Large Carbon Stocks Research Articles

New insights on above ground biomass and forest attributes in tropical montane forests

Despite the potential of tropical montane forests to store and sequester substantial amounts of carbon, little is known about the above ground biomass (AGB) and the factors affecting it in these ecosystems, especially in Africa. We investigated the height-diameter allometry, AGB, and related differences in AGB to taxonomic and structural forest attributes in three distinct forest types (dry, mixed species and elfin) in three mountains of northern Kenya. We established 24 permanent plots (20m×100m) and sampled all trees ≥10cm diameter following standard Rainfor protocols.We identified that different height-diameter allometric models could be used for different forests types, with the exception of the Michaelis–Menten model. In our study area, model choice had little effects on AGB estimates.In general, mixed forests had greater AGB than other forest types: in Mt Nyiro AGB estimates were 611, 408 and 241Mgha−1 for mixed, elfin and dry forests respectively. Forests in Mt Nyiro, the highest mountain had greater AGB than in the other mountains. In our study area, differences in AGB were related to forest structure attributes, with little influence of taxonomic attributes. The mixed and elfin forests in Mt Nyiro, dominated by Podocarpus latifolius and Faurea saligna contained comparable AGB to lowland rainforests, highlighting the importance of tropical montane forests as large carbon stock, which could be released if converted to another land cover type.

Increased nitrous oxide emissions from Arctic peatlands after permafrost thaw

Permafrost in the Arctic is thawing, exposing large carbon and nitrogen stocks for decomposition. Gaseous carbon release from Arctic soils due to permafrost thawing is known to be substantial, but growing evidence suggests that Arctic soils may also be relevant sources of nitrous oxide (N2O). Here we show that N2O emissions from subarctic peatlands increase as the permafrost thaws. In our study, the highest postthaw emissions occurred from bare peat surfaces, a typical landform in permafrost peatlands, where permafrost thaw caused a fivefold increase in emissions (0.56 ± 0.11 vs. 2.81 ± 0.6 mg N2O m-2 d-1). These emission rates match those from tropical forest soils, the world's largest natural terrestrial N2O source. The presence of vegetation, known to limit N2O emissions in tundra, did decrease (by ∼90%) but did not prevent thaw-induced N2O release, whereas waterlogged conditions suppressed the emissions. We show that regions with high probability for N2O emissions cover one-fourth of the Arctic. Our results imply that the Arctic N2O budget will depend strongly on moisture changes, and that a gradual deepening of the active layer will create a strong noncarbon climate change feedback.

Assessing the risk of carbon dioxide emissions from blue carbon ecosystems

“Blue carbon” ecosystems, which include tidal marshes, mangrove forests, and seagrass meadows, have large stocks of organic carbon (Corg) in their soils. These carbon stocks are vulnerable to decomposition and – if degraded – can be released to the atmosphere in the form of CO2. We present a framework to help assess the relative risk of CO2 emissions from degraded soils, thereby supporting inclusion of soil Corg into blue carbon projects and establishing a means to prioritize management for their carbon values. Assessing the risk of CO2 emissions after various kinds of disturbances can be accomplished through knowledge of both the size of the soil Corg stock at a site and the likelihood that the soil Corg will decompose to CO2.

Estimating Large Area Forest Carbon Stocks—A Pragmatic Design Based Strategy

Reducing uncertainty in forest carbon estimates at local and regional scales has become increasingly important due to the centrality of the terrestrial carbon cycle in issues of climate change. In Victoria, Australia, public natural forests extend over 7.2 M ha and constitute a significant and important carbon stock. Recently, a wide range of approaches to estimate carbon stocks within these forests have been developed and applied. However, there are a number of data and estimation limitations associated with these studies. In response, over the last five years, the State of Victoria has implemented a pragmatic plot-based design consisting of pre-stratified permanent observational units located on a state-wide grid. Using the ground sampling grid, we estimated aboveground and belowground carbon stocks (including soil to 0.3 m depth) in both National Parks and State Forests, across a wide range of bioregions. Estimates of carbon stocks and associated uncertainty were conducted using simple design based estimators. We detected significantly more carbon in total aboveground and belowground components in State Forests (408.9 t ha−1, 95% confidence interval 388.8–428.9 t ha−1) than National Parks (267.6 t ha−1, 251.9–283.3 t ha−1). We were also able to estimate forest carbon stocks (and associated uncertainty) for 21 strata that represent all of Victoria’s bioregions and public tenures. It is anticipated that the lessons learnt from this study may support the discussion on planning and implementing low cost large area forest carbon stock sampling in other jurisdictions.

