Belowground Carbon Research Articles

Community identification and carbon storage monitoring of Heritiera littoralis with UAV hyperspectral imaging

The Heritiera littoralis, an important rare semi-mangrove species found in coastal protective forests, plays a crucial role in carbon storage and cycling within mangrove wetland ecosystems. Despite its importance, previous studies have overlooked remote monitoring of its carbon storage. Taking the world’s oldest and largest natural community of H. littoralis in Shenzhen, China, as the study area, this research pioneers the use of UAV hyperspectral imaging to identify the H. littoralis community and estimate its above-ground, below-ground, and total carbon storage. The impacts of five geo-environmental factors (elevation, slope, aspect, vegetation communities, and inland distance from the coastline) on the spatial variability of carbon storage using SHapley Additive exPlanations (SHAP) and multiscale geographically weighted regression (MGWR) methods were also investigated. The results demonstrate that the first derivative bands within the red edge and near-infrared regions, the anthocyanin reflectance index 2 (ARI2) and newly-developed three-band VIs, were sensitive features for community identification and carbon storage estimation within the H. littoralis community. Among the four machine learning models (eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR)), the best identification accuracy for the H. littoralis community was achieved by XGBoost. Among the four machine learning models (XGBoost, RF, SVM and kernel ridge regression (KRR)), RF model achieved the best performance in estimating above-ground (R2 = 0.749, RMSE=1.723 kg/m2, EV (explained variance) = 0.704), below-ground (R2 = 0.636, RMSE=0.6 kg/m2, EV=0.606) and total carbon storage (R2 = 0.613, RMSE=2.592 kg/m2, EV=0.597). SHAP and MGWR analysis showed that elevation and inland distance from the coastline were key factors influencing the spatial variability of carbon storage. In conclusion, this study showcases significant advantages in community identification and carbon storage monitoring of rare mangrove communities, providing valuable insights for biodiversity conservation efforts and management within the H. littoralis ecosystem.

Tree carbon stock and seasonal influence on soil properties in shivpuri-nagarjun national park, nepal

The carbon stock stored within the biomass of tree species is vital in the forest ecosystem as it contributes significantly to the carbon balance. In addition, the physicochemical properties of soil play a critical role, in influencing overall ecosystem health. This study has analyzed the carbon stock and influence of seasonal change on soil physicochemical properties along soil depths in the Shivpuri Nagarjun National Park (SNNP), Nepal. The above-ground biomass carbon stock was found to be 227.09 t/ha and below-ground stock was 45.42 t/ha. Tree species Castanopsis tribuloides exhibited the highest values of above and below-ground tree carbon stock. The soil of the study site was sandy loam and slightly acidic. High temperature and moisture in the monsoon season were followed by an increased bulk density during the pre-monsoon with deeper soil layers. The sand, silt, and clay contents did not differ significantly across the seasons and depths. The key soil nutrients, like carbon, total nitrogen, phosphorus, and potassium were high during the monsoon season at the topsoil layer, which gradually declined with increasing depth in all seasons. The study highlights that the total tree carbon stock in the study site is 272.51 t/ha, with significant seasonal and depth-related variations in soil attributes. The monsoon season, characterized by maximum soil moisture and higher concentrations of essential soil components, is crucial in influencing soil physicochemical properties and offers important insights for forest conservation and management. Bangladesh J. Bot. 53(3): 567-576, 2024 (September)

Symbiotic nitrogen fixation reduces belowground biomass carbon costs of nitrogen acquisition under low, but not high, nitrogen availability.

