Carbon Stock Potential Research Articles

Synthesizing Local Capacities, Multi-Source Remote Sensing and Meta-Learning to Optimize Forest Carbon Assessment in Data-Poor Regions

As the climate emergency escalates, the role of forests in carbon sequestration is paramount. This paper proposes a framework that integrates local capacities, multi-source remote sensing data, and meta-learning to enhance forest carbon assessment methodologies in data-scarce regions. By integrating multi-source optical and radar remote sensing data alongside community forest inventories, we applied a meta-modelling approach using stacked generalization ensemble to estimate forest above-ground carbon (AGC). We also conducted a Kruskal–Wallis test to determine significant differences in AGC among different tree species. The Kruskal–Wallis test (p = 1.37 × 10−13) and Dunn post-hoc analysis revealed significant differences in carbon stock potential among tree species, with Afzelia quanzensis (x~ = 12 kg/ha, P-holm-adj. = 0.05) and the locally known species M’buta (x~ = 6 kg/ha, P-holm-adj. = 5.45 × 10−9) exhibiting a significantly higher median AGC. Our results further showed that combining optical and radar remote sensing data substantially improved prediction accuracy compared to single-source remote sensing data. To improve forest carbon assessment, we employed stacked generalization, combining multiple machine learning algorithms to leverage their complementary strengths and address individual limitations. This ensemble approach yielded more robust estimates than conventional methods. Notably, a stacking ensemble of support vector machines and random forest achieved the highest accuracy (R2 = 0.84, RMSE = 1.36), followed by an ensemble of all base learners (R2 = 0.83, RMSE = 1.39). Additionally, our results demonstrate that factors such as the diversity of base learners and the sensitivity of meta-leaners to optimization can influence stacking performance.

Floristic structure, potential carbon stocks, and dynamics in cocoa-based agroforestry systems in Côte d’Ivoire (West Africa)

With about 46% of global production, Côte d’Ivoire is the world’s leading producer of cocoa beans. However, this production contributes to deforestation, exacerbating the effects of climate change. In response to this observation, this study aims to deepen knowledge on the contribution of agroforestry systems in cocoa production areas in Côte d’Ivoire to atmospheric carbon storage. These main areas are the Centre-West, South-West, and West. In these areas, floristic richness was determined in 115 plots. Carbon stocks in living biomass, dead matter, and soil were evaluated. The dynamics of carbon stocks with age were also determined. The results revealed that the West area contains the most diversified cocoa agroforests, with 161 species compared to 71 and 119 in the Centre-West and South-West, respectively. Entandrophragma angolense, Nesogordonia papaverifera, and Sterculia oblonga, common to these areas, are on the IUCN Red List. Carbon stock varies by area, its history, the practices present, and especially the associated species. Thus, in the former cocoa production zone (Centre-West) and the current main production zone (South-West), Elaeis guineensis is the main carbon reservoir, with 25.576 tC.ha⁻1 in the Centre-West and 36.862 tC.ha⁻1 in the South-West. In the West, local trees form the main carbon reservoir with 11.701 tC.ha⁻1. The dynamics of total carbon stocks show heterogeneous changes in production areas according to the different stages of development of agroforestry systems. This is evidence of the complexity of carbon flow and the dynamics of cocoa systems, which are strongly influenced by the sociology of the producers.

Potential carbon stocks of hardwood, softwood, and varied growth rate species in Pasir Hantap Research Forest, Sukabumi, West Java

Abstract Climate change has become a global phenomenon with signi2icant impacts on the environment. Indonesia has committed to reducing its emissions by 29% by 2030 through domestic efforts and 41% through international cooperation. The forestry sector plays a crucial role, with a potential reduction of 17.2% in emissions. One of the tropical forest areas that has the potential to help store carbon stocks is the Pasir Hantap Research Forest, Sukabumi. Pasir Hantap Research Forest is located in the tropics and is characterized by diverse, naturally occurring and planted vegetation. The forest has varying slopes, ranging from 10° to 45°, which can affect tree growth and biomass. The study will analyze the carbon stock potential of hardwood groups (Shorea sp. mixed), softwood groups (Pinus sp. mixed), fast-growing species groups (Eucalyptus sp. mixed), and slow-growing species groups (Swietenia macrophylla mixed) and examine the in2luence of slope on carbon storage. The overall results of carbon stock estimation in the four groups of stands did not show signi2icantly different results. The highest average carbon stock was in the mixed Swietenia macrophylla group at 423.84 tons/ha, while the lowest average was in the mixed Shorea sp. group at 128.76 tons/ha. The results of carbon stock estimation are negatively correlated with slope. The estimated value of carbon stocks in the mixed Swietenia macrophylla group decreased as the degree of slope increased. Meanwhile, the estimation of carbon stocks in the mixed Pinus group increased as the degree of the slope increased.

