Terrestrial carbon sinks in China and around the world and their contribution to carbon neutrality

Enhancing the terrestrial ecosystem carbon sink (referred to as terrestrial C sink) is an important way to slow down the continuous increase in atmospheric carbon dioxide (CO₂) concentration and to achieve carbon neutrality target. To better understand the characteristics of terrestrial C sinks and their contribution to carbon neutrality, this review summarizes major progress in terrestrial C budget researches during the past decades, clarifies spatial patterns and drivers of terrestrial C sources and sinks in China and around the world, and examines the role of terrestrial C sinks in achieving carbon neutrality target. According to recent studies, the global terrestrial C sink has been increasing from a source of (?0.2±0.9) Pg C yr^?1 (1 Pg=10¹⁵ g) in the 1960s to a sink of (1.9±1.1) Pg C yr^?1 in the 2010s. By synthesizing the published data, we estimate terrestrial C sink of 0.20–0.25 Pg C yr^?1 in China during the past decades, and predict it to be 0.15–0.52 Pg C yr^?1 by 2060. The terrestrial C sinks are mainly located in the mid- and high latitudes of the Northern Hemisphere, while tropical regions act as a weak C sink or source. The C balance differs much among ecosystem types: forest is the major C sink; shrubland, wetland and farmland soil act as C sinks; and whether the grassland functions as C sink or source remains unclear. Desert might be a C sink, but the magnitude and the associated mechanisms are still controversial. Elevated atmospheric CO₂ concentration, nitrogen deposition, climate change, and land cover change are the main drivers of terrestrial C sinks, while other factors such as fires and aerosols would also affect ecosystem C balance. The driving factors of terrestrial C sink differ among regions. Elevated CO₂ concentration and climate change are major drivers of the C sinks in North America and Europe, while afforestation and ecological restoration are additionally important forcing factors of terrestrial C sinks in China. For future studies, we recommend the necessity for intensive and long term ecosystem C monitoring over broad geographic scale to improve terrestrial biosphere models for accurately evaluating terrestrial C budget and its dynamics under various climate change and policy scenarios.

     

Terrestrial nitrogen–carbon cycle interactions at the global scale

Interactions between the terrestrial nitrogen (N) and carbon (C) cycles shape the response of ecosystems to global change. However, the global distribution of nitrogen availability and its importance in global biogeochemistry and biogeochemical interactions with the climate system remain uncertain. Based on projections of a terrestrial biosphere model scaling ecological understanding of nitrogen–carbon cycle interactions to global scales, anthropogenic nitrogen additions since 1860 are estimated to have enriched the terrestrial biosphere by 1.3 Pg N, supporting the sequestration of 11.2 Pg C. Over the same time period, CO₂ fertilization has increased terrestrial carbon storage by 134.0 Pg C, increasing the terrestrial nitrogen stock by 1.2 Pg N. In 2001–2010, terrestrial ecosystems sequestered an estimated total of 27 Tg N yr⁻¹ (1.9 Pg C yr⁻¹), of which 10 Tg N yr⁻¹ (0.2 Pg C yr⁻¹) are due to anthropogenic nitrogen deposition. Nitrogen availability already limits terrestrial carbon sequestration in the boreal and temperate zone, and will constrain future carbon sequestration in response to CO₂ fertilization (regionally by up to 70% compared with an estimate without considering nitrogen–carbon interactions). This reduced terrestrial carbon uptake will probably dominate the role of the terrestrial nitrogen cycle in the climate system, as it accelerates the accumulation of anthropogenic CO₂ in the atmosphere. However, increases of N₂O emissions owing to anthropogenic nitrogen and climate change (at a rate of approx. 0.5 Tg N yr⁻¹ per 1°C degree climate warming) will add an important long-term climate forcing.     

Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends

The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux‐tower‐based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO₂ trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO₂ sensitivity of NPP is compared to the results from four Free‐Air CO₂ Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr^?1) than JU11 (118 ± 6 Pg C yr^?1). In response to rising atmospheric CO₂ concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO₂ than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr^?1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr^?1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is ?3.0 ± 1.5 Pg C yr^?1 °C^?1, within the uncertainty of what derived from RLS (?3.9 ± 1.1 Pg C yr^?1 °C^?1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO₂ and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO₂ concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.     