Many plant species form symbiotic associations with nitrogen-fixing bacteria. Through this symbiosis, plants allocate photosynthate belowground to the bacteria in exchange for nitrogen fixed from the atmosphere. This symbiosis forms an important link between carbon and nitrogen cycles in many ecosystems. However, the economics of this relationship under soil nitrogen availability gradients is not well understood, as plant investment toward symbiotic nitrogen fixation tends to decrease with increasing soil nitrogen availability. Here, we used a manipulation experiment to examine how costs of nitrogen acquisition vary under a factorial combination of soil nitrogen availability and inoculation with Bradyrhizobium japonicum in Glycine max L. (Merr.). We found that inoculation decreased belowground biomass carbon costs to acquire nitrogen and increased total leaf area and total biomass, but these patterns were only observed under low fertilization and were the result of increased plant nitrogen uptake and no change in belowground carbon allocation. These results suggest that symbioses with nitrogen-fixing bacteria reduce carbon costs of nitrogen acquisition by increasing plant nitrogen uptake, but only when soil nitrogen is low, allowing individuals to increase nitrogen allocation to structures that support aboveground growth. This pattern may help explain the prevalence of plants capable of forming these associations in less fertile soils and provides useful insight into understanding the role of nutrient acquisition strategy on plant nitrogen uptake across nitrogen availability gradients.

Exploring the role of canopy cover and environmental factors in shaping carbon storage in Desa’a forest, Ethiopia

BackgroundDry Afromontane forests play a vital role in mitigating climate change by sequestering and storing carbon, as well as reducing greenhouse gas emissions. Despite previous research highlighting the importance of carbon stocks in these ecosystems, the influence of canopy cover and environmental factors on carbon storage in dry Afromontane forests has been barely assessed. This study addresses this knowledge gap by investigating the effects of environmental factors and vegetation cover on carbon stocks in Desa’a forest, a unique and threatened Afromontane dry forest ecosystem in northern Ethiopia. Data on woody vegetation, dead litter, grass biomass, and soil samples were collected from 57 plots. A one-way analysis of variance (ANOVA) was performed at a 95% confidence level (α = 0.05) to examine the influence of canopy cover and environmental factors on the carbon stocks of various pools.ResultsAmong the 35 woody species identified, Juniperus procera was the most dominant, while Carissa edulis Vahl and Eucalyptus globulus were the least dominant. The average total carbon stock was 92.89 Mg ha−1, with contributions from aboveground carbon, below-ground carbon, litter carbon, grass carbon, and soil organic carbon. Among the carbon pools, soil organic carbon had the highest carbon stock, accounting for 76.8% of the total, followed by above-ground biomass carbon at 17.7%. Significant variations in carbon stocks were found across altitude class and canopy level but not slope and aspect factors.ConclusionsIn summary, altitude and canopy level were found to significantly influence carbon stocks in Desa’a forest, providing valuable insights for conservation and climate change mitigation efforts in dry Afromontane forests. Forest intervention planning and management strategies should consider the influence of different environmental variables and tree canopy levels.

Extreme precipitation reduces the recent photosynthetic carbon isotope signal detected in ecosystem respiration in an old-growth temperate forest.

The successful utilization of stable carbon isotope approaches in investigating forest carbon dynamics has relied on the assumption that the carbon isotope compositions (δ13C) therein have detectable temporal variations. However, interpreting the δ13C signal transfer can be challenging, given the complexities involved in disentangling the effect of a single environmental factor, the isotopic dilution effect from background CO2 and the lack of high-resolution δ13C measurements. In this study, we conducted continuous in situ monitoring of atmospheric CO2 (δ13Ca) across a canopy profile in an old-growth temperate forest in northeast China during the normal year 2020 and the wet year 2021. Both years exhibited similar temperature conditions in terms of both seasonal variations and annual averages. We tracked the natural carbon isotope composition from δ13Ca to photosynthate (δ13Cp) and to ecosystem respiration (δ13CReco). We observed significant differences in δ13Ca between the two years. Contrary to in 2020, in 2021 there was a δ13Ca valley in the middle of the growing season, attributed to surges in soil CO2 efflux induced by precipitation, while in 2020 values peaked during that period. Despite substantial and similar seasonal variations in canopy photosynthetic discrimination (Δ13Ccanopy) in the two years, the variability of δ13Cp in 2021 was significantly lower than in 2020, due to corresponding differences in δ13Ca. Furthermore, unlike in 2020, we found almost no changes in δ13CReco in 2021, which we ascribed to the imprint of the δ13Cp signal on above-ground respiration and, more importantly, to the contribution of stable δ13C signals from soil heterotrophic respired CO2. Our findings suggest that extreme precipitation can impede the detectability of recent photosynthetic δ13C signals in ecosystem respiration in forests, thus complicating the interpretation of above- and below-ground carbon linkage using δ13CReco. This study provides new insights for unravelling precipitation-related variations in forest carbon dynamics using stable isotope techniques.

