Regional mangrove vegetation carbon stocks predicted integrating UAV-LiDAR and satellite data.

Using satellite RS data predicting mangrove vegetation carbon stock (MVC) is the popular and efficient approach at a large scale to protect mangroves and promote carbon trading. Satellite data have performed poorly in predicting MVC due to saturation issues. UAV-LiDAR data overcomes these limitations by providing detailed structural vegetation information. However, how to cross-scale integration of UAV-LiDAR and satellite RS data and the selection of features and machine learning methods hampered the practitioner in making a lightweight but efficient model to predict the MVC. Our study integrated UAV-LiDAR, Sentinel-1, and Sentinel-2 to extract spectral, structural, and textural features at the regional scale. We estimated the influences of different combinations between three vegetation features and machine learning methods (Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Regression Tree (GBDT), and Extreme Gradient Regression Tree (XGBOOST)) on the results of MVC prediction, and constructed a framework for estimating mangrove vegetation aboveground (ACG) and belowground (BCG) carbon storage in Zhanjiang, the largest mangrove area of China. Our research shows: 1) Compared to using satellite remote sensing (RS), integrating UAV and satellite RS data and fusing multiple vegetation features significantly improved the accuracy of mangrove vegetation carbon stock (MVC) predictions. 2) Structural features, particularly canopy height retrieved from UAV and satellite RS, are essential indicators for predicting MVC. Combined with spectral and structural features, regional MVC was precisely predicted. 3)Although the influence of different machine learning methods on MVC prediction was not significant, XGBOOST demonstrated relatively high precision. We recommend that mangrove practitioners integrate UAV and satellite RS data to predict MVC at a regional scale. Importantly, governments should prioritize the application of UAV-LiDAR in forestry monitoring and establish a long-term mangrove monitoring database to aid in estimating blue carbon resources and promoting blue carbon trading.

How to maximize the joint benefits of timber production and carbon sequestration for rural areas? A case study of larch plantations in northeast China.

BACKGROUND: Implementing large-scale carbon sink afforestation may contribute to carbon neutrality targets and increase the economic benefits of forests in rural areas. However, how to manage planted forests in China to maximize the joint benefits of timber production and carbon sequestration is still unclear. Therefore, the present study quantified the effects of different rotation lengths, thinning treatments, site quality (SCI), stand density (SDI), and management costs on the joint benefits of carbon sequestration and timber production based on a stand-level model system developed for larch plantations in northeast China. RESULTS: The performances of the different scenarios on carbon stocks were satisfactory, where the variations in the outcomes of final carbon stocks could be explained by up to 90%. The joint benefits increased significantly with the increases of SDIs and SCIs, regardless of which rotation length and thinning treatments were evaluated. Early thinning treatments decreased the joint benefits significantly by approximately 131.53% and 32.16% of middle- and higher-SDIs, however longer rotations (60 years) could enlarge it by approximately 71.39% and 80.27% in scenarios with and without thinning when compared with a shorter rotation length (40 years). Discount rates and timber prices were the two most important variables affecting joint benefits, while the effects of carbon prices were not as significant as expected in the current trading market in China. CONCLUSIONS: The management plans that promote longer rotations, higher stand densities, and no thinning treatments can maximize the joint benefits of carbon sequestration afforestation and timber production from larch plantations located in northeast China.

[Changes in Soil Organic Carbon Density and Its Response to Climate Change and Human Activities Before and After the Grain for Green Project on the Loess Plateau].

Accurately assessing the changes in soil organic carbon storage （SOCS） before and after the Grain for Green Project （GFG） in the Loess Plateau （LP） and exploring the relationship between its spatial and temporal distribution and the influencing factors were important references for the development of regional recycling as well as the formulation of ecological protection policies. Based on the data of climate, human activities, and SOCD in the surface （0-20 cm） and deep （0-100 cm） soil before and after GFG in the LP from 2001 to 2020, we investigated the changes in SOCD at different spatial and temporal scales by using the methods of trend analysis, the kriging method, and variance partitioning analysis. The results showed that： ① Before and after the GFG, the surface SOCS of the whole region increased by 8 338.7×104 t； the deep SOCS increased by 1 160.02×104 t. ② In each bioclimatic subregion, the whole-region average SOCD of Ⅰ （Semi-Humid Forest Region）, Ⅱ （Semi-Humid Semi-Arid Forest and Grassland Region）, and Ⅲ （Semi-Arid Typical Grassland Region） showed a significant increasing trend, with a decreasing trend in Ⅳ （arid semi-arid desert grassland area） and Ⅴ （arid desert area）. ③ The average surface SOCS increase in different ecosystems was ranked as follows： cropland > grassland > woodland > shrubs > bare land and sparse vegetation. The deep soil increase was ranked as follows： grassland > cropland > woodland > shrubs > bare land and sparse vegetation. ④ Climate factors were the most important driving factors for changes in SOCD； the annual average temperature and precipitation were significantly positively correlated with changes in SOCD. The results of the study could provide data support for regional ecological management and land use policy formulation to promote high quality development of the ecological environment in the LP.