Terrestrial gross primary production inferred from satellite fluorescence and vegetation models

Determining the spatial and temporal distribution of terrestrial gross primary production (GPP) is a critical step in closing the Earth's carbon budget. Dynamical global vegetation models (DGVMs) provide mechanistic insight into GPP variability but diverge in predicting the response to climate in poorly investigated regions. Recent advances in the remote sensing of solar‐induced chlorophyll fluorescence (SIF) opens up a new possibility to provide direct global observational constraints for GPP. Here, we apply an optimal estimation approach to infer the global distribution of GPP from an ensemble of eight DGVMs constrained by global measurements of SIF from the Greenhouse Gases Observing SATellite (GOSAT). These estimates are compared to flux tower data in N. America, Europe, and tropical S. America, with careful consideration of scale differences between models, GOSAT, and flux towers. Assimilation of GOSAT SIF with DGVMs causes a redistribution of global productivity from northern latitudes to the tropics of 7–8 Pg C yr^?1 from 2010 to 2012, with reduced GPP in northern forests (~3.6 Pg C yr^?1) and enhanced GPP in tropical forests (~3.7 Pg C yr^?1). This leads to improvements in the structure of the seasonal cycle, including earlier dry season GPP loss and enhanced peak‐to‐trough GPP in tropical forests within the Amazon Basin and reduced growing season length in northern croplands and deciduous forests. Uncertainty in predicted GPP (estimated from the spread of DGVMs) is reduced by 40–70% during peak productivity suggesting the assimilation of GOSAT SIF with models is well‐suited for benchmarking. We conclude that satellite fluorescence augurs a new opportunity to quantify the GPP response to climate drivers and the potential to constrain predictions of carbon cycle evolution.     

Terrestrial nitrogen cycle simulation with a dynamic global vegetation model

A global scale Dynamic Nitrogen scheme (DyN) has been developed and incorporated into the Lund–Posdam–Jena (LPJ) dynamic global vegetation model (DGVM). The DyN is a comprehensive process‐based model of the cycling of N through and within terrestrial ecosystems, with fully interactive coupling to vegetation and C dynamics. The model represents the uptake, allocation and turnover of N in plants, and soil N transformations including mineralization, N₂ fixation, nitrification and denitrification, NH₃ volatilization, N leaching, and N₂, N₂O and NO production and emission. Modelled global patterns of site‐scale nitrogen fluxes and reservoirs are highly correlated to observations reported from different biomes. The simulation of site‐scale net primary production and soil carbon content was improved relative to the original LPJ, which lacked an interactive N cycle, especially in the temporal and boreal regions. Annual N uptake by global natural vegetation was simulated as 1.084 Pg N yr⁻¹, with lowest values <1 g N m⁻² yr⁻¹ (polar desert) and highest values in the range 24–36.5 g N m⁻² yr⁻¹ (tropical forests). Simulated global patterns of annual N uptake are consistent with previous model results by Melillo et al. The model estimates global total nitrogen storage potentials in vegetation (5.3 Pg N), litter (4.6 Pg N) and soil (≥67 Pg as organic N and 0.94 Pg as inorganic N). Simulated global patterns of soil N storage are consistent with the analysis by Post et al. although total simulated N storage is less. Deserts were simulated to store 460 Tg N (up to 0.262 kg N m⁻²) as NO₃⁻, contributing 80% of the global total NO₃⁻ inventory of 580 Tg N. This model result is in agreement with the findings of a large NO₃⁻ pool beneath deserts. Globally, inorganic soil N is a small reservoir, comprising only 1.6% of the global soil N content to 1.5 m soil depth, but the ratio has a very high spatial variability and in hot desert regions, inorganic NO₃⁻ is estimated to be the dominant form of stored N in the soil.     

