Future carbon balance of China's forests under climate change and increasing CO2

Maximizing carbon sequestration potential in Chinese forests through optimal management

Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1-3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

Time Effects of Global Change on Forest Productivity in China from 2001 to 2017

With global warming, the concentrations of fine particulate matter (PM_2.5) and greenhouse gases, such as CO₂, are increasing. However, it is still unknown whether these increases will affect vegetation productivity. Exploring the impacts of global warming on net primary productivity (NPP) will help us understand how ecosystem function responds to climate change in China. Using the Carnegie-Ames-Stanford Approach (CASA) ecosystem model based on remote sensing, we investigated the spatiotemporal changes in NPP across 1137 sites in China from 2001 to 2017. Our results revealed that: (1) Mean Annual Temperature (MAT) and Mean Annual Precipitation (MAP) were significantly positively correlated with NPP (p < 0.01), while PM_2.5 concentration and CO₂ emissions were significantly negatively correlated with NPP (p < 0.01). (2) The positive correlation between temperature, rainfall and NPP gradually weakened over time, while the negative correlation between PM_2.5 concentration, CO₂ emissions and NPP gradually strengthened over time. (3) High levels of PM_2.5 concentration and CO₂ emissions had negative effects on NPP, while high levels of MAT and MAP had positive effects on NPP.

Responses of Forest Net Primary Productivity to Climatic Factors in China during 1982-2015

Forest ecosystems play an important role in the global carbon cycle. Clarifying the large-scale dynamics of net primary productivity (NPP) and its correlation with climatic factors is essential for national forest ecology and management. Hence, this study aimed to explore the effects of major climatic factors on the Carnegie−Ames−Stanford Approach (CASA) model-estimated NPP of the entire forest and all its corresponding vegetation types in China from 1982 to 2015. The spatiotemporal patterns of interannual variability of forest NPP were illustrated using linear regression and geographic information system (GIS) spatial analysis. The correlations between forest NPP and climatic factors were evaluated using partial correlation analysis and sliding correlation analysis. We found that over thirty years, the average annual NPP of the forests was 887 × 1012 g C/a, and the average annual NPP per unit area was 650.73 g C/m2/a. The interannual NPP of the entire forest and all its corresponding vegetation types significantly increased (p < 0.01). The increase in the NPP of evergreen broad-leaved forests was markedly substantial among forest types. From the spatial perspective, the NPP of the entire forest vegetation gradually increased from northwest to southeast. Over the years, the proportions of the entire forest and all its corresponding vegetation types with a considerable increase in NPP were higher than those with a significant decrease, indicating, generally, improvements in forest NPP. We also found climatic factors variably affected the NPP of forests over time considering that the rise in temperature and solar radiation improved the interannual forest NPP, and the decline in precipitation diminished the forest NPP. Such varying strength of the relationship between the interannual forest NPP and climatic factors also varied across many forest types. Understanding the spatiotemporal pattern of forest NPP and its varying responses to climatic change will improve our knowledge to manage forest ecosystems and maintain their sustainability under a changing environment.

Simulated net ecosystem productivity of subtropical forests and its response to climate change in Zhejiang Province, China

