Search

Global warming is a critical factor driving climate change, impacting every aspect of life on Earth. The escalating concentration of greenhouse gasses in the atmosphere, the primary contributor to global warming, necessitates immediate action through effective climate mitigation strategies. This study aimed to quantify the biomass and blue carbon stocks in the eastern coastal mangrove forests of North Sumatra and Aceh Provinces in Indonesia, focusing on key sites in Langkat, Deli Serdang, Batu Bara, Tanjung Balai, and Aceh Tamiang Regencies. We measured carbon stock in three carbon pools: biomass (above and below ground), necromass, and soil. By analyzing tree stands using parameters such as tree height and diameter at breast height within circular plots (7 m in radius, 125 m apart), we gathered fundamental data on forest structure, species composition, and above- and below-ground biomass. Additionally, we collected soil samples at various points and depths, measuring the amount of wood, stems, or branches (necromass) that fell to or died on the forest floor. Data were collected in plots along a line transect, comprising three transects and six circular plots each. Sixteen diverse mangrove species were found, demonstrating rich mangrove biodiversity. The mangrove forests in the five regencies exhibited significant carbon storage potential, with estimated average above-ground carbon ranging from 96 to 356 MgC/ha and average below-ground carbon from 28 to 153 MgC/ha. The estimated average deadwood carbon varied between 50 and 91 MgC/ha, while soil carbon ranged from 1200 to 2500 MgC/ha. These findings underscore the significant carbon storage potential of these mangrove forests, highlighting their importance to global carbon cycling and climate change mitigation. This research contributes to a broader understanding of mangroves as vital blue carbon ecosystems, emphasizing the necessity of conservation efforts such as forest restoration and rehabilitation to enhance their role in stabilizing coastal areas and improving global climate resilience.

Changes in land use from high-nature-value grasslands to arable fields reduce the organic carbon stock in soil, increasing atmospheric carbon concentrations. Maintaining grasslands through traditional agricultural techniques can mitigate climate change by transferring atmospheric carbon to the soil. Benefits of soil organic carbon sequestration include improved soil properties and enhanced ecosystem services and biodiversity. With Romania’s ratification of the Paris Agreement, it is crucial to review climate-related agricultural policies and incentivize carbon sequestration practices in organic soils. This paper presents a soil carbon study in Transylvania’s Târnava Mare region, Romania, known for its preserved cultural landscapes. Soil samples were taken at a depth of 60 cm to assess organic carbon pools under grassland and arable land management across three soil classes: Cernisoils, Hidrisoils, and Luvisoils. Several statistical tests were applied to evaluate the most significant drivers of soil organic carbon sequestration including land use, soil class, and soil depth. The results indicate that land management has the largest impact, with grasslands storing 45% more carbon than arable land on average. This finding should be integrated into national climate action plans, prioritizing the preservation of grasslands and sustainable agricultural practices to support soil organic carbon sequestration.

The increase in atmospheric CO2 leads to global warming and ecological environment deterioration. Carbon storage modeling and assessment can promote the sustainable development of the ecological environment. This paper took Xinjiang as the study area, analyzed the spatial and temporal evolution of land use in four periods from 1990 to 2020, explored the spatial relationship of carbon stocks using the InVEST model, and coupled the GMOP model with the PLUS model to carry out multiple scenarios for the future simulation of land use in the study area. We found (1) Over time, the types with an increasing area were mainly impervious and cropland, and the types with a decreasing area were grassland, snow/ice, and barren; spatially, the types were predominantly barren and grassland, with the conversion of grassland to cropland being more evident in the south of Northern Xinjiang and north of Southern Xinjiang. (2) The evolutionary pattern of terrestrial carbon stocks is increasing and then decreasing in time, and the carbon sink areas are concentrated in the Tarim River Basin and the vicinity of the Ili River; spatially, there are differences in the aggregation between the northern, southern, and eastern borders. By analyzing the transfer in and out of various categories in Xinjiang over the past 30 years, it was obtained that the transfer out of grassland reduced the carbon stock by 5757.84 × 104 t, and the transfer out of Barren increased the carbon stock by 8586.12 × 104 t. (3) The land use layout of the sustainable development scenario is optimal under the conditions of satisfying economic and ecological development. The reduction in terrestrial carbon stocks under the 2020–2030 sustainable development scenario is 209.79 × 104 t, which is smaller than the reduction of 830.79 × 104 t in 2010–2020. Land optimization resulted in a lower loss of carbon stocks and a more rational land-use layout. Future planning in Xinjiang should be based on sustainable development scenarios, integrating land resources, and achieving sustainable economic and ecological development.

Long-term excessive use of fertilizers and intensive cultivation not only decreases soil organic carbon (SOC) and productivity, but also increases greenhouse gas emissions, which is detrimental to sustainable agricultural development. The purpose of this paper is to identify organic amendments suitable for winter wheat growth in the North China Plain by studying the effects of organic amendments on the economic benefits, carbon emissions, and carbon sequestration for winter wheat fields and to provide a theoretical basis for the wide application of organic amendments in agricultural fields. The two nitrogen rates were N0 (0 kg ha−1) and N240 (240 kg ha−1), and the four organic amendments were straw, manure, mushroom residue (M R), and biochar. The results showed that, compared to N0, N240 significantly increased the yield by 244.1–318.4% and the organic carbon storage by 16.7–30.5%, respectively, but increased the carbon emissions by 29.3–45.5%. In addition, soil carbon stocks increased with all three types of organic amendments compared to the straw amendment, with the biochar treatment being the largest, increasing carbon storage by 13.3–33.6%. In terms of yield and economic benefits, compared to the straw amendment, the manure and biochar amendments increased winter wheat yields by 0.0–1.5% and 4.0–13.3%, respectively, and M R slightly decreased wheat yield; only the economic benefit of the M R amendment was greater than that of the straw amendment, with an increase in economic benefit of 1.3% and 8.2% in the 2021–2022 and 2022–2023 seasons, respectively. Furthermore, according to the net ecosystem productivity (NEP), N0 was the source of CO2, while N240 was a sink of CO2. The TOPSIS results showed that N240 with a mushroom residue amendment could be recommended for increasing soil carbon stocks and economic benefits for winter wheat in the NCP and similar regions. Low-cost M R can increase farmer motivation and improve soil organic carbon, making a big step forward in the spread of organic materials on farmland.

In recent years, the “dual carbon” issue has become a major focus of the international community. Changes in land use driven by anthropogenic activities have a profound impact on ecosystem structure and carbon cycling. This study quantitatively assesses the spatiotemporal changes in cropland occupation and supplementation in the Pearl River Delta from 2000 to 2020 using the InVEST model, analyzing the spatial clustering of carbon storage changes caused by variations in cropland area. The PLUS model was employed to simulate land-use patterns and the spatial distribution of carbon storage in four future development scenarios. The results indicate the following: (1) From 2000 to 2020, the net change rate of cropland area in the Pearl River Delta was −0.81%, with a decrease of 16.49 km2 in cropland area, primarily converted to built-up land and forest land. (2) Carbon storage in the Pearl River Delta exhibited a pattern of lower values in the center and higher values in the periphery. The terrestrial ecosystem carbon storage in the Pearl River Delta was 534.62 × 106 t in 2000, 518.60 × 106 t in 2010, and 512.57 × 106 t in 2020, showing an overall decreasing trend. The conversion of cropland and forest land was the main reason for the decline in total regional carbon storage. (3) The area of carbon sequestration lost due to cropland occupation was significantly greater than the area of carbon loss compensated by new cropland, indicating an imbalance in the quality of cropland occupation and supplementation as a crucial factor contributing to regional carbon loss. (4) Under the ecological priority scenario, the expansion of built-up land and the reduction in ecological land such as cropland and forest land were effectively controlled, resulting in the minimal loss of carbon storage. The soil organic carbon pool of cropland is the most active carbon pool in terrestrial ecosystems and has a significant impact on carbon storage. Clarifying the relationship between “cropland protection measures–land use changes–ecosystem carbon storage” will improve cropland protection policies, provide references for regional carbon sequestration enhancement, and support sustainable socio-economic development.

