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The rapid increase in carbon and other greenhouse gases is likely to change the regional and global temperature, and planning of these gases is needed. The present study focused on National Highway-16 of the Srikakulam district, which was upgraded from 4 to 6 lane standards to facilitate traffic. This study intended to compute the carbon sequestration and storage capacity of above and belowground biomass. This helps in the comparison and impact of the road project on flora and its carbon pool, from where future tree stock changes can be prepared. A total of 1930 plots were constructed of criss-crosses of equal size (2 × 100 m). All woody trees with dbh ≥ 30 cm were considered and their diameters were measured. A total of 29 tree species belonging to 13 families were identified; the quantity of macrobiotic carbon sequestered as a whole, i.e., above and below ground, was 768,890.29 tC and 199,911.48 tC , respectively. The mean sequestration rate of carbon as biomass above ground was 1.19 tC/tree, and that below ground was 0.31 tC/tree . The estimated average C-Stock per tree was 1.5 tC ; however, the mean C-Stock per quadrate was 250.2 tC ., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Estimation of plant community composition, aboveground biomass and carbon stock is crucial for understanding forest ecology, strengthening environmental management, and developing effective tools and policies for forest restoration. This study was conducted in nine different forest reserves in Sri Lanka from 2012 to 2018 to examine the impact of community-based forest restoration (CBFR) on stand structural attributes, aboveground biomass, and carbon stock compared to state-managed forests. In total, 180 plots (90 plots in community-managed restoration blocks (CMRBs) and 90 plots assigned to state-managed restoration blocks (SMRBs)) were sampled at the study site. To conduct an inventory of standing trees, circular plots with a radius of 12.6 m (equivalent to an area of 500 square meters) were established. The Shannon diversity index, Allometric equations and Difference in Differences (DID) estimation were used to assess the data. Our study provides evidence of the positive impact of the CBFR program on enriching trees diversity. Considering stand structural attributes of both blocks showed higher trees density in the smaller diameter at breast height (DBH) category, indicating growth in both CMRBs and SMRBs. The results showed that tree biomass and carbon density were disproportionally distributed across the nine different forest reserves. On average, tree biomass and carbon density were higher in SMRBs (79.97 Mg ha -1 , 37.58 Mg C ha -1 ) compared to CMRBs (33.51 Mg ha -1 , 15.74 Mg C ha -1 ). However, CMRBs in Madigala reserve represent the highest biomass (56.53 and 59.92 Mg ha -1 ) and carbon density (26.57 and 28.16 Mg C ha -1 ). The results of biomass and carbon estimates were higher in all SMRBs in the nine different forest reserves compared to CMRBs. The findings suggest that future forest restoration programs in Sri Lanka should enhance participatory approaches to optimize tree species diversity, density and carbon storage, particularly in community-controlled forests. Our findings could assist developing tropical nations in understanding how CBFR impacts forest restoration objectives and improves the provision of ecological services within forests., Competing Interests: The authors declare that they have no competing interests., (© 2024 Ahmad et al.)

Forests, the ancient wooden giants, are both symbols of natural beauty and reservoirs of carbon stocks. The current climate crisis has created an urgent need for an in-depth study of forest ecosystems and carbon stocks. Based on forest inventory data from field surveys and four bioclimatic zones [Zone 1 (Z1, humid forest), Zone 2 (Z2, semi-humid forest), Zone 3 (Z3, semi-humid to semi-arid forest-grassland), and Zone 4 (Z4, semi-arid typical grassland)], two methods [Method 1 (M1) and Method 2 (M2)] were used to estimate carbon stocks in forest ecosystems in Shaanxi Province, China, and explored the spatial patterns of carbon pools and potential influences. The total forest ecosystem carbon pool amounted to 520.80 Tg C, of which 53.60% was stored aboveground, 17.16% belowground, and 29.24% in soil (depth of 0-10 cm). Spatially, there were marked north-south gradients in both biomass (Z2 > Z3 > Z1 > Z4) and soil organic carbon densities (Z1 > Z2 > Z3 > Z4). The differences between aboveground and belowground biomass carbon density across broadleaf, needle-leaf, and broadleaf and needle-leaf mixed forest were not pronounced, while soil organic carbon density had the order of broadleaf (18.38 Mg C/ha) > needle-leaf (11.29 Mg C/ha) > broadleaf and needle-leaf mixed forest (10.33 Mg C/ha). Under an ideal scenario that excludes external factors, mainly forest growth, the sequestration potential of forest biomass by 2032 was estimated by M1 as 85.43 Tg, and by M2 to be substantially higher at 176.21 Tg. As of 2062, M1 estimated 155.97 Tg of sequestration potential for forest biomass. The spatial patterns of forest biomass and soil carbon density were closely related to climatic factors, and these relationships allowed the spatial division into two distinct climatic regions. Moreover, biomass carbon density was significantly correlated with the normalized difference vegetation index, soil silt, and elevation. This study provides key information for promoting the strategic shift from light-green to deep-green forest systems in Shannxi Province and updates the estimation methods of forest ecosystems' carbon pools based on field surveys., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Premise of the Study: Basic wood density is an important ecological trait for woody plants. It is used to characterize species performance and fitness in community ecology and to compute tree and forest biomass in carbon cycle studies. While wood density has been historically measured at 12% moisture, it is convenient for ecological purposes to convert this measure to basic wood density, i.e., the ratio of dry mass over green volume. Basic wood density can then be used to compute tree dry biomass from living tree volume., Methods: Here, we derive a new exact formula to compute the basic wood density D b from the density at moisture content w denoted D w , the fiber saturation point S, and the volumetric shrinkage coefficient R. We estimated a new conversion factor using a global wood technology database where values to use this formula are available for 4022 trees collected in 64 countries (mostly tropical) and representing 872 species., Key Results: We show that previous conversion factors used to convert densities at 12% moisture into basic wood densities are inconsistent. Based on theory and data, we found that basic wood density could be inferred from the density at 12% moisture using the following formula: D b = 0.828D 12 . This value of 0.828 provides basic wood density estimates 4-5% smaller than values inferred from previous conversion factors., Conclusions: This new conversion factor should be used to derive basic wood densities in global wood density databases. Its use would prevent overestimating global forest carbon stocks and allow predicting better tree species community dynamics from wood density., (© 2018 The Authors. American Journal of Botany is published by Wiley Periodicals, Inc. on behalf of the Botanical Society of America.)