Net ecosystem productivity (NEP) is an important index that indicates the carbon sequestration capacity of forest ecosystems. However, the effect of climate change on the spatiotemporal variability in NEP is still unclear. Using the Integrated Terrestrial Ecosystem Carbon-budget (InTEC) model, this study takes the typical subtropical forests in the Zhejiang Province, China as an example, simulated the spatiotemporal patterns of forest NEP from 1979 to 2079 based on historically observed climate data (1979-2015) and data from three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) provided by the Coupled Model Intercomparison Project 5 (CMIP5). We analyzed the responses of NEP at different forest age classes to the variation in meteorological factors. The NEP of Zhejiang's forests decreased from 1979 to 1985 and then increased from 1985 to 2015, with an annual increase rate of 9.66 g C·m^-2·yr^-1 and a cumulative NEP of 364.99 Tg·C. Forest NEP decreased from 2016 to 2079; however, the cumulative NEP continued to increase. The simulated cumulative NEP under the RCP2.6, RCP4.5, and RCP8.5 scenarios was 750 Tg·C, 866 Tg·C, and 958 Tg·C, respectively, at the end of 2079. Partial correlation analysis between forest NEP at different age stages and meteorological factors showed that temperature is the key climatic factor that affects the carbon sequestration capacity of juvenile forests (1979-1999), while precipitation is the key climatic factor that affects middle-aged forests (2000-2015) and mature forests (2016-2079). Adopting appropriate management strategies for forests, such as selective cutting of different ages, is critical for the subtropical forests to adapt to climate change and maintain their high carbon sink capacity.

The role of China's terrestrial carbon sequestration 2010-2060 in offsetting energy-related CO2 emissions

Energy consumption dominates annual CO2 emissions in China. It is essential to significantly reduce CO2 emissions from energy consumption to reach national carbon neutrality by 2060, while the role of terrestrial carbon sequestration in offsetting energy-related CO2 emissions cannot be underestimated. Natural climate solutions (NCS), including improvements in terrestrial carbon sequestration, represent readily deployable options to offset anthropogenic greenhouse gas emissions. However, the extent to which China's terrestrial carbon sequestration in the future, especially when target-oriented managements (TOMs) are implemented, can help to mitigate energy-related CO2 emissions is far from certain. By synthesizing available findings and using several parameter-sparse empirical models that have been calibrated and/or fitted against contemporary measurements, we assessed China's terrestrial carbon sequestration over 2010-2060 and its contribution to offsetting national energy-related CO2 emissions. We show that terrestrial C sequestration in China will increase from 0.375 ± 0.056 (mean ± standard deviation) Pg C yr-1 in the 2010s to 0.458 ± 0.100 Pg C yr-1 under RCP2.6 and 0.493 ± 0.108 Pg C yr-1 under the RCP4.5 scenario in the 2050s, when TOMs are implemented. The majority of carbon sequestration comes from forest, accounting for 67.8-71.4% of the total amount. China's terrestrial ecosystems can offset 12.2-15.0% and 13.4-17.8% of energy-related peak CO2 emissions in 2030 and 2060, respectively. The implementation of TOMs contributes 11.9% of the overall terrestrial carbon sequestration in the 2020s and 23.7% in the 2050s. The most likely strategy to maximize future NCS effectiveness is a full implementation of all applicable cost-effective NCS pathways in China. Our findings highlight the role of terrestrial carbon sequestration in offsetting energy-related CO2 emissions and put forward future needs in the context of carbon neutrality.

An integrated remote sensing and model approach for assessing forest carbon fluxes in China

Forest plays an important role in reducing pressure on the natural environment, weaking the influence of greenhouse effects, and sequestrating atmospheric carbon dioxide. So far, due to the lack of complete understanding of forest ecosystem processes and the limitations on the scope of application of evaluation methods, there are still great uncertainties in the researches on carbon fluxes of forest ecosystems in China at the national level. In this study, an individual tree species FORCCHN model, which could flexibly use the inventory data as the initial field (more accurately) or use the remote sensing information to inverse initial field was applied. The dynamics of key carbon cycle fluxes (net primary productivity (NPP) and net ecosystem productivity (NEP)) and carbon sequestration of forest ecosystems in China from 1982 to 2019 were simulated based on remote sensing data and FORCCHN model. The results showed that forest ecosystems in China had great carbon sequestration potential over the past 39 years. From 1982 to 2019, the NPP of Chinese forests presented a fluctuated increase. Total NPP from 2011 to 2019 ranged from 0.91 PgC·a^-1 to 1.14 PgC·a^-1. Annual average NEP of forest ecosystems in China from 2011 to 2019 was 0.199 PgC·a^-1 (1Pg = 10¹⁵ g). Influenced by climate, soil and vegetation, carbon sequestration potential in Chinese forest ecosystems presented obvious regional differences in space. The spatial distribution of NEP gradually increased from Northwest to Southeast China. From 2011 to 2019, forests in Yunnan Province had the strongest carbon storage capacity (72.79 TgC·a^-1, 1Tg = 10¹² g), followed by forests in Guangxi (18.49 TgC·a^-1) and forests in Guangdong (10.01 TgC·a^-1). Our results not only address concerns about carbon sequestration but also reflect the importance of Chinese forest resources in the development of the national economy and society.