Carbon stocks provide information that is essential for analyzing the role of forests in global climate mitigation, yet they are highly vulnerable to wildfires in Mediterranean ecosystems. These carbon stocks’ exposure to fire is usually estimated from specific allometric equations relating tree height and diameter to the overall amount of aboveground carbon storage. Assessments of vulnerability to fire additionally allow for specific fire resistance (bark thickness, crown basal height) and post-fire recovery traits (cone mass for regeneration, and fine branches or leaves mass for flammability) to be accounted for. These traits are usually considered as static, and their temporal dynamic is rarely assessed, thus preventing a full assessment of carbon stocks’ vulnerability and subsequent cascading effects. This study aimed to measure the pools of carbon stocks of individual trees varying between 30 and 96 years old in the Djbel Mansour Aleppo pine (Pinus halepensis) forest in semi-arid central Tunisia in the southern range of its distribution to fit a sigmoid equation of the carbon pools and traits recovery according to age as a vulnerability framework. Allometric equations were then developed to establish the relationships between fire vulnerability traits and dendrometric independent variables (diameter at breast height, height, and live crown length) for further use in regional vulnerability assessments. The total carbon stocks in trees varied from 29.05 Mg C ha−1 to 92.47 Mg C ha−1. The soil organic carbon stock (SOC) at a maximum soil depth of 0–40 cm varied from 31.67 Mg C ha−1 to 115.67 Mg C ha−1 at a soil depth of 0–70 cm. We could identify an increasing resistance related to increasing bark thickness and basal crown height with age, and enhanced regeneration capacity after 25 years of age with increasing cone biomass, converging toward increasing vulnerability and potential cascading effects under shorter interval fires. These results should be considered for rigorous forest carbon sequestration assessment under increasing fire hazards due to climate and social changes in the region.

Roots play a fundamental role in forest ecosystems, but obtaining samples from deep layers remains a challenging process due to the methodological and financial efforts required. In our quest to understand the dynamics of Eucalyptus roots, we raise three fundamental questions. First, we inquire about the average extent of the roots of two contrasting Eucalyptus genotypes. Next, we explore the factors that directly influence the growth and depth of these roots, addressing elements such as soil type, climate, and water availability. Lastly, we investigate how the variation in Eucalyptus species may impact root growth patterns, biomass, and carbon stock. In this study, we observed that the maximum root depth increased by an average of 20% when genotypes were grown on sites with higher water availability (wet site). E. urophylla stands had a higher biomass and carbon stock (5.7 Mg C ha−1) of fine roots when cultivated on dry sites (annual rainfall~727 mm) than the wet sites (annual rainfall~1590 mm). In E. grandis × E. camaldulensis stands, no significant differences were observed in the stock of fine root biomass (3.2 Mg C ha−1) between the studied environments. Our results demonstrated that genotypes with greater drought tolerance (E. grandis × E. camaldulensis) tend to maintain higher stocks of fine root biomass (3.2–6.3 Mg ha−1) compared to those classified as plastic (E. urophylla), regardless of the edaphoclimatic conditions of the cultivation site. Finally, our research helps understand how Eucalyptus trees adapt to their environment, aiding sustainable forest management and climate change mitigation. We also provide a practical tool to estimate underground biomass, assisting forest managers and policymakers in ensuring long-term forest sustainability.

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.

This study examines the impact of silvicultural and land-use management practices on carbon sequestration in peri-urban forest ecosystems, with a particular focus on human-induced carbon dynamics. The study area’s complex profile spans from a compact native forest to varying degrees of fragmentation. This included areas undergoing secondary succession forest without silvicultural interventions (No-SI) alongside sites subjected to high-intensity (High-SI) and low-intensity silvicultural interventions (Low-SI). The research assessed carbon stocks and sequestration in different carbon pools (living biomass, dead organic matter and soil) using field data, allometric equations and laboratory analysis. Findings reveal a significant correlation between the intensity of anthropogenic interventions and variations in carbon stocks. The CASMOFOR model facilitated the reconstruction of carbon stock and carbon-stock change dynamics over four decades (1980–2022), showing disparities in carbon storage capabilities linked to the structural characteristics of the sites. The Low-SI site had the highest carbon stock in all carbon pools (378 tonnes C ha−1), which is more than double compared to High-SI (161 tonnes C ha−1) or No-SI sites (134 tonnes C ha−1). However, the secondary succession forest (No-SI) demonstrated the highest annual carbon stock change (4.4 tonnes C ha−1 year−1), two times higher than the Low-SI mature stand (2.2 tonnes C ha−1 year−1), emphasising the resilience of forest ecosystems to recover and sustain carbon sequestration capacities after harvesting if forest land use remains unchanged. The study underscores the significant importance of anthropogenic interventions on carbon dynamics, especially for living tree biomass, which has consequences in enhancing carbon sequestration and contributing to emission reduction targets.

The spatial–temporal distribution and evolution characteristics of carbon stock under the influence of land use changes are crucial to the scientific management of environmental resources and the optimization of land spatial layout. Taking the Xiamen–Zhangzhou–Quanzhou urban agglomeration in the southeastern coastal region of China as an example, based on seven land use types from 1990 to 2020, including cultivated land, woodland, and construction land, we quantitatively investigate the spatial–temporal patterns of carbon stock development and the spatial correlation of carbon stock distribution. Additionally, two scenarios for the development of urban and ecological priorities in 2060 are established to investigate the effects of land use changes on carbon stock. The results indicate that (1) the research area has formed a land use spatial pattern centered around urban construction in the eastern bay area, with the western forest area and coastal forest belt serving as ecological barriers. Carbon stock is influenced by land use type, and the distribution of total carbon stock exhibits a spatial aggregation phenomenon characterized by “low in the southeast, high in the north, and medium in the center”. (2) Distance of trunk and secondary roads, elevation, slope, watershed borders, population size, and gross domestic product (GDP) factors are the main drivers of the growth of land use types. The primary causes of the reduction in carbon stock are the widespread conversion of cultivated land, woodland, and grassland into construction land, as well as water and unused land. (3) In 2060, there will be a decrease of 41,712,443.35 Mg in the urban priority development scenario compared to 2020, and a decrease of 29,577,580.48 Mg in the ecological priority development scenario. The estimated carbon stock under the two scenarios varies by 12,134,862.88 Mg. The average carbon storage of Zhangpu County, Quangang County, and Jimei County is expected to rise by one level under the ecological protection scenario, indicating that the vast forest area can become a potential area to maintain carbon stock. It is crucial to encourage the coordinated development of peri-urban agroforestry and ecological barriers, as well as to establish a harmonious spatial pattern of land use and carbon stock at the scale of urban agglomerations.

Forests face a variety of threats in the modern era. Agroforestry systems, both traditional and introduced, have a tremendous capacity for providing sustainable resources and combating the impact of global climate change. Indigenous agroforestry and forest land-use systems are important reservoirs for biodiversity conservation and ecosystem services, providing a potential contribution to livelihood security for rural communities. This study aimed to assess the tree diversity and carbon stock of agroforestry and adjoining forests along altitudinal gradients, ranging between 700 and 2200 masl (i.e., lower, middle, and upper altitudes) by laying sample plots randomly of a size of 20 × 20 m2. In the forest land-use system, the maximum Importance Value Index (IVI) included Dalbergia sissoo (71.10), Pyrus pashia (76.78), and Pinus roxburghii (79.69) at the upper, middle, and lower elevations, respectively, whereas, in the agroforestry land-use system, the IVI reported for Ficus semicordata was 43.05 at the upper, while for Grewia optiva it was at 53.82 at the middle and 59.33 at the lower altitudes. The below-ground biomass density (AGBD) was recorded as 1023.48 t ha−1 (lower), 242.92 t ha−1 (middle), and 1099.35 t ha−1(upper), while in the agroforestry land-use system, the AGBD was 353.48 t ha−1 (lower), 404.32 t ha−1 (middle), and 373.23 t ha−1 (upper). The total carbon density (TCD) values recorded were 630.57, 167.32, and 784.00 t ha−1 in forest land-use systems, and 227.46, 343.23, and 252.47 in agroforestry land-use systems for lower, middle, and upper altitudes, respectively. The Margalef’s Index values for agroforestry and forests ranged from 2.39 to 2.85 and 1.12 to 1.30, respectively. Soil organic carbon (SOC) stock recorded 45.32, 58.92, and 51.13 Mg C ha−1 for agroforestry and 61.73, 42.65, and 71.08 Mg C ha−1 for forest in lower, middle and upper elevations, respectively. The study suggests that selecting land use patterns can be an effective management system for tree species at different elevations for carbon storage, helping to mitigate climate change and aiding in sustainable management of ecosystems in the Garhwal Himalayas.

Accurately mapping crop aboveground biomass (AGB) in a timely manner is crucial for promoting sustainable agricultural practices and effective climate change mitigation actions. To address this challenge, the integration of satellite-based Earth Observation (EO) data with advanced machine learning algorithms offers promising prospects to monitor land and crop phenology over time. However, achieving accurate AGB maps in small crop fields and complex landscapes is still an ongoing challenge. In this study, the AGB was estimated for small sugarcane fields (2) as 0.85 and 0.86 with a root mean square error (RMSE) of 8.84 and 9.61 t/ha for the years 2018 and 2021, respectively. In addition, mapping sugarcane AGB and carbon stock across a large scale showed high spatial variability within fields for both base years. These results exhibited a high potential for effectively depicting the spatial distribution of AGB densities. Finally, it was shown how these highly accurate maps can support, as valuable tools, sustainable agricultural practices, government policy, and decision-making processes.