Accounting for harvested wood products in a forest offset program: Lessons from California

Carbon offset programs, such as that overseen by the California Air Resources Board (CA ARB), have emerged as a strategy for climate change mitigation. Offset projects sequestering carbon earn credits that can be traded on the Cap-and-Trade market to compensate for carbon emissions. The carbon stock embodied in harvested wood products can make up a substantial portion of the sequestered carbon in forest offset projects. In this paper we investigate the sensitivity of the calculations for the number of credits allocated to a forest offset project in the California system. We also examine how alternative models for the decay of harvested wood products might better reflect the dynamics of both the lifetime and cascade chain progression of the products and how this might change the amount of credits earned. The results suggest improved data collection and refinement in methodology would help to improve accuracy and reduce uncertainty in a large and important carbon stock. We conclude with offering suggestions on how an understanding of the dependence of harvested wood product stocks on life cycle parameters might affect the economics of offset programs and assist targeted mitigation efforts.

Variability of fire carbon emissions in equatorial Asia and its nonlinear sensitivity to El Niño

AbstractThe large peatland carbon stocks in the land use change‐affected areas of equatorial Asia are vulnerable to fire. Combining satellite observations of active fire, burned area, and atmospheric concentrations of combustion tracers with a Bayesian inversion, we estimated the amount and variability of fire carbon emissions in equatorial Asia over the period 1997–2015. Emissions in 2015 were of 0.51 ± 0.17 Pg carbon—less than half of the emissions from the previous 1997 extreme El Niño, explained by a less acute water deficit. Fire severity could be empirically hindcasted from the cumulative water deficit with a lead time of 1 to 2 months. Based on CMIP5 climate projections and an exponential empirical relationship found between fire carbon emissions and water deficit, we infer a total fire carbon loss ranging from 12 to 25 Pg by 2100 which is a significant positive feedback to climate warming.

Are global mangrove carbon stocks driven by rainfall?

AbstractMangrove forests produce significant amounts of organic carbon and maintain large carbon stocks in tidally inundated, anoxic soils. This work analyzes new and published data from 17 regions spanning a latitudinal gradient from 22°N to 38°S to assess some of the global drivers (temperature, tidal range, latitude, and rainfall) of mangrove carbon stocks. Mangrove forests from the tropics have larger carbon stocks (895 ± 90 t C ha−1) than the subtropics and temperate regions (547 ± 66 t C ha−1). A multiple regression model showed that 86% of the observed variability is associated with annual rainfall, which is the best predictor of mangrove ecosystem carbon stocks. Therefore, a predicted increase in rainfall along the tropical Indo‐Pacific may increase mangrove forest carbon stocks. However, there are other potentially important factors that may regulate organic matter diagenesis, such as nutrient availability and pore water salinity. Our predictive model shows that if mangrove deforestation is halted, global mangrove forest carbon stocks could increase by almost 10% by 2115 as a result of increased rainfall in the tropics.