Estimation of the relative contributions of forest areal expansion and growth to China's forest stand biomass carbon sequestration from 1977 to 2018

As a prominent part of global and regional terrestrial carbon (C) pools, increases in forest biomass C sinks can be attributed to either forest areal expansion (FAE) or increased biomass C density (IBCD). Accurate estimates of the relative contributions of FAE and IBCD to forest C sequestration can improve our understanding of forest C cycling processes and will help to formulate rational afforestation policies to cope with global warming. In this study, the Continuous Biomass Expansion Factor (CBEF) model and Forest Identity concept were used to map the spatiotemporal variation of the relative contribution of FAE and IBCD to the C sequestration of forest (natural and planted forests) in China and seven regions during the past 40 years. Our results suggest that: (1) total forest biomass C density and stocks of forest increased from 35.41 Mg C ha^-1 and 4128.50 Tg C to 43.95 Mg C ha^-1 and 7906.23 Tg C in China from 1977 to 2018, respectively; (2) for all forests, the IBCD has been a smaller contributor to C sinks than FAE in China from 1977 to 2018 (33.27 vs. 66.73%); (3) the contribution of FAE to C sinks is greater than that of IBCD in planted forests (63.99 vs. 36.01%), while in natural forests, IBCD has a larger contribution than FAE (57.82 vs. 42.18%) from 1977 to 2018 and the relative contribution of FAE has exceeded IBCD in the last decade; and (4) these patterns varied at the regional level such that the relative contribution of FAE increased for planted forests in most regions but for natural forests, IBCD gradually reached saturation and C stocks declined in northern regions in the last decade. The results from this study suggest that total biomass C sinks will keep increasing because of the increased forest area contributed by afforestation and the relatively young trees in planted forests. This study facilitates a more comprehensive assessment of forest C budgets and improves our understanding of ecological mechanisms of forest biomass carbon stock and dynamics.

Impacts of 1.5 °C and 2 °C Global Warming on Net Primary Productivity and Carbon Balance in China’s Terrestrial Ecosystems

Assessing potential impacts of 1.5 °C and 2 °C global warming and identifying the risks of further 0.5 °C warming are crucial for climate adaptation and disaster risk management. Four earth system models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and a process-based ecosystem model are used in this study to assess the impacts and potential risks of the two warming targets on the carbon cycle of China’s terrestrial ecosystems. Results show that warming generally stimulates the increase of net primary productivity (NPP) and net ecosystem productivity (NEP) under both representative concentration pathway (RCP) 4.5 and RCP8.5 scenarios. The projected increments of NPP are higher at 2 °C warming than that at 1.5 °C warming for both RCP4.5 and RCP8.5 scenarios; approximately 13% and 19% under RCP4.5, and 12.5% and 20% under RCP8.5 at 1.5 °C and 2 °C warming, respectively. However, the increasing rate of NPP was projected to decline at 2 °C warming under the RCP4.5 scenario, and the further 0.5 °C temperature rising induces the decreased NPP linear slopes in more than 81% areas of China’s ecosystems. The total NEP is projected to be increased by 53% at 1.5 °C, and by 81% at 2 °C warming. NEP was projected to increase approximately by 28% with the additional 0.5 °C warming. Furthermore, the increasing rate of NEP weakens at 2 °C warming, especially under the RCP8.5 scenario. In summary, China’s total NPP and NEP were projected to increase under both 1.5 °C and 2 °C warming scenarios, although adverse effects (i.e., the drop of NPP growth and the reduction of carbon sequestration capacity) would occur in some regions such as northern China in the process of global warming.