Climate and land-use changes have been contributing to the increase in the occurrence of extreme wildfires, shifting fire regimes and driving desertification, particularly in Mediterranean-climate regions. However, few studies have researched the influence of land use/cover on fire regimes and carbon storage at the broad national scale. To address this gap, we used spatially explicit data from annual burned areas in mainland Portugal to build a typology of fire regimes based on the accumulated burned area and its temporal concentration (Gini Index) between 1984 and 2019. This typology was then combined with carbon stock data and different landscapes to explore relationships between landscape types and two important ecosystem services: wildfire reduction and carbon stock. Multivariate analyses were performed on these data and the results revealed a strong relationship between landscapes dominated by maritime pine and eucalypt plantations and highly hazardous fire regimes, which in turn hold the highest carbon stocks. Shrubland and mixed landscapes were associated with low carbon stocks and less hazardous fire regimes. Specialized agricultural landscapes, as well as mixed native forests and mixed agroforestry landscapes, were the least associated with wildfires. In the case of agricultural landscapes, however, this good wildfire performance is achieved at the cost of the poorest carbon stock, whereas native forests and agroforestry landscapes strike the best trade-off between carbon stock and fire regime. Our findings support how nature-based solutions promoting wildfire mitigation and carbon stock ecosystem services may prevent and revert land degradation harming Mediterranean regions.

Wetlands provide important ecosystem services, such as water conservation, biodiversity protection, and carbon sequestration. The Zoige alpine wetland is the largest high-altitude swamp in the world and plays a critical role in regional ecological balance and climate change. However, little is known about the fate of its soil organic carbon (SOC) storage. In this study, we estimated the degradation status of the wetland over the past 35 years and used machine learning to investigate the dynamics and driving factors of SOC at different soil depths of the Zoige wetland in 1985, 2000, and 2020. We also simulated the future SOC balance under different scenarios. The results showed that the area of Zoige wetland has degraded by 378.71 km2 in the past 35 years. Increased precipitation and solar radiation offset the adverse effects of global warming, making the soil act as a carbon sink in the past 35 years. The total SOC storage of the wetland soils in 1985, 2000, and 2020 was estimated to be 2.03 Pg, 2.05 Pg, and 2.21 Pg, respectively, with 46.95% of SOC distributed in the subsoil layers. Climate change was the most important driving factor controlling the SOC storage of the Zoige wetland, explaining 51.33% of the SOC changes in the soil. Temperature change was always the most important factor controlling wetland SOC, and precipitation had a greater impact on the topsoil. Under the temperature control targets of 1.5 °C and 2 °C, the SOC pool of the Zoige wetland will decrease by 60.21 Tg C and 69.19 Tg C, respectively. Under scenarios of a 10% and 20% increase in precipitation, the wetland soil will accumulate an additional 46.53 Tg C and 118.89 Tg C, respectively. The study results provide important references for the sustainable management of the Zoige wetland under the background of global climate change.

The use of photogrammetry technology for aboveground biomass (AGB) stock estimation in tropical savannas is a challenging task and is still at a preliminary stage. This work aimed to use metrics derived from point clouds, constructed using photogrammetric imaging obtained by an RGB camera on board a remotely piloted aircraft (RPA), to generate a model for estimating AGB stock for the shrubby-woody stratum in savanna areas of Central Brazil (Cerrado). AGB stock was estimated using forest inventory data and an allometric equation. The photogrammetric digital terrain model (DTM) was validated with altimetric field data, demonstrating that the passive sensor can identify topographic variations in sites with discontinuous canopies. The inventory estimated an average AGB of 18.3 (±13.3) Mg ha−1 at the three sampled sites. The AGB model selected was composed of metrics used for height at the 10th and 95th percentile, with an adjusted R2 of 93% and a relative root mean squared error (RMSE) of 16%. AGB distribution maps were generated from the spatialization of the metrics selected for the model, optimizing the visualization and our understanding of the spatial distribution of forest AGB. The study represents a step forward in mapping biomass and carbon stocks in tropical savannas using low-cost remote sensing platforms.

Uncertainties continue to prevail in the potential of natural forests and plantations in carbon stock assessment. The present study was carried out to assess the carbon stock in natural and plantation forests of Manipur using geo-informatics in Imphal East and West districts. The integrated approach of geospatial technology, along with field inventory based data, was used in spatial modeling of biomass carbon of selected natural and plantation forests. The stand density was similar for both LNG and TRS forests (680 individuals ha−1) and lowest for KHP forest (640 individuals ha−1). Paulownia fortunei (770 individuals ha−1) showed highest density among tree species while Tectona grandis (54.07 m2 ha−1) followed by Gmelina arborea (42.18 m2 ha−1) had higher basal area compared to other tree species. The soil moisture content (%) in the natural forest ranged from 19.13 ± 0.47 to 26.9 ± 0.26%. The soil moisture content in the plantation forest ranged from 19.16 ± 0.98 to 25.83 ± 0.06%. The bulk density of natural forests ranged from 1.27 g cm−3 to 1.37 g cm−3 while for plantation forests it ranged from 1.18 g cm−3 to 1.34 g cm−3. Among the studied sites of natural forest, TRS forest had both the highest AGBC value of 132.74 t ha−1 as well as the BGBC value of 38.49 t ha−1. Similarly, among the plantations, T. grandis plantation showed the highest AGBC (193 t ha−1) and BGBC (55.97 t ha−1). On the other hand, Tharosibi forest and T. grandis plantation had the highest total carbon stock for natural and plantation forest with values of 274.824 t ha−1 and 390.88 t ha−1, respectively. The total above-ground carbon stock estimated for the natural forest of KHP, LNG and TRS were 109.60 t ha−1, 79.49 t ha−1 and 132.74 t ha−1, respectively. On the other hand, the estimated total above-ground carbon stock in plantation of GA, PD, PF and TG were 62.93 t ha−1 62.81 t ha−1, 45.85 t ha−1 and 193.82 t ha−1. In the present study, the relationship with the biomass was observed to be better in SAVI compared to NDVI and TVI. The linear regression analysis performed to determine the relationship between the estimated and predicted biomass resulted in a correlation coefficient of R2 = 0.85 for the present study area, which is an indication of a good relationship between the estimated and predicted biomass.

The mitigation of global warming and conservation of biodiversity are two significant environmental challenges today. Estimating and comparing forest carbon stock and plant diversity under different management approaches provide insight into the choice of management approaches for carbon and plant diversity management. We investigated the variation in carbon stock and diversity of plant species in two forest managements under different approaches: the Kakrebihar protection forest (PF) and Sano Surkhet community forest (CF) in Karnali Province, Surkhet, Nepal. In total, 63 sample plots (30 plots in PF and 33 plots in CF) were laid out systematically across the forests. Dendrometric measurements were carried out for trees, poles, and saplings, and representative leaf litter and herb samples were collected. Soil samples were taken at 10 cm, 20 cm, and 30 cm depths using a soil auger. The existing tree volume equations of tree species of interest were used to estimate tree volume, and species-specific wood density and conversion factors were used to obtain total biomass and carbon content. Soil samples were analyzed using the Walkley-Black method to determine soil organic carbon. PF had higher carbon stock, plant species richness, and abundance at the landscape level than CF; however, the scenario differed at the plot level. At the plot level, PF had significantly higher total carbon stock and biomass carbon stock than CF. However, PF and CF were statistically indistinguishable in term of soil carbon stock. At the plot level, PF and CF were statistically indistinguishable regarding richness, Simpson diversity, and Shannon diversity, but PF had significantly higher plant abundance than CF. In conclusion, the value of PF for carbon stock and plant diversity surpassed those of CF. This study suggests that PF might be a better strategy to enhance carbon stock in forests and maintain habitat for various plant species.