Sediment porewaters serve as a transient organic carbon pool at the land-ocean interface.

The organic carbon (OC) cycle at the land-ocean interface is an important component of the global carbon budget, yet the processes that control the transfer, transformation, and burial of OC in these regions remain poorly understood. In this work, we examined sedimentary OC (SOC) in short core sediments, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), and chromophoric dissolved organic matter (CDOM), as well as other solutes in sediment porewaters of the Changjiang Estuary and adjacent East China Sea (ECS) shelf. The main goal of this work is to investigate the variation of the sources and composition of different forms of carbon in estuarine sediments associated with different sedimentary regimes, to further understand the role of sediment porewater in carbon sequestration at the land-ocean interface. Concentrations of Fe2+ and Mn2+ in porewaters of the muddy sediments are much higher than those in the sandy sediments, and SO42- decreases with depth in the deep sediment layer, indicating the degradation of SOC in mobile muds is mainly driven by suboxic and/or anoxic diagenetic processes (e.g., iron-manganese reduction). The accumulation of DIC in the muddy sediment is higher compared to the sandy sediment, indicating relatively complete SOC remineralization. The DOC in porewaters of the muddy areas is mainly composed of highly degraded and low molecular weight humic-like substances (C1), whereas in the sandy area, porewater DOC is mainly composed of less degraded and high molecular weight protein-like substances (C2 and C3). The average DOC stock (28.5 t/km2) in the upper 30 cm sediment porewaters is significantly higher than that of DIC (12.5 t/km2) in sandy area, but less in muddy areas (17.0 t/km2 of DOC vs. 25.4 t/km2 of DIC). The total DOC stock in sediment porewaters of the sandy area accounted for ∼61 % of DOC stock in water column of the ECS, indicating that the porewater is an important DOC pool in the ECS. However, this DOC pool is rather transient due to its high reactivity and mobility, especially in sandy area. Nevertheless, compared with other marine environments, the carbon stock of DOC (average of 43.8 t/km2) in porewaters of stable sedimentary environments is much higher than that of DIC (average of 21.7 t/km2). This work further supports the notion that sedimentary regime plays an important role in OC cycling at the land-ocean interface and highlights the significance of sediment porewaters as a vast carbon pool in marine ecosystems.

Topsoil dilution by subsoil admixture had less impact on soil organic carbon stock development than fertilizer form and erosion state.

Enhancing the agroecosystems carbon (C) sink function for climate mitigation faced challenges, particularly with traditional measures with limited suitability for increasing soil organic carbon (SOC) stocks. Inducing a SOC undersaturation in the topsoil by abrupt subsoil admixture is a way to create an additional C sink. However, the deep tillage traditionally used for this topsoil dilution was not always successful. It was due to a lack of knowledge and suitable approaches to record the effect of all relevant factors in SOC recovery, including soil conditions and fertilizer forms. We addressed these problems by establishing a three-factorial experiment: I) "moderate topsoil dilution," II) "N fertilization form," and III) "soil erosion state," representing three soil types in the hummocky ground moraine landscape of NE Germany. SOC dynamics were determined over a year of winter rye cropping using a novel robotic chamber system capable of measuring CO2 exchange on 36 experimental plots with a reduced methodological bias than previous measuring systems. The averaged net ecosystem carbon balance, a proxy for SOC stock change, indicated that topsoil dilution only reduced further SOC losses. The N fertilizer form had a significantly stronger and more differentiated effect. While the mineral N fertilization consistently produced only C sources, the organic fertilization, in combination with the diluted topsoil, led to a C sink. This C-sink function was, however, more pronounced in the eroded soil than in the non-eroded soil. Overall, the results have made clear that the impact of topsoil dilution on the further development of the SOC stock is only possible if the effect of other relevant factors, such as N fertilizer form and erosion state, are taken into account.