Projection of Net Primary Productivity under Global Warming Scenarios of 1.5 °C and 2.0 °C in Northern China Sandy Areas

Empirical evidence suggests that variations in climate affect the net primary productivity (NPP) across sandy areas over time. However, little is known about the relative impacts of climate change on NPP with global warming of 1.5 and 2.0 °C (GW_1.5 °C_2.0 °C) relative to pre-industrial levels. Here, we used a new set of climate simulations from four Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP 2b) datasets, modified the Carnegie-Ames-Stanford approach (CASA) model and assessed the spatio-temporal variation in NPP in sandy areas of northern China (SAONC). Compared with the reference period (RP, 1986–2005), the NPP variation under four emission scenarios showed clear rising trends and increased most significantly under RCP8.5 with an annual average increase of 2.34 g C/m2. The estimated annual NPP under global warming of 1.5 °C (GW_1.5 °C) increased by 14.17, 10.72, 8.57, and 26.68% in different emission scenarios, and under global warming of 2.0 °C (GW_2.0 °C) it increased by 20.87, 24.01, 29.31, and 39.94%, respectively. In terms of seasonal change, the NPP value under the four emission scenarios changed most significantly in the summer relative to RP, exhibiting a growth of 16.48%. Temperature changes (p > 0.614) had a greater impact on NPP growth than precipitation (p > 0.017), but solar radiation showed a certain negative impact in the middle- and low-latitude regions. NPP showed an increasing trend that changed from the southeast to the central and western regions at GW_1.5 to GW_2.0 °C. NPP was consistent with the spatial change in climate factors and had a promoting role in high latitudes in SAONC, but it was characterized by a certain inhibitory effect at middle and low latitudes in SAONC. The uncertainty of NPP under the four models ranged from 16.29 to 26.52%. Our findings suggest that the impact of GW_1.5 °C is relatively high compared with the current conditions, whereas GW_2.0 °C implies significantly lower projected NPP growth in all areas.

Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink

Satellite observations show that leaf area index (LAI) has increased globally since 1981, but the impact of this vegetation structural change on the global terrestrial carbon cycle has not been systematically evaluated. Through process-based diagnostic ecosystem modeling, we find that the increase in LAI alone was responsible for 12.4% of the accumulated terrestrial carbon sink (95 ± 5 Pg C) from 1981 to 2016, whereas other drivers of CO₂ fertilization, nitrogen deposition, and climate change (temperature, radiation, and precipitation) contributed to 47.0%, 1.1%, and −28.6% of the sink, respectively. The legacy effects of past changes in these drivers prior to 1981 are responsible for the remaining 65.5% of the accumulated sink from 1981 to 2016. These results refine the attribution of the land sink to the various drivers and would help constrain prognostic models that often have large uncertainties in simulating changes in vegetation and their impacts on the global carbon cycle.

There lacks systematic analysis on the importance of vegetation structural change in the global terrestrial carbon cycle. Here the authors conducted a multi-model comparison analysis and find that the increase in leaf area index has been responsible for 12.4% of the accumulated terrestrial carbon sink from 1981 to 2016.