Grassland gross carbon dioxide uptake based on an improved model tree ensemble approach considering human interventions: global estimation and covariation with climate

Grassland ecosystems act as a crucial role in the global carbon cycle and provide vital ecosystem services for many species. However, these low‐productivity and water‐limited ecosystems are sensitive and vulnerable to climate perturbations and human intervention, the latter of which is often not considered due to lack of spatial information regarding the grassland management. Here by the application of a model tree ensemble (MTE‐GRASS) trained on local eddy covariance data and using as predictors gridded climate and management intensity field (grazing and cutting), we first provide an estimate of global grassland gross primary production (GPP). GPP from our study compares well (modeling efficiency NSE = 0.85 spatial; NSE between 0.69 and 0.94 interannual) with that from flux measurement. Global grassland GPP was on average 11 ± 0.31 Pg C yr^?1 and exhibited significantly increasing trend at both annual and seasonal scales, with an annual increase of 0.023 Pg C (0.2%) from 1982 to 2011. Meanwhile, we found that at both annual and seasonal scale, the trend (except for northern summer) and interannual variability of the GPP are primarily driven by arid/semiarid ecosystems, the latter of which is due to the larger variation in precipitation. Grasslands in arid/semiarid regions have a stronger (33 g C m^?2 yr^?1/100 mm) and faster (0‐ to 1‐month time lag) response to precipitation than those in other regions. Although globally spatial gradients (71%) and interannual changes (51%) in GPP were mainly driven by precipitation, where most regions with arid/semiarid climate zone, temperature and radiation together shared half of GPP variability, which is mainly distributed in the high‐latitude or cold regions. Our findings and the results of other studies suggest the overwhelming importance of arid/semiarid regions as a control on grassland ecosystems carbon cycle. Similarly, under the projected future climate change, grassland ecosystems in these regions will be potentially greatly influenced.     

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis‐driven GPP bias was significantly positive with respect to the observed meteorology‐driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m^?2 yr^?1 across sites (ca. 15% of site level GPP). At the northern mid‐/high‐latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20–30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short‐wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site‐level reanalysis‐driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., 2013 ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate‐driven uncertainties in carbon, energy, and water fluxes using a single modeling framework.     

Modelling Seasonal and Inter-annual Variations in Carbon and Water Fluxes in an Arid-Zone <Emphasis Type="Italic">Acacia</Emphasis> Savanna Woodland, 1981–2012

Changes in climatic characteristics such as seasonal and inter-annual variability may affect ecosystem structure and function, hence alter carbon and water budgets of ecosystems. Studies of modelling combined with field experiments can provide essential information to investigate interactions between carbon and water cycles and climate. Here we present a first attempt to investigate the long-term climate controls on seasonal patterns and inter-annual variations in water and carbon exchanges in an arid-zone savanna-woodland ecosystem using a detailed mechanistic soil–plant–atmosphere model (SPA), driven by leaf area index (LAI) simulated by an ecohydrological model (WAVES) and observed climate data during 1981–2012. The SPA was tested against almost 3 years of eddy covariance flux measurements in terms of gross primary productivity (GPP) and evapotranspiration (ET). The model was able to explain 80 and 71% of the variability of observed daily GPP and ET, respectively. Long-term simulations showed that carbon accumulation rates and ET ranged from 20.6 g C m^?2 mon^?1 in the late dry season to 45.8 g C m^?2 mon^?1 in the late wet season, respectively, primarily driven by seasonal variations in LAI and soil moisture. Large climate variations resulted in large seasonal variation in ecosystem water-use efficiency (eWUE). Simulated annual GPP varied between 146.4 and 604.7 g C m^?2 y^?1. Variations in annual ET coincided with that of GPP, ranging from 110.2 to 625.8 mm y^?1. Annual variations in GPP and ET were driven by the annual variations in precipitation and vapour pressure deficit (VPD) but not temperature. The linear coupling of simulated annual GPP and ET resulted in eWUE having relatively small year-to-year variation.     