[Impact of Land Use Change on Carbon Storage in Urban Agglomerations in the Guanzhong Plain].

It is important to study the impact of land use change on terrestrial ecosystem carbon stocks in urban agglomerations for the optimization of land use structure and sustainable development in urban agglomerations. Based on the patch-generating land use simulation (PLUS) model and integrated valuation of ecosystem services and trade-offs (InVEST) model, a simulation was developed that predicted the land use change and carbon stock of the Guanzhong Plain urban agglomeration in 2040 under different scenarios and further analyzed the impact of land use change on carbon stock. The results showed that:① The land use types of the Guanzhong Plain urban agglomeration were mainly cultivated land, forest land, and grassland, which accounted for more than 90 % of the total study area. ② From 2000 to 2020, the carbon stock in the Guanzhong Plain showed a continuous downward trend, with cropland, woodland, and grassland being the main sources of carbon stock in the Guanzhong Plain, and the overall carbon stock declined by 15.12×106 t, with the spatial distribution presenting the distribution characteristics of "high in the north and south and low in the middle." ③ By 2040, the carbon stock would decrease the most under the urban development scenario, with a total reduction of 27.08×106 t, and the least under the ecological development scenario, with a total reduction of 4.14×106t. The research results can provide data support for the high-quality development and rational land use planning of the Guanzhong Plain urban agglomeration.

Fine Root Density Dynamics and Carbon Stock of Eucalyptus spp.: Interplay of Age, Genotype, and Edaphoclimatic Conditions.

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 effects of environmental variability and forest management on natural forest carbon stock in northwestern Ethiopia.

Natural forests are crucial for climate change mitigation and adaptation, but deforestation and degradation challenges highly reduce their value. This study evaluates the potential of natural forest carbon stock and the influence of management interventions on enhancing forest carbon storage capacity. Based on forest area cover, a study was conducted in nine purposely selected forest patches across various forest ecosystems. Data on diameter, height, and environmental variables from various forest management approaches were collected and analyzed with R Ver. 4.1. The findings revealed a substantial difference (p .029) in carbon stock between environmental variables and management interventions. The findings revealed a strong connection between environmental variables and the overall pool of carbon stock within forest patches (p .029). Carbon stocks were highest in the Moist-montane forest ecosystem (778.25 ton/ha), moderate slope (1019.5 ton/ha), lower elevation (614.50 ton/ha), southwest-facing (800.1 ton/ha) and area exclosures (993.2 ton/ha). Accordingly, natural forests, particularly unmanaged parts, are sensitive to anthropogenic stresses, decreasing their ability to efficiently store carbon. As a result, the study highlighted the importance of sustainable forest management, particularly area exclosures and participatory forest management, in increasing forest carbon storage potential.

The largest European forest carbon sinks are in the Dinaric Alps old-growth forests: comparison of direct measurements and standardised approaches.

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

Carbon pools in forest systems and new estimation based on an investigation of carbon sequestration.

