Forest Vegetation Carbon Research Articles

Study on the Synergistic Effects of Karst Carbon Sink and Vegetation Carbon Sink in Watersheds under Different Geological Backgrounds—A Case Study of Darongjiang and Lingqu Watersheds

In this study, the hydrochemistry-runoff method and remote sensing estimation method were used to calculate the karst carbon sink flux (KCSF) and the forest vegetation carbon sequestration flux (FVCSF) in Darongjiang (DRJ) and Lingqu (LQ) watersheds. The results show the following: (1) The KCSF in DRJ and LQ watersheds is 238.43 × 105 t·y−1 and 353.44 × 105 t·y−1, respectively. Influenced by changes in flow rate, the two watersheds both show that their KCSF is higher in the rainy season than in the dry season. (2) The FVCSF in DRJ and LQ watersheds was 680.78 × 107 t·y−1 and 229.63 × 107 t·y−1, respectively. Through comparison, it can be seen that the FVCSF is much higher than the KCSF in both watersheds, but the FVCSF and the KCSF are at the same order of magnitude. (3) Through further analysis of the influence factors on the FVCSF and the KCSF, we found that the highest values of FVCSF are mainly distributed around Kitten Mountain on the upper reach and along the LQ watershed. That may be because most of the upper reach areas are mountainous forestland, and the strong weathering of rocks in the LQ watershed promotes the development of forest vegetation carbon sequestration. Therefore, it can be inferred that there is a certain synergistic effect between the karst carbon sink (KCS) and the forest vegetation carbon sequestration (FVCS) in the study area, and such a synergistic effect is caused by rock weathering.

How does energy utilization affect rural sustainability development in traditional villages? Re-examination from the coupling coordination degree of atmosphere-ecology-socioeconomics system

In the face of global environmental challenges and China's commitment to achieving carbon neutrality, understanding the impact of energy transition in rural areas, particularly in traditional villages, becomes crucial for sustainable development. Based on 703 traditional villages in Hunan Province from 2005 to 2020, this study conducts a comprehensive spatiotemporal analysis of energy utilization, and analyzes the influence of energy utilization on the coupling coordination of the Atmosphere-Ecology-Socioeconomics System. The findings reveal a fluctuating trend in traditional villages' coupling coordination degree (CCD), particularly higher in western Hunan Province, and a notable reduction in regional disparities over time. The traditional villages' atmospheric conditions are better than the social and ecological conditions, which reflects the importance of improving socioeconomics and ecological subsystems for coupling coordination development. The study identifies that all seven energy utilization factors have positive effects on CCD. Forest vegetation carbon stocks and total energy consumption are critical drivers of CCD, highlighting spatial heterogeneity in their impacts on the CCD across different regions. Additionally, from 2005 to 2020, the effects of Forest Understory Vegetation Carbon Stocks on coupling coordination changed from widespread to localized, while Total Energy Consumption's impact was consistently localized. This paper reevaluates the role of energy management in enhancing the quality of traditional village habitats and offers valuable insights into environmental management and sustainable development in traditional villages, providing compelling evidence for policymakers.

Shedding light on the increased carbon uptake by a boreal forest under diffuse solar radiation across multiple scales.

Solar radiation is scattered by cloud cover, aerosols and other particles in the atmosphere, all of which are affected by global changes. Furthermore, the diffuse fraction of solar radiation is increased by more frequent forest fires and likewise would be if climate interventions such as stratospheric aerosol injection were adopted. Forest ecosystem studies predict that an increase in diffuse radiation would result in higher productivity, but ecophysiological data are required to identify the processes responsible within the forest canopy. In our study, the response of a boreal forest to direct, diffuse and heterogeneous solar radiation conditions was examined during the daytime in the growing season to determine how carbon uptake is affected by radiation conditions at different scales. A 10-year data set of ecosystem, shoot and forest floor vegetation carbon and water-flux data was examined. Ecosystem-level carbon assimilation was higher under diffuse radiation conditions in comparison with direct radiation conditions at equivalent total photosynthetically active radiation (PAR). This was driven by both an increase in shoot and forest floor vegetation photosynthetic rate. Most notably, ecosystem-scale productivity was strongly related to the absolute amount of diffuse PAR, since it integrates both changes in total PAR and diffuse fraction. This finding provides a gateway to explore the processes by which absolute diffuse PAR enhances productivity, and the long-term persistence of this effect under scenarios of higher global diffuse radiation.