Roles of Climate Change and Increasing CO2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model

Net primary productivity (NPP) is the key component of the terrestrial carbon cycle, and terrestrial NPP trends under increasing CO2 and climate change in the past and future are of great significance in the study of the global carbon budget. Here, the LPJ-DGVM was employed to simulate the magnitude and pattern of China’s terrestrial NPP using long-term series data to understand the response of terrestrial NPP to increasing CO2 concentration and climate change. The results showed that total NPP of China’s terrestrial ecosystem increased from 2.8 to 3.6 Pg C yr−1 over the period of 1961–2016, with an annual average of 3.1 Pg C yr−1. The average NPP showed a gradient decrease from the southeast to northwest. Southwest China and Northwest China, comprising mostly arid and semi-arid regions, exhibited the largest increase rate in total NPP among the six geographical regions of China. Additionally, large interannual variability around the NPP trends was presented, and NPP anomalies in China’s terrestrial ecosystem are strongly associated with the El Niño-Southern Oscillation (ENSO). Southwest China made the largest contribution to the interannual variability of national total NPP. The total NPP of China’s terrestrial ecosystem continuously increased with the concurrent increase in the CO2 concentration and climate change under different scenarios in the future. During the period from 2091 to 2100, the average total NPP under the A2 and RCP85 scenarios would reach 4.9 and 5.1 Pg C yr−1 respectively, higher than 4.2 and 3.9 Pg C yr−1 under the B1 and RCP45 scenarios. Forests, especially temperate forests, make the largest contribution to the future increase in NPP. The increase in CO2 concentration would play a dominant role in driving further NPP increase in China’s terrestrial ecosystems, and climate change may slightly attenuate the fertilization effect of CO2 on NPP.

Future biomass carbon sequestration capacity of Chinese forests

Chinese forests, characterized by relatively young stand age, represent a significant biomass carbon (C) sink over the past several decades. Nevertheless, it is unclear how forest biomass C sequestration capacity in China will evolve as forest age, climate and atmospheric CO₂ concentration change continuously. Here, we present a semi-empirical model that incorporates forest age and climatic factors for each forest type to estimate the effects of forest age and climate change on total forest biomass, under three different scenarios based on the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We estimate that age-related forest biomass C sequestration to be 6.69 Pg C (∼0.17 Pg C a^-1) from the 2000s to the 2040s. Climate change induces a rather weak increase in total forest biomass C sequestration (0.52-0.60 Pg C by the 2040s). We show that rising CO₂ concentrations could further increase the total forest biomass C sequestration by 1.68-3.12 Pg C in the 2040s across all three scenarios. Overall, the total forest biomass in China would increase by 8.89-10.37 Pg C by the end of 2040s. Our findings highlight the benefits of Chinese afforestation programs, continued climate change and increasing CO₂ concentration in sustaining the forest biomass C sink in the near future, and could therefore be useful for designing more realistic climate change mitigation policies such as continuous forestation programs and careful choice of tree species.

Effects of climate warming on net primary productivity in China during 1961-2010

The response of ecosystems to different magnitudes of climate warming and corresponding precipitation changes during the last few decades may provide an important reference for predicting the magnitude and trajectory of net primary productivity (NPP) in the future. In this study, a process‐based ecosystem model, Carbon Exchange between Vegetation, Soil and Atmosphere (CEVSA), was used to investigate the response of NPP to warming at both national and subregional scales during 1961–2010. The results suggest that a 1.3°C increase in temperature stimulated the positive changing trend in NPP at national scale during the past 50 years. Regardless of the magnitude of temperature increase, warming enhanced the increase in NPP; however, the positive trend of NPP decreased when warming exceeded 2°C. The largest increase in NPP was found in regions where temperature increased by 1–2°C, and this rate of increase also contributed the most to the total increase in NPP in China's terrestrial ecosystems. Decreasing precipitation depressed the positive trend in NPP that was stimulated by warming. In northern China, warming depressed the increasing trend of NPP and warming that was accompanied by decreasing precipitation led to negative changing trends in NPP in large parts of northern China, especially when warming exceeded 2°C. However, warming stimulated the increase in NPP until warming was greater than 2°C, and decreased precipitation helped to increase the NPP in southern China.