Forests, the ancient wooden giants, are both symbols of natural beauty and reservoirs of carbon stocks. The current climate crisis has created an urgent need for an in-depth study of forest ecosystems and carbon stocks. Based on forest inventory data from field surveys and four bioclimatic zones [Zone 1 (Z1, humid forest), Zone 2 (Z2, semi-humid forest), Zone 3 (Z3, semi-humid to semi-arid forest-grassland), and Zone 4 (Z4, semi-arid typical grassland)], two methods [Method 1 (M1) and Method 2 (M2)] were used to estimate carbon stocks in forest ecosystems in Shaanxi Province, China, and explored the spatial patterns of carbon pools and potential influences. The total forest ecosystem carbon pool amounted to 520.80 Tg C, of which 53.60% was stored aboveground, 17.16% belowground, and 29.24% in soil (depth of 0-10 cm). Spatially, there were marked north-south gradients in both biomass (Z2 > Z3 > Z1 > Z4) and soil organic carbon densities (Z1 > Z2 > Z3 > Z4). The differences between aboveground and belowground biomass carbon density across broadleaf, needle-leaf, and broadleaf and needle-leaf mixed forest were not pronounced, while soil organic carbon density had the order of broadleaf (18.38 Mg C/ha) > needle-leaf (11.29 Mg C/ha) > broadleaf and needle-leaf mixed forest (10.33 Mg C/ha). Under an ideal scenario that excludes external factors, mainly forest growth, the sequestration potential of forest biomass by 2032 was estimated by M1 as 85.43 Tg, and by M2 to be substantially higher at 176.21 Tg. As of 2062, M1 estimated 155.97 Tg of sequestration potential for forest biomass. The spatial patterns of forest biomass and soil carbon density were closely related to climatic factors, and these relationships allowed the spatial division into two distinct climatic regions. Moreover, biomass carbon density was significantly correlated with the normalized difference vegetation index, soil silt, and elevation. This study provides key information for promoting the strategic shift from light-green to deep-green forest systems in Shannxi Province and updates the estimation methods of forest ecosystems' carbon pools based on field surveys.

Changes in carbon stocks according to stand development stages in oriental beech forests in the Marmara Region of Türkiye.

This study was conducted to determine the changes in carbon stocks of oriental beech (Fagus orientalis) according to stand development stage in the Marmara Region of Türkiye. For this purpose, sample plots were taken from a total of 32 areas encompassing four stand development stages (young, middle age, mature and overmature stand). The diameter at breast height and height of all trees in the sample plots were measured, and only three dominant trees's ages per plot were determined. Aboveground carbon stock was calculated using equations developed for beech forests, while the coefficients in the Agriculture, Forestry and Other Land Use guide were used to determine belowground carbon stocks. A soil pit was dug in each plot and soil samples were taken at different depths (0-10, 10-30, 30-60, 60-100 cm). In addition, litters were sampled from four different 25 × 25 cm sections in each plot, and then the physical and chemical properties of the soil and litters were analysed. The variations in carbon stocks in above- and below-ground tree mass, litter and soil, and in ecosystem carbon stocks according to development stage were examined by analysis of variance and Duncan test, and the relationships between the carbon stocks were investigated by correlation analysis. Aboveground (AG) and belowground (BG) tree, soil and ecosystem carbon stocks showed significant differences between the four stand development stages (P < 0.05), but not the litter carbon stocks (P > 0.05). AG and BG tree and ecosystem carbon stocks increased with progressive stand development stages, while the soil carbon stock was the highest at the young stage. These findings will contribute to the preparation of forest management plans and the national greenhouse gas inventory.

Assessment of Phytomass and Carbon Stock in the Ecosystems of the Central Forest Steppe of the East European Plain: Integrated Approach of Terrestrial Environmental Monitoring and Remote Sensing with Unmanned Aerial Vehicles.

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.

Biomass patterns in Srivilliputhur Wildlife Sanctuary: exploring factors and gradients with machine learning approach.

Forest biomass plays a crucial role in the global carbon cycle as a significant contributor derived from both soil and trees. This study focuses on investigating tree carbon stock (TCS) and estimating aboveground biomass (AGB) based on elevation within the Srivilliputhur Wildlife Sanctuary forest, while also exploring the various factors that influence their contribution. Utilizing a non-destructive approach for carbon estimation, we found that the total tree biomass in this region ranged from 220.9 Mg/ha (in Z6) to 720.6 Mg/ha (Z2), while tree carbon stock ranged from 103.8 to 338.7 Mg/ha. While Kruskal-Wallis tests did not reveal a significant relationship (p = 0.09) between TCS and elevation, linear regression showed a weak correlation (R2 = 0.002, p < 0.05) with elevation. To delve deeper into the factors influencing TCS and biomass distribution, we employed a random forest (RF) machine learning algorithm, demonstrating that stand structural attributes, such as basal area (BA), diameter at breast height (DBH), and density, held a more prominent role than climatic variables, including temperature, precipitation, and slope. Generalized linear models (GLM) were also utilized, confirming that BA, mean DBH, and elevation significantly influenced AGB (p ≤ 0.001), with species richness, precipitation, and temperature having lower significance (p ≤ 0.01) comparatively. Overall, the RF model exhibited superior performance (R2 = 0.92, RMSE = 0.12) in terms of root mean square error (RMSE) compared to GLM (R2 = 0.88, RMSE = 0.35). These findings shed light on the intricate dynamics of biomass distribution and the importance of both stand structural and climatic factors in shaping forest ecosystems.