Thinning increases forest ecosystem carbon stocks

Thinning, a major measure of forest management, is known to alter carbon sequestration by affecting the forest microclimate and soil environmental conditions. However, how thinning effect on forest ecosystem carbon stocks have presented inconsistent results. Therefore, we conducted 1776 pairs of thinning experiment observations worldwide to explore how thinning affects forest vegetation and soil carbon stocks. The results showed that overall thinning significantly increased total tree aboveground biomass carbon stocks (AGCtotal, +23.9%, +1.3 Mg ha-1 yr-1), understory vegetation carbon stocks (UVC, +68.3%, 0.12 Mg ha-1 yr-1), and soil organic carbon stocks (SOCstocks, +4.8%, 1.0 Mg ha-1 yr-1) at the global, but exhibited significantly decreased carbon stocks of litterfall (LBC, –9.6%, –0.03 Mg ha-1 yr-1). Belowground biomass carbon stocks remained unchanged under thinning. The sensitivity of carbon sequestration to thinning gradually disappeared after 6 years, except for AGCtotal, as they were jointly subject to stand density and thinning intensity and not just recovery ages. The response to UVC was more positive in medium-density (1500 – 3000 trees ha-1) and moderately thinned (30 – 50%) stands, and the thinning effects on UVC and SOCstocks were more noticeable in the subtropical and temperate zones. In summary, thinning enhanced forest ecosystem carbon sinks (+2.4 Mg ha-1 yr-1) but reduced carbon stocks in low-density stands (≤ 1500 trees ha-1). Soil moisture content (SMC, +6.6%) and bulk density (BD, –1.5%) dynamics after thinning were important factors regulating vegetation growth and soil carbon cycling processes.

Learning ensembles of process-based models for high accurately evaluating the one-hundred-year carbon sink potential of China’s forest ecosystem

China’s forests play a vital role in the global carbon cycle through the absorption of atmospheric CO2 to mitigate climate change caused by the increase of anthropogenic CO2. It is essential to evaluate the carbon sink potential (CSP) of China’s forest ecosystem. Combining NDVI, field-investigated, and vegetation and soil carbon density data modeled by process-based models, we developed the state-of-the-art learning ensembles model of process-based models (the multi-model random forest ensemble (MMRFE) model) to evaluate the carbon stocks of China’s forest ecosystem in historical (1982–2021) and future (2022–2081, without NDVI-driven data) periods. Meanwhile, we proposed a new carbon sink index (CSindex) to scientifically and accurately evaluate carbon sink status and identify carbon sink intensity zones, reducing the probability of random misjudgments as a carbon sink. The new MMRFE models showed good simulation results in simulating forest vegetation and soil carbon density in China (significant positive correlation with the observed values, r = 0.94, P < 0.001). The modeled results show that a cumulative increase of 1.33 Pg C in historical carbon stocks of forest ecosystem is equivalent to 48.62 Bt CO2, which is approximately 52.03% of the cumulative increased CO2 emissions in China from 1959 to 2018. In the next 60 years, China’s forest ecosystem will absorb annually 1.69 (RCP45 scenario) to 1.85 (RCP85 scenario) Bt CO2. Compared with the carbon stock in the historical period, the cumulative absorption of CO2 by China’s forest ecosystem in 2032–2036, 2062–2066, and 2077–2081 are approximately 11.25–39.68, 110.66–121.49 and 101.31–111.11 Bt CO2, respectively. In historical and future periods, the medium and strong carbon sink intensity regions identified by the historical CSindex covered 65% of the total forest area, cumulative absorbing approximately 31.60 and 65.83–72.22 Bt CO2, respectively. In the future, China’s forest ecosystem has a large CSP with a non-continuous increasing trend. However, the CSP should not be underestimated. Notably, the medium carbon sink intensity region should be the priority for natural carbon sequestration action. This study not only provides an important methodological basis for accurately estimating the future CSP of forest ecosystem but also provides important decision support for future forest ecosystem carbon sequestration action.

Forest Carbon Sequestration Potential in China under Different SSP-RCP Scenarios

The estimation of forest carbon sequestration and its economic value as a carbon sink are important elements of global carbon cycle research. In this study, based on the predicted forestland changes under the future shared socioeconomic pathways SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5, the growth equations of different tree species were fitted using forest inventory data, and the biomass conversion factor continuum function method was used to estimate forest vegetation carbon fixation at the national scale. The carbon sink potential of the forest ecosystems in 2020–2100 was estimated under the three scenarios. Under the three social scenarios, the fixed amount of forest carbon in China exhibits a significant upward trend. Forest area increases the most, and carbon sequestration increases the most rapidly under SSP1-RCP2.6. The carbon sequestration level in Southwest China is higher than in other parts of the country, and those in Northwest and East China are lower than the national average. In order to continuously improve the carbon sequestration capacity of terrestrial ecosystem resources in China, the following actions are recommended: strengthen the protection projects of natural forests in various regions, improve the level of forest management, and gradually achieve the goal of carbon neutrality in China.