Experimental warming in a dryland community reduced plant photosynthesis and soil CO2 efflux although the relationship between the fluxes remained unchanged

Summary Drylands represent our planet's largest terrestrial biome and, due to their extensive area, maintain large stocks of carbon (C). Accordingly, understanding how dryland C cycling will respond to climate change is imperative for accurately forecasting global C cycling and future climate. However, it remains difficult to predict how increased temperature will affect dryland C cycling, as substantial uncertainties surround the potential responses of the two main C fluxes: plant photosynthesis and soil CO2 efflux. In addition to a need for an improved understanding of climate effects on individual dryland C fluxes, there is also notable uncertainty regarding how climate change may influence the relationship between these fluxes. To address this important knowledge gap, we measured a growing season's in situ photosynthesis, plant biomass accumulation and soil CO2 efflux of mature Achnatherum hymenoides (a common and ecologically important C3 bunchgrass growing throughout western North America) exposed to ambient or elevated temperature (+2 °C above ambient, warmed via infrared lamps) for 3 years. The 2 °C increase in temperature caused a significant reduction in photosynthesis, plant growth and soil CO2 efflux. Of important note, photosynthesis and soil respiration appeared tightly coupled and the relationship between these fluxes was not altered by the elevated temperature treatment, suggesting C fixation's strong control of both above‐ground and below‐ground dryland C cycling. Leaf water use efficiency was substantially increased in the elevated temperature treatment compared to the control treatment. Taken together, our results suggest notable declines in photosynthesis with relatively subtle warming, reveal strong coupling between above‐ and below‐ground C fluxes in this dryland and highlight temperature's strong effect on fundamental components of dryland C and water cycles.

Substantial role of macroalgae in marine carbon sequestration

Marine macroalgae are dominant primary producers in coastal zones. A review of the published literature suggests that macroalgae may play an important role in carbon sequestration. Vegetated coastal habitats have been identified as important carbon sinks. In contrast to angiosperm-based habitats such as seagrass meadows, salt marshes and mangroves, marine macroalgae have largely been excluded from discussions of marine carbon sinks. Macroalgae are the dominant primary producers in the coastal zone, but they typically do not grow in habitats that are considered to accumulate large stocks of organic carbon. However, the presence of macroalgal carbon in the deep sea and sediments, where it is effectively sequestered from the atmosphere, has been reported. A synthesis of these data suggests that macroalgae could represent an important source of the carbon sequestered in marine sediments and the deep ocean. We propose two main modes for the transport of macroalgae to the deep ocean and sediments: macroalgal material drifting through submarine canyons, and the sinking of negatively buoyant macroalgal detritus. A rough estimate suggests that macroalgae could sequester about 173 TgC yr−1 (with a range of 61–268 TgC yr−1) globally. About 90% of this sequestration occurs through export to the deep sea, and the rest through burial in coastal sediments. This estimate exceeds that for carbon sequestered in angiosperm-based coastal habitats.

Seagrass, mangrove and saltmarsh sedimentary carbon stocks in an urban estuary; Coffs Harbour, Australia

Coastal vegetation (seagrass, mangrove and saltmarsh) termed “blue carbon” systems have recently been noted for their potentially large carbon storage capacities. This study quantifies sedimentary blue carbon stocks in an urban estuary containing seagrass (Zostera muelleri), mangrove (Avicennia marina), and saltmarsh (Sporobolus virginicus) habitats in the Coffs Creek Estuary (NSW, Australia). The objective of this study is to investigate the carbon storage dynamics, including the evaluation of potential influences from the plant cover and geomorphology. The sediment carbon stock results presented in this work show that mangroves store more carbon, 1070 ± 827 compared to 858 ± 190 and 365 ± 255 Mg ha−1 than saltmarsh and seagrass, respectively. These results are of interest because in Coffs Creek alone, mangroves have expanded (in area) by more than 25% from 1986 to 2011. The large sediment carbon stocks found in this urban system emphasize the benefits of restoring and protecting these ecosystems as a way of offsetting atmospheric carbon dioxide (CO2) emissions.

