Carbon cycling of Chinese forests: From carbon storage, dynamics to models

He, Jin‐Sheng

doi:10.1007/s11427-012-4285-z

Cited by 14 publications

(8 citation statements)

References 16 publications

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“…Biomass estimates are a prerequisite for precisely quantifying forest carbon stocks and their dynamics [7,8], and accurate quantification of forest biomass is therefore of great importance. Estimating tree and forest biomass is also essential for informing greenhouse gas mitigation [9,10], and forest ecosystem services such as wildlife habitat and timber [11,12].…”

Section: Introductionmentioning

confidence: 99%

Aboveground Biomass Allocation and Additive Allometric Models for Natural Larix gmelinii in the Western Daxing’anling Mountains, Northeastern China

Meng

Jia

Liu

et al. 2019

Forests

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Accurate estimates of tree component and aboveground biomass strongly depend on robust and precise allometric equations. However, site-specific and suitable biomass equations are currently scarce for natural Larix gmelinii forests in the western Daxing’anling Mountains, northeastern China. This study aimed to evaluate the biomass allocation patterns within tree components and develop additive allometric biomass equations for species of L. gmelinii. A total of 58 trees were destructively sampled and measured for wood (inside bark), bark, branch and leaf biomass. For each component, we assessed the share of biomass allocated to different components by computing its ratio; we also tested two allometric equations based on diameter at breast height (dbh) alone, and dbh fitted with height (h) as independent variables. Seemingly unrelated regression methodology was used to fit an additive system of biomass allometric equations. We performed an independent dataset to evaluate the predictive ability of the best model system. The results revealed that wood biomass accounted for approximately 60% of the aboveground biomass. Wood and branch biomass ratios increased with increasing dbh, while a reverse trend was observed for bark and leaf biomass ratios. All models showed good fitting results with Adj.R2 = 0.958–0.995. Tree dbh provided the lowest estimation errors in the regressions associated with branches and leaves, while dbh2 × h generated the most precise models for stems (wood and bark). We conclude that these allometric equations will accurately predict biomass for Larix trees in the western Daxing’anling Mountains.

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Section: Introductionmentioning

confidence: 99%

Aboveground Biomass Allocation and Additive Allometric Models for Natural Larix gmelinii in the Western Daxing’anling Mountains, Northeastern China

Meng

Jia

Liu

et al. 2019

Forests

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“…Accurately identifying the spatial patterns and controlling mechanisms of forest C storage is important because enhancing their storage is considered the most effective and economical approach to partially sequestering anthropogenic CO 2 emissions (Fang et al, 2007;Gower, 2003;Houghton, 2005). Although some studies have demonstrated that, on a regional scale, vegetation C storage in forests reduces with increasing latitude, while soil C storage increases (He, 2012;Wang et al, 2001a;Wei et al, 2013;Zhou et al, 2000); most studies have focused on vegetation C storage or soil C storage separately, primarily due to the limitations of data sources. Therefore, the spatial patterns of forest C storage therefore remain unclear at large scales (Davidson et al, 2000;Kato and Tang, 2008;Liu et al, 2012;Prentice and Fung, 1990).…”

Section: Introductionmentioning

confidence: 99%

Forest carbon storage along the north-south transect of eastern China: Spatial patterns, allocation, and influencing factors

Wen

2016

Ecological Indicators

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a b s t r a c tForests play an important role in sequestrating atmospheric CO 2 ; therefore, understanding the spatial variations and controlling mechanisms of forest carbon (C) storage is important. In this study, we collected data on forest C storage along a north-south transect of eastern China from literature published between 2004 and 2014. The collected data, which were from over 2000 plots, allowed us to explore the latitudinal patterns in forest C storage. The results showed that vegetation C storage decreased with increasing latitude, while soil C storage increased. This spatial pattern of vegetation C storage was more apparent for mature forests (forest age > 80 years). Furthermore, latitudinal patterns in forest C storage, both in vegetation and in soil, became stronger with increasing statistical scale, increasing from plot scale to latitudinal scale (2-5• ). However, total forest C storage (vegetation + soil) had no apparent latitudinal pattern. Interestingly, the allocation ratios of forest C storage between vegetation and soil had a negative logarithmic relationship with latitude. These results suggest that in eastern China, climatic factors control latitudinal patterns in the forest C storage of vegetation and soil, albeit in different ways (positive for vegetation and negative for soil), and also control the allocation ratios of forest C storage between vegetation and soil. Furthermore, the latitudinal patterns of forest C storage were opposite for vegetation and soil, resulting from the different climatic controlling mechanism.

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“…Lun et al [26] studied the influence of the biological cycle and the industrial cycle on the forest carbon cycle and proposed measures for carbon emission reduction. He [27] explored China's carbon cycle of the forest ecological system from the viewpoint of the reserve, dynamics and development pattern.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling on Regional Atmosphere-Soil-Land Plant Carbon Cycle Dynamic System

Tian

Dong

et al. 2016

Sustainability

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This paper establishes a nonlinear carbon cycle model based on the analysis of the carbon flux relationship among the atmosphere cycle, soil cycle and land cycle. By using nonlinear dynamics method, we examine the regional carbon cycle evolution along with the temporal evolution of the regional carbon flux. A neural network has been employed to identify the parameters of the proposed model, accordingly. In the numerical study, we propose the atmosphere-soil-land cycle model for Nanjing city of China. Then, the carbon cycle evolution of Nanjing has been simulated with the given model and actual data.

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Carbon cycling of Chinese forests: From carbon storage, dynamics to models

Cited by 14 publications

References 16 publications

Aboveground Biomass Allocation and Additive Allometric Models for Natural Larix gmelinii in the Western Daxing’anling Mountains, Northeastern China

Aboveground Biomass Allocation and Additive Allometric Models for Natural Larix gmelinii in the Western Daxing’anling Mountains, Northeastern China

Forest carbon storage along the north-south transect of eastern China: Spatial patterns, allocation, and influencing factors

Modeling on Regional Atmosphere-Soil-Land Plant Carbon Cycle Dynamic System

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