Carbon Balance and Management最新文献

{"title":"The influence of agricultural drought on carbon emissions across the four sub-regions of China","authors":"Tehseen Javed,&nbsp;Zhenhua Wang,&nbsp;Jian Liu,&nbsp;Wenhao Li,&nbsp;Haixia Lin,&nbsp;Pengpeng Chen,&nbsp;Jihong Zhang","doi":"10.1186/s13021-025-00300-9","DOIUrl":"10.1186/s13021-025-00300-9","url":null,"abstract":"<div><p>Vegetation is crucial in carbon sequestration, as it stores soil carbon and biomass. However, agricultural droughts significantly reduce vegetation growth, directly impacting the amount of carbon sequestered through photosynthesis. This study investigates the effects of agricultural drought on carbon emissions across four sub-regions of China, Northwest China, North China, the Qinghai-Tibet region, and South China, from 2001 to 2020. Three remote sensing-based drought indices, the Moisture Anomaly Index (MAI), Vegetation Anomaly Index (VAI), and Temperature Anomaly Index (TAI) were used for drought monitoring. Advanced statistical techniques were employed to explore the relationship between these indices and carbon emissions, including auto-correlation and spatial cross-correlation. The results indicate that temporal variations between carbon emissions and agricultural drought indices exhibit distinct regional patterns. Among the indices, VAI demonstrated the strongest correlation with carbon emissions, with values ranging from <i>r</i> = 0.56 to 0.76. Carbon emissions varied significantly across regions, with the highest recorded in North China, followed by South China, Northwest China, and Qinghai-Tibet regions. Spatial cross-correlation analysis revealed that the highest positive correlation <i>(r</i> &gt; 0.5) between carbon emissions and drought indices was observed in South China, whereas a moderate correlation was found between MAI and carbon emissions in Northwest China. The correlation between VAI and carbon emissions ranged from <i>r</i> = -0.6 to &gt; 0.8. TAI exhibited a positive correlation with carbon emissions in South China, whereas negative correlations were observed in Northwest China and northeast North China. These findings provide valuable insights for mitigating drought-induced carbon emissions and promoting sustainable land management practices.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00300-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal-spatial evolution analysis of carbon emission efficiency in the logistics industry of coastal provinces in China based on the super-efficiency SBM model","authors":"Beilei Wang,&nbsp;Meiling Liu,&nbsp;Shan Gao","doi":"10.1186/s13021-025-00299-z","DOIUrl":"10.1186/s13021-025-00299-z","url":null,"abstract":"<div><h3>Background</h3><p>The logistics industry is a pillar industry of China’s national economic development, and coastal provinces, as the core of China’s economic development, have highly developed logistics industry. However, the rapid development of the logistics industry in China’s coastal provinces is usually accompanied by high carbon emissions. Therefore, improving the carbon emission efficiency of the logistics industry (LCEE) in China’s coastal provinces is one of the main contents to achieve \"China’s dual carbon goals\". Existing research indicates that LCEE is closely related to the efficiency levels of neighboring regions, and its temporal and spatial evolution characteristics are also influenced by the change of neighborhood efficiency. However, less attention has been given to the role of geographic proximity in analyzing the temporal and spatial evolution characteristics. Thus, this paper introduces the spatial lag factor into the Markov chain (MC) to obtain the spatial Markov chain (SMC), examining the influence of neighboring provinces’ LCEE on the spatial evolution of the local LCEE in China’s coastal provinces.</p><h3>Results</h3><p>The results show that: For most years between 2007 and 2022, in China’s eleven coastal provinces, the LCEE values were less than one. These low LCEE values indicated that the potential for emission reduction had not been fully tapped, and low-carbon development faced significant challenges. The primary obstacle to improving LCEE during the study period was low technical efficiency, and the development of the technology level was crucial for enhancing LCEE. In 2007–2011 and 2015, the spatial distribution of LCEE exhibited significant spatial clustering features. The primary type of spatial clustering was high-high clustering, which indicated there was an obvious trend of regional coordinated development. The LCEE of neighboring provinces influenced the state transition probabilities of their own states, and spatial spillover effects in these provinces were very evident.</p><h3>Conclusions</h3><p>This study conducted an in-depth analysis of the temporal-spatial evolution characteristics of LCEE in China’s coastal provinces. There are significant differences in LCEE among these provinces. Each province needs to reduce the carbon dioxide emissions of the logistics industry and improve the LCEE through regional cooperation, technological investment, and targeted policies, so as to promote the sustainable development of the logistics industry in China’s coastal provinces.