Changes in Forest Vegetation Carbon Storage and Its Driving Forces in Subtropical Red Soil Hilly Region over the Past 34 Years: A Case Study of Taihe County, China

After decades of afforestation, China’s forest coverage has increased significantly, but the forest quality and its impact on ecosystem services are still controversial. Taking forest vegetation carbon storage as an example, most assessment results based on the national forest inventory data showed that the contribution of enlarged forest area to the increase in China’s forest vegetation carbon storage was higher than that of the change in forest quality (vegetation carbon density). This means that the increase in forest carbon storage in China was mostly contributed by the increase in forest area and was less due to the increased forest vegetation carbon density. However, the national forest inventory data are based on national permanent plots that may be protected or are less disturbed to some extent. Therefore, the contribution of the change in forest quality to the increase in forest vegetation carbon storage, as evaluated from the national forest inventory data, might be overestimated, especially in regions with frequent human activities. To test the hypothesis, we selected Taihe County, a typical representative of the red soil hilly region in subtropical China, where the population is dense, economic development is fast, and the forest has experienced destruction and re-establishment. To accurately assess the impact of changes in the forest area and forest quality on forest vegetation carbon storage variation in real situations, we collected and used a series of remote sensing images from 1986 to 2019, inventory data for forest management, and field data. The results showed that the forest area and forest vegetation carbon density increased from 10.85 × 104 ha and 17.89 Mg/ha in 1986 to 16.40 × 104 ha and 26.51 Mg/ha in 2019, with an increase of 51.11% and 48.23%, respectively. Meanwhile, the forest vegetation carbon storage increased by 123.99%, from 1.94 Tg in 1986 to 4.35 Tg in 2019, suggesting a significant carbon sequestration ability. Further analysis showed that the contributions of changes in forest area and forest quality to the forest vegetation carbon storage variation were 1.23 Tg (51.19%) and 1.17 Tg (48.81%), respectively. The result implies that the increase in forest area and forest quality almost contributed equally to the increase in forest vegetation carbon storage during the 34 years of vegetation restoration in Taihe County. However, forest vegetation carbon density controlled the variation of forest vegetation carbon storage in all three forest developing stages. The precision of our results was also tested with two inventory datasets for forest management in Taihe County in 2009 and 2019. The relative contribution of forest vegetation carbon density is lower than most of the previous study results using national forest inventory data in this region, indicating that the contribution of change in the forest vegetation carbon density to the forest vegetation carbon storage variation might be overestimated based on these national permanent plots, which were protected or less disturbed to some extent.

Impact of the Management Scale on the Technical Efficiency of Forest Vegetation Carbon Sequestration: A Case Study of State-Owned Forestry Enterprises in Northeast China

Improving the technical efficiency of forest vegetation carbon sequestration is an effective way to accelerate the pace and reduce the cost of carbon neutrality in China. Therefore, it is particularly important to explore the technical efficiency, influencing factors, and optimization paths of forest vegetation carbon sequestration. This work uses a 21-year panel data set (2000–2020) of 87 state-owned forestry enterprises (SOFEs) in Northeast China and combines geographic information system (GIS) and remote sensing (RS) technology. First, stochastic frontier analysis (SFA) was used to quantitatively analyze the technical efficiency of forest vegetation carbon sequestration in different SOFEs during different periods. Then, the individual fixed-effects model was used to examine the factors influencing technical efficiency under the control of climate factors. Finally, the panel threshold model was used to determine the impact of different management scales on the technical efficiency of forest vegetation carbon sequestration. The main results were as follows: technological progress can effectively reduce forestry investment and improve the technical efficiency of forest vegetation carbon sequestration production. There was technological progress in forest vegetation carbon sequestration production during the study period, but the rate of technological progress showed a decreasing trend. Forest management scale, total output value, employee wages, precipitation, and sun duration had a significant positive impact, whereas wood production had a significant negative impact on the technical efficiency of carbon sequestration. The impact of different management scales on the technical efficiency of carbon sequestration is highly heterogeneous. The study established an analytical framework for researching the technical efficiency and optimization of forest vegetation carbon sequestration, providing a theoretical and practical basis for forest management.

Spatial variation analysis of urban forest vegetation carbon storage and sequestration in built-up areas of Beijing based on i-Tree Eco and Kriging

To explore available methods for assessing the orientation, magnitude, and role of urban forests in abating climate change, i-Tree Eco and Kriging interpolation were employed to quantify and map the carbon storage and sequestration capability of trees in urban forests. Specifically, urban tree field data were collected from 981 sample plots throughout five types of urban forests in the built-up area of Beijing, China, and used to estimate carbon storage and sequestration within each individual plot and the area as a whole. These data were subsequently subjected to Kriging interpolation to map carbon storage and sequestration within the study area. The results showed that the carbon storage and sequestration patterns in the urban forests in Beijing exhibit noticeable spatial heterogeneity, and that there is a clear, statistically significant distribution of high and low value areas. Furthermore, urban planning, the degree of urbanization, and the urban forest structure effect the carbon spatial distribution. This work provides a reference for prudent planning and construction of urban forests and will aid decision-makers in designing eco-friendly urban environments.