Effects of Grazing on Plant Diversity and Their Carbon Stocks in Different Types of Grasslands

With the drying and warming of the climate and irrational grazing, various types of grasslands in Inner Mongolia have been degraded to different degrees, and different management modes will inevitably affect the plant diversity and vegetation carbon stock of soil grasslands. To clarify the changes and influencing factors of plant diversity and carbon stock in different types of grasslands under different management modes, plant species composition, aboveground biomass, and vegetation carbon were analyzed based on 18 sentinel monitoring stations across three different types of grasslands in Inner Mongolia. The results showed that grazing increased the dominance of typical grassland and desert grassland, whereas meadow grassland decreased, and the evenness index and Shannon Wiener diversity index increased less in meadow grassland and desert grassland. Grazing decreased graminaceous biomass in meadow grassland and typical grassland, whereas it increased in desert grassland. Above-ground vegetation and below-ground root carbon stocks were much higher than those in grazing areas, 1.5 and 1.2 higher, respectively, but vegetation carbon stocks in long-term grazing sites were significantly lower than those in short-term grazing. Further, the structural equations showed that the effects of geographic location, climatic factors, and soil factors on the biomass and vegetation carbon stocks of the three grassland types differed significantly. The results can provide a reference for the ecologically sustainable development of grassland and the optimization of management mode.

Spatio-temporal Dynamics of Land Use/Cover Change and Associated Carbon Stocks in Kanyabaha Wetland in Rukiga District, Uganda

Wetlands play an important ecological function of sequestering atmospheric carbon dioxide and thereby moderating adverse impacts of climate change. It is therefore important to understand the dynamics of carbon stocks in wetland vegetation and soils. This study investigated the spatio-temporal dynamics of aboveground, belowground, and total carbon stocks in Kanyabaha Wetland, located in Rukiga District, Uganda, spanning from 1990 to 2021. Through field sampling and laboratory analysis, aboveground carbon stocks were assessed by harvesting vegetation biomass and converting it to carbon stock using established conversion factors. Soil samples collected at different depths (0-20cm, 20-50cm, 50-100cm) were analyzed for soil organic carbon content to determine belowground carbon stocks. The study reveals variable spatio-temporal patterns of carbon stocks across land use types, with papyrus-dominated areas exhibiting the highest aboveground carbon stocks (49.66 tC/ha), followed by small-scale farmlands (33.73 tC/ha) and tree plantations (23.01 tC/ha). Conversely, built-up areas exhibit the lowest carbon stocks (1.29 tC/ha). Temporal analysis reveals fluctuating patterns in carbon stocks, with increases observed in built-up areas and small-scale farmlands, and decreases in grasslands and tree plantations that could be due to changes in hydrological cycle. Belowground carbon stocks follow similar trends, with papyrus areas maintaining the highest stocks (39.96 tC/ha), particularly at deeper soil depths that exhibit the highest carbon accumulation due to its extensive network of papyrus rhizome. Changes in land use, especially reclamation of the wetlands for farming and settlements affected carbon capture and storage in the wetland ecosystem. These findings highlight the importance of targeted conservation of natural wetlands and sustainable land management strategies in the Kanyabaha Wetland catchment for enhanced carbon sequestration. Further, in depth studies in the variability of carbon stocks due to various eco-climatic factors and anthropogenic activities are necessary to support sustainable wetland land management practices in Uganda.