Quantitative assessments of water-use efficiency in Temperate Eurasian Steppe along an aridity gradient

Water-use efficiency (WUE), defined as the ratio of net primary productivity (NPP) to evapotranspiration (ET), is an important indicator to represent the trade-off pattern between vegetation productivity and water consumption. Its dynamics under climate change are important to ecohydrology and ecosystem management, especially in the drylands. In this study, we modified and used a late version of Boreal Ecosystem Productivity Simulator (BEPS), to quantify the WUE in the typical dryland ecosystems, Temperate Eurasian Steppe (TES). The Aridity Index (AI) was used to specify the terrestrial water availability condition. The regional results showed that during the period of 1999–2008, the WUE has a clear decreasing trend in the spatial distribution from arid to humid areas. The highest annual average WUE was in dry and semi-humid sub-region (DSH) with 0.88 gC mm^-1 and the lowest was in arid sub-region (AR) with 0.22 gC mm^-1. A two-stage pattern of WUE was found in TES. That is, WUE would enhance with lower aridity stress, but decline under the humid environment. Over 65% of the region exhibited increasing WUE. This enhancement, however, could not indicate that the grasslands were getting better because the NPP even slightly decreased. It was mainly attributed to the reduction of ET over 70% of the region, which is closely related to the rainfall decrease. The results also suggested a similar negative spatial correlation between the WUE and the mean annual precipitation (MAP) at the driest and the most humid ends. This regional pattern reflected the different roles of water in regulating the terrestrial ecosystems under different aridity levels. This study could facilitate the understanding of the interactions between terrestrial carbon and water cycles, and thus contribute to a sustainable management of nature resources in the dryland ecosystems.

Prediction CH4 Emissions from the Wetlands in the Sanjiang Plain of Northeastern China in the 21st Century

The Sanjiang Plain has been experienced significant wetland loss due to expanded agricultural activities, and will be potentially restored by the China National Wetland Conservation Action Plan (NWCP) in future. The objective of this study is to evaluate the impact of future climate warming and wetland restoration on wetland CH4 emissions in northeast China. We used an atmosphere-vegetation interaction model (AVIM2) to drive a modified biogeophysical model (CH4MODwetland), and projected CH4 flux variations from the Sanjiang Plain wetlands under different Representative Concentration Pathway scenarios throughout the 21st century. Model validation showed that the regressions between the observed and simulated CH4 fluxes by the modified model produced an R2 of 0.49 with a slope of 0.87 (p<0.001, n = 237). According to the AVIM2 simulation, the net primary productivity of the Sanjiang Plain wetlands will increase by 38.2 g m-2 yr-1, 116.6 g m-2 yr-1 and 250.4 g m-2 yr-1 under RCP 2.6, RCP 4.5 and RCP 8.5, respectively, by the end of this century. For RCP 2.6, 4.5 and 8.5 scenarios, the CH4 fluxes will increase by 5.7 g m-2 yr-1, 57.5 g m-2 yr-1 and 112.2 g m-2 yr-1. Combined with the wetland restoration, the regional emissions will increase by 0.18‒1.52 Tg. The CH4 emissions will be stimulated by climate change and wetland restoration. Regional wetland restoration planning should be directed against different climate scenarios in order to suppress methane emissions.

The stage-classified matrix models project a significant increase in biomass carbon stocks in China's forests between 2005 and 2050

China’s forests are characterized by young age, low carbon (C) density and a large plantation area, implying a high potential for increasing C sinks in the future. Using data of provincial forest area and biomass C density from China’s forest inventories between 1994 and 2008 and the planned forest coverage of the country by 2050, we developed a stage-classified matrix model to predict biomass C stocks of China’s forests from 2005 to 2050. The results showed that total forest biomass C stock would increase from 6.43 Pg C (1 Pg = 10¹⁵ g) in 2005 to 9.97 Pg C (95% confidence interval: 8.98 ~ 11.07 Pg C) in 2050, with an overall net C gain of 78.8 Tg C yr⁻¹ (56.7 ~ 103.3 Tg C yr⁻¹; 1 Tg = 10¹² g). Our findings suggest that China’s forests will be a large and persistent biomass C sink through 2050.