Despite the general recognition that fragmentation can reduce forest biomass through edge effects, a systematic review of the literature does not reveal a clear role of edges in modulating biomass loss. Additionally, the edge effects appear to be constrained by matrix type, suggesting that landscape composition has an influence on biomass stocks. The lack of empirical evidence of pervasive edge-related biomass losses across tropical forests highlights the necessity for a general framework linking landscape structure with aboveground biomass. Here, we propose a conceptual model in which landscape composition and configuration mediate the magnitude of edge effects and seed-flux among forest patches, which ultimately has an influence on biomass. Our model hypothesizes that a rapid reduction of biomass can occur below a threshold of forest cover loss. Just below this threshold, we predict that changes in landscape configuration can strongly influence the patch's isolation, thus enhancing biomass loss. Moreover, we expect a synergism between landscape composition and patch attributes, where matrix type mediates the effects of edges on species decline, particularly for shade-tolerant species. To test our conceptual framework, we propose a sampling protocol where the effects of edges, forest amount, forest isolation, fragment size, and matrix type on biomass stocks can be assessed both collectively and individually. The proposed model unifies the combined effects of landscape and patch structure on biomass into a single framework, providing a new set of main drivers of biomass loss in human-modified landscapes. We argue that carbon trading agendas (e.g., REDD+) and carbon-conservation initiatives must go beyond the effects of forest loss and edges on biomass, considering the whole set of effects on biomass related to changes in landscape composition and configuration., (© 2017 John Wiley & Sons Ltd.)

Natural forests in South-East Asia have been extensively converted into other land-use systems in the past decades and still show high deforestation rates. Historically, lowland forests have been converted into rubber forests, but more recently, the dominant conversion is into oil palm plantations. While it is expected that the large-scale conversion has strong effects on the carbon cycle, detailed studies quantifying carbon pools and total net primary production (NPPtotal ) in above- and belowground tree biomass in land-use systems replacing rainforest (incl. oil palm plantations) are rare so far. We measured above- and belowground carbon pools in tree biomass together with NPPtotal in natural old-growth forests, 'jungle rubber' agroforests under natural tree cover, and rubber and oil palm monocultures in Sumatra. In total, 32 stands (eight plot replicates per land-use system) were studied in two different regions. Total tree biomass in the natural forest (mean: 384 Mg ha(-1) ) was more than two times higher than in jungle rubber stands (147 Mg ha(-1) ) and >four times higher than in monoculture rubber and oil palm plantations (78 and 50 Mg ha(-1) ). NPPtotal was higher in the natural forest (24 Mg ha(-1)  yr(-1) ) than in the rubber systems (20 and 15 Mg ha(-1)  yr(-1) ), but was highest in the oil palm system (33 Mg ha(-1)  yr(-1) ) due to very high fruit production (15-20 Mg ha(-1)  yr(-1) ). NPPtotal was dominated in all systems by aboveground production, but belowground productivity was significantly higher in the natural forest and jungle rubber than in plantations. We conclude that conversion of natural lowland forest into different agricultural systems leads to a strong reduction not only in the biomass carbon pool (up to 166 Mg C ha(-1) ) but also in carbon sequestration as carbon residence time (i.e. biomass-C:NPP-C) was 3-10 times higher in the natural forest than in rubber and oil palm plantations., (© 2015 John Wiley & Sons Ltd.)

Forests are essential for the ecological functioning providing critical habitats for biodiversity and hold large biomass, which are affected by bioclimatic and topographical variables. This study investigated the topographic factor (elevation) that play an important role in forest diversity and biomass distribution. The present study examined the relationship between topographical (viz. elevation, slope, aspects) and Bioclimatic variables (temperature/ precipitation) with measured biomass of Tropical forests. The study area selected is Sariska Tiger Reserve (STR), a tropical forest with high conservation priorities with fewer disturbances. Earth observation datasets such as ALOS-PALSAR, SRTM, and GEDI aboveground biomass density (AGBD) are retrieved in the Cloud computing platform (GGE) to generate outcomes. The study also utilized Bioclimatic variables such as maximum, minimum and mean temperature during warmest/coldest month and warmest, coldest, wettest, driest Quarters. GEDI derived mean biomass was observed to be 1.3 to 95 Mg/ha ± (0.68–5.88 SD). The data was statistically analyzed using correlation coefficient (R) for topographic and bioclimatic variables. Results specified six Biodiversity indices (BDI), and six bioclimatic variables during analysis. Correlation coefficient (R) indicated strong positive relationship of three biodiversity indices with elevation for Shannon - Weiner index (R = 0.71) followed by Margalef richness index (R = 0.65) and reciprocal Simpson index (R = 0.61). While Buzas and Gibson Index (R=−0.45), Berger dominance index (R=−0.27), and Menhinick index (R=−0.51) showed negative correlation with elevation. Overall, topographic and bioclimatic variables are governed by elevation for biomass and carbon stocks (with r=−0.41). Similarly, correlation coefficient (R) of elevation against max temperature during Warmest month (MTMW), Warmest Quarter (MTWarQ) and Wettest Quarter (MTWetQ) indicated strong negative correlation with R value of −0.88, −0.88, and − 0.87 respectivelry. It is followed by MTColdest Quarter (R=−0.85) and MinTCM (R=−0.84). while lowest correlation was shown by Min Temp during Driest Quarter with R=−0.23. Outcomes showed declining trends of biomass stocks ranged from 129.44 mg/t to 7.07 mg/t with significantly increasing trends till mid elevation and thereafter decreasing trends of tree biomass with increasing elevation. Highest biomass of 95 mg/t (GEDI derived) and Field measured Biomass of 129.44 mg/t was observed at intermediate elevation of 530 m after that showed decline in biomass distribution. Elevation can act as a dominant determinant for AGB in tropical forest for several reasons, such as topographic variations, temperature variations, precipitation patterns, soil nutrient availability, species adaptation, disturbance regimes, and most influencing one is human activities. Therefore, elevation can be a crucial predictor in conjunction with other factors to influence biomass at undisturbed places with high slopes and controlled species richness, distribution and biomass accumulation in tree species. Highlights: 1. Elevation effects species distribution and richness (in conjunction with bioclimatic factors). 2. Highest biomass of 95 mg/t (GEDI derived) and Field measured Biomass of 129.44 mg/t was observed at intermediate elevation of 530 m after that declining trend in biomass distribution (elevation ranges from 262 m to 721m). 3. Topographical and Bioclimatic variables' relationship against biomass and biodiversity index. 4. Cloud computing applications (GGE) provide datasets for fast analysis and outcomes for local and global scales. [ABSTRACT FROM AUTHOR]

Economic, social, and ecological aspects of the environment are all impacted differently by mining in different parts of the world. When mining activities end and leave the area bare, rehabilitation and revegetation are required to minimize the impacts of mining in general. By fixing carbon in tree biomass, these interventions have a positive effect on increasing carbon storage. Measuring carbon stock is essential to evaluating the effectiveness of these interventions. This study was conducted in an inactive mining area in Marinduque, Philippines. Plots for sampling were created in areas that were not yet undergoing rehabilitation as well as those that were. The above-ground carbon stock and biomass were estimated using the allometric equation provided by IPCC (Intergovernmental Panel on Climate Change) and Sourcebook for Land Use, Land-Use Change and Forestry Projects as references, respectively. The results for areas undergoing rehabilitation and those that were not indicated 4.297 t/ha and 0.0509 t/ha, respectively. The former has an above-ground carbon stock of 2.1485 t/ha, and the latter has 0.2545 t/ha. This shows a successful increase in biomass and carbon stock in the area undergoing rehabilitation. This comparison suggests that rehabilitation and revegetation should be implemented in mining areas to help mitigate the impacts of mining while also sequestering carbon. Policies and activities that will protect the current rehabilitation efforts and expand this rehabilitation to other inactive mining areas should be incorporated for future research.