The study compares the performance of a hierarchical Bayesian geostatistical methodology with a frequentist geostatistical approach, specifically, Kriging with External Drift (KED), for predicting C stock using prediction aides from the Landsat-8 and Sentinel-2 multispectral remote sensing platforms. The frequentist geostatistical approach’s reliance on the long-run frequency of repeated experiments for constructing confidence intervals is not always practical or feasible, as practitioners typically have access to a single dataset due to cost constraints on surveys and sampling. We evaluated two approaches for C stock prediction using two new generation multispectral remote sensing datasets because of the inherent uncertainty characterizing spatial prediction problems in the unsampled locations, as well as differences in how the Bayesian and frequentist geostatistical paradigms handle uncertainty. Information on C stock spectral prediction in the form of NDVI, SAVI, and EVI derived from multispectral remote sensing platforms, Landsat-8 and Sentinel-2, was used to build Bayesian and frequentist-based C stock predictive models in the sampled plantation forest ecosystem. Sentinel-2-based C stock predictive models outperform their Landsat-8 counterparts using both the Bayesian and frequentist inference approaches. However, the Bayesian-based Sentinel-2 C stock predictive model (RMSE = 0.17 MgCha−1) is more accurate than its frequentist-based Sentinel-2 (RMSE = 1.19 MgCha−1) C stock equivalent. The Sentinel-2 frequentist-based C stock predictive model gave the C stock prediction range of 1 ≤ MgCha−1 ≤ 290, whilst the Sentinel-2 Bayesian-based C stock predictive model resulted in the prediction range of 1 ≤ MgCha−1 ≤ 285. However, both the Bayesian and frequentist C stock predictive models built with the Landsat-8 sensor overpredicted the sampled C stock because the range of predicted values fell outside the range of the observed C stock values. As a result, we recommend and conclude that the Bayesian-based C stock prediction method, when it is combined with high-quality remote sensing data such as that of Sentinel-2, is an effective inferential statistical methodology for reporting C stock in managed plantation forest ecosystems.

Several agroforestry systems prevail in different agro-ecological zones of Pakistan, and cover a remarkable area of 19.3 million hectares. They not only play an important role in slowing down CO2 emissions, but also contribute to mitigating climate change. However, in many regions, the relevant effect of agroforestry systems on overall carbon (C) stock and their reliance on various factors are quite unidentified. This study was planned to assess the biomass accumulation and C stocks of different commonly practiced agroforestry systems (boundary, bund, scattered, agri-horticulture) and their constituent land use types (tree + cropland) through a non-destructive approach (allometric equations) in a semi-arid region of Punjab, Pakistan. The results showed that the highest plant biomass (87.12 t ha−1) increased by 46%, 17%, 78%, and 339%, and C stock (42.77 t ha−1) increased by 49.51%, 20%, 82%, and 361% in the boundary planting system compared to the bund, scattered, agri-horti and sole cropland, respectively. The soil organic carbon (SOC) stock at all three depths, 0–15 cm, 15–30 cm & 30–45 cm, was found in the following order: boundary planting system > bund planting system > agri-horti system > scattered planting system > agricultural system, with a maximum in the boundary planting system and minimum in the sole cropping system at all three depths. Overall, the total C stock of the ecosystem’s vegetation + soil C (0–30 cm) in the forested area was 275 t ha−1, equating to 37 t ha−1 in the agricultural system alone. Our results highlighted that agroforestry systems have the highest potential for C sequestration. We suggest that research and investment in agroforestry systems can be a successful way for Pakistan to achieve some of its climate change mitigation goals.

Long-term excessive use of fertilizers and intensive cultivation not only decreases soil organic carbon (SOC) and productivity, but also increases greenhouse gas emissions, which is detrimental to sustainable agricultural development. The purpose of this paper is to identify organic amendments suitable for winter wheat growth in the North China Plain by studying the effects of organic amendments on the economic benefits, carbon emissions, and carbon sequestration for winter wheat fields and to provide a theoretical basis for the wide application of organic amendments in agricultural fields. The two nitrogen rates were N0 (0 kg ha -1 ) and N240 (240 kg ha -1 ), and the four organic amendments were straw, manure, mushroom residue (M R), and biochar. The results showed that, compared to N0, N240 significantly increased the yield by 244.1-318.4% and the organic carbon storage by 16.7-30.5%, respectively, but increased the carbon emissions by 29.3-45.5%. In addition, soil carbon stocks increased with all three types of organic amendments compared to the straw amendment, with the biochar treatment being the largest, increasing carbon storage by 13.3-33.6%. In terms of yield and economic benefits, compared to the straw amendment, the manure and biochar amendments increased winter wheat yields by 0.0-1.5% and 4.0-13.3%, respectively, and M R slightly decreased wheat yield; only the economic benefit of the M R amendment was greater than that of the straw amendment, with an increase in economic benefit of 1.3% and 8.2% in the 2021-2022 and 2022-2023 seasons, respectively. Furthermore, according to the net ecosystem productivity (NEP), N0 was the source of CO 2 , while N240 was a sink of CO 2 . The TOPSIS results showed that N240 with a mushroom residue amendment could be recommended for increasing soil carbon stocks and economic benefits for winter wheat in the NCP and similar regions. Low-cost M R can increase farmer motivation and improve soil organic carbon, making a big step forward in the spread of organic materials on farmland.

Forests play an important role in combating the challenges posed by changing climate through sequestering carbon in their living biomasses and the soil. Tropical forests, which harbour a large number of species, are anticipated to play a great role in this regard due to the favourable growing environments. However, there is limited knowledge of the variability in carbon stock among land use types and its relationship with biodiversity. Therefore, this study assessed the variability in storing the different carbon pools among natural forest, woodland and khat plantation land use types. It also explored the relationship between biodiversity and carbon storage in the different carbon pools. Plant inventory and sample collection were undertaken following standard methods. In addition, soil samples were taken at three depth profile classes of 0–30 cm (top layer), 30–60 cm (middle layer) and 60–100 cm (bottom layer). Results of the study revealed that there was no statistically significant relationship between biodiversity and total biomass carbon, soil organic carbon or total carbon stock at a 95% level of confidence. The results indicated that the natural forest had the highest plant biomass (456.93 Mg ha−1) followed by woodland (19.78 Mg ha−1) and khat plantation (2.46 Mg ha−1). Consequently, the total carbon stock estimate of the natural forest (366.47 Mg ha−1) was significantly larger than that of the woodland (141.85 Mg ha−1) and khat plantation (125.86 Mg ha−1). The variation in total carbon stock among land use types arises from the variation in the total biomass carbon stock. The study results also revealed that soil organic carbon stock decreased with soil depth in all the land-use types. The findings of this study have implication of improving topsoil management in monoculture crops such as khat plantation and conserving natural forests for enhancing carbon sequestration potentials.

Biochar (BC) soil amendments could partially counteract soil carbon (C) stock decrease in broad-leaved forests in Italy; however, its effects on the growth of representative tree species—Fagus sylvatica L. and Quercus cerris L.—has not yet been addressed. We examine whether seed germination and growth of these species are affected by addition of BC obtained from deciduous broadleaf trees. Seeds were left to germinate in greenhouse conditions under three different BC amendments: 0% (control), 10% and 20% (v/v). Seedlings were then subjected to controlled conditions under the same BC percentage. Biochar effects on seed germination were assessed measuring germination time and percentage, while effects on photosynthesis were assessed using leaf chlorophyll content (mg/m2) and photosynthetic efficiency (FV/FM). Plant growth was estimated by recording leaf number, longest leaf length and plant height. Biochar treatments had no negative effects on germination and early growth stage of the two species. Positive effects were found on the chlorophyll content of both species (ca. +8%) regardless of the treatment and on the leaf number (+30%), leaf length (+14%) and plant height (+48%) of Q. cerris (only with 10% BC). Biochar applications seem, therefore, a suitable method for increasing broad-leaved forest C stock in Italy.

Aspen trees (Populus tremula L., 1753) are native to the boreal region of Siberia. These species’ fast growth and ability to regrow from root suckers mean carbon farms can be created using aspen trees for efficient atmospheric carbon sequestration. This paper presents the findings of research focusing on the dynamics of aspen forests’ growth and conditions in a changing climate according to forest inventories conducted in 1972, 1982, 2002 and partially 2021. The research was carried out in aspen stands growing in the Central Siberian subtaiga forest-steppe ecoregion. From 1982 to 2002, there was a steady trend towards increasing growing season temperature sum. At the same time, the amount of precipitation in the same season and period did not exceed the median value. With an increase in the temperature sum in 1982–2002 from 1800 °C to 2100 °C, the average forest carbon stock increased from 0.56 to 1.48 tonnes of carbon per hectare per year. This statement is true for pure aspen forests aged 10 to 30 years. A drastic decrease in the carbon sequestration potential was observed in aspen stands from the age of 40. After 55 years, the average increase in aspen forests’ carbon stock leveled off, and the differences became insignificant. Along with age-related increasing biomass growth rates in aspen forests, natural and pathological dieback led to reductions in resilience and wood loss. Aspen is characterized by rapid early growth rates, which allows aspen forests’ sequestration potential to be used to achieve effective carbon conservation.

