of 3161 forest plots and three future climate scenarios. The results showed that logistic equations provided a good fit for vegetation biomass with forest age in natural and planted forests. The FCS model has been verified with forest biomass data, and model uncertainty is discussed. The increment of vegetation C storage in China's forest vegetation from 2010 to 2050 was estimated as 13.92 Pg C, while the average vegetation C sequestration rate was 0.34 Pg C yr-1 with a 95% confidence interval of 0.28-0.42 Pg C yr-1 , which differed significantly between forest types. The largest contributor to the increment was deciduous broadleaf forest (37.8%), while the smallest was deciduous needleleaf forest (2.7%). The vegetation C sequestration rate might reach its maximum around 2020, although vegetation C storage increases continually. It is estimated that vegetation C sequestration might offset 6-8% of China's future emissions. Furthermore, there was a significant negative relationship between vegetation C sequestration rate and C emission rate in different provinces of China, suggesting that developed provinces might need to compensate for undeveloped provinces through C trade. Our findings will provide valuable guidelines to policymakers for designing afforestation strategies and forest C trade in China.

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.

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.

With a pace of about twice the observed rate of global warming, the temperature on the Qinghai-Tibetan Plateau (Earth's 'third pole') has increased by 0.2 °C per decade over the past 50 years, which results in significant permafrost thawing and glacier retreat. Our review suggested that warming enhanced net primary production and soil respiration, decreased methane (CH(4)) emissions from wetlands and increased CH(4) consumption of meadows, but might increase CH(4) emissions from lakes. Warming-induced permafrost thawing and glaciers melting would also result in substantial emission of old carbon dioxide (CO(2)) and CH(4). Nitrous oxide (N(2)O) emission was not stimulated by warming itself, but might be slightly enhanced by wetting. However, there are many uncertainties in such biogeochemical cycles under climate change. Human activities (e.g. grazing, land cover changes) further modified the biogeochemical cycles and amplified such uncertainties on the plateau. If the projected warming and wetting continues, the future biogeochemical cycles will be more complicated. So facing research in this field is an ongoing challenge of integrating field observations with process-based ecosystem models to predict the impacts of future climate change and human activities at various temporal and spatial scales. To reduce the uncertainties and to improve the precision of the predictions of the impacts of climate change and human activities on biogeochemical cycles, efforts should focus on conducting more field observation studies, integrating data within improved models, and developing new knowledge about coupling among carbon, nitrogen, and phosphorus biogeochemical cycles as well as about the role of microbes in these cycles.

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.

Sources of methane (CH4 ) become highly variable for countries undergoing a heightened period of development due to both human activity and climate change. An urgent need therefore exists to budget key sources of CH4 , such as wetlands (rice paddies and natural wetlands) and lakes (including reservoirs and ponds), which are sensitive to these changes. For this study, references in relation to CH4 emissions from rice paddies, natural wetlands, and lakes in China were first reviewed and then reestimated based on the review itself. Total emissions from the three CH4 sources were 11.25 Tg CH4 yr(-1) (ranging from 7.98 to 15.16 Tg CH4 yr(-1) ). Among the emissions, 8.11 Tg CH4 yr(-1) (ranging from 5.20 to 11.36 Tg CH4 yr(-1) ) derived from rice paddies, 2.69 Tg CH4 yr(-1) (ranging from 2.46 to 3.20 Tg CH4 yr(-1) ) from natural wetlands, and 0.46 Tg CH4 yr(-1) (ranging from 0.33 to 0.59 Tg CH4 yr(-1) ) from lakes (including reservoirs and ponds). Plentiful water and warm conditions, as well as its large rice paddy area make rice paddies in southeastern China the greatest overall source of CH4 , accounting for approximately 55% of total paddy emissions. Natural wetland estimates were slightly higher than the other estimates owing to the higher CH4 emissions recorded within Qinghai-Tibetan Plateau peatlands. Total CH4 emissions from lakes were estimated for the first time by this study, with three quarters from the littoral zone and one quarter from lake surfaces. Rice paddies, natural wetlands, and lakes are not constant sources of CH4 , but decreasing ones influenced by anthropogenic activity and climate change. A new progress-based model used in conjunction with more observations through model-data fusion approach could help obtain better estimates and insights with regard to CH4 emissions deriving from wetlands and lakes in China.