Multispectral data were used to estimate the above-ground forest biomass in the newly established carbon polygon in Bashkortostan. Field measurements were compared with Normalised Difference Vegetation Index (NDVI) and Normalised Green-Red Difference Index (NGRDI) obtained from the Global Inventory Monitoring and Modelling System (GIMMS) dataset. The relationship between measured biomass values and vegetation indicators was linear; NDVI has the highest correlation coefficient with above-ground biomass and greatest significance at all sites, so regression relationships with NDVI were used to map the above-ground biomass. [ABSTRACT FROM AUTHOR]

Economic, social, and ecological aspects of the environment are all impacted differently by mining in different parts of the world. When mining activities end and leave the area bare, rehabilitation and revegetation are required to minimize the impacts of mining in general. By fixing carbon in tree biomass, these interventions have a positive effect on increasing carbon storage. Measuring carbon stock is essential to evaluating the effectiveness of these interventions. This study was conducted in an inactive mining area in Marinduque, Philippines. Plots for sampling were created in areas that were not yet undergoing rehabilitation as well as those that were. The above-ground carbon stock and biomass were estimated using the allometric equation provided by IPCC (Intergovernmental Panel on Climate Change) and Sourcebook for Land Use, Land-Use Change and Forestry Projects as references, respectively. The results for areas undergoing rehabilitation and those that were not indicated 4.297 t/ha and 0.0509 t/ha, respectively. The former has an above-ground carbon stock of 2.1485 t/ha, and the latter has 0.2545 t/ha. This shows a successful increase in biomass and carbon stock in the area undergoing rehabilitation. This comparison suggests that rehabilitation and revegetation should be implemented in mining areas to help mitigate the impacts of mining while also sequestering carbon. Policies and activities that will protect the current rehabilitation efforts and expand this rehabilitation to other inactive mining areas should be incorporated for future research. [ABSTRACT FROM AUTHOR]

Abstract Background Carbon (C) sink and stock are among the most important ecosystem services provided by forests in climate change mitigation policies. In this context, old-growth forests constitute an essential reference point for the development of close-to-nature silviculture, including C management techniques. Despite their small extent in Europe, temperate old-growth forests are assumed to be among the most prominent in terms of biomass and C stored. However, monitoring and reporting of C stocks is still poorly understood. To better understand the C stock amount and distribution in temperate old-growth forests, we estimated the C stock of two old-growth stands in the Dinaric Alps applying different assessment methods, including direct and indirect approaches (e.g., field measurements and allometric equations vs. IPCC standard methods). This paper presents the quantification and the distribution of C across the five main forest C pools (i.e., aboveground, belowground, deadwood, litter and soil) in the study areas and the differences between the applied methods. Results We report a very prominent C stock in both study areas (507 Mg C ha− 1), concentrated in a few large trees (36% of C in 5% of trees). Moreover, we found significant differences in C stock estimation between direct and indirect methods. Indeed, the latter tended to underestimate or overestimate depending on the pool considered. Conclusions Comparison of our results with previous studies and data collected in European forests highlights the prominence of temperate forests, among which the Dinaric Alps old-growth forests are the largest. These findings provide an important benchmark for the development of future approaches to the management of the European temperate forests. However, further and deeper research on C stock and fluxes in old-growth stands is of prime importance to understand the potential and limits of the climate mitigation role of forests.

Urban green spaces have received little attention for climate change mitigation by way of carbon dioxide (CO2) sequestration. The present study explores the diversity and CO2 mitigation value of roadside tree species in Sagar city, India. Various diversity and richness indices were determined to assess the diversity structure of these discontinuous vegetations. The CO2 mitigation value was determined by estimating biomass and carbon stock through a non-destructive method. The study area was found to include 1,130 individuals belonging to 26 families and 66 species. A higher value of diversity indices (Simpson's, 0.95 and Shannon's, 3.42) and lower Simpson's index of dominance (0.05), along with the higher value of species richness (9.25) and evenness (0.82) showed good diversity and uniform distribution of the species. The CO2 mitigation value for the present study area was 66.62 Mg/ha, along with a total biomass value of 36.3 Mg/ha and a carbon stock of 18.15 Mg C/ha. Observations from the study show that these types of vegetations do play a substantial role in carbon sequestration. The results of this study will be useful to give an insight into the significance of these roadside trees to policymakers and the necessity for careful management of them. [ABSTRACT FROM AUTHOR]

Forested areas provide various services, including crucial carbon sequestration for climate change mitigation. The Madhupur Sal Forest (MSF) in Bangladesh was studied extensively for its ecosystem services and carbon sequestration potential. Research conducted from February to August 2023 in Gaira and Dokhola villages assessed local community benefits and biodiversity. Interviews with 50 respondents and analysis of 20 plots were conducted to study carbon sequestration in the MSF. Twenty identified ecosystem services range from fuel and wood to cultural and economic advantages. Eight tree species, totaling 401 trees, were identified, with Ficus hispida being the most effective in annual carbon sequestration. Shorea robusta showed less efficacy in carbon sequestration, resulting in a total forest capture of 12 004 657.8 pounds per year. The study highlights the MSF's significant contribution to global climate change mitigation. Emphasis is placed on the need for enhanced carbon sequestration through forest management, reforestation, and afforestation projects in deforested areas. Despite diverse ecosystem services, the MSF faces threats, necessitating collaborative conservation efforts, sustainable management practices, and community involvement for its vitality. [ABSTRACT FROM AUTHOR]

Spatialization of biomass and carbon stocks is essential for a good understanding of the forest stand and its characteristics, especially in degraded Mediterranean cork oak forests. Furthermore, the analysis of biomass and carbon stock changes and dynamics is essential for understanding the carbon cycle, in particular carbon emissions and stocks, in order to make projections, especially in the context of climate change. In this research, we use a multidimensional framework integrating forest survey data, LiDAR UAV data, and extracted vegetation indices from Landsat imagery (NDVI, ARVI, CIG, etc.) to model and spatialize cork oak biomass and carbon stocks on a large scale. For this purpose, we explore the use of univariate and multivariate regression modeling and examine several types of regression, namely, multiple linear regression, stepwise linear regression, random forest regression, simple linear regression, logarithmic regression, and quadratic and cubic regression. The results show that for multivariate regression, stepwise regression gives good results, with R2 equal to 80% and 65% and RMSE equal to 2.59 and 1.52 Mg/ha for biomass and carbon stock, respectively. Random forest regression, chosen as the ML algorithm, gives acceptable results, explaining 80% and 60% of the variation in biomass and carbon stock, respectively, and an RMSE of 2.74 and 1.72 Mg/ha for biomass and carbon stock, respectively. For the univariate regression, the simple linear regression is chosen because it gives satisfactory results, close to those of the quadratic and cubic regressions, but with a simpler equation. The vegetation index chosen is ARVI, which shows good performance indices, close to those of the NDVI and CIG. The assessment of biomass and carbon stock changes in the study area over 35 years (1985–2020) showed a slight increase of less than 10 Mg/ha and a decrease in biomass and carbon stock over a large area. [ABSTRACT FROM AUTHOR]