Wooded biocorridors substantially improve soil properties in low-altitude rural benchlands.

This study examines soil properties in 30- and 60-year-old agricultural biocorridors and provides a comparative overview with neighbouring farmland. Both mixed and undisturbed soil samples were collected from six farmland/biocorridor study areas to assess a wide spectrum of physical, hydrophysical, chemical and biological soil properties. Biocorridor soils were characterised by higher water retention capacities, porosity, aeration and soil carbon stock, the latter increasing with depth. On the other hand, biocorridor bulk density under forest vegetation cover was lower, indicating progressive soil restoration. Slightly lower soil reactions in biocorridor soils disproved the hypothesis that nutrient-rich soils under biocorridors would form substrates with a high base cation content, leading to soil acidification. Biological activity, expressed through respiration coefficients, was generally low due to unfavourable physical conditions (clayey or silty-clay substrates), with the lowest levels in biocorridors. Nevertheless, biocorridor soil microbiota displayed more effective utilisation of organic matter as a carbon and nitrogen source, with lighter-textured soils tending to show more effective organic matter utilisation after excluding the influence of land use. Our results confirm biocorridors as an important landscape component, contributing to both soil stability and local revitalisation of soil environments and further emphasising their potential as climate-change mitigation tools in their role as carbon sinks.

Accurate carbon storage estimation for the salt marsh ecosystem based on Bayesian maximum entropy approach - A case study for the Spartina alterniflora ecosystem.

The blue carbon ecosystem, including the salt marsh ecosystem, possesses a significant carbon sequestration potential. Therefore, accurately quantifying the carbon storage within such ecosystems is crucial for the adequate accounting of carbon sequestration. The present work chose a Spartina alterniflora ecosystem in the Xiaogan Island (China) as the study area (approximately 11 ha), and employed the Bayesian maximum entropy (BME) approach to assimilate both hard organic carbon (OC) data and soft OC data measured from 2 cm and 10 cm stratified samples. A 3-dimensional model was developed for space-time OC estimation purposes based on the sediment chronology results. The 10-fold BME cross validation results demonstrated a high estimation accuracy, with the R2, RMSE and MAE values equal to 0.8564, 0.1026 % and 0.0748 %, respectively. A noteworthy outcome was the BME-generated carbon storage density maps with 1 m spatial resolution. These maps revealed that the carbon storage density at the top 30 cm sediment depth in the stable zone (with elder stand age of S. alterniflora) was higher than that in the rapid expansion zone, i.e., 71.79 t/ha vs. 69.82 t/ha, respectively. Additionally, the study found that the averaged carbon burial rate and the total carbon storage at the top 30 cm sediment depth across the study area were 266 g C/m2/yr and 781.50 t, respectively. Lastly, the proposed BME-based framework of carbon storage estimation was found to be versatile and applicable to other blue carbon ecosystems. This approach can foster the development of a standardized carbon sink metrological methodology for diverse blue carbon ecosystems.

Replacing Spartina alterniflora with northward-afforested mangroves has the potential to acquire extra blue carbon.

Climate change provides an opportunity for the northward expansion of mangroves, and thus, the afforestation of mangroves at higher latitude areas presents an achievable way for coastal restoration, especially where invasive species S. alterniflora needs to be clipped. However, it is unclear whether replacing S. alterniflora with northward-afforested mangroves would benefit carbon sequestration. In the study, we examined the key CO2 and CH4 exchange processes in a young (3 yr) northward-afforested wetland dominated by K. obovata. We also collected soil cores from various ages (3, 15, 30, and 60 years) to analyze the carbon storage characteristics of mangrove stands using a space-for-time substitution approach. Our findings revealed that the young northward mangroves exhibited obvious seasonal variations in net ecosystem CO2 exchange (NEE) and functioned as a moderate carbon sink, with an average annual NEE of -107.9 g C m-2 yr-1. Additionally, the CH4 emissions from the northward mangroves were lower in comparison to natural mangroves, with the primary source being the soil. Furthermore, when comparing the vertical distribution of soil carbon, it became evident that both S. alterniflora and mangroves contributed to organic carbon accumulation in the upper soil layers. Our study also identified a clear correlation that the biomass and carbon stocks of mangroves increased logarithmically with age (R2 = 0.69, p < 0.001). Notably, both vegetation and soil carbon stocks (especially in the deeper layers) of the 15 yr northward mangroves, were markedly higher than those of S. alterniflora. This suggests that replacing S. alterniflora with northward-afforested mangroves is an effective long-term strategy for future coasts to enhance blue carbon sequestration.