Effects of Stand Structure and Topography on Forest Vegetation Carbon Density in Jiangxi Province

Stand structure and topography are important factors affecting forest vegetation carbon density (FVCD). Revealing the interaction mechanisms between stand structure and topography on FVCD is of great significance for enhancing forest vegetation carbon storage and achieving regional carbon neutrality. Based on stratified sampling, systematic distribution and forest continuous inventory sample plots in Jiangxi province, the variation characteristics of FVCD and its correlations with stand structure and topographic factors were studied. The results are as follows: (1) The average FVCD in Jiangxi province was 44.23 Mg/ha, which was dominated by the carbon density of the arbor layer, accounting for about 81.39% of the total forest—far lower than the average level of global FVCD, which proved that the forest in Jiangxi province was dominated by middle-age and young forests with low carbon density, and also showed that the potential for forest vegetation carbon storage in Jiangxi province was huge. (2) Except for vegetation carbon densities of shrub and herb layers, the vegetation carbon densities of other forest layers in Jiangxi province were significantly different among different forest types. Volume per unit area was the most important factor affecting the vegetation carbon densities of arbor and total forest, and vegetation carbon density–volume models of the main forests were built for vegetation carbon density calculation in Jiangxi province. (3) The vegetation carbon densities of arbor layer, snag and log layer, and total forest increased significantly with increases in elevation and slope. Except for the shrub layer and herb layer, the vegetation carbon densities of the other layers and the total forest had extremely significant or significant differences between slope position gradients—indicating that the effect of topography on FVCD in Jiangxi province was significant, mainly through influencing of forest distribution and human disturbance intensity.

Dynamic response of the vegetation carbon storage in the sanjiang plain to changes in land use/cover and climate

Large-scale human activities especially the destruction of forest land, grassland, and unused land result in a large amount of carbon release into the atmosphere and cause drastic changes in land use/cover in the Sanjiang Plain. As a climate change-sensitive and ecologically vulnerable area, the Sanjiang Plain ecosystem’s carbon cycle is affected by significant climate change. Therefore, it is important that studying the impact of the changes in land use/cover and climate on vegetation carbon storage in the Sanjiang Plain. Remote sensing, temperature, and precipitation data in four periods from 2001 to 2015 are used as bases in conducting an analysis of land use/cove types and spatio-temporal variation of vegetation carbon density and carbon storage in growing season using model and related analysis methods. Moreover, the impact of land use/cover change and climate change on vegetation carbon density and carbon storage is discussed. The findings are as follows. (1) Cultivated land in the Sanjiang Plain increased, while forest land, grassland and unused land generally decreased. (2) Vegetation carbon density increased, in which the average carbon density of cultivated land, grassland, and unused land varied insignificantly, while that of forest land increased continuously from 4.18 kg C/m2 in 2001 to 7.65 kg C/m2 in 2015. Vegetation carbon storage increased from 159.18 Tg C in 2001 to 256.83 Tg C in 2015, of which vegetation carbon storage of forest land contributed 94% and 97%, respectively. (3) Conversion of land use/cover types resulted in a 22.76-TgC loss of vegetation carbon storage. Although the forest land area decreased by 3389.5 km2, vegetation carbon storage in the research area increased by 97.65 Tg C owing to the increase of forest carbon density. (4) Pixel-by-pixel analysis showed that vegetation carbon storage in the majority of the areas of the Sanjiang Plain are negatively correlated with temperature and positively correlated with precipitation. The results showed that changes of land use/cover types and vegetation carbon density directly lead to a change in vegetation carbon storage, with the change of forest vegetation carbon density being the main driver affecting vegetation carbon storage variation. The increase of temperature mainly suppresses the vegetation carbon density, and the increase of precipitation mainly promotes it.

Linking Forest Vegetation and Soil Carbon Stock in Northwestern Russia

Research Highlights: It was found that both tree species and ground vegetation affected soil carbon stock in boreal forests. Carbon stocks in the mineral layers were related negatively to the C/N ratio in the organic horizon and pine proportion in the growing stock volume, and positively to the share of herbaceous plants and the proportion of spruce. Background and Objectives: Existing research showed the effects of tree species on soil carbon stocks in organic horizons, but these effects were less clear in mineral horizons. Little is known about the effects of ground vegetation on soil carbon stock. This study aims to identify associations between the forest vegetation composition and soil carbon stocks in northwestern Russia. Materials and Methods: Research data from 109 pine, spruce and birch forests of different Cajander’s and Sukachev’s types with different functional compositions of ground vegetation at autonomous positions are discussed in this paper. The V-test was used to assess the impact of vegetation on soil carbon stocks. Results: Variations in Carbon stocks in the mineral layers were associated with the soil types and vegetation composition. Carbic Albic Podzols accumulated the least amount of carbon in the mineral profile. Carbon stock in the mineral layers in pine forests was considerably lower than in spruce and birch forests. Spruce forests with the highest share of herbaceous plants were characterised by the highest carbon stocks in the mineral layers, while pine forests with dwarf shrubs and green mosses accumulated more carbon in the organic layers, but carbon stocks in the mineral layers here were the lowest. Conclusions: Differences in soil carbon stocks between and within northern and middle taiga in northwestern Russia were associated not only with soil types but also with the proportions of forest types dominated by different tree species and ground vegetation functional groups.

Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2

Abstract. Anthropogenic land-use and land-cover change activities play a critical role in Earth system dynamics through significant alterations to biogeophysical and biogeochemical properties at local to global scales. To quantify the magnitude of these impacts, climate models need consistent land-cover change time series at a global scale, based on land-use information from observations or dedicated land-use change models. However, a specific land-use change cannot be unambiguously mapped to a specific land-cover change. Here, nine translation rules are evaluated based on assumptions about the way land-use change could potentially impact land cover. Utilizing the Global Land-use Model 2 (GLM2), the model underlying the latest Land-Use Harmonization dataset (LUH2), the land-cover dynamics resulting from land-use change were simulated based on multiple alternative translation rules from 850 to 2015 globally. For each rule, the resulting forest cover, carbon density and carbon emissions were compared with independent estimates from remote sensing observations, U.N. Food and Agricultural Organization reports, and other studies. The translation rule previously suggested by the authors of the HYDE 3.2 dataset, that underlies LUH2, is consistent with the results of our examinations at global, country and grid scales. This rule recommends that for CMIP6 simulations, models should (1) completely clear vegetation in land-use changes from primary and secondary land (including both forested and non-forested) to cropland, urban land and managed pasture; (2) completely clear vegetation in land-use changes from primary forest and/or secondary forest to rangeland; (3) keep vegetation in land-use changes from primary non-forest and/or secondary non-forest to rangeland. Our analysis shows that this rule is one of three (out of nine) rules that produce comparable estimates of forest cover, vegetation carbon and emissions to independent estimates and also mitigate the anomalously high carbon emissions from land-use change observed in previous studies in the 1950s. According to the three translation rules, contemporary global forest area is estimated to be 37.42×106 km2, within the range derived from remote sensing products. Likewise, the estimated carbon stock is in close agreement with reference biomass datasets, particularly over regions with more than 50 % forest cover.

The Relative Importance of Succession, Stand Age and Stand Factors on Carbon Allocation of Korean Pine Forests in the Northern Mt. Xiaoxing’anling, China

Exploring carbon allocation pattern and its influencing factors is of great significance for estimating the carbon sequestration rate and potential of forest ecosystems. Here, we investigate all carbon pool components (including above and belowground biomass of tree, shrub and herb layers, and dead biomass and soil carbon pools) in four successional stages of broad-leaved and Korean pine (Pinus koraiensis Siebold &amp; Zucc.) mixed forests in Northeast China. We explore the change of allocation among carbon pools with succession and examine the relative importance of succession, stand age, and stand factors on carbon allocation pattern. Our results illustrate that above- and belowground vegetation carbon increase as maximum tree height increases. Below- to aboveground vegetation carbon ratio (R/S ratio) decreases significantly with succession and increases significantly as mean diameter at breast height (DBH) increases, but does not significantly correlate with stand age. With succession and increasing stand age, understory (shrub, herb) to tree carbon ratio (understory/tree ratio) and soil to vegetation carbon ratio (soil/vegetation ratio) decrease significantly. The joint effect of succession, stand age, and stand factors have the largest contribution on above- and belowground vegetation carbon and understory/tree ratio (26.83%, 27.93%, and 49.48% of variations explained, respectively). As for the pure effects, stand factors explain the largest proportion of variations in vegetation aboveground carbon (11.25%) and soil carbon (20.18%). Meanwhile, succession is the variable with the largest contribution to vegetation belowground carbon (12.64%), R/S ratio (21.83%), understory/tree ratio (25.84%), and soil/vegetation ratio (6.68%). Overall, these results suggest that species composition change during forest succession, instead of stand factors and stand age, is the main driver of forest vegetation carbon allocation. In contrast, stand factors play a major role in soil carbon allocation. Our findings suggest more studies to better understand the role of species composition (in addition to stand factors and age) on biomass allocation, and the influence of stand factors and litterfalls on soil carbon sequestration, which are critical to improve forest management strategies (e.g., adjustment of species composition and forest structure) to increase the future ability of forest carbon sequestration.