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00299-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting CO2 emissions in BRICS countries using the grey breakpoint prediction models","authors":"Huiping Wang,&nbsp;Xinge Guo","doi":"10.1186/s13021-025-00301-8","DOIUrl":"10.1186/s13021-025-00301-8","url":null,"abstract":"<div><p>In this paper, three novel grey breakpoint prediction models are proposed based on calculating the development coefficient and grey action of grey prediction models after fuzzy breakpoints, unifying the calculation methods for parameter estimation and the relevant time-response equations, and using the particle swarm optimisation algorithm to optimise the two-stage background values. Finally, the novel grey breakpoint prediction models are used to simulate and forecast the CO₂ emissions in BRICS countries. We can see that by setting time breakpoints and fuzzy breakpoint intervals, the novel methods successfully detect abrupt changes in the system and achieve accurate predictions, thus improving the accuracy and applicability of the grey model. The new grey breakpoint prediction models demonstrate better estimation in all cases in CO₂ emissions forecasting. The projections show that between 2022 and 2025, CO₂ emissions in Brazil and South Africa will decrease each year, while CO₂ emissions in China, Russia and India will increase each year, but the upwards trend in India shows signs of slowing.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00301-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crop rotation and the impact on soil carbon in the U.S. Corn Belt","authors":"Yining Wu,&nbsp;Eric C. Davis,&nbsp;Brent L. Sohngen","doi":"10.1186/s13021-025-00293-5","DOIUrl":"10.1186/s13021-025-00293-5","url":null,"abstract":"<div><p>Soils are receiving increasing attention as carbon sinks that can reduce atmospheric CO₂. While common Best Management Practices (BMP), such as cover crops, reduced or minimum tillage, and advanced nutrient management, have been considered as alternatives to build soil carbon storage in managed crop fields, crop-species choices have often been overlooked. This paper uses the Rapid Carbon Assessment (RaCA) data from U.S. Department of Agriculture (USDA), to examine how the rotation of two of the most widely used crops in the U.S., corn and soybeans, influences Soil Organic Carbon (SOC) stocks. We show that at the depths of 0 to 100 cm, corn is correlated with a higher level of SOC stocks than soybeans, and the more years that corn is cultivated the higher the SOC stocks. Specifically, an additional year of corn planted every 3 years is estimated to increase SOC stocks at depths of 0 to 100 cm by 25.1%. Based on our analysis, were all the land in the U.S. states of Ohio, Indiana, Iowa, and Illinois that are currently either mono-cropped with soybeans or follow some sort of soybean-corn rotation converted to corn mono-cropping, the estimated gain in SOC would be 896.7 million Mg C (1 Megagram = 1 ton). This represents a theoretical upper limit for SOC improvements. If current rotational practices were shifted such that corn was planted in 2 of every 3 years in the same region, the theoretical increase in SOC stocks is estimated to be 172.9 million Mg C. Multiplying this result by a Social Cost of Carbon priced at $678/t C in 2020 U.S. dollars (Rennert et al. in Nature 610:687–692, 2022), the total benefits are estimated at $117 billion.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00293-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Avoiding global deforestation by taxing land in agricultural production: the implications for global markets","authors":"Eric C. Davis,&nbsp;Maros Ivanic,&nbsp;Brent Sohngen","doi":"10.1186/s13021-025-00291-7","DOIUrl":"10.1186/s13021-025-00291-7","url":null,"abstract":"<div><p>The projected growth in population and incomes is expected to create pressure to convert forestland into farmland. At the same time, the increasingly negative climate impacts are expected to generate further pressure to enhance the terrestrial carbon sink. Even though these goals are incompatible as reversing the deforestation trend by afforesting cropland would result in negative market impacts such as higher food prices, using the GTAP and GTM models, we find that these impacts would be relatively small if the goal of preserving 144.2 million hectares of forestland that otherwise would be converted to agricultural land by 2033 is achieved through a tax on land use in agricultural production. As to the economic price for doing so, the avoided deforestation would in most regions of the world result in less agricultural output and higher market prices. This is estimated to impact the well-being of global consumers by $119.7 billion, which translates to a global average cost of $13.78 per person in 2033.