Estimates Of Soil Carbon Stocks Research Articles

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.

Statistical Estimation of Soil Carbon Stocks in Chungcheong Province through Digital Soil Mapping and Multiple Linear Regression

Statistical Estimation of Soil Carbon Stocks in Chungcheong Province through Digital Soil Mapping and Multiple Linear Regression

Multi-scale mapping of Australia’s terrestrial and blue carbon stocks and their continental and bioregional drivers

The soil in terrestrial and coastal blue carbon ecosystems is an important carbon sink. National carbon inventories require accurate assessments of soil carbon in these ecosystems to aid conservation, preservation, and nature-based climate change mitigation strategies. Here we harmonise measurements from Australia’s terrestrial and blue carbon ecosystems and apply multi-scale machine learning to derive spatially explicit estimates of soil carbon stocks and the environmental drivers of variation. We find that climate and vegetation are the primary drivers of variation at the continental scale, while ecosystem type, terrain, clay content, mineralogy and nutrients drive subregional variations. We estimate that in the top 0–30 cm soil layer, terrestrial ecosystems hold 27.6 Gt (19.6–39.0 Gt), and blue carbon ecosystems 0.35 Gt (0.20–0.62 Gt). Tall open eucalypt and mangrove forests have the largest soil carbon content by area, while eucalypt woodlands and hummock grasslands have the largest total carbon stock due to the vast areas they occupy. Our findings suggest these are essential ecosystems for conservation, preservation, emissions avoidance, and climate change mitigation because of the additional co-benefits they provide.

Enabling soil carbon farming: presentation of a robust, affordable, and scalable method for soil carbon stock assessment

The main hurdle in instrumentalizing agricultural soils to sequester atmospheric carbon is the development of methods to measure soil carbon stocks which are robust, scalable, and widely applicable. Our objective is to develop an approach that can help overcome these hurdles. In this paper, we present the Wageningen Soil Carbon STOck pRotocol (SoilCASTOR). SoilCASTOR uses a novel approach fusing satellite data, direct proximal sensing-based soil measurements, and machine learning to yield soil carbon stock estimates. The method has been tested and applied in the USA on fields with agricultural land use. Results show that the estimates are precise and repeatable and that the approach could be rapidly scalable. The precision of farm C stocks is below 5% enabling detection of soil organic carbon changes desired for the 4 per 1000 initiative. The assessment can be done robustly with as few as 0.5 sample per hectare for farms varying from 20 to 150 hectares. These findings could enable the structural implementation of carbon farming.

Going Local: How Coastal Environmental Settings Can Help Improve Global Mangrove Carbon Storage and Flux Estimates

AbstractThe magnitude and variability of mangrove carbon storage are uncertain and still being discussed. In a recent article, Breithaupt and Steinmuller (2022, https://doi.org/10.1029/2022GL100177) completed a literature review and compared mangrove organic carbon burial rates between different coastal environmental settings (CES) that integrate sedimentary supply (terrigenous vs. carbonate) and hydrogeomorphic settings (delta, estuary, lagoon, open coast). They found greater burial rates in terrigenous delta and estuaries while lower rates were reported in lagoons and carbonate settings. Surprisingly, these CES relationships do not strictly match previous mangrove soil carbon stock estimates but were consistent with biomass stocks. The CES approach used by Breithaupt and Steinmuller should be used for other mangrove carbon stocks and fluxes estimates to refine our understanding of mangrove carbon cycling and storage.

НЕУЧТЕННЫЕ ФАКТОРЫ, ОПРЕДЕЛЯЮЩИЕ ЗАПАСЫ УГЛЕРОДА В ЛЕСНЫХ ПОЧВАХ

The sources of uncertainties in estimating soil carbon stocks in forest ecosystems, including abiotic (mechanical composition of soil) and biotic (plants, earthworms) factors, are discussed. The results of comparative assessment of soil carbon storage in coniferous-broadleaved and taiga forests based on direct measurements and pedotransfer functions are presented. It is shown that the estimation of soil carbon stocks in forests based on both direct measurements and pedotransfer functions requires, along with other soil formation factors, taking into account the most dynamic ones, including plants and soil biota, as well as the history of nature management. The calculation of soil carbon stocks should be carried out with account of fine earth (<2 mm fraction) content.