Climatic and edaphic controls over tropical forest diversity and vegetation carbon storage

Tropical rainforests harbor exceptionally high biodiversity and store large amounts of carbon in vegetation biomass. However, regional variation in plant species richness and vegetation carbon stock can be substantial, and may be related to the heterogeneity of topoedaphic properties. Therefore, aboveground vegetation carbon storage typically differs between geographic forest regions in association with the locally dominant plant functional group. A better understanding of the underlying factors controlling tropical forest diversity and vegetation carbon storage could be critical for predicting tropical carbon sink strength in response to projected climate change. Based on regionally replicated 1-ha forest inventory plots established in a region of high geomorphological heterogeneity we investigated how climatic and edaphic factors affect tropical forest diversity and vegetation carbon storage. Plant species richness (of all living stems >10 cm in diameter) ranged from 69 to 127 ha−1 and vegetation carbon storage ranged from 114 to 200 t ha−1. While plant species richness was controlled by climate and soil water availability, vegetation carbon storage was strongly related to wood density and soil phosphorus availability. Results suggest that local heterogeneity in resource availability and plant functional composition should be considered to improve projections of tropical forest ecosystem functioning under future scenarios.

Contributions of National Key Forestry Ecology Projects to the forest vegetation carbon storage in China

Planted forests in China have continuously stored large amounts of vegetation carbon since the implementation of the National Key Forestry Ecology Projects (NKFEPs). However, the time variation of the contribution of NKFEP-covered planted forests to the national forest vegetation carbon storage has not been systematically documented. Moreover, predicting the future vegetation carbon storage of NKFEP-covered planted forests is of great significance for global climate change. Thus, we collected vegetation carbon density data on China’s forests from 251 published articles to clarify the contributions and vegetation carbon sequestration potential of NKFEP-covered planted forests. The results showed that the vegetation carbon density of NKFEP-covered planted forests ranged from 23.49 to 68.88 Mg ha−1, that slight differences existed among the NKFEP-covered planted forests during 2009–2018, and that slight changes occurred from 1989 to 2018. The total contribution rate of NKFEP-covered planted forests to China’s forest vegetation carbon storage was 36.29% during 2009–2018, and the contribution rates of most NKFEPs during 2009–2018 were higher than those during 1999–2008. The total vegetation carbon sequestration potential ranged from 4.22 to 8.67 Pg under four scenarios, in which NKFEP-covered planted forests contributed 40%, 60%, 80% and 100% of the vegetation carbon storage of natural forests in the corresponding NKFEP regions, respectively. These results indicate that NKFEP-covered planted forests significantly contribute to the vegetation carbon storage of China’s forests, and that NKFEP-covered planted forests have large vegetation carbon sequestration potential, which is beneficial for future national and global forest carbon fixation.