Lowland tropical rainforests provide an abundance of biodiversity as well as dynamic and stable ecosystems. These forests include tropical peat forests in various locations and forest types that have vegetation structure and composition characteristics, and carbon stocks that still need to be explored more deeply. Research on the structure and the composition of the vegetation and carbon stock in the old secondary peat forest was carried out in the protected areas of Bukit Batu, Riau Province, and Muara Merang, South Sumatra Province. Based on a 1-hectare permanent plot established in Bukit Batu and Muara Merang, 25 subplots of 20 m by 20 m were established in each location for measurement purposes. The results showed that Bukit Batu and Muara Merang had 42 and 36 species belonging to 26 and 20 families, respectively. Bukit Batu had a species diversity index (H') of 2.93, and the dominant tree species were Palaquium xanthochymum with an importance value index (IVI) = 66.27%, Eugenia sp. (IVI = 32.76%), and Litsea sp. (IVI = 18.39%). The Muara Merang location had a species diversity index (H') of 2.82, and the dominant tree species were Eugenia sp. (IVI = 60.88%), Alseodaphne insignis (IVI = 26.34%), and Adenanthera pavonina (IVI = 22.11%). In Bukit Batu, forest stands with a diameter of ≥10 cm contained a biomass of 178.10 tonnes/ha and carbon stock of 83.70 tonnes C/ha, which is equal to 307.20 tonnes CO2/ha. Meanwhile, in Muara Merang, it was 190.41 tonnes/ha and 89.49 tonnes C/ha, which is equal to 328.44 tonnes CO2/ha. This research, especially that in Bukit Batu, Riau Province, enriches the data and information available to date and is very useful in supporting restoration practices in Riau Province's Giam Siak Kecil Biosphere Reserve, which was designated by UNESCO as part of the Man and Biosphere Program. [ABSTRACT FROM AUTHOR]

Estimation of plant community composition, aboveground biomass and carbon stock is crucial for understanding forest ecology, strengthening environmental management, and developing effective tools and policies for forest restoration. This study was conducted in nine different forest reserves in Sri Lanka from 2012 to 2018 to examine the impact of community-based forest restoration (CBFR) on stand structural attributes, aboveground biomass, and carbon stock compared to state-managed forests. In total, 180 plots (90 plots in community-managed restoration blocks (CMRBs) and 90 plots assigned to state-managed restoration blocks (SMRBs)) were sampled at the study site. To conduct an inventory of standing trees, circular plots with a radius of 12.6 m (equivalent to an area of 500 square meters) were established. The Shannon diversity index, Allometric equations and Difference in Differences (DID) estimation were used to assess the data. Our study provides evidence of the positive impact of the CBFR program on enriching trees diversity. Considering stand structural attributes of both blocks showed higher trees density in the smaller diameter at breast height (DBH) category, indicating growth in both CMRBs and SMRBs. The results showed that tree biomass and carbon density were disproportionally distributed across the nine different forest reserves. On average, tree biomass and carbon density were higher in SMRBs (79.97 Mg ha−1, 37.58 Mg C ha−1) compared to CMRBs (33.51 Mg ha−1, 15.74 Mg C ha−1). However, CMRBs in Madigala reserve represent the highest biomass (56.53 and 59.92 Mg ha−1) and carbon density (26.57 and 28.16 Mg C ha−1). The results of biomass and carbon estimates were higher in all SMRBs in the nine different forest reserves compared to CMRBs. The findings suggest that future forest restoration programs in Sri Lanka should enhance participatory approaches to optimize tree species diversity, density and carbon storage, particularly in community-controlled forests. Our findings could assist developing tropical nations in understanding how CBFR impacts forest restoration objectives and improves the provision of ecological services within forests.

Agroforestry plays a pivotal role in mitigating greenhouse gas (GHG) emissions and addressing the challenges posed by climate change. While carbon sequestration efforts have primarily centred on forests, it is imperative to acknowledge the contribution that non-forest ecosystems, such as agroforestry, can offer. This study investigated the influence of agroforestry systems on the variation of biomass carbon stocks in the Sahelo-Sudanian and Sudanian regions of the Senegalese Groundnut basin. Three primary agroforestry systems were studied: silvopastoral, agrisilvicultural, and agrosilvopastoral. Forty-six (46) 100 m × 100 m plots were sampled, within which 1 × 1 m2 subplots were used to sample understory biomass across three agroforestry systems in the two climatic zones. Analysis of variance was performed to assess the influence of agroforestry systems and climatic zones on biomass carbon stocks. The findings showed that in the Sahelo-Sudanian region, the agrisilvicultural system exhibited the highest AGC + BGC stocks, averaging 43.42 ± 21.61 tCha−1. In contrast, the silvopastoral system showed significantly higher AGC + BGC stocks, which amounted to 36.33 ± 12.27 tCha−1 in the Sudanian region. On the other hand, understory carbon stocks were significantly higher (p < 0.01) in the agrisilvicultural and agrosilvopastoral systems than in the silvopastoral system in both climatic zones. Agroforestry systems had a significant effect on AGC + BGC stocks within climatic zones. Nevertheless, the effect was less pronounced when comparing across climatic regions. These results underscore the importance of specific land management practices interacting with local climatic conditions to influence AGC + BGC stocks. Therefore, policy makers should carefully consider the interaction of these factors when implementing carbon management practices and planning mitigation strategies in West Africa. [ABSTRACT FROM AUTHOR]

Accurate estimations of biomass and its temporal dynamics are crucial for monitoring the carbon cycle in forest ecosystems and assessing forest carbon sequestration potentials. Recent studies have shown that integrating process-based models (PBMs) with remote sensing data can enhance simulations from stand to regional scales, significantly improving the ability to simulate forest growth and carbon stock dynamics. However, the utilization of PBMs for large-scale simulation of larch carbon storage distribution is still limited. In this study, we applied the parameterized 3-PG (Physiological Principles Predicting Growth) model across the Mengjiagang Forest Farm (MFF) to make broad-scale predictions of the biomass and carbon stocks of Larix olgensis plantation. The model was used to simulate average diameter at breast height (DBH) and total biomass, which were later validated with a wide range of observation data including sample plot data, forest management inventory data, and airborne laser scanning data. The results showed that the 3-PG model had relatively high accuracy for predicting both DBH and total biomass at stand and regional scale, with determination coefficients ranging from 0.78 to 0.88. Based on the estimation of total biomass, we successfully produced a carbon stock map of the Larix olgensis plantation in MFF with a spatial resolution of 20 m, which helps with relevant management advice. These findings indicate that the integration of 3-PG model and remote sensing data can well predict the biomass and carbon stock at regional and even larger scales. In addition, this integration facilitates the evaluation of forest carbon sequestration capacity and the development of forest management plans. [ABSTRACT FROM AUTHOR]