Different climate sensitivity of particulate and mineral-associated soil organic matter

Soil carbon sequestration is seen as an effective means to draw down atmospheric CO2, but at the same time warming may accelerate the loss of extant soil carbon, so an accurate estimation of soil carbon stocks and their vulnerability to climate change is required. Here we demonstrate how separating soil carbon into particulate and mineral-associated organic matter (POM and MAOM, respectively) aids in the understanding of its vulnerability to climate change and identification of carbon sequestration strategies. By coupling European-wide databases with soil organic matter physical fractionation, we assessed the current geographical distribution of mineral topsoil carbon in POM and MAOM by land cover using a machine-learning approach. Further, using observed climate relationships, we projected the vulnerability of carbon in POM and MAOM to future climate change. Arable and coniferous forest soils contain the largest and most vulnerable carbon stocks when cumulated at the European scale. Although we show a lower carbon loss from mineral topsoils with climate change (2.5 ± 1.2 PgC by 2080) than those in some previous predictions, we urge the implementation of coniferous forest management practices that increase plant inputs to soils to offset POM losses, and the adoption of best management practices to avert the loss of and to build up both POM and MAOM in arable soils. Particulate and mineral-associated soil organic carbon have different climate sensitivity and distributions in Europe, according to analyses of measurements of soil carbon fractions from 352 topsoils.

Estimation of Soil Carbon Stocks of Urban Freshwater Wetlands in the Colombo Ramsar Wetland City and their Potential Role in Climate Change Mitigation

Wetlands hold significant potential for climate change mitigation due to their high capacity to sequester atmospheric carbon dioxide (CO2). Colombo, Sri Lanka was recently declared as one of the eighteen global Ramsar wetland cities. The current study represents the first attempt to quantify soil organic carbon (SOC) stocks held by the urban freshwater wetlands in Colombo. The study focused on the extensive urban wetland ecosystems of Kolonnawa wetland and Thalawathugoda wetland park. SOC stocks were determined using three parameters: depth of soil, bulk density, and SOC concentration. Loss on ignition method was used in quantifying SOC concentrations. Average SOC stocks, up to a depth of 60 cm at Kolonnawa wetland and Thalawathugoda wetland park were estimated at 504 ± 14 t C/ha and 550 ± 23 t C/ha, respectively. Furthermore, the total SOC stock at Kolonnawa wetland and Thalawathugoda wetland park were estimated at 198,408 ± 5564 t CO2eq and 66,313 ± 2764 t CO2eq, respectively. When considering global estimates, it was found that freshwater wetlands in Colombo hold a higher SOC stock than tropical wet forests and tropical dry forests. The current study highlights the importance of urban ecosystems in mitigating the ever increasing concentrations of atmospheric CO2 .

Field scale estimates of soil carbon stocks on ten heavy textured farms across Ireland

The world's soils store vast amounts (≈2,500 GT) of Carbon which acts as a vital sink to counterbalance the effects of increasing atmospheric carbon dioxide. There have been fruitful efforts to quantify soil Carbon stocks at national scales, which are required for policy level decisions but lack the high resolution required to support farm specific decisions. It is hypothesised that farm scale evaluations of soils can provide insight that is masked in national scale studies and can allow for spatially explicit management approaches to optimise soil Carbon storage and sequestration, such that it can be prioritized within profitable production systems. The objective of the present study was to estimate Carbon stocks on a range of heavy textured soils at field and farm scale and to quantify Carbon storage relative to national scale estimates. Ten grassland dairy farms (mean area of 52.2 Ha) were surveyed, sampled and classified to determine soil types and quantify soil Carbon stores. The level of Carbon present (mean: 346.0 T/Ha) at these sites was greater than previous averages on such soils quantified at national scale (by a factor of 1.1–3.9 depending on soil type). Furthermore, if Carbon saturation potential was realised, the amount of Carbon stored could be increased by an average of 792.1 T/Ha in each profile (from 346.0 to 1138.1 T/Ha). Current management has fostered the retention of large stores of soil Carbon on such soils/farms which co-exist within highly productive farm systems. As there is a societal demand to retain and enhance soil carbon stores to mitigate climate change, high Carbon soils should be identified and, under appropriate policies, commodified to offer a direct incentive to retain soil Carbon. The value of this resource should be recognised and polices to ensure a spatially explicit approach for soil Carbon management should be adopted.

Comparison With Global Soil Radiocarbon Observations Indicates Needed Carbon Cycle Improvements in the E3SM Land Model

AbstractWe evaluated global soil organic carbon (SOC) stocks and turnover time predictions from a global land model (ELMv1‐ECA) integrated in an Earth System Model (E3SM) by comparing them with observed soil bulk and Δ14C values around the world. We analyzed observed and simulated SOC stocks and Δ14C values using machine learning methods at the Earth System Model grid cell scale (~200 km). In grid cells with sufficient observations, the model provided reasonable estimates of soil carbon stocks across soil depth and Δ14C values near the surface but underestimated Δ14C at depth. Among many explanatory variables, soil albedo index, soil order, plant function type, air temperature, and SOC content were major factors affecting predicted SOC Δ14C values. The influences of soil albedo index, soil order, and air temperature were primarily important in the shallow subsurface (≤30 cm). We also performed sensitivity studies using different vertical root distributions and decomposition turnover times and compared to observed SOC stock and Δ14C profiles. The analyses support the role of vegetation in affecting soil carbon turnover, particularly in deep soil, possibly through supplying fresh carbon and degrading physical‐chemical protection of SOC via root activities. Allowing for grid cell‐specific rooting and decomposition rates substantially reduced discrepancies between observed and predicted Δ14C values and SOC content. Our results highlight the need for more explicit representation of roots, microbes, and soil physical protection in land models.