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00291-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143612327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investing in U.S. forests to mitigate climate change","authors":"Alice Favero,&nbsp;Justin Baker,&nbsp;Brent Sohngen,&nbsp;Adam Daigneault,&nbsp;Christopher Wade,&nbsp;Sara Ohrel,&nbsp;Shaun Ragnauth","doi":"10.1186/s13021-025-00292-6","DOIUrl":"10.1186/s13021-025-00292-6","url":null,"abstract":"<div><p>In recent years several U.S. federal policies have been adopted to support forest-based climate mitigation actions. This study focuses on current federal funds allocated to forest for climate change mitigation activities to assess how much they could deliver in terms of net sequestration under a best-case (optimized) scenario where the cheapest abatement options are implemented first and if these funds are in line to achieve domestic targets for 2030 and 2050. Multiple investments pathways are tested under two different assumptions on CO₂ fertilization to provide a range of future mitigation projections from forests. Results show that under annual investments in line with current federal funds (around $640 million), the expected net carbon flux of U.S. forests is around 745 MtCO₂/yr in 2030 (+ 12% increase from baseline) and if the investments expand after 2030 the net flux is expected to be 786 MtCO₂/yr in 2050 (+ 17% increase from baseline). When CO₂ fertilization is accounted for, the projections of net forest carbon sequestration increase by 17% in 2030 and about 1 GtCO₂ net sequestration achieved under federal funds in 2050, increasing the likelihood of meeting both short-term and long-term domestic targets.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00292-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143583656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating carbon stocks and woody perennials diversity in cropland agroforestry on three different land ecosystems in Bangladesh","authors":"Mohammad Kamrul Hasan,&nbsp;Nasima Akther Roshni,&nbsp;Rojina Akter","doi":"10.1186/s13021-024-00288-8","DOIUrl":"10.1186/s13021-024-00288-8","url":null,"abstract":"<div><h3>Background</h3><p>Cropland agroforestry practices are widely adopted over various land ecosystems in Bangladesh, offering the potential to capture carbon (C) and safeguard biodiversity. Lack of accurate assessments of biomass carbon and the diversity of woody perennials in cropland agroforestry practices across different land ecosystems presents a hurdle for the efficient execution of initiatives such as REDD + and comparable mechanisms. The present research sought to estimate biomass carbon stocks and diversity of woody species, exploring the influence of stand structure and diversity indices on these C stocks. We conducted woody perennials’ inventory in 180 sampling quadrates (10 m × 10 m) from cropland agroforestry practices in forest, plains land, and char land ecosystems.</p><h3>Results</h3><p>Altogether, we identified 42 woody species; however, the predominant species in three land ecosystems were <i>Acacia auriculiformis, Gmelina arborea, and Tectona grandis. Swietenia macrophylla and Swietenia mahogany</i> contributed the greatest amount of carbon stocks. Carbon stocks in woody perennials were 30–44% higher in plains land and forest land ecosystems compared to the char land ecosystem, attributable to significantly increased stand density, basal area and diameter. The significantly highest Shannon–Wiener index (2.75) and Margalef’s richness index (3.37) were found in forest land compared to other ecosystems. The highest total carbon stocks (131.27 Mg C ha⁻¹) of cropland agroforestry were found in the forest land ecosystem, which had the greatest soil organic carbon, density, and richness of woody perennials. A rise in the richness and diversity index of woody species by one unit led to a concurrent increase of 12 and 8 Mg C ha⁻¹ in carbon stocks, respectively.</p><h3>Conclusions</h3><p>Cropland agroforestry practices in the forest land ecosystem are more diverse and could sequester more carbon stock than in the other two land ecosystems in Bangladesh. The biomass C stocks of woody species were positively correlated with stand structure and diversity, having the potential to contribute to biodiversity conservation in Bangladesh and other similar countries.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-024-00288-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing forest carbon projections requires improved convergence between ecological and economic models","authors":"Madisen R. Fuller,&nbsp;Manaswini Ganjam,&nbsp;Justin S. Baker,&nbsp;Robert C. Abt","doi":"10.1186/s13021-024-00290-0","DOIUrl":"10.1186/s13021-024-00290-0","url":null,"abstract":"<div><p>Forests have the potential to contribute significantly to global climate policy efforts through enhanced carbon sequestration and storage in terrestrial systems and wood products. Projections models simulate changes future in forest carbon fluxes under different environmental, economic, and policy conditions and can inform landowners and policymakers on how to best utilize global forests for mitigating climate change. However, forest carbon modeling frameworks are often developed and applied in a highly disciplinary manner, e.g., with ecological and economic modeling communities typically operating in silos or through soft model linkages through input–output parametric relationships. Recent disciplinary divides between economic and ecological research communities confound policy guidance on levers to increase forest carbon sinks and enhance ecosystem resilience to global change. This paper reviews and summarizes the expansive literature on forest carbon modeling within economic and ecological disciplines, discusses the benefits and limitations of commonly used models, and proposes a convergence approach to better integrating ecological and economic systems frameworks. More specifically, we highlight the critical feedback loops that exist when economic and ecological carbon models operate independently and discuss the benefits of a more integrated approach. We then describe an iterative approach that involves the sharing of methodology, perspectives, and data between the regimented model types. An integrated approach can reduce the limitations or disciplinary bias of forest carbon models by exploiting and merging their relative strengths.