Comparison of Carbon Stock Potential of Different ‘Trees Outside Forest’ Systems of Palakkad District, Kerala: A Step Towards Climate Change Mitigation

ABSTRACTCarbon stock options to mitigate climate change have become a significant area of interest as every possible way to address this global issue is being explored. Afforestation and ecosystem restoration activities are widely adopted to improve the potential of the land in carbon storage. The Kerala State Action Plan on Climate Change proposed the ‘Trees outside forests (Tof)’ as an effective mechanism to mitigate climate change. Due to its discrete distribution and non‐uniformity, there are fewer attempts to measure the potential of these systems. Palakkad district of Kerala has a discrete climate due to the Palaghat gap and the absence of a coastal line. The district also has a major population depending on agriculture. This study tried to determine and compare the carbon (C) stock potential of the three ‘Trees outside forest (Tof)’ conditions prevailing in the Palakkad district, Kerala. The carbon stock by standing biomass and soil of four sites of undisturbed natural vegetation, monoculture plantation, and home garden were estimated using allometric equations and computations. The natural vegetation was found to have a higher carbon stock potential (238.58 Mg ha−1) compared with monoculture plantation (166.23 Mg ha−1) and human habitat (74.87 Mg ha−1). Also, natural vegetation's soil organic carbon content was much higher than monoculture plantations and home gardens. The study also estimated the soil deterioration index of each land use compared with the natural vegetation and barren land. The results of the study suggested that land use has a great influence on soil quality and carbon stock potential. Proper management of these Tof systems can enhance their productivity and contribute accountable support towards mitigating climate change.

Carbon stocks and sequestration from small tree patches in grassland landscapes in Aotearoa-New Zealand

ABSTRACT Small patches of trees add structural heterogeneity to grassland landscapes, support biodiversity, and provide essential ecosystem services including carbon stocks and sequestration, erosion control, and shade provision. In Aotearoa-New Zealand (A-NZ) small patches of trees have further cultural significance within Te Ao Māori – the worldview of the indigenous Māori people. However, economic pressures have driven the management of grasslands either towards removing tree cover to enhance agricultural productivity, or large-scale conversion of grassland to production forests. Protecting existing small patches of trees, and encouraging their establishment across grassland landscapes, is challenging since the current extent and benefits of these patches is not known. This study demonstrates the critical contributions of small tree patches (those less than one hectare in area) in A-NZ grassland landscapes. Using a high-resolution tree cover dataset, we mapped 1,639,015 small tree patches in grasslands across A-NZ, with grassland small tree patches covering a total land area of between 185,589 ha and 187,928 ha. We used a probabilistic simulation approach to estimate carbon stocks and annual sequestration, revealing a potential aboveground carbon stock between 11.6 and 29.3 million tonnes (Mt) of carbon and an annual biomass sequestration of 0.3 Mt to 0.8 Mt. Despite their current exclusion from the national carbon emissions market, economic valuation suggests a liability of between $NZ 86.9 million and $NZ 8.6 billion (€47.9 million to €4.7. billion) if the small tree patches were felled, and a market value of between $NZ 2.0 million and $NZ 237.6 million (€1.1 and 130.9 million) annually for sequestration. Existing policies, including afforestation incentives, do not encourage protection or establishment of small patches of trees. Significant policy adjustments are required to recognize, protect, and incentivize the conservation and establishment of small patches of trees within grassland landscapes.