Forest and tree cover loss decreases the ecosystem services that they may provide such as food and livelihood, protection from calamities, oxygen to breathe, and storing of carbon. This study assessed the diversity, species composition, and carbon stock potential of trees located in Aurora, Philippines. Two areas were surveyed to represent preserved and developed ecosystems. The preserved ecosystem was represented by the ultramafic forest in Baler, Aurora, whereas the developed ecosystem was represented by the urbanizing portion of Dipaculao, Aurora. The sampling site in Baler included 27,400 m2 plots and the site surveyed in Dipaculao had a total of 72.72 hectares of developed area. Results showed a higher tree diversity in Baler (H′ = 4.096) than in Dipaculao (H′ = 3.278). Species composition assessment also revealed a higher number of ecologically important species in Baler. Ecologically important species in Baler included 100% natives, 34.5% endemics, and 20.86% threatened. Dominant species in Baler were the native, endemic, and threatened Xanthostemon philippinensis Merr. and the native Teijsmanniodendron ahernianum (Merr.) Bakh. On the other hand, the developed ecosystem had 54.4% native, 4.41% endemic, and 11.76% threatened species. Dipaculao was dominated by introduced and invasive species such as Swietenia macrophylla King and Gmelina arborea Roxb. ex Sm. For the tree carbon stock assessment, a tremendous difference was found wherein the preserved ecosystem had 272.28 tons/ha carbon whereas the developed ecosystem had 16.28 tons/ha carbon. This study revealed ideal forest ecosystem characteristics in preserved forests with high diversity, the presence of many important species, and a large amount of carbon stock. This calls for immediate action from the government to continuously protect the natural forests and prioritize proper land use planning and the right choice of species to be integrated with developed areas to improve the ecosystem’s capacity to provide vital ecological services.

Climate change requires mitigation actions, mainly preventive, by reducing greenhouse gas emissions; however, carbon sequestration is a complementary measure. Although short-term carbon sequestration can be somewhat effective, it is really interesting when it is permanent. Sequestration calculates the carbon removed from the atmosphere over a period, while the stock expresses the cumulative carbon of a forest. Sequestration and stock are closely related, but ecosystem service valuation often focuses on the former, which can discourage forest maintenance. This study analyzes carbon sequestration and storage in four pine forests located in central Spain, comparing its valuation for different equivalence times, a period considered sufficient to compensate for the emission of one ton of CO2 into the atmosphere. Equilibrium equivalence times were calculated for each forest, defined as the period in which carbon sequestration and stock payments are equal; values ranged from 33 to 101 years, with significant correlations with commercial volume and carbon stock. Equivalence times of 30–50 years are reasonable in Mediterranean forest stands with moderate growth and density, while in dense mature stands this time should increase to 50–100 years. Valuing carbon stocks and paying for them in a sustained manner over time promotes sustainable forest management, while the sale of sequestration credits may generate a speculative “greenwashing” market. In addition, payments for stocks can be applied to any forest stand and not only to new plantations. Carbon stock valuation is a win–win strategy for climate change mitigation, sustainable forest management, and rural development.

Terrestrial carbon sequestration capacity is an important indicator of ecosystem service function, and the carbon storage value can reflect the climate regulation capacity of the regional ecological environment. The Zoigê alpine grassland is a representative area of the Qinghai-Tibet Plateau grassland ecosystem, with carbon sequestration types such as alpine grassland and marsh meadow and also an important water-conserving area in the upper reaches of the Yangtze River and the Yellow River. In this study, based on the land use/cover change pattern of the Zoigê alpine grassland region from 2000 to 2020, the carbon density coefficients corrected by the regional average annual precipitation and temperature factors were used to assess the carbon stocks of the Zoigê alpine grassland for three periods from 2000 to 2020 using the InVEST model. The results showed that the carbon stocks of the Zoigê alpine grassland region were 786.19 Tg, 780.02 Tg, and 775.22 Tg in 2000, 2010, and 2020, respectively, with a cumulative loss of 10.97 Tg and carbon densities of 183.70 t/ha, 182.26 t/ha, and 181.14 t/ha, showing a decreasing trend year by year. The carbon stock of the grassland ecosystem is the absolute contributor to the regional carbon stock, and the carbon stock accounts for 75.28% of the total carbon stock. The increase in the cultivated land area with a lower carbon density and the decrease in the grassland area with a higher carbon density are the main factors leading to the decrease in the carbon stock in the regional ecosystem of the Zoigê alpine grassland.

The effects of conservation strategies on soil organic carbon (SOC) and phosphorus (P) dynamics in dryland wheat under semi-arid temperate conditions are not well understood. This study quantified the effects of tillage and straw management on SOC concentrations and stocks and P fractions after 40 years of dryland wheat under a semi-arid temperate climate. The treatments were straw management (burned and not burned) combined with tillage methods (conventional tillage (CT), stubble mulch (SM), and no-tillage (NT)). Fertilizer nitrogen (N) and P were applied annually at 60 and 12.5 kg ha−1, respectively. The soils were sampled from 0–50, 50–200, 200–400, 400–600, 600–800, and 800–1000 mm depths, and analyzed using standard methods. The concentration of SOC was not affected by tillage and straw management, except in 200–400 mm where it was higher where the straw was burned rather than retained. The total C stock (0–1000 mm) was higher under NT with straw burning, CT with no burning, and SM, than NT with straw retention and CT with burning. In the topsoil, NT had significantly (p < 0.05) higher Bray 1 P, NaOH II Pi, and residual P than SM and CT, while burning straw increased Bray 1 P and NaHCO3 Pi concentrations. The findings imply that while the SOC concentration is not significantly affected by tillage, but is increased by burning in the subsoil only, the total C stock is improved by NT with burned straw, CT with straw retention, and SM, while the labile P fractions are increased by NT with burned straw, relative to CT with burned straw, in the semi-arid dryland wheat region.

Urban expansion and ecological restoration policies can simultaneously affect land-cover changes and further affect ecosystem services (ES). However, it is unclear whether and to what extent the distribution and equity of urban ES are influenced by the stage of urban development and government policies. This study aims to assess the quantity and equity of ES under different scenarios in cites of China and Europe. Firstly, we used the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model to simulate future land cover under three scenarios: business-as-usual (BAU), a market-liberal scenario (MLS), and an ecological protection scenario (EPS). Then using ecosystem service model approaches and the landscape analysis, the dynamics of green infrastructure (GI) fraction and connectivity, carbon sequestration, and PM2.5 removal were further evaluated. The results show that: (1) over the past 20 years, Chinese cities have experienced dramatic changes in land cover and ES relative to European cities. (2) Two metropolises in China, Shanghai and Beijing have experienced an increase in the fraction and connectivity of GI and ES in the long-term built-up areas between 2010 and 2020. (3) EPS scenarios are not only effective in increasing the quantity of ES but also in improving the equity of ES distribution. The proposed framework as well as the results may provide important guidance for future urban planning and sustainable city development.

Seagrass ecosystems sequester carbon at disproportionately high rates compared to terrestrial ecosystems and represent a powerful potential contributor to climate change mitigation and adaptation projects. However, at a local scale, rich heterogeneity in seagrass ecosystems may lead to variability in carbon sequestration. Differences in carbon sequestration rates, both within and between seagrass meadows, are related to a wide range of interrelated biophysical and environmental variables that are difficult to measure holistically using traditional field surveys. Improved methods for producing robust, spatially explicit estimates of seagrass carbon storage across large areas would be highly valuable, but must capture complex biophysical heterogeneity and variability to be accurate and useful. Here, we review the current and emerging literature on biophysical processes which shape carbon storage in seagrass beds, alongside studies that map seagrass characteristics using satellite remote sensing data, to create a blueprint for the development of remote sensing-enabled proxies for seagrass carbon stock and sequestration. Applications of satellite remote sensing included measuring seagrass meadow extent, estimating above-ground biomass, mapping species composition, quantifying patchiness and patch connectivity, determining broader landscape environmental contexts, and characterising seagrass life cycles. All of these characteristics may contribute to variability in seagrass carbon storage. As such, remote sensing methods are uniquely placed to enable proxy-based estimates of seagrass carbon stock by capturing their biophysical characteristics, in addition to the spatiotemporal heterogeneity and variability of these characteristics. Though the outlined approach is complex, it is suitable for accurately and efficiently producing a full picture of seagrass carbon stock. This review has drawn links between the processes of seagrass carbon sequestration and the capabilities of remote sensing to detect and characterise these processes. These links will facilitate the development of remote sensing-enabled proxies and support spatially explicit estimates of carbon stock, ensuring climate change mitigation and adaptation projects involving seagrass are accounted for with increased accuracy and reliability.