Comprehensive assessment of carbon productivity, allocation and storage in three Amazonian forests

The allocation and cycling of carbon (C) within forests is an important component of the biospheric C cycle, but is particularly understudied within tropical forests. We synthesise reported and unpublished results from three lowland rainforest sites in Amazonia (in the regions of Manaus, Tapajós and Caxiuanã), all major sites of the Large‐Scale Biosphere–Atmosphere Programme (LBA). We attempt a comprehensive synthesis of the C stocks, nutrient status and, particularly, the allocation and internal C dynamics of all three sites. The calculated net primary productivities (NPP) are 10.1±1.4 Mg C ha⁻¹ yr⁻¹ (Manaus), 14.4±1.3 Mg C ha⁻¹ yr⁻¹ (Tapajós) and 10.0±1.2 Mg C ha⁻¹ yr⁻¹ (Caxiuanã). All errors bars report standard errors. Soil and leaf nutrient analyses indicate that Tapajós has significantly more plant‐available phosphorus and calcium. Autotrophic respiration at all three sites (14.9–21.4 Mg C ha yr⁻¹) is more challenging to measure, with the largest component and greatest source of uncertainty being leaf dark respiration. Comparison of measured soil respiration with that predicted from C cycling measurements provides an independent constraint. It shows general good agreement at all three sites, with perhaps some evidence for measured soil respiration being less than expected. Twenty to thirty percent of fixed C is allocated belowground. Comparison of gross primary productivity (GPP), derived from ecosystem flux measurements with that derived from component studies (NPP plus autotrophic respiration) provides an additional crosscheck. The two approaches are in good agreement, giving increased confidence in both approaches to estimating GPP. The ecosystem carbon‐use efficiency (CUEs), the ratio of NPP to GPP, is similar at Manaus (0.34±0.10) and Caxiuanã (0.32±0.07), but may be higher at Tapajós (0.49±0.16), although the difference is not significant. Old growth or infertile tropical forests may have low CUE compared with recently disturbed and/or fertile forests.     

Holocene radiative forcing impact of northern peatland carbon accumulation and methane emissions

Throughout the Holocene, northern peatlands have both accumulated carbon and emitted methane. Their impact on climate radiative forcing has been the net of cooling (persistent CO₂ uptake) and warming (persistent CH₄ emission). We evaluated this by developing very simple Holocene peatland carbon flux trajectories, and using these as inputs to a simple atmospheric perturbation model. Flux trajectories are based on estimates of contemporary CH₄ flux (15–50 Tg CH₄ yr⁻¹), total accumulated peat C (250–450 Pg C), and peatland initiation dates. The contemporary perturbations to the atmosphere due to northern peatlands are an increase of ∼100 ppbv CH₄ and a decrease of ∼35 ppmv CO₂. The net radiative forcing impact northern peatlands is currently about −0.2 to −0.5 W m⁻² (a cooling). It is likely that peatlands initially caused a net warming of up to +0.1 W m⁻², but have been causing an increasing net cooling for the past 8000–11 000 years. A series of sensitivity simulations indicate that the current radiative forcing impact is determined primarily by the magnitude of the contemporary methane flux and the magnitude of the total C accumulated as peat, and that radiative forcing dynamics during the Holocene depended on flux trajectory, but the overall pattern was similar in all cases.     

遥感GPP模型在中亚干旱区4个典型生态系统的适用性评价

总初级生产力(GPP)是全球生态系统碳循环的重要组成部分,对全球气候变化有重要影响。目前有多种遥感模型可以模拟总初级生产力,比较不同遥感模型在中亚干旱区上的适用性对推进全球干旱区碳收支估算具有重要意义。基于涡度协相关技术观测的四个地面站数据验证MOD17、VODCA2、VPM、TG、SANIRv五种模型的模拟精度。结果表明：(1)基于光能利用率理论的MOD17、VPM模型模拟咸海荒漠植被和阜康荒漠植被GPP的精度最高(R²分别为0.52和0.80),但在模拟草地、农田生态系统生产力时存在较明显的低估(RE>20%);基于植被指数的遥感模型TG模型、SANIRv模型模拟巴尔喀什湖草地生态系统和乌兰乌苏农田生态系统GPP的精度最高(R²分别为0.91和0.81),同时模拟值与实测值的相对误差也较低;基于微波的VODCA2模型模拟各生态系统生产力的效果最差。(2)水分亏缺是限制植被GPP的主要因素,因此是否合理考虑水分胁迫是影响GPP模型在中亚干旱区适用性的重要因素。研究揭示了遥感GPP模型在中亚干旱区的应用潜力,为推进全球植被碳通量的准确估...     

Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 1. Primary production

We conducted an ensemble modeling exercise using the Terrestrial Observation and Prediction System (TOPS) to evaluate sources of uncertainty in carbon flux estimates resulting from structural differences among ecosystem models. The experiment ran public‐domain versions of biome‐bgc, lpj, casa , and tops‐bgc over North America at 8 km resolution and for the period of 1982–2006. We developed the Hierarchical Framework for Diagnosing Ecosystem Models (HFDEM) to separate the simulated biogeochemistry into a cascade of three functional tiers and sequentially examine their characteristics in climate (temperature–precipitation) and other spaces. Analysis of the simulated annual gross primary production (GPP) in the climate domain indicates a general agreement among the models, all showing optimal GPP in regions where the relationship between annual average temperature (T, °C) and annual total precipitation (P, mm) is defined by P=50T+500. However, differences in simulated GPP are identified in magnitudes and distribution patterns. For forests, the GPP gradient along P=50T+500 ranges from ～50 g C yr^?1 m^?2 °C^?1 (casa ) to ～125 g C yr^?1 m^?2 °C^?1 (biome‐bgc ) in cold/temperate regions; for nonforests, the diversity among GPP distributions is even larger. Positive linear relationships are found between annual GPP and annual mean leaf area index (LAI) in all models. For biome‐bgc and lpj , such relationships lead to a positive feedback from LAI growth to GPP enhancement. Different approaches to constrain this feedback lead to different sensitivity of the models to disturbances such as fire, which contribute significantly to the diversity in GPP stated above. The ratios between independently simulated NPP and GPP are close to 50% on average; however, their distribution patterns vary significantly between models, reflecting the difficulties in estimating autotrophic respiration across various climate regimes. Although these results are drawn from our experiments with the tested model versions, the developed methodology has potential for other model exercises.     

The contributions of land-use change, CO2 fertilization, and climate variability to the Eastern US carbon sink

Atmospheric measurements and land‐based inventories imply that terrestrial ecosystems in the northern hemisphere are taking up significant amounts of anthropogenic cabon dioxide (CO₂) emissions; however, there is considerable disagreement about the causes of this uptake, and its expected future trajectory. In this paper, we use the ecosystem demography (ED) model to quantify the contributions of disturbance history, CO₂ fertilization and climate variability to the past, current, and future terrestrial carbon fluxes in the Eastern United States. The simulations indicate that forest regrowth following agricultural abandonment accounts for uptake of 0.11 Pg C yr^?1 in the 1980s and 0.15 Pg C yr^?1 in the 1990s, and regrowth following forest harvesting accounts for an additional 0.1 Pg C yr^?1 of uptake during both these decades. The addition of CO₂ fertilization into the model simulations increases carbon uptake rates to 0.38 Pg C yr^?1 in the 1980s and 0.47 Pg C yr^?1 in the 1990s. Comparisons of predicted aboveground carbon uptake to regional‐scale forest inventory measurements indicate that the model's predictions in the absence of CO₂ fertilization are 14% lower than observed, while in the presence of CO₂ fertilization, predicted uptake rates are 28% larger than observed. Comparable results are obtained from comparisons of predicted total Net Ecosystem Productivity to the carbon fluxes observed at the Harvard Forest flux tower site and in model simulations free‐air CO₂ enrichment (FACE) experiments. These results imply that disturbance history is the principal mechanism responsible for current carbon uptake in the Eastern United States, and that conventional biogeochemical formulations of plant growth overestimate the response of plants to rising CO₂ levels. Model projections out to 2100 imply that the carbon uptake arising from forest regrowth will increasingly be dominated by forest regrowth following harvesting. Consequently, actual carbon storage declines to near zero by the end of the 21st century as the forest regrowth that has occurred since agricultural abandonment comes into equilibrium with the landscape's new disturbance regime. Incorporating interannual climate variability into the model simulations gives rise to large interannual variation in regional carbon fluxes, indicating that long‐term measurements are necessary to detect the signature of processes that give rise to long‐term uptake and storage.     