Carbon flow from roots to rhizobacterial networks: Grafting effects

Plants recruit microorganisms from bulk soil by secreting easily available organic carbon into the rhizosphere. Grafting often increases the disease resistance of agricultural plants by modifying this carbon flow from roots into rhizosphere and by recruiting active microorganisms that suppress pathogens. Here, we continuously labeled grafted and ungrafted watermelon plants in a 13CO2 atmosphere to identify the active microorganisms assimilating root exudates. Multi-omics associated technologies (amplicon sequencing, metagenomics and metabolomics) combined with 13C tracing were used to examine the carbon flows, microbial utilization and transformation in the rhizosphere. The number of potentially active bacterial species recruited in the rhizosphere of grafted plants and utilizing root exudates was four times more than in ungrafted plants. These potentially active species matched to metagenome-assembled-genomes (MAGs) mainly belonging to Sphingomonas in the rhizosphere of ungrafted plants, and to Sphingomonas, Chitinophaga, Dyadobacter and Pseudoxanthomonas in the rhizosphere of grafted plants. Sphingomonas possesses the functional potential to metabolize a plant self-toxic substance, namely 4-hydroxybenzoic acid. Furthermore, grafting shaped the complex metabolic interactions and changed the original metabolic dependence between the potentially active bacterial species. Grafting plants diversified belowground carbon flows, activating a greater number of beneficial microbes.

Exploring carbon storage and sequestration as affected by land use/land cover changes toward achieving sustainable development goals

Understanding the impact of changes in land use/land cover (LULC) on carbon sequestration (Cseq) and emission leads to achieving sustainable development goals (SDGs). For this, Business-As-Usual (BAU) and Sustainable Development (SD) scenarios were examined in Azarshar city, Iran which is faced with urban intensification. The spatiotemporal dynamics of the carbon cycle and influences of various urban growth indicators are still unclear even under climate change, rapid urbanization, and ecological deterioration. In this research, total carbon storage (Cts) and Cseq were determined at four carbon pools i.e., aboveground carbon (AGC), belowground carbon (BGC), dead organic carbon (DeOC), and soil organic carbon (SOC). This research revealed a successful implementation of integrated CA-Markov and InVEST models in delineating LULC changes between 2013 and 2033. It was concluded that land resources management play a crucial role in decreasing Cseq along with increasing carbon emission across the study area. The modelling results showed a significant shifting from barren and cropland to developed land uses. This research goes beyond providing supporting evidence that urban expansion is a key factor driving the aforementioned changes, but also illustrates the importance of remote sensing in ecological modelling, especially where information is sparse.

To improve estimates of neotropical forest carbon stocks more direct measurements are needed: An example from the Southwestern Amazon

Tropical forests play a critical role in the global carbon cycle, storing 40–55 % of terrestrial plant carbon and significantly contributing to primary productivity. However, uncertainties persist in estimating carbon stocks and fluxes, exhibiting variation across the Neotropics, Africa, and Asia tropical forest regions. Despite hosting some of the most densely sampled forests, significant uncertainties persist in biomass and forest carbon stock estimates in the Neotropics. Although the Southwestern Amazon (SWA) forests span over 20 million hectares, no specific biomass or above- and below-ground carbon model has been calibrated for this region thus far. In our study, we conducted direct forest inventories in the SWA to address the following question: Do the allometric patterns, biomass, and carbon stocks observed in the Southwestern Amazon differ from those found in other regions of the Amazon or Pantropical? Our research reveals substantial differences in water and carbon content, biomass stocks, above- and below-ground oven-dry biomass ratios, and allometric patterns between SWA forests and other Amazonian and Pantropical forests. We have demonstrated that these differences result in overestimations of forest biomass when applying allometric equations developed for other Amazonian and Pantropical regions to the open forests of Southwestern Amazonia. This overestimation can reach up to 37 % when using equations from the eastern Amazon, and between 26 % and 46 % depending on the applied Pantropical equation. The use of an inappropriate factor for the root-to-shoot ratio in the Southwestern Amazon (SWA) can lead to overestimates of belowground oven-dry biomass by up to 20 %. To reduce uncertainties related to estimates of forest carbon stock and flux in Neotropical forests, it is necessary to enhance the density of direct biomass measurements, particularly in southwestern Amazonia.

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.