Shrubbery and young plantations, with a large number of tree species, take up a broad area in subtropical Chinese forests and contribute a significant part to forest biomass and carbon (C) stocks. However, the biomass and C stocks of shrubbery and young plantations were generally underestimated or excluded in forest biomass calculations due to the scarce of standard equations for estimating biomass. The aim of this study was to develop appropriate regression equations for biomass estimation of shrubbery and young plantations. A total of 108 individuals of 15 most widespread shrub and young tree species were sampled by destructive harvesting, and the dry weight of each component of trees, i.e., foliage, branch, stem and root were obtained. The dry biomass of each component was correlated with plant height (H), basal diameter of stem (D), crown area (CA) and their composite variables D2H and CV (CA × H) by using seemingly uncorrelated regression, and the best fitted model was chosen according to the determination coefficient (R2), root mean squared error (RMSE), Akaike's information criterion (AIC) and percent relative standard errors (PRSE) less than 25%. In the species-specific equations, H, D or D2H were used as the appropriate independent variables in most of the equations, and only a few of them were CA or CV. In the multiple species equations, H was an important variable to predict the biomass, but the predictors of biomass equation for different functional groups or life forms were different due to diversity of external morphology. The species-specific equations had low biases, while the general equations for functional groups and life forms showed comparable biases, and the general equations for all species had the highest prediction biases. Therefore, general equations for functional groups or life forms are recommended to estimate biomass for species without species-specific allometric equations. [ABSTRACT FROM AUTHOR]

Land use and management are key factors affecting the transformation of soil organic matter. Indeed, stocks of decomposing organic matter are not always sufficiently replenished under current production. This study presents an assessment of the biomass and carbon stock in the Sudano-Sahelian savannah of Laf, Cameroon. Following a floristic inventory of the main land use types in the locality, the above-ground biomass was estimated and the carbon stock deduced. Biomass measurements were carried out in plots of 2500 m2 (50 m × 50 m) in the four main land use of the locality (tree stratum, shrub stratum, cultivared land, and fallow). Shrub biomass and ground litter mass are estimated in 10 m × 10 m plots, while the biomass of herbaceous is estimated in five 1 m × 1 m subplots, delimited at each top and in the center of the 10 m × 10 m plot. The carbon stock in the soil was assessed in the square plots of 25 cm × 25 cm, in the center of each subplot at a depth of 50 cm in five intervals of 10 cm each. The results of the floristic inventories revealed that the tree stratum is the richest in species (32 species). In the four main land use type of Laf, 20 family and 46 woody plant species were determined, and Combretum micranthum with 15.23% is the most frequent species. The total tree biomass is 242.65 t/ha and fallow (140.69 ± 11.96 t/ha) is the highest land use type. In the soil, the results showed that the 0–10-cm depth contains the highest amount of carbon. The fallow soils are also the richest in carbon with a content of 1.32 ± 0.31 tC/ha in the 0–10-cm depth. The carbon stock decreases with depth in the different land use types. The results obtained show that fallowing and the rational use of land make it possible to obtain good agricultural yields. Thus, this study is a contribution to the carbon stock assessment in the world in order to prevent famine in poor localities. [ABSTRACT FROM AUTHOR]

ABSTRACTAccurate carbon (C) stock estimation is crucial for C sequestration research, environmental protection, and policy formulation related to C management. Although research on C stock in forests, oceans, soil, and desert has received increasing attention, relatively few studies have focused on urban C stock. Moreover, the current mainstream methods for C stock assessment, including field surveys and satellite mapping, are characterised by notable limitations, including being labour-intensive and having limited real-time data acquisition capabilities. Therefore, this paper aims to assess urban C stock and proposes a novel two-stage estimation model based on deep learning and unmanned aerial vehicle (UAV) remote sensing. The first stage is that tree areas recognition via YOLOv5 and achieved 0.792 precision, 0.814 recall, and 0.805 mAP scores, respectively. In the second stage, a grid generation strategy and a Convolutional Neural Network (CNN) regression model were developed to estimate C stock based on recognised tree areas (R2 = 0.711, RMSE = 26.08 kg). Three regions with a minimum of 300 trees in each area were selected as validation sets. The experimental results, in terms of R2 and RMSE in kg, were (0.717, 0.711, 0.686) and (27.263, 27.857, 28.945), respectively.

Agroforestry is a land management strategy with high potential for carbon sequestration. However, the high carbon sequestration potential for agroforestry is still doubtful in many developing countries. This study investigates smallholder farmers’ preferred woody species for agroforestry and their carbon stock potential in West African Savannah. A sample of 345 smallholder farmers was selected across the four area councils within the Nandom Municipality. The plot method was adopted in surveying the woody species on farmlands. A non-destructive biomass estimation method was used by applying an area specific allometric model. A factor of 0.47 was used to convert the biomass of the preferred tree species to carbon. Parkia biglobosa, Acacia sp, Vitellaria paradoxa, Mangifera indica, and Azadirachta indica were the most preferred tree species. The preference for the tree species was based on the socio-economic and environmental benefits smallholders derived from the tree species. Vitellaria paradoxa and Parkia biglobosa were the tree species with the highest carbon stock potential. The study recommends that the Ministry of Food and Agriculture, in collaboration with the Forestry Service Commission and Non-Governmental Organisations interested in promoting agricultural activities, should facilitate training smallholder farmers on the nursery and integration of these tree species with their crops.