川西米亚罗自然保护区森林地上碳储量遥感估算

PDF HTML阅读 XML下载 导出引用 引用提醒 川西米亚罗自然保护区森林地上碳储量遥感估算 DOI: 10.5846/stxb201807281610 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 四川省科技厅应用基础项目（2017JY0155）；四川省中医药管理局重大专项（2018PC005） Estimation of forest aboveground carbon storage in Sichuan Miyaluo Nature Reserve based on remote sensing Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:研究米亚罗自然保护区的森林地上碳储量，有利于掌握高山峡谷区森林植被碳储量的分布特点，对区域森林资源的有效科学管理和维护森林生态环境具有重要意义。通过对保护区内的7个主要树种分别构建模型来初步估测森林地上碳储量，利用实地调查的样地数据与同期Landsat 8遥感卫星影像，得到波段信息、植被指数、主成分分析、纹理特征、地形因子、植被生长六大类共80个因子，用以构建乔木层不同树种地上碳储量的多元线性逐步回归模型，而灌木层的碳储量则由生物量密度法估算得出。研究结果表明：①模型预测值与实测值相关系数在0.675-0.775之间，精度较高，预测结果可靠；②米亚罗自然保护区森林地上碳储量为5.861 Tg，其中乔木层5.632 Tg，灌木层0.229 Tg。云冷杉林是研究区分布最广的林分类型，其碳储量为5.098 Tg，占森林地上碳储量总量的86.98%，在维持区域碳平衡方面发挥着重要作用。③研究区森林平均碳密度为53.138 t/hm2，其中冷杉的碳密度最高，达到74.467 t/hm2。④区域内森林地上碳储量以杂谷脑河流域及支流为中心，以一定缓冲距离呈树枝状发散分布，海拔3000-4000 m区域的森林植被碳储量最大，且阴坡的碳储量明显高于阳坡。 Abstract:The Miyaluo Nature Reserve is an important carbon sequestration region in Western Sichuan. Study of aboveground forest carbon storage in Miyaluo Nature Reserve is necessary for elucidating the distribution characteristics of forest vegetation carbon storage in alpine gorge areas. Furthermore, it is of great significance to the scientific management of forest resources and the maintenance of forest ecological environments in the nature reserves. In this study, carbon storage models were established for seven main tree species to estimate the carbon storage on forest land. Firstly, 897 samples were obtained from a field survey, and sample biomass and carbon storage were calculated based on the volume-derived biomass method. Secondly, Landsat 8 satellite remote sensing data were used to obtain image characteristics of forest vegetation. Thirdly, combined with forest survey data, 80 factors were determined that were classified into six categories (band information, vegetation index, principal component analysis, texture features, topographic factors, and vegetation growth). Moreover, the correlation between these factors and the biomass of different tree species was analyzed, according to the order of Pearson's correlation coefficient, the significant correlation factors were then introduced into the multiple linear stepwise regression equation as independent variables, and the estimation models of aboveground carbon storage of different tree species in the tree layer were established. Finally, the aboveground carbon storage of the arbor layer was calculated by the estimation model, and the carbon storage in the shrub layer was calculated using the average biomass density method. The results showed that ① the accuracy of models for carbon storage estimation was within the margin of error, and the correlation coefficient between the measured value and the predicted value of the model was 0.675-0.775. ② The total carbon storage in the forest in the Miyaluo Nature Reserve was 5.861 Tg, of which the aboveground carbon storage in the arbor layer was 5.632 Tg, and the carbon storage in the shrub layer was 0.229 Tg. The order of the aboveground carbon storage of the prominent species was Abies faberi > Picea asperata > Tsuga chinensis > Larix gmelimi > Quercus acutissima > Betula chinensis > Pinus tabulaeformis > Pinus armandi; The total carbon storage of fir trees was 5.098 Tg, accounting for 86.98% of the aboveground carbon storage in the study area. The spruce-fir forest was the most widely distributed forest type in the Miyaluo Nature Reserve, and it played an important role in maintaining the carbon balance. ③ The average carbon density in the forest in Miyaluo Nature Reserve was 53.138 t/hm2, and the carbon density of Chinese fir species was higher than the average. The carbon density of fir was much higher than that of other tree species and was 74.467 t/hm2. ④ The spatial distribution characteristics of aboveground forest carbon storage in the study area were obtained by overlapping the Digital Elevation Model (DEM) with carbon storage. Taking the Zagunao River and its tributaries as the center, the carbon storage spatial distribution data were extended to the surrounding area by a given buffer distance in the whole region, similar to arborization. The largest area of forest vegetation carbon storage was distributed in regions with elevation of 3000-4000 m. The aboveground carbon storage on shady slopes was higher than that on sunny slopes. 参考文献 相似文献 引证文献

Estimation of forest vegetation carbon storage in Hunan Province, China based on k-NN method and domestic high-resolution data

To promote the application of domestic high-resolution satellite data in large-scale carbon storage estimation and measurement, a total of 206 high-resolution remote sensing images covering Hunan Province were used as the data source, and the estimated minimum unit was fixed as a 0.06 hm2 square composed of multiple pixels. Through the establishment and purification of the interpretation marks, in the extraction of forest information, the pixel-based method and object-oriented classification method were used to compare. In the estimation of carbon storage of arbor forest, the robust estimate, partial least squares method and k-NN estimate were used to compare. Finally, we estimated forest carbon storage in Hunan Province and generated the distribution map of carbon density levels. The results showed that the interpretation mark based on the automatic extraction of plots could increase the extraction accuracy of arbor forest after purification. For the estimation of forest carbon storage at large-scale, the k-NN algorithm embodied a large advantage in forest information extraction and arbor forest carbon storage modeling. The average classification accuracy of the 206 scene images was 76.8%, the average RMSE was 8.95 t·hm-2, the average RRMSE was 19.1%, and the total carbon stock in Hunan Province was 22.28 Mt. The results provided effective reference for the estimation and measurement of forest carbon storage at the provincial and national scales.