Tree traits are a stronger predictor of bee traits and species richness than taxonomic diversity

Abstract Functional traits help to understand biological diversity and the mechanism by which ecological communities are structured and how they respond to the environment. For example, the high tree species diversity within tropical forests can be grouped into a few functional attributes, wood density, size and dependence on animal pollination or seed dispersal. However, little is known about how these traits influence animal taxonomic and functional diversity in the forests. We carried out a vegetation census on six plots (20 × 100 m) within the National Forest of Carajás (Amazon biome) to identify forest canopy species and their functional traits. Within the same plot, we also applied three bee sampling methods (entomological nets, honey traps and scent traps). By characterizing the functional traits of trees and bees, we were able to predict bee functional diversity better than with taxonomic diversity alone via combinations of tree traits like size, wood density, dependence on pollinators and extinction risk. We found that larger trees with low wood density were negatively associated with small, eusocial tree cavity nesting bees. The richness and abundance of trees with high extinction risk was positively associated with the richness of medium‐sized solitary bees. The dominance in the community of pollinator‐dependent trees (average diameter in the basal area) was negatively associated with the richness of above‐ground and cavity nesting bees. Our findings suggest that the composition of the tree community limits the availability of nesting resources for specific groups of bees. Moreover, the presence of trees with higher extinction risk (conservation value) was associated with a greater variety of bee traits and was the only metric associated with overall bee richness. As expected, functional traits shed light on the mechanism that might drive high diversity within tropical forests. In addition, there appears to be complementarity in terms of conservation value and carbon stock potential, as areas that habour tree species with higher extinction risk and higher wood density are also those with overall greater bee and functional diversity. Finally, our study can contribute to the restoration of plant—pollinator community by providing an understanding of the vegetation community that contributes to biodiversity maintenance. Read the free Plain Language Summary for this article on the Journal blog.

Interconnectivity can be as important as habitat type in explaining carbon stocks in the coastal lagoons of arid regions

Coastal blue carbon ecosystems, typically comprising interconnected habitat mosaics, are globally important pathways of carbon sequestration and play a significant role in climate change regulation and mitigation. Current coastal management strategies often rely on simplified regional carbon stock estimates, that overlook the geographical variability and intricate ecological dynamics within these ecosystems. This study adopts a seascape ecology approach to evaluate the role of multiple seascape characteristics on carbon storage in two arid region coastal lagoons. We show that seascape location is the most influential driver of carbon stocks. Additionally, carbon isotopic variability, a proxy for connectivity, can be as influential as habitat type, particularly in the UAQ lagoon. This challenges the conventional reliance on data from individual habitat types (e.g., seagrass, mangrove, or tidal marsh) and highlights the context-dependency of carbon stocks. Moreover, the specific characteristics driving carbon stocks vary between seascapes: in Khor Faridah, connectivity to seagrass and mangrove habitats is crucial, while in the UAQ lagoon, sheltered and elevated areas are more influential. Our findings suggest that the interconnectivity between different habitat types, such as mangroves and saltmarshes, significantly enhances carbon storage. This is especially pronounced in large, sheltered mangrove habitat types within upper intertidal zones. Notably, small patches of mangroves, up to 10 ha, are associated with an approximate 10 % increase in carbon stocks. These results underscore the need for a more holistic, context-specific approach to designing nature-based solutions for coastal management and ecosystem restoration. By considering the specific characteristics and connectivity of seascape mosaics, we can more effectively enhance carbon stock potential in coastal ecosystems. This study contributes to a deeper spatially explicit understanding of the complex factors influencing carbon stocks in blue carbon ecosystems, highlighting the importance of tailored management strategies that reflect the unique ecological patterns of each seascape.

Assessment of Soil Carbon Stock Potential in Different Soil Layers of Grassland Ecosystems

Mostly soil carbon stock research is done in areas with natural vegetation, ignoring university campuses. This study assesses soil carbon stocks in different soil layers of grassland ecosystems within the Bharathiar University campus in Tamil Nadu, India. Soil samples were collected from grasslands in four sections (namely, East section, West section, North section, and South section) of the campus and analyzed for carbon content across depths of 0-10cm, 10-20cm, and 20-30cm. Results indicate soil carbon stocks in grassland ecosystems ranging from 1.36% to 2.26%, with notable variations observed among campus sections and soil layers. One-way ANOVA revealed that there is a significant variation in soil carbon stock values among the four sections in the 20-30cm layer (F(3,16)=3.865, p<0.05), but not for the 0-10cm layer (F(3,16)=1.454, p>0.05) and the 10-20cm layer (F(3,16)=3.011, p>0.05). Pearson’s Correlation analysis revealed that the soil carbon stock had no significant relationships with soil pH, Conductivity, and total dissolved solids at all four sections of the university campus, except for a positive correlation between soil carbon stock and total dissolved solids at the East section (r=0.563, p<0.05), and between soil carbon stock and soil pH at the South section (r=0.550, p<0.05). These findings underscore the complexity of soil carbon dynamics in grassland ecosystems of university campuses and emphasize the potential for localized assessments to inform sustainable land management strategies. This study contributes valuable insights into enhancing carbon sequestration efforts at the university campus, useful for global climate change mitigation. Integrating such localized findings into broader environmental policies can optimize carbon management strategies across similar ecosystems globally.