Matang Mangrove Forest Reserve (MMFR) in peninsular Malaysia has been managed for pole and charcoal production from Rhizophora stands with a 30-year rotation cycle since 1902. The aim of this study is to estimate the carbon budget of the MMFR by considering the carbon stock of the forest, evaluated from remote sensing data (Landsat TM and ETM+, JERS-1 SAR, ALOS PALSAR, ALOS-2 PALSAR-2, SRTM, TANDEM-X, and WorldView-2) for aboveground carbon and field data for belowground carbon. This was investigated in combination with the emissions from the silvicultural activities in the production chain, plus the distribution and consumer-related activities covering the supply chain, estimated with appropriate emission factors. The aboveground biomass carbon stock of the productive forest was of 1.4 TgC, while for the protective forest (not used for silviculture) it was at least equal to 1.2 TgC. The total soil carbon of ca. 32 TgC shows the potential of the MMFR as a carbon sink. However, the commercial exploitation of mangroves also generates greenhouse gasses with an estimate of nearly 152.80 Mg C ha−1 during charcoal production and up to 0.53 Mg C ha−1 during pole production, for a total emission of 1.8 TgC. Consequently, if the productive forest alone is considered, then the carbon budget is negative, and the ongoing silvicultural management seems to be an unsustainable practice that needs a reduction in the exploited area of at least 20% to achieve carbon neutrality. However, even with the current management, and considering the protective forest together with the productive zones, the MMFR carbon budget is slightly positive, thus showing the importance of mangrove conservation as part of the management for the preservation of the carbon stock.

Bhimal (Grewia oppositifolia) is the most important agroforestry tree species used for fodder, fuel and fiber in the Himalayan region. In the present study, G. oppositifolia-based traditional agroforestry systems were selected for the estimation of carbon stock and the production potential of barnyard millet (Echinochloa frumentacea) and finger millet (Eleusine coracana), with two elevational ranges, i.e., 1000–1400 and 1400–1800 m amsl, in Garhwal Himalaya, India. The results of the investigation showed a decline in the growth and yield attributes of both the millet crops under the G. oppositifolia-based agroforestry system at both elevations as compared to their respective control sites (sole crops). Among the elevations, the total number of tillers per plant (2.70 and 2.48), the number of active tillers per plant (2.18 and 2.25), panicle length (17.63 cm and 6.95 cm), 1000-seed weight (5.49 g and 4.33 g), grain yield (10.77 q ha−1 and 11.35 q ha−1), straw yield (37.43 q ha−1 and 30.15 q ha−1), biological yield (48.21 q ha−1 and 41.51 q ha−1) and the harvest index (22.53% and 27.78%) were recorded as higher in the lower elevation in both E. frumentacea and E. coracana, respectively, while plant population per m2 (18.64 and 25.26, respectively) was recorded as higher in the upper elevation. Plant height for E. frumentacea (180.40 cm) was also observed to be higher in the upper elevation, while for E. coracana (98.04 cm), it was recorded as higher in the lower elevation. Tree carbon stock was reported negatively with an increase in altitude. The maximum amount of sequestered carbon in the tree biomass for G. oppositifolia was 23.29 Mg ha−1 at the lower elevation and 18.09 Mg ha−1 at the upper elevation. Total carbon stock in the tree biomass was reported to be the highest (15.15 Mg ha−1) in the 10–20 cm diameter class, followed by 20–30 cm (6.99 Mg ha−1), >30 cm (2.75 Mg ha−1) and the lowest (2.32 Mg ha−1) in the E. frumentacea and E. coracana was not reduced so severely under the G. oppositifolia system; however, keeping in mind the other benefits of this multipurpose tree, i.e., carbon sequestration and socioecological relevance, farmers can get benefit from adopting these crops under G. oppositifolia-based agroforestry systems.

Grazing management strategies tend to have different effects on rangeland plant production. Changes in grazing management can, therefore, affect the carbon stock potential of rangelands. Despite rangeland ecosystems being important global sinks for carbon, we know relatively little about the effect of traditional grazing management practices on their potential to store carbon. In this study, we evaluated the carbon stock and change rate of rangelands using three traditional grazing management practices in the semiarid pastoral ecosystem of eastern Ethiopia. By comparing data on vegetation and soil carbon stocks, we found that there was a strong significant difference (p < 0.001) between these different management practices. In particular, the establishment of enclosures was associated with an annual increase in carbon stocks of soil (3%) and woody (11.9%) and herbaceous (57.6%) biomass, when compared to communal open lands. Both enclosure and browsing management practices were found to have the highest levels of soil organic carbon stocks, differing only in terms of the amount of woody and herbaceous biomass. Thus, modest changes in traditional grazing management practices can play an important role in carbon storage and sequestration. Further research is required on a wider range of traditional pastoral management practices across space and time, as understanding these processes is key to combating global climate change.

The need to put into practice sustainable agricultural production systems has been supported by agroecology science that seeks to optimize land use to food production with the lowest impact on soil. This study evaluated soil quality, based on physical and chemical attributes, in agroforestry (AGF) and silvopastoral (SILVP) systems developed for large-scale food production. The study was carried out in the municipality of Itirapina, state of São Paulo, in two areas with AGF and SILVP system, compared to an area with a forest fragment and another with pasture in a Quartzipisamment Sand Neosol. The soil collections were carried out in the layers of 0.00–0.05, 0.05–0.10, 0.10–0.20, and 0.20–0.40 m, where physical soil attributes were evaluated (total porosity, microporosity, and microporosity, density, mean diameter of aggregates) as well as chemical attributes (macro- and micronutrients), in addition to carbon and nitrogen storage. To interpret the data, Tukey’s test was applied to compare means, and principal component analysis was used to better characterize the study environments. The results showed that agroforestry and silvopastoral systems developed for large-scale production are efficient in improving chemical and physical attributes that reflect on soil quality, especially in the superficial layers of the soil, overcoming pasture and the natural regeneration process. Carbon and nitrogen storage were the main variables that differentiated the production systems, highlighting the importance of the AGF and SILVP systems as more sustainable agricultural intensification strategies, even in soils of low agricultural suitability.

Roots play a fundamental role in forest ecosystems, but obtaining samples from deep layers remains a challenging process due to the methodological and financial efforts required. In our quest to understand the dynamics of Eucalyptus roots, we raise three fundamental questions. First, we inquire about the average extent of the roots of two contrasting Eucalyptus genotypes. Next, we explore the factors that directly influence the growth and depth of these roots, addressing elements such as soil type, climate, and water availability. Lastly, we investigate how the variation in Eucalyptus species may impact root growth patterns, biomass, and carbon stock. In this study, we observed that the maximum root depth increased by an average of 20% when genotypes were grown on sites with higher water availability (wet site). E. urophylla stands had a higher biomass and carbon stock (5.7 Mg C ha -1 ) of fine roots when cultivated on dry sites (annual rainfall~727 mm) than the wet sites (annual rainfall~1590 mm). In E. grandis × E. camaldulensis stands, no significant differences were observed in the stock of fine root biomass (3.2 Mg C ha -1 ) between the studied environments. Our results demonstrated that genotypes with greater drought tolerance ( E. grandis × E. camaldulensis ) tend to maintain higher stocks of fine root biomass (3.2-6.3 Mg ha -1 ) compared to those classified as plastic ( E. urophylla ), regardless of the edaphoclimatic conditions of the cultivation site. Finally, our research helps understand how Eucalyptus trees adapt to their environment, aiding sustainable forest management and climate change mitigation. We also provide a practical tool to estimate underground biomass, assisting forest managers and policymakers in ensuring long-term forest sustainability.

The rapid and accurate estimation of aboveground forest phytomass remains a challenging research task. In general, methods for estimating phytomass fall mainly into the category of field measurements performed by ground-based methods, but approaches based on remote sensing and ecological modelling have been increasingly applied. The aim is to develop the scientific and methodological framework for the remote sensing estimation of qualitative and quantitative characteristics of forest stands, using the combination of surveys and machine learning models to determine phytomass of forest stands and calculate the carbon balance. Even-aged stands of different tree species growing in the forest steppe zone of the East European Plain were chosen as test objects. We have applied the modernized methodological approaches to compare and integrate forest and tree stand characteristics obtained by ground-based and UAV-based comprehensive surveys; additionally, we developed computer vision models and methods for determining the same characteristics by remote sensing methods. The key advantage of the proposed methodology for remote monitoring and carbon balance control over existing analogues is the minimization of the amount of groundwork and, consequently, the reduction inlabor costs without loss of information quality. Reliable data on phytomass volumes will allow for operational control of the forest carbon storage, which is essential for decision-making processes. This is important for the environmental monitoring of forests and green spaces of various economic categories. The proposed methodology is necessary for the monitoring and control of ecological-climatic and anthropogenic-technogenic transformations in various landscapes. The development is useful for organizing the management of ecosystems, environmental protection, and managing the recreational and economic resources of landscapes with natural forests and forest plantations.