2001—2018年中国总初级生产力时空变化的遥感研究

总初级生产力（GPP）是绿色植被吸收大气中CO₂进行光合作用生产的有机质,是陆地生态系统碳循环研究的一个关键参数。利用遥感数据和气象数据驱动的双叶光能利用率DTEC模型计算了2001-2018年中国逐月GPP,并结合日光诱导叶绿素荧光（SIF）反演的GOSIF GPP数据集,分析了中国陆地生态系统2001-2018年GPP的时空变化特征。结果表明：（1） GOSIF和DTEC模拟的中国多年GPP平均值分别为7.23 Pg C和6.93 Pg C,在空间分布上呈现东南部高西北部低的特征;（2）2001-2018年,中国GPP呈显著增长（P<0.01）,年增长幅度分别为0.094 PgC/a （GOSIF）和0.073 PgC/a （DTEC）。而已有研究估计的中国GPP年增长幅度约为0.02-0.057 PgC/a,低估了GPP增长趋势。（3）在中国通量网6个通量站的GPP验证表明,两种模型精度高、表现好,都能较好地模拟观测站的GPP季节变化。（4） GOSIF GPP的精度优于DTEC GPP模型,这可能是由于SIF与GPP存在直接机理联系。GOSIF GPP算法能客观地反映植被生产力状况,而DTEC模型更适合自然条件下植被生产力的模拟。     

Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models

The possible responses of ecosystem processes to rising atmospheric CO₂ concentration and climate change are illustrated using six dynamic global vegetation models that explicitly represent the interactions of ecosystem carbon and water exchanges with vegetation dynamics. The models are driven by the IPCC IS92a scenario of rising CO₂ ( Wigley et al. 1991 ), and by climate changes resulting from effective CO₂ concentrations corresponding to IS92a, simulated by the coupled ocean atmosphere model HadCM2‐SUL. Simulations with changing CO₂ alone show a widely distributed terrestrial carbon sink of 1.4–3.8 Pg C y^?1 during the 1990s, rising to 3.7–8.6 Pg C y^?1 a century later. Simulations including climate change show a reduced sink both today (0.6–3.0 Pg C y^?1) and a century later (0.3–6.6 Pg C y^?1) as a result of the impacts of climate change on NEP of tropical and southern hemisphere ecosystems. In all models, the rate of increase of NEP begins to level off around 2030 as a consequence of the ‘diminishing return’ of physiological CO₂ effects at high CO₂ concentrations. Four out of the six models show a further, climate‐induced decline in NEP resulting from increased heterotrophic respiration and declining tropical NPP after 2050. Changes in vegetation structure influence the magnitude and spatial pattern of the carbon sink and, in combination with changing climate, also freshwater availability (runoff). It is shown that these changes, once set in motion, would continue to evolve for at least a century even if atmospheric CO₂ concentration and climate could be instantaneously stabilized. The results should be considered illustrative in the sense that the choice of CO₂ concentration scenario was arbitrary and only one climate model scenario was used. However, the results serve to indicate a range of possible biospheric responses to CO₂ and climate change. They reveal major uncertainties about the response of NEP to climate change resulting, primarily, from differences in the way that modelled global NPP responds to a changing climate. The simulations illustrate, however, that the magnitude of possible biospheric influences on the carbon balance requires that this factor is taken into account for future scenarios of atmospheric CO₂ and climate change.     