Concomitant changes of annual precipitation and its seasonal distribution within the context of global climate change have dramatic impacts on aboveground net primary productivity (ANPP) of grassland ecosystems. In this study, combining remote sensing products with in situ measurements of ANPP, we quantified the effects of mean annual precipitation (MAP) and precipitation seasonal distribution (PSD) on the spatial variations in ANPP along a climate gradient in Eurasian temperate grassland. Our results indicated that ANPP increased exponentially with MAP for the entire temperate grassland, but linearly for a specific grassland type, i.e. the desert steppe, typical steppe, and meadow steppe from arid to humid regions. The slope of the linear relationship appeared to be steeper in the more humid meadow steppe than that in the drier typical and desert steppes. PSD also had significant effect on the spatial variations in ANPP. It explained 39.4% of the spatial ANPP for the entire grassland investigated, being comparable with the explanatory power of MAP (40.0%). On the other hand, the relative contribution of PSD and MAP is grassland type specific. MAP exhibited a much stronger explanatory power than PSD for the desert steppe and the meadow steppe at the dry and wet end, respectively. However, PSD was the dominant factor affecting the spatial variation in ANPP for the median typical steppe. Our results imply that altered pattern of PSD due to climate change may be as important as the total amount in terms of effects on ANPP in Eurasian temperate grassland.

Soil net nitrogen (N) mineralization (Nmin) is a pivotal process in the global N cycle regulating the N availability of plant growth. Understanding the spatial patterns of Nmin, its temperature sensitivity (Q10) and regulatory mechanisms is critical for improving the management of soil nutrients. In this study, we evaluated 379 peer-reviewed scientific papers to explore how Nmin and the Q10 of Nmin varied among different ecosystems and regions at the global scale. The results showed that Nmin varied significantly among different ecosystems with a global average of 2.41 mg N soil kg−1 day−1. Furthermore, Nmin significantly decreased with increasing latitude and altitude. The Q10 varied significantly among different ecosystems with a global average of 2.21, ranging from the highest found in forest soils (2.43) and the lowest found for grassland soils (1.67) and significantly increased with increasing latitude. Path analyses indicated that Nmin was primarily affected by the content of soil organic carbon (C), soil C:N ratio, and clay content, where Q10 was primarily influenced by the soil C:N ratio and soil pH. Furthermore, the activation energy (Ea) of soil N mineralization was significantly and negative correlated with the substrate quality index among all ecosystems, indicating the applicability of the carbon quality temperature hypothesis to soil N mineralization at a global scale. These findings provided empirical evidence supporting that soil N availability, under global warming scenarios, is expected to increase stronger in colder regions as compared with that low-latitude regions due to the higher Q10. This may alleviate the restriction of N supply for increased primary productivity at higher latitudes.

National Natural Science Foundation of China [30590381, 30670384]; Knowledge Innovation Project of the Chinese Academy of Sciences [KZCX2-YW-432]; National Key Research and Development Program [2002CB412501]; 'Hundred Talents' Program of the Chinese Acade

Soils with pedogenic carbonate cover about 30% (3.44 x 10(6) km(2)) of China, mainly across its arid and semiarid regions in the Northwest. Based on the second national soil survey (1979-1992), total soil inorganic carbon (SIC) storage in China was estimated to be 53.3 +/- 6.3 PgC (1 Pg=10(15) g) to the depth investigated to 2 m. Soil inorganic carbon storages were 4.6, 10.6, 11.1, and 20.8 Pg for the depth ranges of 0-0.1, 0.1-0.3, 0.3-0.5, and 0.5-1 m, respectively. Stocks for 0.1, 0.3, 0.5, and 1 m of depth accounted for 8.7%, 28.7%, 49.6%, and 88.9% of total SIC, respectively. In contrast with soil organic carbon (SOC) storage, which is highest under 500-800 mm yr(-1) of mean precipitation, SIC storage peaks where mean precipitation is shrubland, cropland > marsh, forest, meadow. Densities of SIC increased generally with depth in all ecosystem types with the exception of deserts and marshes where it peaked in intermediate layers (0.1-0.3 m for first and 0.3-0.5 m for latter). Being an abundant component of soil carbon stocks in China, SIC dynamics and the process involved in its accumulation or loss from soils require a better understanding.