基于森林清查资料的河南省森林植被碳储量动态变化

PDF HTML阅读 XML下载 导出引用 引用提醒 基于森林清查资料的河南省森林植被碳储量动态变化 DOI: 10.5846/stxb201807081487 作者: 作者单位: 河南科技大学,河南科技大学,河南科技大学,河南科技大学,河南科技大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（31700367）；河南省高等学校青年骨干教师培养计划项目（2016GGJS-062）；河南科技大学学科提升振兴A计划项目（13660001，13660002）；河南科技大学博士科研启动基金（4024-13480081） Dynamic of forest vegetation carbon storage in He'nan Province based on forest inventory data Author: Affiliation: Henan University of Science and Technology,Hean University of Science and Technology,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:利用1994-1998年、1999-2003年、2004-2008年、2009-2013年河南省4期森林资源清查数据，运用生物量转换因子连续函数法和平均生物量法，估算了1998-2013年河南省森林植被的碳储量和碳密度变化。研究结果表明，河南省森林植被碳储量由1998年的45.57 Tg增加到2013年的107.98 Tg，年均碳汇量为4.16 Tg/a。乔木林碳储量和碳密度分别由1998年的33.54 Tg和22.39 Mg/hm2增加到2013年的97.11 Tg和31.80 Mg/hm2。乔木林碳储量在所有植被类型中占主体，4个森林清查时期乔木林碳储量占森林植被总碳储量的比例分别为73.60%、79.22%、85.63%和89.93%。2013年森林清查时，乔木林中杨树和栎类碳储量最大，分别占总碳储量的37.61%和25.22%，各龄组乔木林碳密度大小顺序依次为成熟林 > 近熟林 > 中龄林 > 过熟林 > 幼龄林。阔叶林面积、碳储量、碳密度均高于针叶林，阔叶林是河南省森林碳汇的主要贡献者。人工林面积、碳储量、碳密度增加幅度都要高于天然林，人工林碳储量由1998年的9.62 Tg增加到2013年的55.67 Tg，占乔木林碳储量总增量的77.15%，人工林碳密度由1998年的17.86 Mg/hm2提高到2013年的32.01 Mg/hm2，人工林在河南省森林碳汇中逐步发挥重要的作用，逐渐成为河南省森林碳汇的主体，随着人工林生长为具有较高碳密度的成熟林，河南省乔木林将具有较大的碳汇潜力。 Abstract:Based on the forest resources inventory data of 1994-1998, 1999-2003, 2004-2008, and 2009-2013 in He'nan Province, the dynamic changes in forest vegetation carbon storage and density between 1998 and 2013 were estimated by using the continuous biomass expansion factor method and average biomass method. The results showed that the carbon storage of forest vegetation in the He'nan Province increased from 45.57 Tg in 1998 to 107.98 Tg in 2013, with an annual carbon sink of 4.16 Tg year-1. The carbon storage and density of arbor forests increased from 33.54 Tg and 22.39 Mg hm-2 in 1998 to 97.11 Tg and 31.80 Mg hm-2 in 2013, respectively. The carbon storage of arbor forests comprised the largest proportion of storage for all vegetation types; the proportion of carbon storage of arbor forests to total carbon storage of forest vegetation in the four forest inventory periods was 73.60%, 79.22%, 85.63%, and 89.93%, respectively. In 2013, Populus and Quercus had the largest carbon storage, accounting for 37.61% and 25.22% of the total carbon storage in arbor forests, respectively. The carbon density of arbor forests in each age group was ranked in the following order:mature forest > premature forest > middle-aged forest > over-mature forest > young-aged forest. The area, carbon storage and carbon density of broad-leaved forests were higher than those of coniferous forests, and broad-leaved forests were the main contributor to the forest carbon sink in He'nan Province. The area, carbon storage and carbon density of the planted forests increased more than the natural forests. The carbon storage of planted forests increased from 9.62 Tg in 1998 to 55.67 Tg in 2013, accounting for 77.15% of the total increment of carbon storage in arbor forests. The carbon density of planted forests increased from 17.86 Mg hm-2 in 1998 to 32.01 Mg hm-2 in 2013. The importance of the role of planted forests in the forest carbon sink of He'nan Province is gradually emerging. As the planted forests grow into mature forest with a high carbon density, the arbor forests in He'nan Province will have greater carbon sequestration potential. 参考文献 相似文献 引证文献

Forest carbon storage in Guizhou Province based on field measurement dataset

Accurate estimation of forest carbon storage is crucial in understanding global and regional carbon cycles and projecting future ecological and economic scenarios. Guizhou is the largest karst landform province in China; 61.9% of its land area is characterized as karst. However, monitoring its field biomass and carbon storage is difficult. This study synthesized and analyzed a comprehensive database of direct field observations of forest vegetation and soil carbon storage in Guizhou Province by using data from existing literature. The total vegetation carbon storage in Guizhou Province was 488.170 TgC, the average vegetation carbon density (VCD) was 27.866 MgC hm−2, the total amount of soil organic carbon (SOC) (20 cm) was 1017.364 TgC, and the average SOC density was 58.074 MgC hm−2. Among all vegetation types, needleleaf forest had the highest vegetation carbon stocks, and scrub presented the highest SOC storage. The vegetation and SOC storage values of the karst landform were 282.352 and 614.825 TgC, respectively, which were higher than those of the non-karst landform. VCD was concentrated at 10–40 MgC hm−2, and SOC density was concentrated at 40–60, 60–80, and 80–100 MgC hm−2. This comprehensive regional data synthesis and analysis based on direct field measurement of vegetation and soil will improve our understanding of the forest carbon cycle in karst landforms under a changing climate.