Major overlap in plant and soil organic carbon hotspots across Africa

Terrestrial plant and soil organic carbon stocks are critical for regulating climate change, enhancing soil fertility, and supporting biodiversity. While a global-scale decoupling between plant and soil organic carbon has been documented, the hotspots and interconnections between these two carbon compartments across Africa, the second-largest continent on the planet, have been significantly overlooked. Here, we have compiled over 10,000 existing soil organic carbon observations to generate a high-resolution map, illustrating the distribution pattern of soil organic carbon in Africa. We then showed that above- and below-ground plant carbon are significantly and positively correlated with soil organic carbon across Africa. Both soil and plant carbon compartments shared major hotspots in the tropical regions. Our study provides critical insights into the spatial distribution of carbon hotspots across Africa, essential for soil conservation and safeguarding terrestrial carbon stocks amidst the challenges of climate change.

A new data-driven map predicts substantial undocumented peatland areas in Amazonia

Abstract Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441 025–1700 000 km2) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first field-data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of 251 015 km2 (95th percentile confidence interval: 128 671–373 359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs relatively well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold Campinarana or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin.

Rhizosphere effects and microbial N limitations drive the root N limitations in the rhizosphere during secondary succession in a Pinus tabuliformis forest in North China.

Rhizosphere effects (REs) have recently been identified as important regulators of root and microbial nutrient acquisition and are positively involved in nutrient cycling of belowground carbon (C), nitrogen (N), and phosphorus (P). Nutrient conditions of the fine roots and soil N are likely to influence REs. Still, it is unclear how REs of soil nutrients themselves variably impact the supply of nutrients to plants in terms of the responses to soil N due to succession. In this study, we applied both fine roots and extracellular enzymes for vector analysis and stoichiometry of N:P to explore the metabolic limitations of roots and rhizospheric soil microbes and their relationships with REs across five levels of soil N (0, 5, 10, 15, and 20kg N m-2 year-1) along successional age classes of 42, 55, and 65 years in a Pinus tabuliformis forest. Overall, the metabolism of root and rhizospheric soil microbes was mediated by soil N. N limitation of roots initially decreased before increasing, whereas that of microbes demonstrated opposite trends to the N levels owing to competition for inorganic N between them by REs of NO3 --N. However, N limitations of both roots and microbes were alleviated in young stands and increased with succession after the application of N. In addition, root N limitations were manipulated by REs of three different soil N-related indicators, i.e., total N, NH4 +-N, and NO3 --N. Rhizospheric soil microbial N limitation was almost unaffected by REs due to their strong homeostasis but was an important driver in the regulation of root N limitation. Our results indicated that successional age was the most critical driver that directly and indirectly affected root N metabolism. However, the level of N application had a slight effect on root N limitation. Microbial N limitation and variations in the REs of N indicators regulated root N limitation in the rhizosphere. As a result, roots utilized REs to sequester N to alleviate N limitations. Thesefindings contribute to novel mechanistic perspectives on the sustainability of N nutrition by regulating N cycling in a system of plant-soil-microbes in the rhizosphere to adapt to global N deposition or the heterogeneous distribution of bioavailable soil N with succession.

Accounting for deep soil carbon in tropical forest conservation payments

Secondary tropical forests are at the forefront of deforestation pressures. They store large amounts of carbon, which, if compensated for to avoid net emissions associated with conversion to non-forest uses, may help advance tropical forest conservation. We measured above- and below-ground carbon stocks down to 1 m soil depth across a secondary forest and in oil palm plantations in Malaysia. We calculated net carbon losses when converting secondary forests to oil palm plantations and estimated payments to avoid net emissions arising from land conversion to a 22-year oil palm rotation, based on land opportunity costs per hectare. We explored how estimates would vary between forests by also extracting carbon stock data for primary forest from the literature. When tree and soil carbon was accounted for, payments of US$18–51 tCO2–1 for secondary forests and US$14–40 tCO2–1 for primary forest would equal opportunity costs associated with oil palm plantations per hectare. If detailed assessments of soil carbon were not accounted for, payments to offset opportunity costs would need to be considerably higher for secondary forests (US$28–80 tCO2–1). These results show that assessment of carbon stocks down to 1 m soil depth in tropical forests can substantially influence the estimated value of avoided-emission payments.