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-024-00290-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating territorial pattern changes into the relationship between carbon sequestration and water yield in the Yangtze River Basin, China","authors":"Zelin Liu,&nbsp;Xiaoting Yu,&nbsp;Cong Liu,&nbsp;Ziying Zou,&nbsp;Changhui Peng,&nbsp;Peng Li,&nbsp;Jiayi Tang,&nbsp;Haoyun Liu,&nbsp;Yihang Zhu,&nbsp;Chunbo Huang","doi":"10.1186/s13021-024-00289-7","DOIUrl":"10.1186/s13021-024-00289-7","url":null,"abstract":"<div><p>Territorial pattern plays an important role in regional ecosystem management and service provision. It is significant to demonstrate the coordination relationships between the territorial space evolutions and ecosystem services for sustainable regional development. This study focused on quantifying the impacts of production-living-ecological space change on carbon sequestration and water yield in the upper and middle-lower reaches of the Yangtze River Basin. Our results indicated that the production-living-ecological space variation trends are similar between the upper and middle-lower reaches during 2000–2020, while their impacts on ecosystem services are different in their respective regions. In the upper reaches, the changes in production and ecological space had a direct positive impact on NPP while the changes of living space had a negative impact on the NPP. However, the changes of production-living-ecological space had no significant effects on the water yield. In contrast, the changes of production and ecological space had no significant effect on the NPP in the middle-lower reaches, while the changes of ecological space had a positive effect on the water yield. Additionally, we also found that social-economic factors had no significant effects on the changes of ecological space in the middle-lower reaches of the Basin. We suggested that policy makers need to optimize the distribution of territorial space in order to maintain sustainable development.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-024-00289-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved aboveground biomass estimation and regional assessment with aerial lidar in California’s subalpine forests","authors":"Sara Winsemius,&nbsp;Chad Babcock,&nbsp;Van R. Kane,&nbsp;Kat J. Bormann,&nbsp;Hugh D. Safford,&nbsp;Yufang Jin","doi":"10.1186/s13021-024-00286-w","DOIUrl":"10.1186/s13021-024-00286-w","url":null,"abstract":"<div><h3>Background</h3><p>Understanding the impacts of climate change on forest aboveground biomass is a high priority for land managers. High elevation subalpine forests provide many important ecosystem services, including carbon sequestration, and are vulnerable to climate change, which has altered forest structure and disturbance regimes. Although large, regional studies have advanced aboveground biomass mapping with satellite data, typically using a general approach broadly calibrated or trained with available field data, it is unclear how well these models work in less prevalent and highly heterogeneous forest types such as the subalpine. Monitoring biomass using methods that model uncertainty at multiple scales is critical to ensure that local relationships between biomass and input variables are retained. Forest structure metrics from lidar are particularly valuable alongside field data for mapping aboveground biomass, due to their high correlation with biomass.</p><h3>Results</h3><p>We estimated aboveground woody biomass of live and dead trees and uncertainty at 30 m resolution in subalpine forests of the Sierra Nevada, California, from aerial lidar data in combination with a collection of field inventory data, using a Bayesian geostatistical model. The ten-fold cross-validation resulted in excellent model calibration of our subalpine-specific model (94.7% of measured plot biomass within the predicted 95% credible interval). When evaluated against two commonly referenced regional estimates based on Landsat optical imagery, root mean square error, relative standard error, and bias of our estimations were substantially lower, demonstrating the benefits of local modeling for subalpine forests. We mapped AGB over four management units in the Sierra Nevada and found variable biomass density ranging from 92.4 to 199.2 Mg/ha across these management units, highlighting the importance of high quality, local field and remote sensing data.</p><h3>Conclusions</h3><p>By applying a relatively new Bayesian geostatistical modeling method to a novel forest type, our study produced the most accurate and precise aboveground biomass estimates to date for Sierra Nevada subalpine forests at 30 m pixel and management unit scales. Our estimates of total aboveground biomass within the management units had low uncertainty and can be used effectively in carbon accounting and carbon trading markets.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"19 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-024-00286-w","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142859462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}