Understanding the variations in plant diversity, soil physico-chemical characteristics, and biomass storage under an age chronosequence of farm forests is crucial to advance our knowledge of their potential role in biodiversity conservation, soil management and climate change mitigation. The present work was conducted from September 2018 to February 2020 in randomly selected young unmanaged farm forests categorized into ≤ 5, 5–10 and 10–15 years old age classes with standard procedures of estimating diversity indices, biomass, carbon and soil physico-chemical parameters. Overall species richness of the plantations was 28, of which 11 were trees, 9 herbs, 3 shrubs, 3 climbers and 2 ferns. The quantitative vegetation parameters and diversity indices estimated indicate that the farm forests' plant assemblages constitute mainly native species. Based on IVI values, herbs were the most critical species, followed by shrubs and trees. With the increasing farm age, the species richness, the vegetative parameters and diversity indices decreased. The soil of the plantations was inconsistant nature and unstable characteristics as they did not exhibit any discrete trend with plantation age. Total biomass and organic carbon storage increased with increasing farm age. The overall mean total plant biomass, soil organic carbon, and ecosystem carbon storage in the farm forests were 87.94, 39.62 and 80.96 Mg ha− 1, respectively. Every subsequent increase of farm age by five years increased the ecosystem carbon stock by 33.22% and 4.09%, respectively while; the total increment was 38.67% from lowest to highest age class. The quantum of carbon storage in these farm forests was less than those reported for the native forests. Still, it can convert an unutilized agricultural landscape to a net carbon sink or even earn carbon credits. Moreover, the vegetation heterogeneity developed in these farm forests within a short span of 15 years can develop into semi-natural secondary forests with multiple social and ecological benefits in the long run. [ABSTRACT FROM AUTHOR]

The necessity to identify ecosystems with high carbon sink capacity as an alternative mitigation approach to terrestrial carbon sequestration has increased due to hazards such as global warming from emissions of Green House Gases mainly due to anthropogenic activities. Tea is an intensively managed perennial cash crop planted beneath a canopy of shade trees. They provide a prospect for the reduction of climate change while providing economic incentives so much so that some states and the country are dependent on the plantations and the revenue generated out of the tea gardens. Tea and shade trees together can store a significant quantity of atmospheric CO2 in the plants and the soil. The area of the gardens and the shade trees that grow in them makes it very necessary to estimate the amount of carbon sequestered in tea agroforestry systems and define their role as carbon sinks countering the climatic changes and the mitigation of the same. [ABSTRACT FROM AUTHOR]

Lowland tropical rainforests provide an abundance of biodiversity as well as dynamic and stable ecosystems. These forests include tropical peat forests in various locations and forest types that have vegetation structure and composition characteristics, and carbon stocks that still need to be explored more deeply. Research on the structure and the composition of the vegetation and carbon stock in the old secondary peat forest was carried out in the protected areas of Bukit Batu, Riau Province, and Muara Merang, South Sumatra Province. Based on a 1-hectare permanent plot established in Bukit Batu and Muara Merang, 25 subplots of 20 m by 20 m were established in each location for measurement purposes. The results showed that Bukit Batu and Muara Merang had 42 and 36 species belonging to 26 and 20 families, respectively. Bukit Batu had a species diversity index (H’) of 2.93, and the dominant tree species were Palaquium xanthochymum with an importance value index (IVI) = 66.27%, Eugenia sp. (IVI = 32.76%), and Litsea sp. (IVI = 18.39%). The Muara Merang location had a species diversity index (H’) of 2.82, and the dominant tree species were Eugenia sp. (IVI = 60.88%), Alseodaphne insignis (IVI = 26.34%), and Adenanthera pavonina (IVI = 22.11%). In Bukit Batu, forest stands with a diameter of ≥10 cm contained a biomass of 178.10 tonnes/ha and carbon stock of 83.70 tonnes C/ha, which is equal to 307.20 tonnes CO2/ha. Meanwhile, in Muara Merang, it was 190.41 tonnes/ha and 89.49 tonnes C/ha, which is equal to 328.44 tonnes CO2/ha. This research, especially that in Bukit Batu, Riau Province, enriches the data and information available to date and is very useful in supporting restoration practices in Riau Province’s Giam Siak Kecil Biosphere Reserve, which was designated by UNESCO as part of the Man and Biosphere Program.

Spatialization of biomass and carbon stocks is essential for a good understanding of the forest stand and its characteristics, especially in degraded Mediterranean cork oak forests. Furthermore, the analysis of biomass and carbon stock changes and dynamics is essential for understanding the carbon cycle, in particular carbon emissions and stocks, in order to make projections, especially in the context of climate change. In this research, we use a multidimensional framework integrating forest survey data, LiDAR UAV data, and extracted vegetation indices from Landsat imagery (NDVI, ARVI, CIG, etc.) to model and spatialize cork oak biomass and carbon stocks on a large scale. For this purpose, we explore the use of univariate and multivariate regression modeling and examine several types of regression, namely, multiple linear regression, stepwise linear regression, random forest regression, simple linear regression, logarithmic regression, and quadratic and cubic regression. The results show that for multivariate regression, stepwise regression gives good results, with R2 equal to 80% and 65% and RMSE equal to 2.59 and 1.52 Mg/ha for biomass and carbon stock, respectively. Random forest regression, chosen as the ML algorithm, gives acceptable results, explaining 80% and 60% of the variation in biomass and carbon stock, respectively, and an RMSE of 2.74 and 1.72 Mg/ha for biomass and carbon stock, respectively. For the univariate regression, the simple linear regression is chosen because it gives satisfactory results, close to those of the quadratic and cubic regressions, but with a simpler equation. The vegetation index chosen is ARVI, which shows good performance indices, close to those of the NDVI and CIG. The assessment of biomass and carbon stock changes in the study area over 35 years (1985–2020) showed a slight increase of less than 10 Mg/ha and a decrease in biomass and carbon stock over a large area.

Mangroves are the remarkably productive ecosystems of the world which losses its natural existence to a great portion and presently emphasis is given on its plantation for future conservation. Thus, present study focused on the development of biomass models for the Sonneratia caseolaris (L.) and Sonneratia apetala (Buch-Ham), and assessment of carbon stock for the plantation of central coastal areas of Bangladesh. Semi-destructive approach was applied for estimating the biomass of trees. The best-fit TAGB models for S. apetala and S. caseolaris plantations were Ln (TAGB) = -1.89 + 2.10 * Ln(D) + 0.23*Ln(H), and Ln (TAGB) = -3.09 + 2.31*Ln(D) + 0.35*Ln(H), respectively. Carbon stocks in TAGB and below-ground were estimated for a young mangrove plantation (40 years) with Sonneratia apetala separately. The mean ecosystem carbon stock (above- and below-ground) of young and mature were estimated to be 350.53 ± 14.23 t C/ha and 483.64 ± 16.35 t C/ha, respectively which varied significant (p

Even though, the blue carbon ecosystems are gaining keen research interest around the globe, the carbon stock of South-West coast of India was poorly reported, and this study is a pioneer attempt and will be an important document for filling the gaps in uncertainties in global carbon stock assessment and also will increase knowledge on biomass variability among mangrove species and mangrove habitats. The study also highlighted the vital role of biomass carbon pool for long-term soil carbon burial. We estimated the above and below-ground biomass carbon stock of 13 mangrove species using two common allometric equations and species-specific equations and reported a very high mean total living biomass carbon stock of Kochi mangroves at 237.19 ± 113.82 Mg C ha−1, 295.78 ± 143.14 Mg C ha−1, and 272.42 ± 132.78 Mg C ha−1 according to Chave's, Komiyama equation and species-specific equation respectively corresponding to carbon dioxide equivalent (CO2e) of approximately 4,37,774.51 Mg CO2e. The biomass stock was significantly differed between the stations (p = 0.000) and also within species (p = 0.020). Among the mangrove species, Avicennia officinalis contributed highest and Bruguiera sexangula contributed least. Variation was observed for biomass stock of mangroves with large trunk diameter while comparing different allometric equations and therefore projected the need for the development of site- and species-specific equations for solving the uncertainty in global mangrove carbon stock. The study observed that dominant mangrove vegetation type, salinity and also the geomorphology of mangrove habitat had strong influence on variability in biomass stock within a small regional area. The study also suggests that understanding the structure and biomass carbon storage of each regional mangrove habitats can be wisely used in mangrove restoration and conservation programmes and in turn for nature-based solutions for climate change mitigation efforts. [ABSTRACT FROM AUTHOR]