Assessing the Impacts of land Use Change on Carbon Sequestration: A Comprehensive Analysis for Kochi City, India

Land use typologies play a pivotal role in determining the carbon sequestration capacity of urban ecosystems. Ashuman activities continue to reshape landscapes, understanding the impact of different land uses on carbon storageis crucial for developing effective climate change mitigation strategies for cities. This paper aims to analyse therelationship between land use typologies and carbon sequestration. Carbon sequestered in the selected city i.e., Kochiis quantified using the InVEST Carbon Storage and Sequestration model (Integrated Valuation of Ecosystem Servicesand Tradeoffs), coupled with remote sensing. The model uses input data on carbon pools including above-ground,below-ground, soil biomass, and dead carbon matter. The change in carbon sequestration with change in land usebetween 2003 and 2023 is calculated. The study reveals that there has been a reduction in wetland areas by 59 %which leads to 63% less sequestration of carbon highlighting the implication of land use on carbon sequestration.

Geographical Environment and Plant Functional Group Shape the Spatial Variation Pattern of Plant Carbon Density in Subalpine-Alpine Grasslands of the Eastern Loess Plateau, China

The carbon density of subalpine-alpine grasslands (SGs) is significantly vital to sustaining the carbon cycle in global terrestrial ecosystems. However, on the Loess Plateau of China, it remains unclear how the geographical environment and plant functional groups affect the spatial variation pattern of plant carbon density in these grasslands. Here, nine typical SGs distributed in the eastern Loess Plateau with elevations ranging from 1720 to 3045 m were investigated. The biomass indices from grassland plants of different functional groups were investigated using plot surveys. The Kriging interpolation method was used to explore the spatial variation pattern of plant carbon density along geographical gradients. We found that (1) the total plant carbon density of SGs was 2676.825 g C/m2 on the eastern plateau, with 37.07%, 37.50%, and 25.43% contributed by the northern, central, and southern areas, respectively. Above- (666.338 g C/m2) and belowground (2010.488 g C/m2) carbon density accounted for 24.9% and 75.11% of the total, respectively. (2) At the horizontal scale, the plant carbon density in the northern SGs was high in the northwest and low in the southeast; in the central SGs, it was low in the northwest and high in the southeast; and in the southern SGs, it was high in the southwest and low in the northeast. At the vertical scale, plant carbon density in all SGs decreased with increasing altitude. (3) The carbon density of grasses, forbs, and sedges was 247.419 g C/m2, 26.073 g C/m2, and 23.471 g C/m2, respectively. With increased latitude, the carbon density of all functional groups (grasses, forbs, and sedges) decreased; the carbon density of forbs and grasses increased with increased longitude, while that of sedges decreased; and with increased altitude, the carbon density of all functional groups increased. In conclusion, the spatial variation pattern of plant carbon density in the SGs was not only influenced by the geographical environment but also by the plant functional groups at the horizontal and vertical scales on the eastern Loess Plateau of China.

Firebreaks and Their Effect on Vegetation Composition and Diversity in Grasslands of Golden Gate Highlands National Park, South Africa

Southern African grasslands with a rich flora, shaped by fire, grazing, climate and geology, as well as playing a role in carbon sequestration, are becoming more important in conservation. Fire is often used as a management tool to improve vegetation and to protect property against uncontrolled fire. We therefore attempt to determine the effect consecutive burning has on vegetation. Paired plots along firebreaks were used to collect vegetation data using the Braun-Blanquet cover abundance scale. Soil samples were also collected to determine the impact of fire on below-ground nitrogen (N) and carbon (C) stocks and ratios. The results indicate that there is no difference between the plant communities of the firebreaks and the adjacent grassland; however, there are certain species that are favoured by firebreaks and others by the adjacent grassland. There is also no difference in diversity between the firebreaks and adjacent grassland areas. Carbon and nitrogen stocks as well as C:N ratios did not differ significantly between the firebreaks and the adjacent grassland plots although trends indicate a decline in both C and N with repeated burning.