Carbon carry capacity and carbon sequestration potential in China based on an integrated analysis of mature forest biomass

Forests play an important role in acting as a carbon sink of terrestrial ecosystem. Although global forests have huge carbon carrying capacity (CCC) and carbon sequestration potential (CSP), there were few quantification reports on Chinese forests. We collected and compiled a forest biomass dataset of China, a total of 5841 sites, based on forest inventory and literature search results. From the dataset we extracted 338 sites with forests aged over 80 years, a threshold for defining mature forest, to establish the mature forest biomass dataset. After analyzing the spatial pattern of the carbon density of Chinese mature forests and its controlling factors, we used carbon density of mature forests as the reference level, and conservatively estimated the CCC of the forests in China by interpolation methods of Regression Kriging, Inverse Distance Weighted and Partial Thin Plate Smoothing Spline. Combining with the sixth National Forest Resources Inventory, we also estimated the forest CSP. The results revealed positive relationships between carbon density of mature forests and temperature, precipitation and stand age, and the horizontal and elevational patterns of carbon density of mature forests can be well predicted by temperature and precipitation. The total CCC and CSP of the existing forests are 19.87 and 13.86 Pg C, respectively. Subtropical forests would have more CCC and CSP than other biomes. Consequently, relying on forests to uptake carbon by decreasing disturbance on forests would be an alternative approach for mitigating greenhouse gas concentration effects besides afforestation and reforestation.

Responses of terrestrial ecosystems' net primary productivity to future regional climate change in China

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems' response to global climate change. China's ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund-Potsdam-Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China's terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.

Relationships between net primary productivity and stand age for several forest types and their influence on China's carbon balance

Affected by natural and anthropogenic disturbances such as forest fires, insect-induced mortality and harvesting, forest stand age plays an important role in determining the distribution of carbon pools and fluxes in a variety of forest ecosystems. An improved understanding of the relationship between net primary productivity (NPP) and stand age (i.e., age-related increase and decline in forest productivity) is essential for the simulation and prediction of the global carbon cycle at annual, decadal, centurial, or even longer temporal scales. In this paper, we developed functions describing the relationship between national mean NPP and stand age using stand age information derived from forest inventory data and NPP simulated by the BEPS (Boreal Ecosystem Productivity Simulator) model in 2001. Due to differences in ecobiophysical characteristics of different forest types, NPP-age equations were developed for five typical forest ecosystems in China (deciduous needleleaf forest (DNF), evergreen needleleaf forest in tropic and subtropical zones (ENF-S), deciduous broadleaf forest (DBF), evergreen broadleaf forest (EBF), and mixed broadleaf forest (MBF)). For DNF, ENF-S, EBF, and MBF, changes in NPP with age were well fitted with a common non-linear function, with R(2) values equal to 0.90, 0.75, 0.66, and 0.67, respectively. In contrast, a second order polynomial was best suitable for simulating the change of NPP for DBF, with an R(2) value of 0.79. The timing and magnitude of the maximum NPP varied with forest types. DNF, EBF, and MBF reached the peak NPP at the age of 54, 40, and 32 years, respectively, while the NPP of ENF-S maximizes at the age of 13 years. The highest NPP of DBF appeared at 122 years. NPP was generally lower in older stands with the exception of DBF, and this particular finding runs counter to the paradigm of age-related decline in forest growth. Evaluation based on measurements of NPP and stand age at the plot-level demonstrates the reliability and applicability of the fitted NPP-age relationships. These relationships were used to replace the normalized NPP-age relationship used in the original InTEC (Integrated Terrestrial Ecosystem Carbon) model, to improve the accuracy of estimated carbon balance for China's forest ecosystems. With the revised NPP-age relationship, the InTEC model simulated a larger carbon source from 1950-1980 and a larger carbon sink from 1985-2001 for China's forests than the original InTEC model did because of the modification to the age-related carbon dynamics in forests. This finding confirms the importance of considering the dynamics of NPP related to forest age in estimating regional and global terrestrial carbon budgets.