Through 2-3-year (2003-2005) continuous eddy covariance measurements of carbon dioxide and water vapor fluxes, we examined the seasonal, inter-annual, and inter-ecosystem variations in the ecosystem-level water use efficiency (WUE, defined as the ratio of gross primary production, GPP, to evapotranspiration, ET) at four Chinese grassland ecosystems in the Qinghai-Tibet Plateau and North China. Representing the most prevalent grassland types in China, the four ecosystems are an alpine swamp meadow ecosystem, an alpine shrub-meadow ecosystem, an alpine meadow-steppe ecosystem, and a temperate steppe ecosystem, which illustrate a water availability gradient and thus provide us an opportunity to quantify environmental and biological controls on ecosystem WUE at different spatiotemporal scales. Seasonally, WUE tracked closely with GPP at the four ecosystems, being low at the beginning and the end of the growing seasons and high during the active periods of plant growth. Such consistent correspondence between WUE and GPP suggested that photosynthetic processes were the dominant regulator of the seasonal variations in WUE. Further investigation indicated that the regulations were mainly due to the effect of leaf area index (LAI) on carbon assimilation and on the ratio of transpiration to ET (T/ET). Besides, except for the swamp meadow, LAI also controlled the year-to-year and site-to-site variations in WUE in the same way, resulting in the years or sites with high productivity being accompanied by high WUE. The general good correlation between LAI and ecosystem WUE indicates that it may be possible to predict grassland ecosystem WUE simply with LAI. Our results also imply that climate change-induced shifts in vegetation structure, and consequently LAI may have a significant impact on the relationship between ecosystem carbon and water cycles in grasslands.

Grazing exclusion (GE) is considered to be an effective approach to restore degraded grasslands and to improve their carbon (C) sequestration. However, the C dynamics and related controlling factors in grasslands with GE have not been well characterized. This synthesis examines the dynamics of soil C content and vegetation biomass with the recovery age through synthesizing results of 51 sites in grasslands in China. The results illustrate increases in soil C content and vegetation biomass with GE at most sites. Generally, both soil C content and vegetation biomass arrive at steady state after 15 years of GE. In comparison, the rates of increase in above- and belowground biomass declined exponentially with the age of GE, whereas soil C content declined in a milder (linear) way, implying a lagged response of soil C to the inputs from plant biomass. Mean annual precipitation (MAP) and the rate of soil nitrogen (N) change were the main factors affecting the rate of soil C content change. MAP played a major role at the early stage, whereas the rate of soil N change was the major contributor at the middle and late stages. Our results imply that the national grassland restoration projects in China may be more beneficial for C sequestration in humid regions with high MAP. In addition, increased soil N supply to grasslands with GE at the latter recovery stage may enhance ecosystem C sequestration capacity.

Thus far, grassland ecosystem research has mainly been focused on low-lying grassland areas, whereas research on high-altitude grassland areas, especially on the carbon budget of remote areas like the Qinghai-Tibetan plateau is insufficient. To address this issue, flux of CO2 were measured over an alpine shrubland ecosystem (37 degrees 36'N, 101 degrees 18'E; 325 above sea level [a. s. l.]) on the Qinghai-Tibetan Plateau, China, for 2 years (2003 and 2004) with the eddy covariance method. The vegetation is dominated by formation Potentilla fruticosa L. The soil is Mol-Cryic Cambisols. To interpret the biotic and abiotic factors that modulate CO2 flux over the course of a year we decomposed net ecosystem CO2 exchange (NEE) into its constituent components, and ecosystem respiration (R-eco). Results showed that seasonal trends of annual total biomass and NEE followed closely the change in leaf area index. Integrated NEE were -58.5 and -75.5 g C m(-2), respectively, for the 2003 and 2004 years. Carbon uptake was mainly attributed from June, July, August, and September of the growing season. In July, NEE reached seasonal peaks of similar magnitude (4-5 g C m(-2) day(-1)) each of the 2 years. Also, the integrated night-time NEE reached comparable peak values (1.5-2 g C m(-2) day(-1)) in the 2 years of study. Despite the large difference in time between carbon uptake and release (carbon uptake time < release time), the alpine shrubland was carbon sink. This is probably because the ecosystem respiration at our site was confined significantly by low temperature and small biomass and large day/night temperature difference and usually soil moisture was not limiting factor for carbon uptake. In general, R-eco was an exponential function of soil temperature, but with season-dependent values of Q(10). The temperature-dependent respiration model failed immediately after rain events, when large pulses of R-eco were observed. Thus, for this alpine shrubland in Qinghai-Tibetan plateau, the timing of rain events had more impact than the total amount of precipitation on ecosystem R-eco and NEE.