Climate change impacts of forest conversion (Study on forest conversion for food estate/ national food granary program in Central Kalimantan)

Background: The Food Estate policy or national food granary program is a food development concept that is integrated with agriculture, plantations and animal husbandry, one of which is in the area of openings in natural forests covering an area of 156,000 ha in Central Kalimantan. This program is designed to prepare national food security in order to respond to the Food and Agriculture (FAO) Report on the threat of a global food crisis due to the impact of the Covid 19 pandemic. Changes in forest cover from previously green land to agricultural land will cause loss of forest cover in the form of vegetation or trees that have ecosystem services as carbon dioxide absorbers from the air. Methods: The impact of forest conversion is analyzed by conducting spatial analysis of land cover and calculating potential carbon stocks lost, as well as providing suggestions or solutions to problems or gaps from an economic, social, and political environmental perspective. Findings: From the results of literature studies, the government must learn from the experience of food estate projects on peatlands in the past where peatlands became thin and when the dry season arrived, the land would be flammable due to lack of attention to the biophysical aspects of the soil. Conclusion: In addition, economic and social aspects involve and assist the community in carrying out food security programs and agricultural technology sophistication. Novelty/Originality of this Study: This analysis provides a unique perspective on the climate change impacts of forest conversion for food estate programs, bridging the gap between national food security policies and environmental conservation imperatives.

Benthic habitat mapping for estimating seagrass carbon stock across Takabonerate Islands, Indonesia

Data on benthic habitat cover are essential for monitoring and managing coastal areas, providing valuable ecosystem services for local communities. Moreover, seagrass extent is crucial for estimating carbon stock using Tier-1 calculations. On the other side, remote sensing technology has proven effective in mapping benthic habitat cover, including seagrass, over large local areas. Therefore, this research aims to map specific benthic habitats in a local area to obtain high-accuracy estimates of seagrass extent for carbon stock estimation. The study was conducted in the Takabonerate Islands, Indonesia, using Sentinel-2A imagery. The study involved field data processing, which enabled the mapping of eight benthic habitat classes using Sentinel-2A images, along with the steps for Sentinel-2A image processing for benthic habitat mapping. The benthic habitat map was produced following image correction steps, including atmospheric, sunglint, and water column corrections, followed by image classification using a Neural Net Classifier (NNC). Seagrass carbon stock estimation was performed using the Tier-1 equation from IPCC 2013. The study revealed a total benthic habitat area of 57,538.04 ha, with a seagrass area of 3127.42 ha for carbon stock estimation. The potential seagrass carbon stock in the study area was estimated to range from 337.76 GgC/ha to 31.27 GgC/ha using the Tier-1 equation. The overall accuracy of the benthic habitat map was 80.5 %, calculated using a confusion matrix table. The spatial information from this study can be used by local coastal managers and governments for baseline and monitoring purposes. The key interpretations from this study provide valuable findings that can be adapted and improved for future local mapping purposes.

Assessment of Species Composition, Diversity and Carbon Stock in a Community Managed Forest of Udaypur District of Nepal

Species composition, diversity, and carbon sock of forests are all critical factors that affect the ability of forests to provide various important ecosystem services. However, there is a notable dearth of research regarding these factors in the community forests of Udaypur district. Therefore, this research was undertaken to assess species composition, and biodiversity and quantify the carbon stock potential of the Sringar community forest (CF) of the Udaypur district of Eastern Nepal. A total of 57 circular plots of 500m2 were inventoried using a systematic random sampling method with 0.5 % sampling intensity. In the CF, 17 tree species from 15 genera and 11 families were identified. The dominant tree species, Shorea robusta observed with a maximum importance value index (IVI) (176.15). According to our study, the total biomass and carbon stock in Sringar CF were 276.98 ton ha-1 and 138.18 ton ha-1, respectively. Accurate estimation of soil carbon stocks is crucial for long-term forest management and climate change mitigation, and the integration of advanced monitoring techniques and predictive models to enhance accuracy and account for future climate projections is needed.