Biomass carbon stocks in China's forests between 2000 and 2050: a prediction based on forest biomass-age relationships

China's forests are characterized by young forest age, low carbon density and a large area of planted forests, and thus have high potential to act as carbon sinks in the future. Using China's national forest inventory data during 1994-1998 and 1999-2003, and direct field measurements, we investigated the relationships between forest biomass density and forest age for 36 major forest types. Statistical approaches and the predicted future forest area from the national forestry development plan were applied to estimate the potential of forest biomass carbon storage in China during 2000-2050. Under an assumption of continuous natural forest growth, China's existing forest biomass carbon (C) stock would increase from 5.86 Pg C (1 Pg=10(15) g) in 1999-2003 to 10.23 Pg C in 2050, resulting in a total increase of 4.37 Pg C. Newly planted forests through afforestation and reforestation will sequestrate an additional 2.86 Pg C in biomass. Overall, China's forests will potentially act as a carbon sink for 7.23 Pg C during the period 2000-2050, with an average carbon sink of 0.14 Pg C yr(-1). This suggests that China's forests will be a significant carbon sink in the next 50 years.

Estimating rainforest biomass stocks and carbon loss from deforestation and degradation in Papua New Guinea 1972-2002: Best estimates, uncertainties and research needs

Reduction of carbon emissions from tropical deforestation and forest degradation is being considered a cost-effective way of mitigating the impacts of global warming. If such reductions are to be implemented, accurate and repeatable measurements of forest cover change and biomass will be required. In Papua New Guinea (PNG), which has one of the world's largest remaining areas of tropical forest, we used the best available data to estimate rainforest carbon stocks, and emissions from deforestation and degradation. We collated all available PNG field measurements which could be used to estimate carbon stocks in logged and unlogged forest. We extrapolated these plot-level estimates across the forested landscape using high-resolution forest mapping. We found the best estimate of forest carbon stocks contained in logged and unlogged forest in 2002 to be 4770 Mt (+/-13%). Our best estimate of gross forest carbon released through deforestation and degradation between 1972 and 2002 was 1178 Mt (+/-18%). By applying a long-term forest change model, we estimated that the carbon loss resulting from deforestation and degradation in 2001 was 53 Mt (+/-18%), rising from 24 Mt (+/-15%) in 1972. Forty-one percent of 2001 emissions resulted from logging, rising from 21% in 1972. Reducing emissions from logging is therefore a priority for PNG. The large uncertainty in our estimates of carbon stocks and fluxes is primarily due to the dearth of field measurements in both logged and unlogged forest, and the lack of PNG logging damage studies. Research priorities for PNG to increase the accuracy of forest carbon stock assessments are the collection of field measurements in unlogged forest and more spatially explicit logging damage studies.

Enhancing forest carbon sequestration in China: toward an integration of scientific and socio-economic perspectives

This article serves as an introduction to this special issue, "China's Forest Carbon Sequestration", representing major results of a project sponsored by the Canadian International Development Agency and the Chinese Academy of Sciences. China occupies a pivotal position globally as a principle emitter of carbon dioxide, as host to some of the world's largest reforestation efforts, and as a key player in international negotiations aimed at reducing global greenhouse gas emission. The goals of this project are to develop remote sensing approaches for quantifying forest carbon balance in China in a transparent manner, and information and tools to support land-use decisions for enhanced carbon sequestration (CS) that are science based and economically and socially viable. The project consists of three components: (i) remote sensing and carbon modeling, (ii) forest and soil assessment, and (iii) integrated assessment of the socio-economic implications of CS via forest management. Articles included in this special issue are highlights of the results of each of these components.