The low profitability of agricultural products in a globalized market context is causing the abandonment of less profitable agroforestry systems in Spain. This fact is implicated in a change in land use, increasing the forest area, which could alter the carbon stock in the soil. Thus, the objective of this study was to determine if the abandonment of rural areas and the change in land use has an impact on the soil organic carbon stock in agroforestry systems in southwestern Spain. Through historical aerial photographs and current satellite images, sites were identified where samples of abandoned agricultural soils in the 1950s were collected. They were compared with soil samples from adjacent locations whose agricultural activities continue to this day. After more than 60 years, the abandonment of agricultural activity is associated with a 54% increase in C concentration and 34.8% in soil organic carbon in the upper 30 cm of soil profiles. Therefore, the abandonment of agricultural land has influenced the carbon stock of this territory, becoming a carbon sink.

The current study was conducted to estimate the carbon (C) storage status of agroforestry systems, via a non-destructive strategy. A total of 75 plots (0.405 ha each) were selected by adopting a lottery method of random sampling for C stock estimations for soil, trees and crops in the Mandi-Bahauddin district, Punjab, Pakistan. Results revealed that the existing number of trees in selected farm plots varied from 25 to 30 trees/ha. Total mean tree carbon stock ranged from 9.97 to 133 Mg C ha−1, between 5–10 km away from the brick kilns in the study area. The decreasing order in terms of carbon storage potential of trees was Eucalyptus camaldulensis > Syzygium cumin > Popolus ciliata > Acacia nilotica > Ziziphus manritiana > Citrus sinensis > Azadirachtta Indica > Delbergia sisso > Bambusa vulgaris > Melia azadarach > Morus alba. Average soil carbon pools ranged from 10.3–12.5 Mg C ha−1 in the study area. Meanwhile, maximum C stock for wheat (2.08 × 106 Mg C) and rice (1.97 × 106 Mg C) was recorded in the cultivated area of Tehsil Mandi-Bahauddin. The entire ecosystem of the study area had an estimated woody vegetation carbon stock of 68.5 Mg C ha−1 and a soil carbon stock of 10.7 Mg C ha−1. These results highlight that climate-smart agriculture has great potential to lock up more carbon and help in the reduction of CO2 emissions to the atmosphere, and can be further used in planning policies for executing tree planting agendas on cultivated lands and for planning future carbon sequestration ventures in Pakistan.

Current LiDAR-based methods for detecting forest change use a host of statistically selected variables which typically lack a biological link with the characteristics of the ecosystem. Consensus of the literature indicates that many authors use LiDAR to derive ecosystem morphological traits (EMTs)—namely, vegetation height, vegetation cover, and vertical structural complexity—to identify small-scale changes in forest ecosystems. Here, we provide a conceptual, biological model for predicting forest aboveground biomass (AGB) change based on EMTs. We show that through use of a multitemporal dataset it is possible to not only identify losses caused by logging in the period between data collection but also identify regions of regrowth from prior logging using EMTs. This sensitivity to the change in forest dynamics was the criterion by which LiDAR metrics were selected as proxies for each EMT. For vegetation height, results showed that the top-of-canopy height derived from a canopy height model was more sensitive to logging than the average or high percentile of raw LiDAR height distributions. For vegetation cover metrics, lower height thresholds for fractional cover calculations were more sensitive to selective logging and the regeneration of understory. For describing the structural complexity in the vertical profile, the Gini coefficient was found to be superior to foliage height diversity for detecting the dynamics occurring over the years after logging. The subsequent conceptual model for AGB estimation obtained a level of accuracy which was comparable to a model that was statistically optimised for that same area. We argue that a widespread adoption of an EMT-based conceptual approach would improve the transferability and comparability of LiDAR models for AGB worldwide.

Given the significance of national carbon inventories, the importance of large-scale estimates of carbon stocks is increasing. Accurate biomass estimates are essential for tracking changes in the carbon stock through repeated assessment of carbon stock, widely used for both vegetation and soil, to estimate carbon sequestration. Objectives: The aim of our study was to determine the variability of several aspects of the carbon stock value when the input matrix was (1) expressed either as a vector or as a raster; (2) expressed as in local (1:10,000) or regional (1:100,000) scale data; and (3) rasterized with different pixel sizes of 1, 10, 100, and 1000 m. Method: The look-up table method, where expert carbon content values are attached to the mapped landscape matrix. Results: Different formats of input matrix did not show fundamental differences with exceptions of the biggest raster of size 1000 m for the local level. At the regional level, no differences were notable. Conclusions: The results contribute to the specification of best practices for the evaluation of carbon storage as a mitigation measure, as well as the implementation of national carbon inventories.

The sub-tropical broadleaved forests in Pakistan are the main constituents of the ecosystem services playing a vital role in the global carbon cycle. Monotheca buxifolia (Falc.) A. DC. is an important constituent of these forests, encompassing a variety of ecological and commercial uses. To our best knowledge, no quantitative studies have been conducted in these forests across the landscape to establish a baseline for future monitoring. We investigated the forest structural attributes, growing stock characteristics and total biomass carbon stock and established relationships among them in the phytocoenosis of Monotheca forests along an altitudinal gradient in Pakistan to expand an eco-systemic model for assessment of the originally-implemented conservation strategies. A floristic survey recorded 4986 individuals of 27 species in overstory and 59 species in the understory stratum. Species richness (ANOVA; F = 3.239; p = 0.045) and Simpson’s diversity (ANOVA; F = 2.802; p = 0.043) differed significantly in three altitudinal zones, with a maximum value for lower elevations, followed by middle and higher elevations. Based on the importance values, Acacia modesta and Olea ferruginea are strong companions of M. buxifolia at lower and higher altitudes, whereas forests at mid elevation represent pure crop of M. buxifolia (IVI = ≥85.85%). A similar pattern in stem density, volume and Basal area were also recorded. The carbon stock in trees stratum (51.81 T ha−1) and understory vegetation (0.148 T ha−1) contributes high values in the lower elevation forests. In contrast, soil carbon had maximum values at higher elevation (36.21 T ha−1) and minimum at lower elevation (16.69 T ha−1) zones. Aboveground biomass carbon stock (AGB BMC) of woody trees, understory vegetation and soil organic carbon (SOC) were estimated higher (77.72 T ha−1) at higher and lower (68.65 T ha−1) elevations. Likewise, the AGB BMC exhibited a significant (p < 0.05) negative correlation with elevation and positive correlation with soil carbon. We concluded that lower elevation forests are more diverse and floristically rich in comparison to higher altitudinal forests. Similarly, the biomass carbon of Monotheca forests were recorded maximum at low altitudes followed by high and middle ranges, respectively.

As compared with conventional approaches for reducing carbon emissions, the strategies of reducing emissions from deforestations and forest degradation (REDD) can greatly reduce costs. Hence, the United Nations Framework Convention on Climate Change regards the REDD strategies as a crucial approach to mitigate climate change. To respond to climate change, Taiwan passed the Greenhouse Gas Reduction and Management Act to control the emissions of greenhouse gases. In 2021, the Taiwan government has announced that it will achieve the carbon neutrality target by 2050. Accordingly, starting with focusing on the carbon sink, the REDD strategies have been considered a recognized and feasible strategy in Taiwan. This study analyzed the net present value and carbon storage for various land-use types to estimate the carbon stock and opportunity cost of land-use changes. When the change of agricultural land to artificial forests generated carbon stock, the opportunity cost of carbon stock was negative. Contrarily, restoring artificial forests (which refer to a kind of forest that is formed through artificial planting, cultivation, and conservation) to agricultural land would generate carbon emissions, but create additional income. Since the opportunity cost of carbon storage needs to be lower than the carbon market price so that landlords have incentives to conduct REDD+, the outcomes of this study can provide a reference for the government to set an appropriate subsidy or price for carbon sinks. It is suggested that the government should offer sufficient incentives to reforest collapsed land, and implement interventions, promote carbon trading policies, or regulate the development of agricultural land so as to maintain artificial broadleaf forests for increased carbon storage.