Carbon Stock Potential of Coconut Plantations in University Campus: A Case Study from Coimbatore, India

The urgent need to mitigate climate change has prompted researchers to explore various avenues for carbon sequestration. One such avenue is the utilization of natural ecosystems like forests and plantations. Coconut plantations in university campuses play a vital role in carbon sequestration in mitigation of climate change. In this case study, we report the potential of coconut plantation from Bharathiar University campus, India. Four plots of 50 m × 50 m were randomly sampled from the coconut plantation in Bharathiar University campus. Carbon stock of the coconut plantation was calculated based on field survey and allometric equations. A total of 171 trees were recorded from the four plots totalling one hectare (ha) area. The total carbon stock determined for the one ha of coconut plantation sampled from Bharathiar University campus was 31.69 tonne/ha and the mean carbon stock per tree was 0.19 ± 0.06 tonne/tree. We have discussed the carbon stock of coconut tree allocation by above-ground and below-ground parts. This case study highlights the importance of coconut plantations in university campuses in support of curbing the atmospheric carbon concentration. We suggest for plantation of coconut trees in university campuses, that can serve not only as carbon sinks but also contribute to fulfilling the sustainable development goals of the nation.

The potential biomass, carbon stock and CO2 sequestration of forest litters at Sibolangit nature park

Several factors generated CO2 releasing into the atmosphere in large quantities and persist. The CO2 concentration is continuously increase (exceeding 400 ppm in 2019) leading to more negative impact of global warming and climate change. Biomass is a key parameter in estimating and predicting ecosystem productivity, carbon storage, nutrient sharing, and fuel accumulation in assessing an ecosystem. This study aims to analyze the biomass, carbon stock and carbon sequestration of forest litters at Sibolangit nature park. The research data was recorded at Sibolangit Tourism Park, located in Sibolangit, Deli Serdang, North Sumatera. 0.5 m x 0.5 m plot was placed based on the simple random sampling method to collect the litters. The 5% sampling intensity was applied resulting in total of 30 sampling plots. All litter in the sample plots was collected and weighed to determine the wet weight. 100 grams of sample was then placed in a sample plastic and labelled. The litter biomass was calculated using the formula according to SNI7724-2011. This research calculated the biomass, carbon stock, and carbon sequestration of litter at Sibolangit nature park, i.e., 86.92 ton ha−1, 40.85 ton ha−1, and 149.94 ton ha−1. The results support the role of Sibolangit nature park in climate change mitigation by reduction of carbon emission.

Comparative Carbon Stock Potential of Indigenous Agroforestry Systems in Silte Wereda, Southern Ethiopia

Agroforestry system (AFS) is described as one of the promising mitigation options for climate change through its high carbon sequestration capacity. This study was conducted in Silite District; Southern Ethiopia to assess the unaccounted carbon stock potential of selected traditional agroforestry systems. The study assessed the carbon stock potential of AFS biomass and soil carbon pools. Biomass and soil samples were taken from temporary plots laid for this study, 20 × 20 m for home garden, 50 × 100 m for parkland, and 10 × 10 m for woodlot AFS. Height (H) and diameter at breast height (DBH) were taken from the sample plots to estimate biomass carbon. Litter, herb, and grass samples were collected from 1 m2 quadrant within the main plot. The findings show that the total biomass carbon ranged from (1.28-7 Mg ha -1) though there was no significant difference among the systems and higher biomass carbon was attributed by parkland AFS while the lowest was woodlot. A significantly higher amount of SOC was recorded in home garden AFS along the two depths (82.5 Mg ha -1) than the other two systems and the lowest was attributed to parkland (41.7 Mg ha -1). Therefore, this traditional AFS should be supported for their contributions in climate change mitigation schemes as they can sequester a reasonable amount of carbon

Exploring the best nutrient management options for improving the maize yield for future climate change scenario with DSSAT crop simulation model in century old Permanent Manurial Experiment