Traditional homegardens change to perennial monocropping of khat (Catha edulis) reduced woody species and enset conservation and climate change mitigation potentials of the Wondo Genet landscape of southern Ethiopia.

Smallholder farmers in the Wondo Genet were forced to switch from long-standing, diverse traditional home gardens to monoculture khat production due to increasing population pressure-induced farmland constraints. The composition of woody species and the biomass carbon stock are thought to drop as homegardens transition from polyculture to monoculture; however there is little quantitative evidence to support this claim. This study was started to assess the effects on woody species, enset, and biomass carbon of converting traditional homegardens to a fast spreading perennial monocropping of khat (Catha edulis Forskal). In 10 m × 10 m (100m2) plots from 43 farms with neighboring land use patterns for each homegarden and khat, woody species and enset were inventoried, the total number of tree, shrub, and enset species counted, as well as the height and diameter of each species measured. To determine the biomass carbon stock of each land use type, both general and species-specific allometric equations are used. Simpson's diversity index, Shannon-Wiener, and Shannon equitability were used to evaluate the diversity of enset and woody species. There were 27 different types of woody species identified, with trees making up 67 % of the total and shrubs accounting for 33 %. Shannon, Simpson, and the richness of woody species all decreased by 46 %, 51 %, and 38 %, respectively, in comparison to residential gardens. For homegardens and khat, respectively, the mean Evenness values were 0.876 and 0.539. In homegardens, Coffea arabica was the most valuable woody species, followed by Cordia africana Lam, Persea americana, Eucalyptus camaldulensis, and Grevillea Robusta. In contrast, Catha edulis was the most valuable woody species in the Khat land use type, followed by Coffea arabica, Croton macrostachyus Del, and Cordia africana. In comparison to homegardens, the above-ground, below-ground, and total biomass carbon reported in khat land use types were reduced by 18 %, 63 %, and 42 %, respectively. Grevillea and Eucalyptus species made up 51 % of the total biomass carbon stock in the homegardens, which suggests that khat and quickly expanding fast-growing plants have displaced native woody species.Understanding the long-term effects of agro-biodiversity loss requires greater research on the implications of the decline in woody species diversity and biomass carbon stock on soil fertility and sustainable farming. This is due to the numerous functions that woody species and enset play.

Forest carbon stock development following extreme drought-induced dieback of coniferous stands in Central Europe: a CBM-CFS3 model application.

BACKGROUND: We analyze the forest carbon stock development following the recent historically unprecedented dieback of coniferous stands in the Czech Republic. The drought-induced bark-beetle infestation resulted in record-high sanitary logging and total harvest more than doubled from the previous period. It turned Czech forestry from a long-term carbon sink offsetting about 6% of the country's greenhouse gas emissions since 1990 to a significant source of CO2 emissions in recent years (2018-2021). In 2020, the forestry sector contributed nearly 10% to the country's overall GHG emissions. Using the nationally calibrated Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) at a regional (NUTS3) spatial resolution, we analyzed four scenarios of forest carbon stock development until 2070. Two critical points arise: the short-term prognosis for reducing current emissions from forestry and the implementation of adaptive forest management focused on tree species change and sustained carbon accumulation. RESULTS: This study used four different spruce forest dieback scenarios to assess the impact of adaptive forest management on the forest carbon stock change and CO2 emissions, tree species composition, harvest possibilities, and forest structure in response to the recent unprecedented calamitous dieback in the Czech Republic. The model analysis indicates that Czech forestry may stabilize by 2025 Subsequently, it may become a sustained sink of about 3 Mt CO2 eq./year (excluding the contribution of harvested wood products), while enhancing forest resilience by the gradual implementation of adaptation measures. The speed of adaptation is linked to harvest intensity and severity of the current calamity. Under the pessimistic Black scenario, the proportion of spruce stands declines from the current 43-20% by 2070, in favor of more suited tree species such as fir and broadleaves. These species would also constitute over 50% of the harvest potential, increasingly contributing to harvest levels like those generated by Czech forestry prior to the current calamity. The standing stock would only be recovered in 50 years under the optimistic Green scenario. CONCLUSION: The results show progress of adaptive management by implementing tree species change and quantify the expected harvest and mitigation potential in Czech forestry until 2070.