Above and belowground carbon stocks among organic soil wetland types, accounting for peat bathymetry

Wetlands are widely recognized for their carbon (C) sequestration capacity and importance at mitigating climate change. Yet, to best inform regional conservation planning, the variability of C stocks among wetland types and between above and belowground compartments requires further investigation. Additionally, the bathymetry of peat basins has often been ignored, with soil C stock calculations mostly relying on the thickest peat section, potentially leading to overestimates. Here, we sampled vegetation and soil of 57 wetlands of southeastern Canada to characterize the variability of above and belowground organic C stocks among four wetland types: open bogs, open fens, swamps, and forested peatlands. We also compared carbon stock estimation approaches considering peat bathymetry or not. Results showed that peat thickness, and thus soil organic C (SOC), varied substantially within sites due to peat basin shapes. Omitting bathymetry led to site-scale SOC overestimates of about 20–38 % on average, depending on the approach used, with wide variability among sites (overestimates up to 200 %). Belowground C stocks varied among wetland types with mean values of 132, 101, 19, and 44 kg C m−2 for bogs, fens, swamps, and forested peatlands, respectively. Aboveground C was nearly zero in open bogs and fens but reached ∼30 % of total C stock in swamps and ∼ 15 % in forested peatlands. C stocks in tree roots and shrubs were negligible. Despite the lower C density (per m2) of swamps and forested peatlands, these ecosystems represented the dominant C stocks at the regional scale due to their abundance in the landscape. Overall, the four wetland types stored an estimated 2–7 times more C than forest per unit area. Evaluating differences in C stocks according to wetland type, while integrating peat bathymetry in calculations, can significantly improve regional wetland conservation planning.

Total Carbon Storage in Uneven-Aged Pure Beech Stands in the Western Part of the Balkans

Forest ecosystems represent one of the largest and most important ecosystems on Earth, containing close to 80% of the biomass of our planet. As such, they play a significant role in the global carbon cycle because through photosynthesis, forests absorb more carbon than they emit and thus accumulate it. The most important species in deciduous forests in Europe, European beech (Fagus sylvatica L.), is of exceptional importance from the aspect of carbon storage. Considering that the state of carbon in pure beech forests is poorly investigated in the western part of the Balkans, the need for total carbon research was imposed to complete the picture of its stocks and factors that impact it. Research on total carbon (TC) storage in uneven-aged pure beech stands in the western part of the Balkans was carried out in three regions located approximately at the same latitude, but different longitude, imposing different macro-habitat characteristics. This research aimed to determine the TC stock and to examine the effects of orographic factors, stand canopy, and macroclimate on its values. TC stock in forest biomass was determined using appropriate regression equations and formulas, while soil organic carbon stock was determined using ICP forests methodology. Effects of different factors on carbon stock were examined using ANOVA (Type II Sums of Squares), General Linear Hypothesis Test (GLHT), and regression analyses. It was found that the largest TC stock is located in the region of Eastern Serbia (SRB) where its macroclimate is classified as suitable for hornbeam and sessile oak or mixed beech-oak stands. It was found that anthropogenic activity plays a significant role in the size of the carbon stock stored in above-ground biomass via alteration of forest canopy. The results also indicate that Aboveground Carbon (AGC) stocks are approximately proportional to Belowground Carbon (BGC; C in belowground biomass + soil C) stocks. What makes the difference is the structure of BGC, as the share of Soil Organic Carbon (SOC) is higher in the regions of Eastern Republic of Srpska (ERS) and Western Republic of Srpska (WRS), which are climatically classified as highly suitable for beech. Further analysis has shown that the amount of SOC decreases with increasing aridity levels. Given the results, management goals should be aimed at increasing the stock of biomass for the sake of carbon sequestration and for reducing the adverse effects of climate change, as a large amount of carbon can be stored in the above-ground and belowground biomass.