Vegetation absorbs carbon dioxide (CO2) emissions during photosynthesis. Covering more areas with trees will increase the CO2 absorption capacity more substantially than other vegetation like bushes, grasses, or rice fields. Trees convert the CO2 captured during photosynthesis into organic carbon to be stored in biomass. Woody trees account for approximately 60% of the total aboveground tree biomass, and trunks, where food reserves produced in photosynthesis are stored, have relatively large biomass compared to other parts of the tree. The biomass of a vegetation stand determines the optimization of air pollutant absorption in urban areas. Yogyakarta City is the center for tourism, education, and cultural activities in Indonesia, which is vulnerable to land-use conversion, a factor of the shrinking green space. This study aimed to estimate carbon stock from vegetation biomass in Yogyakarta City using the remote sensing product SPOT-7 imagery. To calculate the vegetation biomass, the diameter at breast height (DBH) of stands was measured in the field. Then, statistical analyses were performed to determine the correlation and regression between the actual or observed biomass and the Normalized Difference Vegetation Index (NDVI) value derived from the SPOT-7 image. The regression model used was y = 1.4277x - 0.0849. The total biomass produced in Yogyakarta City was estimated at 1,399,487.1 tonnes, which contained 643,764.1 tonnes of carbon stock. [ABSTRACT FROM AUTHOR]

Wood specific gravity (WSG) is one of the important variables in biomass and carbon stock estimation through non-destructive method. Present study was conducted in a tropical dry deciduous forest in central India. A non-destructive method was adopted for biomass estimation. Habitat specific WSG of all the species present in the study area was determined using maximum moisture content method. Reported WSG values of the same species were procured from global wood density database. The present paper deals with the comparison of biomass and carbon stock of mature individuals estimated using habitat specific WSG and WSG procured from the database for the same species. Further, comparison was made among biomass and carbon values estimated using habitat specific WSG and without WSG for juvenile individuals. Procured WSG from database for different tree species were found to be higher in most cases than the WSG determined in the habitat. Results envisage that biomass estimates using non habitat specific WSG (database) over-estimate the biomass and carbon stock. Total biomass (including both mature and juvenile individuals) per hectare was 24.2% higher with reported WSG for mature individuals and without WSG for juvenile individuals than using habitat specific WSG for both mature and juvenile individuals. It is calculated that using WSG from data base may result in increased AGB by 1.5 × 108 Mg and 6.6 × 108 Mg at state and national level respectively. We suggest the consideration of habitat specific WSG for biomass and carbon estimation in non-destructive method for both mature and juvenile individuals. [ABSTRACT FROM AUTHOR]

A study was conducted during 2019-20 to document the predominant tree species, biomass, carbon stock and sequestration of undisturbed natural forest lands (40 years) across the 18 mandals of the Vikarabad district (3386 sq. km area with 109,325 population) of Telangana state. Results revealed that the predominant tree species consisted of Eucalyptus grandis, Tectona grandis, Azadirachta indica and Ficus benghalensis. The highest total biomass, carbon stock and sequestration were registered with Eucalyptus grandis (179.08, 89.54 and 328.62 tonne ha-1 respectively) followed by Ficus benghalensis (140.66, 70.33 and 258.10 tonne ha-1 respectively) and Tamarindus indica (51.60, 25.80 and 94.68 tonne ha-1 respectively) and minimum with Pongamia pinnata (0.31, 0.15 and 0.57 tonne ha-1 respectively). Deviation in volume, carbon stock and sequestration was due to the variation in height, girth and biomass of individual tree species. The results identified the potent tree species with high C stocks and sequestration for regions with similar climates and useful for environmental education to the people for climate change mitigation. [ABSTRACT FROM AUTHOR]

The foremost role of forest vegetation in storing biomass and carbon (C) stock constitutes one of the main nature-based solutions to mitigate climate change. In this study, we aimed to quantify biomass and C stock partitioning in multiple vegetation strata (tree, shrub, herb, and ground floor layers) of major forest types in Jammu and Kashmir, Western Himalaya, India. We used a stratified random cluster sampling strategy to collect field data in 96 forest stands of 12 forest types (altitudinal range: 350 to 3450 m) in the study region. We evaluated the degree to which the carbon stock of the entire ecosystem was dependent on the multiple vegetation strata using the Pearson method. Across all the forest types, the average total ecosystem-level biomass was estimated to be 181.95 Mgha−1 (range: 60.64–528.98). Forest strata-wise, the maximum biomass of 172.92 Mgha−1 (range: 50.64-514.97) was found in the tree vegetation, followed by 5.58 Mgha−1 (range: 2.59–8.93) in understory vegetation (shrubs and herbaceous), and 3.44 Mgha−1 (range: 0.97 and 9.14) in the forest floor. The total ecosystem-level biomass showed a peak at mid-elevation coniferous forest types, whereas the lowest was observed in low-elevation broad leaved forest types. At the ecosystem-level, on average, the understory contributed 3% and the forest floor 2% to the total C stock across the forest types. The shrub layer contributed up to 80% of total understory C, with the herbaceous layer accounting for the remaining 20%. The ordination analysis clearly shows that anthropogenic and environmental variables significantly (p ≤ 0.002) influence the forest types' C stock in the region. Our findings have significant implications for conserving natural forest ecosystems and restoring degraded forest landscapes in this Himalayan region, which in turn can lead to better carbon sequestration and climate mitigation outcomes. [ABSTRACT FROM AUTHOR]

Abstract Background In Ethiopia, highland bamboo has been cultivated in various niches: farmlands, riverbanks, woodlot boundaries, and homesteads, and agroforestry systems. However, the biomass and carbon storage of potential of bamboo forests across niches is not well characterized in Ethiopia. Therefore, this study was conducted to estimate the biomass and carbon storage potential of highland bamboo plantations in northwestern Ethiopia. To this end, a total of 60 circular plots measuring 100 m2 with a radius of 5.64 m were randomly established on the homestead, woodlot, and riverbank plantation niches to conduct the inventory. The biomass storage of bamboo was calculated based on previously published allometric equations. Biomass and carbon stock variations among age-classes and niches of bamboo forests were analyzed using analysis of variance (ANOVA) and subsequent pairwise means comparisons of carbon stocks among niches were performed via post hoc Tukey test at p