Mangrove ecosystems in Southeast Asia region: Mangrove extent, blue carbon potential and CO2 emissions in 1996-2020.

This study aimed to analyze mangrove extent (ME), carbon stock, blue carbon potential, and CO2 emission from 1996 to 2020 in Southeast Asia region. The data was obtained through the Global Mangrove Alliance (GMA) on the platform www.globalmangrovewatch.org v.3. Furthermore, ME was analyzed descriptively and the triggers for mangrove land changes in each country were investigated through a relevant literature review. The spatial analysis was conducted for blue carbon potential, while CO2 emission was derived by multiplying net change by emission factor (EF) of mangrove ecosystem. The results showed that the total ME in Southeast Asia was 5.07 million hectares (Mha) in 1996, decreasing to 4.82 Mha by 2020 due to various land uses, primarily shrimp farming. The total carbon stock potential was 2367.68 MtC, while a blue carbon potential was 8682.32 MtCO2-e, consisting of 1304.33 MtCO2-e and 7377.99 MtCO2-e from above-ground and soil carbon. Indonesia contributed 5939.57 MtCO2-e to blue carbon potential, while Singapore and Timor-Leste had the lowest contributions of 1.05 MtCO2-e and 1.37 MtCO2-e, respectively. Carbon stock potential (AGC and SOC) in Southeast Asia was influenced by ME conditions. The relationship between ME and AGC was found to be exponential (AGC = 0.0307e0.8938x; R2 = 0.9331; rME-AGC = 0.9964, P < 0.01). Similarly, ME and SOC, or AGC and SOC showed a relationship where SOC = 0.2e0.8829x (R2 = 0.937, rME-SOC = 0.9965 and rAGC-SOC = 0.9989, P < 0.01). The average CO2-e emission in Southeast Asia reached 17.0760 MtCO2-e yr-1 and the largest were attributed to Indonesia at 16.3817 MtCO2-e yr-1. Meanwhile, Brunei and Timor Leste did not show CO2-e emission as mangrove in these countries absorbed more CO2 from the atmosphere at -0.034 MtCO2-e yr-1 and -0.0002 MtCO2-e yr-1, respectively.

Long-term warming increased carbon sequestration capacity in a humid subtropical forest.

Tropical and subtropical forests play a crucial role in global carbon (C) pools, and their responses to warming can significantly impact C-climate feedback and predictions of future global warming. Despite earth system models projecting reductions in land C storage with warming, the magnitude of this response varies greatly between models, particularly in tropical and subtropical regions. Here, we conducted a field ecosystem-level warming experiment in a subtropical forest in southern China, by translocating mesocosms (ecosystem composed of soils and plants) across 600 m elevation gradients with temperature gradients of 2.1°C (moderate warming), to explore the response of ecosystem C dynamics of the subtropical forest to continuous 6-year warming. Compared with the control, the ecosystem C stock decreased by 3.8% under the first year of 2.1°C warming; but increased by 13.4% by the sixth year of 2.1°C warming. The increased ecosystem C stock by the sixth year of warming was mainly attributed to a combination of sustained increased plant C stock due to the maintenance of a high plant growth rate and unchanged soil C stock. The unchanged soil C stock was driven by compensating and offsetting thermal adaptation of soil microorganisms (unresponsive soil respiration and enzyme activity, and more stable microbial community), increased plant C input, and inhibitory C loss (decreased C leaching and inhibited temperature sensitivity of soil respiration) from soil drying. These results suggest that the humid subtropical forest C pool would not necessarily diminish consistently under future long-term warming. We highlight that differential and asynchronous responses of plant and soil C processes over relatively long-term periods should be considered when predicting the effects of climate warming on ecosystem C dynamics of subtropical forests.