Increasing the C sequestration potential and higher soil organic carbon stocks with the application of organic manures will reflect in the improvement of crop productivity. Long-term monitoring approach is essential to evaluate these impacts, especially given the escalating effects of climate change on agriculture. Recognizing this, a 112-year-long Permanent Manurial Experiment (PME) at Tamil Nadu Agricultural University, Coimbatore, India, investigates the influence of application of organic manures. Utilizing the DSSAT crop simulation model, the study assessed the impact of organic manure, specifically NPK + FYM (Farm Yard Manure), on maize yield over 25 years on a sandy-loam Alfisol. Data collected from the field experiment including crop growth parameters, management options, weather, and soil data were used for simulations. Results showed a 93.8% agreement between simulated and observed yields, endorsing NPK + FYM treatment with a 20% increase in grain yield by 2032 compared to using 100% NPK alone. Furthermore, the study explored future climate change scenarios’ impact on maize yield. It highlighted that NPK + FYM consistently outperformed other treatments, emphasizing its efficacy in increasing the yields under changing climatic conditions. This approach emerges as promising for enhancing carbon sequestration, elevating soil organic carbon stocks, and significantly improving crop productivity. In conclusion, adopting the NPK + FYM treatment is recommended to achieve optimal maize yield outcomes, surpassing the effects of using NPK or FYM independently. This research signifies the potential of combining organic manures with synthetic fertilizers in sustainable agriculture amid evolving climate challenges.

Carbon stock of shatto forest along altitudinal gradients in masha district, southwest ethiopia: a contribution to climate change mitigation

Forests play a significant role in climate change mitigation through carbon sequestration from the atmosphere and retaining carbon in above and belowground biomass of trees, litter biomass and soil. However, there is little empirical data on the potential carbon stock of Ethiopia’s various forests. Therefore, this study was carried out to estimate the carbon stock potential of Shatto Forest along altitudinal gradients and its contribution to climate change mitigation in Masha district, southwest Ethiopia. Using a systematic sampling design, a total of 30 plots measuring 20 x 20 m were established at 200 m intervals along seven transect lines in order to inventory the woody species. Within the main plot, a 1 m x 1 m sub-plot was used to collect soil samples and litter biomass. The biomass carbon stock was estimated using allometric equations. Results revealed that the mean total carbon stock of the study forest was 714.4 ton/ha, of which 337.38ton/ha, 67.48 ton/ha, 0.79 ton/ha and 308.75 ton/ha were stored in the aboveground carbon, belowground carbon, leaf litter carbon and soil organic carbon, respectively. The mean total CO2 equivalent of the study forest was also 2621.85 ton/ha. Along the altitudinal gradients of the study forest, the total carbon stocks contributed by the forest varied significantly at (p < 0.05), with the largest stock found at lower elevation and the lowest stock found at higher elevation. Based on the study findings, it is concluded that the forest under investigation possessed a substantial carbon stock capacity, allowing it to sequester a significant amount of CO2 and mitigate climate change while offering other ecosystem services. Thus, in order to optimize the forest’s capacity to store carbon and obtain the financial benefits of CO2 mitigation, reduced emission from deforestation and degradation (REDD+) program in the area should be integrated with carbon sequestration.

Potential Carbon Stock of Seagrass Biomass in Malang Regency

Research on blue carbon content in seagrass beds also has important implications for coastal ecosystem management. The goals of this research are: (1) To determine the composition of seagrass species; (2) to analyze the health of the seagrass ecosystem; and (3) and to analyze the carbon content stored in seagrass biomass on the coast of Malang Regency. This research was conducted in 2018 at five stations, namely: Kondang Merak Beach (St 1), Balekambang Beach (St 2), Gatra Beach (St 3), Sendangbiru Beach (St 4), and Waru-Waru Beach (St 5) of Malang Regency. The method used to collect data refers to Seagrass Watch. The biomass value of seagrass species can be estimated by measuring the wet weight and dry weight of seagrass. Analysis of carbon content in seagrass biomass can be calculated using a method that refers to The First Nation-Wide Assessment Identifies Valuable Blue-carbon. There are five types of seagrasses found on five beaches in Malang Regency, namely: Halodule pinifolia, Halodule uninervis, Halophila ovalis, Syringodium isotifolium, and Thalassia hemprichii. This seagrass meadow ecosystem is in an unhealthy condition, with a small biomass value. Seagrass beds that are formed only in the form of small spots (1.19 Ha) are known to be able to store carbon of 0.0544 Mg C.