Climate change caused by various activities of human activity has produced carbon dioxide gas affecting global warming. Seagrass ecosystem has the ability to absorb and store large quantities of carbon that can reduce carbon emissions. Objectives of this study is to assess seagrass population structure, assess carbon deposits estimation and water quality parameters. The method used in this research is purposive sampling method and location determination used line Transect quadrant method which refers to LIPI method. Carbon measurements in seagrass samples used LOI method. Seagrass species found in the waters of Baluran National Park are Enhalus acoroides, Thalassia hemprichii, Cymodocea rotundata, Cymodocea serrulata, Syringodium isoetifolium, Halophila minor, Halophila ovalis dan Halodule uninervis. The seagrass Enhalus acoroides has a highest biomass value and an estimate of carbon deposits 37.817 gC/m2. The total estimate of the highest carbon stock is obtained at the bottom of the substrate 40.063 ton. Perubahan iklim yang disebabkan oleh berbagai aktifitas kegiatan manusia menghasilkan gas karbon diokasida yang berdampak pada pemanasan global. Ekosistem padang lamun memiliki kemampuan untuk menyerap dan menyimpan karbon dalam jumlah besar yang dapat mengurangi emisi karbon. Tujuan penelitian ini adalah: 1) mengkaji struktur populasi lamun, 2) mengkaji estimasi simpanan karbon, 3) mengkaji parameter kualitas air di Taman Nasional Baluran. Metode yang digunakan yaitu purposive sampling method dan penentuan lokasi menggunakan metode line transect quadrant yang mengacu pada metode LIPI. Pengukuran kualitas air dilakukan secara langsung di lapangan sesuai Standar Nasional Indonesia (SNI) dan pengukuran karbon pada sampel lamun menggunakan metode LOI. Berdasarkan hasil penelitian, diketahui bahwa Spesies lamun yang ditemukan di perairain Taman Nasional Baluran adalah Enhalus acoroides, Thalassia hemprichii, Cymodocea rotundata, Cymodocea serrulata, Syringodium isoetifolium, Halophila minor, Halophila ovalis dan Halodule uninervis. Jenis lamun Enhalus acoroides mempunyai nilai biomassa dan estimasi simpanan karbon paling tinggi yaitu 37,817 gC/m2. Estimasi total stok karbon tertinggi didapatkan pada bagian bawah substrat (rhizoma dan akar) sebesar 40,063 ton.

Forest biomass, being the main indicator of ecosystem productivity, is used in assessing the global carbon cycle and modeling climate change. The aim of the research is to assess the reserves of carbon and terrestrial biomass in forest ecosystems, using satellite images. In the method of obtaining data of terrestrial biomass and carbon stock based on the integration of ground-based (field, desk) forest studies, remote sensing of the Earth is considered. An assessment of carbon stocks and terrestrial biomass in forest ecosystems adjacent to Lake Talkas, located on the eastern slopes of the Southern Urals, was carried out. We used regression analysis to predict AGB. Studies have shown the reserves of aboveground biomass in the sample areas to be closely correlated with the values of the vegetation index, NDVI. The closeness of the relationship between the NDVI values at the study points with aboveground biomass is characterized by a correlation coefficient equal to 0.877. The NDVI values in the tested areas vary from 0.60 to 0.80. The highest indicator of terrestrial biomass was 245.69 t/ha, the lowest—4.42 t/ha. Estimated carbon reserves using NDVI in the studied forest areas growing along Lake Talkas ranged from 2.07 t/ha to 115.47 t/ha with an average CO2 reserve of 40.2 t/ha. It can therefore be concluded that the use of the NDVI is a reliable method for assessing AGB and carbon stocks in forest ecosystems.Highlights: Forest biomass is an important indicator of ecosystem productivity. Hyperspectral data can improve the prediction of compared forest biomass. Proper management can increase the ability of forests to absorb more carbon. The research used a modern Sentinel-2 satellite to map the reserves of terrestrial biomass and carbon. [ABSTRACT FROM AUTHOR]

Utilizing available land efficiently in the cities helps in climate stabilization through carbon sequestration and conserves biodiversity, apart from providing many other ecosystem benefits. This study investigates the diversity and carbon sequestration in trees that are grown in different landscapes of cities such as residential area, avenue trees, parks, industrial area and around lakes in one of the wards of Bengaluru city. In the present study, 44 tree species belonging to 23 families were recorded among the different landscapes mentioned. Among the five landscapes studied, the highest tree population is noticed among the avenue trees. Pongamia pinnata is the most dominant tree species. The residential area had the highest tree biomass and Parks had the lowest biomass assessed from the top ten dominant trees that constituted about 82 per cent of the population. Total carbon sequestered by the trees from the study area is 505 tons and total CO2 sequestered is 1852 tons. The total amount of carbon stocked in five landscapes varied from 155 tons km-1 in the industrial area, followed by avenue trees (143 tons km-1) and least was found around the lakes (26 tons km-1). Thus, maintaining trees in urban areas help in conserving biodiversity and ameliorating climate. [ABSTRACT FROM AUTHOR]

Carbon dioxide reduction by trees is an important ecosystem service for human well-being. It is often overlooked by beneficiaries, and rarely taken into account in studies. The aim of this study was to determine the carbon sequestration potential of the vegetation of the forest relic of the Peleforo Gon Coulibaly University in Korhogo (Northern Côte d'Ivoire). For the collection of dendrometric data, all individuals with a diameter at breast height (dbh) ≥ 5 cm were measured in 900 m² square plots (30 m x 30 m). The average density of woody plants was 788 plants/ha. The distribution by diameter classes of the woody plants revealed a predominance of small diameter individuals. The amount of biomass produced by the forest reserve was 219.92 t/ha corresponding to a sequestered carbon stock of 109.96 t/ha, and a CO2 equivalent of 403.18 t/ha. Individually, local species such as Adansonia digitata and Ceiba pentandra sequester the most CO2 in the reserve. The total amount of carbon sequestered was estimated at 16942.07 tonnes. This carbon stock potential shows the importance of the compensatory role of the forest reserve in the carbon dioxide emissions from anthropogenic activities in the Poro region.

Urban forests have a role in climate regulation by managing greenhouse gas emissions. The aim of this study was to assess the potential carbon (C) stock of both above ground biomass (AGB) and below-ground biomass (BGB) in the un-conserved Entoto mount forest and to determine their contribution to mitigating climate change and enhancing ecosystem services. The selected study sites recorded a total of 417 trees, with Eucalyptus globulus covering 45.08% of the species and Juniperus procera covering 38.13%. The average AGB was 114.28 ton/hectare (t/ha), while BGB it was 22.28 t/ha. The average C content in the AGB was 53.73 t/ha, while in the BGB it was 10.81 t/ha. This study enhances the comprehension of the forest’s present ecological condition and facilitates decision-making processes for conservation and sustainable development.