Integrating peatlands into the coupled Canadian Land Surface Scheme (CLASS) v3.6 and the Canadian Terrestrial Ecosystem Model (CTEM) v2.0

Abstract. Peatlands, which contain large carbon stocks that must be accounted for in the global carbon budget, are poorly represented in many earth system models. We integrated peatlands into the coupled Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM), which together simulate the fluxes of water, energy, and CO2 at the land surface–atmosphere boundary in the family of Canadian Earth system models (CanESMs). New components and algorithms were added to represent the unique features of peatlands, such as their characteristic ground floor vegetation (mosses), the slow decomposition of carbon in the water-logged soils and the interaction between the water, energy, and carbon cycles. This paper presents the modifications introduced into the CLASS–CTEM modelling framework together with site-level evaluations of the model performance for simulated water, energy and carbon fluxes at eight different peatland sites. The simulated daily gross primary production (GPP) and ecosystem respiration are well correlated with observations, with values of the Pearson correlation coefficient higher than 0.8 and 0.75 respectively. The simulated mean annual net ecosystem production at the eight test sites is 87 g C m−2 yr−1, which is 22 g C m−2 yr−1 higher than the observed annual mean. The general peatland model compares well with other site-level and regional-level models for peatlands, and is able to represent bogs and fens under a range of climatic and geographical conditions.

Changes in carbon storage with land management promoted by payment for ecosystem services

SUMMARYAndean grasslands (páramos) are highly valued for their role in regional water supply as well as for their biodiversity and large soil carbon stocks. Several Payment for Ecosystem Services (PES) programmes promote either afforestation or alteration of traditional burning regimes under the assumption that these land management strategies will maximize páramo ecosystem services, including carbon storage. However, knowledge of the effects of incentivized land uses is limited. In an evaluation of how afforestation and elimination of burning affect carbon storage at a site in southern Ecuador, we found the highest above-ground biomass carbon levels at afforested sites (99.3–122.0 t C ha−1), while grassland sites reached 23.9 t C ha−1after 45 years of burn exclusion. Soil carbon storage from 0–20 cm was high across all sites (172.8–201.9 t C ha−1), but was significantly lower with afforestation than with burn exclusion. These findings suggest that, although afforestation is generally favoured when carbon is the primary ecosystem service of interest, grasslands with infrequent burning have important potential as a land management strategy when both above-ground biomass and soil carbon are considered. These results are relevant to the development and adaptation of PES programmes focused on carbon as well as those focused on multiple ecosystem services.

Heterogeneity of carbon loss and its temperature sensitivity in East-European subarctic tundra soils.

Arctic peatlands store large stocks of organic carbon which are vulnerable to the climate change but their fate is uncertain. There is increasing evidence that a part of it will be lost as a result of faster microbial mineralization. We studied the vulnerability of 3500-5900 years old bare peat uplifted from permafrost layers by cryogenic processes to the surface of an arctic peat plateau. We aimed to find biotic and abiotic drivers of CLOSS from old peat and compare them with those of adjacent, young vegetated soils of the peat plateau and mineral tundra. The soils were incubated in laboratory at three temperatures (4°C, 12°C and 20°C) and two oxygen levels (aerobic, anaerobic). CLOSS was monitored and soil parameters (organic carbon quality, nutrient availability, microbial activity, biomass and stoichiometry, and extracellular oxidative and hydrolytic enzyme pools) were determined. We found that CLOSS from the old peat was constrained by low microbial biomass representing only 0.22% of organic carbon. CLOSS was only slightly reduced by the absence of oxygen and exponentially increased with temperature, showing the same temperature sensitivity under both aerobic and anaerobic conditions. We conclude that carbon in the old bare peat is stabilized by a combination of physical, chemical and biological controls including soil compaction, organic carbon quality, low microbial biomass and the absence of plants.

MODELLING THE CARBON STOCKS ESTIMATION OF THE TROPICAL LOWLAND DIPTEROCARP FOREST USING LIDAR AND REMOTELY SENSED DATA

Abstract. Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland Dipterocarp forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p < 0.01) with correlation coefficient (r) is 0.909 which shown that there a good relationship between carbon and DBH predictors to improve the inventory estimates of carbon using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland Dipterocarp forest.