Remotely sensed vegetation indices (VIs) have been widely used to estimate the aboveground biomass (AGB) carbon stock of coastal wetlands by establishing Vis-related linear models. However, these models always have high uncertainties due to the large spatial variation and fragmentation of coastal wetlands. In this paper, an efficient coastal wetland AGB model for the Bohami Rim coastal wetlands was presented based on multiple data sets. The model was developed statistically with 7 independent variables from 23 metrics derived from remote sensing, topography, and climate data. Compared to previous models, it had better performance, with a root mean square error and r value of 188.32 g m−2 and 0.74, respectively. Using the model, we firstly generated a regional coastal wetland AGB map with a 10 m spatial resolution. Based on the AGB map, the AGB carbon stock of the Bohai Rim coastal wetland was 2.11 Tg C in 2019. The study demonstrated that integrating emerging high spatial resolution multi-remote sensing data and several auxiliary metrics can effectively improve VIs-based coastal wetland AGB models. Such models with emerging freely available data sets will allow for the rapid monitoring and better understanding of the special role that “blue carbon” plays in global carbon cycle.

The transformation of the natural landscape into an impervious surface due to urbanization has often been considered an important driver of environmental change, affecting essential urban ecological processes and ecosystem services. Continuous forest degradation and deforestation due to urbanization have led to an increase in atmospheric carbon emissions, risks, and impacts associated with climate change within urban landscapes and beyond them. Hence, urban reforestation has become a reliable long-term alternative for carbon sink and climate change mitigation. However, there is an urgent need for spatially accurate and concise quantification of these forest carbon stocks in order to understand and effectively monitor the accumulation and progress on such ecosystem services. Hence, this study sought to examine the prospect of Sentinel-2 spectral data in quantifying carbon stock in a reforested urban landscape using the random forest ensemble. Results show that Sentinel-2 spectral data estimated reforested forest carbon stock to an RMSE between 0.378 and 0.466 t·ha−1 and R2 of 79.82 and 77.96% using calibration and validation datasets. Based on random forest variable selection and backward elimination approaches, the red-edge normalized difference vegetation index, enhanced vegetation index, modified simple ratio index, and normalized difference vegetation index were the best subset of predictor variables of carbon stock. These findings demonstrate the value and prospects of Sentinel-2 spectral data for predicting carbon stock in reforested urban landscapes. This information is critical for adopting informed management policies and plans for optimizing urban reforested landscapes carbon sequestration capacity and improving their climate change mitigation potential.

The introduction and implementation of the REDD+ (Reduced emission from the deforestation and forest degradation) program has resulted in an investigation of forest carbon from a local to global scale. Due to being the most productive terrestrial ecosystem, forests play an important role in mitigating climate change as they act as major carbon stores. Leasehold forestry (LF) is a participatory model of forest management whereby patches of degraded forest are handed over to groups from low-income households to improve forest conditions and reduce poverty. The planting of grasses in the forest floor and the introduction of fodder species, and promotion of natural regeneration by the removal of shrubs have contributed towards increased plant diversity and higher economic return in leasehold forests. The improved condition of the forest might significantly increase the environmental services provided by the forest, including carbon sequestration. However, studies on the quantification of carbon stock in leasehold forestry are lacking. We estimated the forest carbon stock of leasehold forests in three carbon pools namely Above Ground Tree Biomass (AGTB), Below Ground Tree Biomass (BGTB) and Above Ground Sapling Biomass (AGSB) in Nawalpur district in Nepal and assessed its variations with respect to restoration activities. Furthermore, we analyzed trade-off and synergies between carbon stock and tree diversity. Concentric sample plots with sub plots of 8.92, 5.64 and 1 m radius for trees, sapling and regeneration respectively were systematically laid out using 1% sampling intensity in three Leasehold Forest User Group (LFUG) clusters. Over these circles we collected information about trees (height, diameter at breast height (dbh) and species name), sapling (species name and dbh) and regeneration (species name and count) were collected from respective sub-plots. Average carbon stock was found to be 11.40 t/ha and the carbon stock in the tree-based restoration plot (14.49 t/ha) was significantly higher than in the non-tree-based restoration plot (3.81 t/ha). In contrast to majority of previous findings, we found synergy between carbon stock and tree diversity. Poor forest condition and restoration activities were the major reasons for such synergy. We recommend restoration of leasehold forests through protection and management of existing natural forests and planting of diverse trees.

Accurate estimates of soil organic carbon (SOC) are critical for evaluating the impacts of crop and nutrient management practices on soil sustainability and global climate change. Temporal and spatial variations in topsoil (0–0.20 m) SOC were analyzed using 43,743 soil samples in China’s croplands. The soil database in our study was collected from the International Plant Nutrition Institute (IPNI) China Program. The results showed an increasing trend in SOC density (SOCD) for both grain and cash crops from 1991 to 2012. The average SOCD increased by 16.8, 17.4, 11.8 and 8.7% in the north central, northwest, southeast and southwest regions, respectively, whereas average SOCD decreased by 1.3% for the northeast region between the 1991–2001 and 2002–2012 periods. For both grain and cash crops, the SOCD frequency distribution (%) increased in the ranges of 10–20, 20–30 and 30–40 Mg C ha−1 from the 1991–2001 to the 2002–2012, but decreased in the ranges of 0–10 and 50–60 Mg C ha−1. Additionally, SOCD increased in most major soil types across China’s cropland regions, except in phaeozems, chernozems and umbrisols, where it decreased by 8.6–18.7% mainly due to water runoff, soil erosion, and low C input. The overall SOC stock (SOCS) in China’s cropland increased by 260 Tg C (23.7 Tg C yr−1) from 1991–2001 to 2002–2012, which was partially due to the increased crop residue return, improved fertilization and adopted conservation tillage over the period. This SOC increase represents a potential offset in carbon dioxide (CO2) emissions that could help reduce the overall net CO2 emissions in China.

Mapping the spatial variation of forest aboveground biomass (AGB) at the national or regional scale is important for estimating carbon emissions and removals and contributing to global stocktake and balancing the carbon budget. Recently, several gridded forest AGB products have been produced for China by integrating remote sensing data and field measurements, yet significant discrepancies remain among these products in their estimated AGB carbon, varying from 5.04 to 9.81 Pg C. To reduce this uncertainty, here, we first compiled independent, high-quality field measurements of AGB using a systematic and consistent protocol across China from 2011 to 2015. We applied two different approaches, an optimal weighting technique (WT) and a random forest regression method (RF), to develop two observationally constrained hybrid forest AGB products in China by integrating five existing AGB products. The WT method uses a linear combination of the five existing AGB products with weightings that minimize biases with respect to the field measurements, and the RF method uses decision trees to predict a hybrid AGB map by minimizing the bias and variance with respect to the field measurements. The forest AGB stock in China was 7.73 Pg C for the WT estimates and 8.13 Pg C for the RF estimates. Evaluation with the field measurements showed that the two hybrid AGB products had a lower RMSE (29.6 and 24.3 Mg/ha) and bias (−4.6 and −3.8 Mg/ha) than all five participating AGB datasets. Our study demonstrated both the WT and RF methods can be used to harmonize existing AGB maps with field measurements to improve the spatial variability and reduce the uncertainty of carbon stocks. The new spatial AGB maps of China can be used to improve estimates of carbon emissions and removals at the national and subnational scales.

Mangrove forests provide a large variety of ecosystem services (ES) to coastal societies. Using a case study focusing on the Ajuruteua peninsula in Northern Brazil and two ES, food provisioning (ES1) and global climate regulation (ES2), this paper proposes a new framework for quantifying and valuing mangrove ES and allow for their small-scale mapping. We modelled and spatialised the two ES from different perspectives, the demand (ES1) and the supply (ES2) side respectively. This was performed by combining worldwide databases related to the global human population (ES1) or mangrove distribution and canopy height (ES2) with locally derived parameters, such as crab catches (ES1) or species-specific allometric equations based on local estimates of tree structural parameters (ES2). Based on this approach, we could estimate that the area delivers the basic nutrition of about 1400 households, which equals 2.7 million USD, and that the mangrove biomass in the area contains 2.1 million Mg C, amounting to 50.9 million USD, if it were paid as certificates. In addition to those figures, we provide high-resolution maps showing which areas are more valuable for the two respective ES, information that could help inform management strategies in the future.

The soil has lost organic matter in the past centuries. Adding organic matter to soils is one of the management practices applied to recover the levels of soil carbon of the past and to improve soil properties. Is it a good practice to reduce global warming? In fact, one of the practices promoted to combat climate change is increasing soil organic matter. However, the addition of organic residues to the soil could facilitate the liberation of CO2 and wastes could also have no positive effects on soil properties (i.e., pollution). In this sense, what it is important is: (a) to know which is the expected effect of the organic matter added to the soil; (b) how this application alters the soil processes; (c) which are the management practices that should be applied; (d) how much is the real amount of carbon sequester by the soil and; (e) the balance at short and long period after the application of the organic matter. The adequate strategy should be to favour the increment of biologically stabilized soil organic matter considering medium and long time. However, it is necessary to adapt the strategies to the local environmental conditions.