Response of terrestrial carbon uptake to climate interannual variability in China

The interest in national terrestrial ecosystem carbon budgets has been increasing because the Kyoto Protocol has included some terrestrial carbon sinks in a legally binding framework for controlling greenhouse gases emissions. Accurate quantification of the terrestrial carbon sink must account the interannual variations associated with climate variability and change. This study used a process‐based biogeochemical model and a remote sensing‐based production efficiency model to estimate the variations in net primary production (NPP), soil heterotrophic respiration (HR), and net ecosystem production (NEP) caused by climate variability and atmospheric CO₂ increases in China during the period 1981–2000. The results show that China's terrestrial NPP varied between 2.86 and 3.37 Gt C yr^?1 with a growth rate of 0.32% year^?1 and HR varied between 2.89 and 3.21 Gt C yr^?1 with a growth rate of 0.40% year^?1 in the period 1981–1998. Whereas the increases in HR were related mainly to warming, the increases in NPP were attributed to increases in precipitation and atmospheric CO₂. Net ecosystem production (NEP) varied between ?0.32 and 0.25 Gt C yr^?1 with a mean value of 0.07 Gt C yr^?1, leading to carbon accumulation of 0.79 Gt in vegetation and 0.43 Gt in soils during the period. To the interannual variations in NEP changes in NPP contributed more than HR in arid northern China but less in moist southern China. NEP had no a statistically significant trend, but the mean annual NEP for the 1990s was lower than for the 1980s as the increases in NEP in southern China were offset by the decreases in northern China. These estimates indicate that China's terrestrial ecosystems were taking up carbon but the capacity was undermined by the ongoing climate change. The estimated NEP related to climate variation and atmospheric CO₂ increases may account for from 40 to 80% to the total terrestrial carbon sink in China.     

How uncertainties in future climate change predictions translate into future terrestrial carbon fluxes

We forced a global terrestrial carbon cycle model by climate fields of 14 ocean and atmosphere general circulation models (OAGCMs) to simulate the response of terrestrial carbon pools and fluxes to climate change over the next century. These models participated in the second phase of the Coupled Model Intercomparison Project (CMIP2), where a 1% per year increase of atmospheric CO₂ was prescribed. We obtain a reduction in net land uptake because of climate change ranging between 1.4 and 5.7 Gt C yr^?1 at the time of atmospheric CO₂ doubling. Such a reduction in terrestrial carbon sinks is largely dominated by the response of tropical ecosystems, where soil water stress occurs. The uncertainty in the simulated land carbon cycle response is the consequence of discrepancies in land temperature and precipitation changes simulated by the OAGCMs. We use a statistical approach to assess the coherence of the land carbon fluxes response to climate change. The biospheric carbon fluxes and pools changes have a coherent response in the tropics, in the Mediterranean region and in high latitudes of the Northern Hemisphere. This is because of a good coherence of soil water content change in the first two regions and of temperature change in the high latitudes of the Northern Hemisphere. Then we evaluate the carbon uptake uncertainties to the assumptions on plant productivity sensitivity to atmospheric CO₂ and on decomposition rate sensitivity to temperature. We show that these uncertainties are on the same order of magnitude than the uncertainty because of climate change. Finally, we find that the OAGCMs having the largest climate sensitivities to CO₂ are the ones with the largest soil drying in the tropics, and therefore with the largest reduction of carbon uptake.     

Seasonal responses of terrestrial ecosystem water‐use efficiency to climate change

Ecosystem water‐use efficiency (EWUE) is an indicator of carbon–water interactions and is defined as the ratio of carbon assimilation (GPP) to evapotranspiration (ET). Previous research suggests an increasing long‐term trend in annual EWUE over many regions and is largely attributed to the physiological effects of rising CO₂. The seasonal trends in EWUE, however, have not yet been analyzed. In this study, we investigate seasonal EWUE trends and responses to various drivers during 1982–2008. The seasonal cycle for two variants of EWUE, water‐use efficiency (WUE, GPP/ET), and transpiration‐based WUE (WUE_t, the ratio of GPP and transpiration), is analyzed from 0.5° gridded fields from four process‐based models and satellite‐based products, as well as a network of 63 local flux tower observations. WUE derived from flux tower observations shows moderate seasonal variation for most latitude bands, which is in agreement with satellite‐based products. In contrast, the seasonal EWUE trends are not well captured by the same satellite‐based products. Trend analysis, based on process‐model factorial simulations separating effects of climate, CO₂, and nitrogen deposition (NDEP), further suggests that the seasonal EWUE trends are mainly associated with seasonal trends of climate, whereas CO₂ and NDEP do not show obvious seasonal difference in EWUE trends. About 66% grid cells show positive annual WUE trends, mainly over mid‐ and high northern latitudes. In these regions, spring climate change has amplified the effect of CO₂ in increasing WUE by more than 0.005 gC m⁻² mm⁻¹ yr⁻¹ for 41% pixels. Multiple regression analysis further shows that the increase in springtime WUE in the northern hemisphere is the result of GPP increasing faster than ET because of the higher temperature sensitivity of GPP relative to ET. The partitioning of annual EWUE to seasonal components provides new insight into the relative sensitivities of GPP and ET to climate, CO_2, and NDEP.     