MODELLING THE CARBON STOCKS ESTIMATION OF THE TROPICAL LOWLAND DIPTEROCARP FOREST USING LIDAR AND REMOTELY SENSED DATA

Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland <i>Dipterocarp</i> forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p < 0.01) with correlation coefficient (r) is 0.909 which shown that there a good relationship between carbon and DBH predictors to improve the inventory estimates of carbon using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland <i>Dipterocarp</i> forest.

Legacy effects of grassland management on soil carbon to depth.

The importance of managing land to optimize carbon sequestration for climate change mitigation is widely recognized, with grasslands being identified as having the potential to sequester additional carbon. However, most soil carbon inventories only consider surface soils, and most large-scale surveys group ecosystems into broad habitats without considering management intensity. Consequently, little is known about the quantity of deep soil carbon and its sensitivity to management. From a nationwide survey of grassland soils to 1m depth, we show that carbon in grassland soils is vulnerable to management and that these management effects can be detected to considerable depth down the soil profile, albeit at decreasing significance with depth. Carbon concentrations in soil decreased as management intensity increased, but greatest soil carbon stocks (accounting for bulk density differences), were at intermediate levels of management. Our study also highlights the considerable amounts of carbon in subsurface soil below 30cm, which is missed by standard carbon inventories. We estimate grassland soil carbon in Great Britain to be 2097TgC to a depth of 1m, with ~60% of this carbon being below 30cm. Total stocks of soil carbon (tha(-1) ) to 1m depth were 10.7% greater at intermediate relative to intensive management, which equates to 10.1tha(-1) in surface soils (0-30cm), and 13.7tha(-1) in soils from 30 to 100cm depth. Our findings highlight the existence of substantial carbon stocks at depth in grassland soils that are sensitive to management. This is of high relevance globally, given the extent of land cover and large stocks of carbon held in temperate managed grasslands. Our findings have implications for the future management of grasslands for carbon storage and climate mitigation, and for global carbon models which do not currently account for changes in soil carbon to depth with management.

ABOVEGROUND BIOMASS AND CARBON STOCK ESTIMATION USING DOUBLE SAMPLING APPROACH AND REMOTELY-SENSED DATA

Tropical forest embraces a large stock of carbon and contributes to the enormous amount of aboveground biomass (AGB) in the global carbon cycle. In order to quantify the carbon inventory, field data is vital for accurately determining the forest parameter such as diameter at the breast height (DBH), height of the tree (h) ,crown diameter (CD) and tree species. The merging of the multi-sensory remote sensing which is LiDAR (Light Detection and Ranging) and very high resolution satellite imagery can reduce the labor intensive of field sampling for a large area of carbon inventory data. Double sampling approach which is combination of the field sampling plot measurement with ancillary remote sensing data used to improve the precision of AGB estimation compared by using field data alone. Hence, this study aims: (1) to describe the use of field data plots in a statistical way, and (2) to determine the potential of LiDAR data in a double sampling forest aboveground biomass and carbon stock inventories and (3) to compare the used of field data plot itself or combination with LiDAR data to quantify the aboveground biomass and carbon stock for upcoming inventories.

Future vegetation–climate interactions in Eastern Siberia: an assessment of the competing effects of CO<sub>2</sub> and secondary organic aerosols

Abstract. Disproportional warming in the northern high latitudes and large carbon stocks in boreal and (sub)arctic ecosystems have raised concerns as to whether substantial positive climate feedbacks from biogeochemical process responses should be expected. Such feedbacks occur when increasing temperatures lead, for example, to a net release of CO2 or CH4. However, temperature-enhanced emissions of biogenic volatile organic compounds (BVOCs) have been shown to contribute to the growth of secondary organic aerosol (SOA), which is known to have a negative radiative climate effect. Combining measurements in Eastern Siberia with model-based estimates of vegetation and permafrost dynamics, BVOC emissions, and aerosol growth, we assess here possible future changes in ecosystem CO2 balance and BVOC–SOA interactions and discuss these changes in terms of possible climate effects. Globally, the effects of changes in Siberian ecosystem CO2 balance and SOA formation are small, but when concentrating on Siberia and the Northern Hemisphere the negative forcing from changed aerosol direct and indirect effects become notable – even though the associated temperature response would not necessarily follow a similar spatial pattern. While our analysis does not include other important processes that are of relevance for the climate system, the CO2 and BVOC–SOA interplay serves as an example for the complexity of the interactions between emissions and vegetation dynamics that underlie individual terrestrial processes and highlights the importance of addressing ecosystem–climate feedbacks in consistent, process-based model frameworks.

Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models

Alpine ecosystems like the Qinghai-Tibet Plateau strongly respond to global warming. Their soils, containing large carbon stocks, release more carbon dioxide as a possible consequence. Reciprocally, this may intensify climate warming. The Qinghai-Tibet plateaús large and almost inaccessible terrain results in a general data scarcity for this area making the quantification of soil carbon dynamics challenging. The current study provides an area-wide estimation of soil respiration for the Qinghai-Tibet Plateau, which is a key region for climate change studies due to its size and sensitivity. We compared the ability of six regression models to predict soil respiration that were developed within different studies and are based on mean annual air temperature, mean annual precipitation and belowground biomass. We used the WorldClim data sets to approximate annual soil respiration on a regional scale. Compared to field measurements of soil respiration at single spots in different vegetation zones on the Qinghai-Tibet Plateau (max. 1876.63gCm−2year−1), our predicted results (max. 1765.13gCm−2year−1) appear to be consistent. The basic difference between grasslands and forests in soil respiration is indicated by all regression models, however, a more precise differentiation between vegetation types is only exhibited by the regression model based on mean annual precipitation. Overall, this model performs best for most and the largest vegetation zones. Nevertheless, the approximations of the model based on mean annual temperature by Raich and Schlesinger (1992) with a lower constant better represent the vegetation zone of the alpine steppe. With this spatial estimation of soil respiration at a regional scale, a basis for assessing an area-specific potential of greenhouse gas emissions on the Qinghai-Tibet Plateau is provided. Moreover, we quantify a complex soil ecological process for this data-scarce area.

Effects of Stand Origin and Near-Natural Restoration on the Stock and Structural Composition of Fallen Trees in Mid-Subtropical Forests

Fallen trees comprise an important part of forest ecosystems and serve a central role in maintaining the biodiversity and tree regeneration of forests. However, the effects of stand origin and near-natural restoration on the biomass and carbon stock of fallen trees remain unclear. Based on 60 sampling plots of field surveys of mid-subtropical forests in Jiangxi Province, we investigated the stock and structural composition of fallen trees in artificial coniferous forests (Acf), natural coniferous forests (Ncf) (e.g., different stand origins) and natural evergreen broadleaf forests (Nebf) (e.g., near-natural restoration). The following results were obtained: (1) the largest biomass and carbon stocks of fallen trees among three forest types (Nebf, Ncf and Acf) were measured for Nebf; (2) the fallen tree biomass and carbon stock in natural Cunninghamia lanceolata forest (Nclf) were significantly larger than that in artificial Cunninghamia lanceolata forest (Aclf), and the fallen tree biomass and carbon stock in natural Pinus massoniana forest (Npf) were also significantly larger than those in artificial Pinus massoniana forest (Apf); (3) the diameter class allocation in natural forests was more uniform than that in artificial forests; (4) the biomass of fallen trees with mild decay was not significantly different among forest types within stand origin or among the stand origin within forest types; however, the biomass of fallen trees with moderate and heavy decay significantly differed among stand origin (Aclf vs. Nclf, Apf vs. Npf), but was not significant among the forest types (Aclf vs. Apf, Nclf vs. Apf) within a stand origin. Our results suggested that the large biomass and carbon stock of fallen trees in Nebf may serve a significant role in mitigating global warming and carbon cycles in mid-subtropical forests. Therefore, stand origin and near-natural restoration exert significant effects on the carbon stock and structural composition of fallen trees in mid-subtropical forests.