Soil carbon stock potential in pastoral and silvopastoral systems in the Peruvian Amazon

Research evaluating the impact of silvopastoral systems on physical and biological properties of Amazonian soils is scarce. Thus, this study aimed to compare the soil carbon storage potential and physical and chemical soil properties of silvopastoral systems (SPS) and conventional pastoral systems (CPS) in the San Martin region of Peru. Using the Walkley and Black method, we analyzed soil organic matter at two different depths (0–15 cm and 15–30 cm). In addition, bulk density, soil moisture, total porosity, and mechanical resistance were measured in both systems. The highest (P < 0.05) carbon stocks were reported at 0–15 cm of depth with values of 31.4 Mg ha−1 and 34.4 Mg ha−1 for CPS and SPS, respectively. At 15–30 cm depth, the total carbon stock was higher for SPS, with 29.12 Mg ha−1, than for CPS, which had 26.4 Mg ha−1. Despite the absence of statistically significant differences, soil carbon stocks were higher in SPS. No significant differences in soil moisture were found between systems, although soil moisture was slightly greater in SPS than CPS (28 and 25%, respectively). The CPS had 59% of the total porosity, which was higher than the SPS. Mechanical resistance was lower in SPS (2.15 kg/cm2) than in CPS (2.33 kg/cm2) at 10 cm of depth. These results indicated that the SPS has the potential to store more carbon and improve physical and chemical traits in the soil than the CPS.

Forest Carbon Modeling in Poplar and Black Locust Short Rotation Coppice Plantation in Hungary

Forest carbon dynamic modeling for estimating the carbon stock in short rotation coppice bioenergy plantation in Hungary will be vital for better comprehending the role of black locust (Robinia pseudoacacia) and poplar (Populus sp.) in carbon dioxide sequestration from the atmosphere. The research aims were to estimate the potential carbon stock and describe the carbon distribution of the short rotation coppice bioenergy plantation above and below ground. Various sources were used to acquire parameterization data for developing forest carbon dynamic models. CO2FIX modeling V.3.2 was utilized in the data analysis to estimate the total carbon stock in biomass, soil, harvested wood products, and bioenergy compartments. Modeling has been around for 45 years. In this research, the total carbon stock of black locust and poplar at the end of the simulation period was 64.13 and 131.08 MgC.ha-1, respectively. The average carbon allocation above and below ground for black locust and poplar was 0.76, 19.76, 1.80, and 21.67 MgC.ha-1, respectively. In conclusion, poplar outperformed black locust regarding carbon storage in the short rotation coppice bioenergy plantation. Below ground carbon allocation was much higher than above ground. Therefore, more attention should be paid on below ground allocation through environmentally friendly soil management. Keywords: bioenergy plantation, carbon dynamics, climate change mitigation, CO2FIX model, fast growing species

Identification of Suitable Mangrove Distribution Areas and Estimation of Carbon Stocks for Mangrove Protection and Restoration Action Plan in China

Mangrove forests are significant blue carbon pools on the Earth with strong carbon sequestration capacity and play an important role in combating climate change. To improve the capacity of regional carbon sinks, China has implemented a Special Action Plan for Mangrove Protection and Restoration (2020–2025). In this context, based on the MaxEnt model, this study analyzed the important environmental factors affecting the distribution of mangrove forests, combined with the planning objectives and carbon density parameters of different regions; assessed the habitat suitability areas of China’s mangrove forests; and predicted their future carbon stock potential. The results showed the following: (1) Elevation was the most important factor affecting the overall distribution of mangrove forests in China, and the optimal elevation of mangrove distribution was 0.52 m. (2) The most suitable areas of mangrove forests in China were mainly distributed in Hainan, Guangxi, and Guangdong, which had great potential for carbon stock. Danzhou Bay and Hongpai Harbor in Hainan, Lianzhou Bay in Guangxi, and the Huangmao Sea in Guangdong are potential areas for habitat suitability but are not yet under high levels of protection. (3) Achieving the goals of this action plan was expected to increase carbon stocks by 4.13 Tg C. Other suitable areas not included in this plan could still increase carbon stocks by 7.99 Tg C in the long term. The study could provide a scientific basis for siting mangrove restoration areas and developing efficient management policies.