Vegetation clumping modulates global photosynthesis through adjusting canopy light environment

The spatial dispersion of photoelements within a vegetation canopy, quantified by the clumping index (CI), directly regulates the within-canopy light environment and photosynthesis rate, but is not commonly implemented in terrestrial biosphere models to estimate the ecosystem carbon cycle. A few global CI products have been developed recently with remote sensing measurements, making it possible to examine the global impacts of CI. This study deployed CI in the radiative transfer scheme of the Community Land Model version 5 (CLM5) and used the revised CLM5 to quantitatively evaluate the extent to which CI can affect canopy absorbed radiation and gross primary production (GPP), and for the first time, considering the uncertainty and seasonal variation of CI with multiple remote sensing products. Compared to the results without considering the CI impact, the revised CLM5 estimated that sunlit canopy absorbed up to 9%–15% and 23%–34% less direct and diffuse radiation, respectively, while shaded canopy absorbed 3%–18% more diffuse radiation across different biome types. The CI impacts on canopy light conditions included changes in canopy light absorption, and sunlit–shaded leaf area fraction related to nitrogen distribution and thus the maximum rate of Rubisco carboxylase activity (V_cmax), which together decreased photosynthesis in sunlit canopy by 5.9–7.2 PgC year⁻¹ while enhanced photosynthesis by 6.9–8.2 PgC year⁻¹ in shaded canopy. With higher light use efficiency of shaded leaves, shaded canopy increased photosynthesis compensated and exceeded the lost photosynthesis in sunlit canopy, resulting in 1.0 ± 0.12 PgC year⁻¹ net increase in GPP. The uncertainty of GPP due to the different input CI datasets was much larger than that caused by CI seasonal variations, and was up to 50% of the magnitude of GPP interannual variations in the tropical regions. This study highlights the necessity of considering the impacts of CI and its uncertainty in terrestrial biosphere models.     

Amazonia and the modern carbon cycle: lessons learned

In this paper, we review some critical issues regarding carbon cycling in Amazonia, as revealed by several studies conducted in the Large Scale Biosphere Atmosphere Experiment in Amazonia (LBA). We evaluate both the contribution of this magnificent biome for the global net primary productivity/net ecosystem exchange (NPP/NEE) and the feedbacks of climate change on the dynamics of Amazonia. In order to place Amazonia in a global perspective and make the carbon flux obtained through the LBA project comparable with global carbon budgets, we extrapolated NPP/NEE values found by LBA studies to the entire area of the Brazilian Amazon covered by rainforest. The carbon emissions due to land use changes for the tropical regions of the world produced values from 0.96 to 2.4 Pg C year⁻¹, while atmospheric CO₂ inversion models have recently indicated that tropical lands in the Americas could be exchanging a net 0.62±1.15 Pg C year⁻¹ with the atmosphere. The difference calculated from these two methods would imply a local sink of approximately 1.6–1.7 Pg C year⁻¹, or a source of 0.85 ton C ha⁻¹ year⁻¹. Using our crude extrapolation of LBA values for the Amazon forests (5 million km²) we estimate a range for the C flux in the region of −3.0 to 0.75 Pg C year⁻¹. The exercise here does not account for environmental variability across the region, but it is an important driver for present and future studies linking local process (i.e. nutrient availability, photosynthetic capacity, and so forth) to global and regional dynamic approaches.