Lithology and coarse fraction adjusted bulk density estimates for determining total organic carbon stocks in dryland soils

Pedotransfer functions (PTFs) have been developed to estimate soil fine fraction bulk density (BDFF) using the relationships with soil organic carbon content (SOC) and particle size distribution. Current PTF's overlook the influence of lithology on BDFF estimations. In this study, we examine this influence by developing two PTF's for total bulk density (BDT), which includes both fine (FF) and coarse fragments (CF), using measured percent SOC in soils derived from felsic and mafic lithologies (90 felsic and 52 mafic, 142 total). Our results show that SOC is highly correlated with BDT in soils derived from felsic (R2 value of 0.79, p < 0.0001) and mafic (R2 value of 0.84, p < 0.0001) material and that the relationships for these two lithologies are highly distinctive. In addition, we adjust estimated BDT with soil pedon CF content (>2 mm) to determine estimated BDFF. We use an independently collected validation subset of 70 samples to compare our model against 23 published PTFs. When accounting for lithological differences in BDT and adjusting for site-specific CF content, which is highly variable vertically and horizontally within the watershed, we observe substantial improvements (average of 10.05 ± 4.89%) in BDFF estimation and associated errors compared to other PTFs. Findings from our study demonstrate that incorporating both lithology and CF content into site-specific empirical relationships can provide reliable BDFF and consequently soil carbon stock estimates.

Landscape variation in soil carbon stocks and respiration in an Arctic tundra ecosystem, west Greenland

ABSTRACT The magnitude and acceleration of carbon dioxide emissions from warming Arctic tundra soil is an important part of the Region’s influence on the Earth’s climate system. We investigated the links between soil carbon stocks, soil organic matter decomposition, vegetation heterogeneity, temperature, and environmental sensitivities in dwarf shrub tundra near Kangerlussuaq, Greenland. We quantified carbon stocks of forty-two soil profiles using bulk density estimates based on previous studies in the region. The soil profiles were located within six vegetation types at nine study sites, distributed across an environmental gradient. We also monitored air and soil temperature and measured in situ soil respiration to quantify variation in carbon flux between vegetation types. For spatial extrapolation, we created a high-resolution land cover classification map of the study area. Aside from a single soil profile taken from a fen soil (54.55 kg C m−2; 2.13 kg N m−2), the highest carbon stocks were found in wet grassland soils (mean, 95% CI: 34.87 kg C m−2, [27.30, 44.55]). These same grassland soils also had the highest mid-growing-season soil respiration rates. Our estimation of soil carbon stocks and mid-growing-season soil respiration measurements indicate that grassland soils are a “hot spot” for soil carbon storage and soil carbon dioxide efflux. Even though shrub, steppe, and mixed vegetation had lower average soil carbon stocks (14.66 – 20.17 kg C m−2), these vegetation types played an important role in carbon cycling at the landscape scale because they cover approximately 50 percent of the terrestrial landscape and store approximately 68 percent of the landscape soil organic carbon. The heterogeneous soil carbon stocks in this landscape may be sensitive to key environmental changes, such as shrub expansion and climate change. These environmental drivers could possibly result in a trend toward decreased soil carbon storage and increased release of greenhouse gases into the atmosphere.

Large Differences in Global and Regional Total Soil Carbon Stock Estimates Based on SoilGrids, HWSD, and NCSCD: Intercomparison and Evaluation Based on Field Data From USA, England, Wales, and France

AbstractSoils are the major component of the terrestrial ecosystem and the largest organic carbon reservoir on Earth. However, they are a nonrenewable natural resource and especially reactive to human disturbance and climate change. Despite its importance, soil carbon dynamics is an important source of uncertainty for future climate predictions and there is a growing need for more precise information to better understand the mechanisms controlling soil carbon dynamics and better constrain Earth system models. The aim of our work is to compare soil organic carbon stocks given by different global and regional databases that already exist. We calculated global and regional soil carbon stocks at 1 m depth given by three existing databases (SoilGrids, the Harmonized World Soil Database, and the Northern Circumpolar Soil Carbon Database). We observed that total stocks predicted by each product differ greatly: it is estimated to be around 3,400 Pg by SoilGrids and is about 2,500 Pg according to Harmonized World Soil Database. This difference is marked in particular for boreal regions where differences can be related to high disparities in soil organic carbon concentration. Differences in other regions are more limited and may be related to differences in bulk density estimates. Finally, evaluation of the three data sets versus ground truth data shows that (i) there is a significant difference in spatial patterns between ground truth data and compared data sets and that (ii) data sets underestimate by more than 40% the soil organic carbon stock compared to field data.

Carbon storage in US wetlands.

Wetland soils contain some of the highest stores of soil carbon in the biosphere. However, there is little understanding of the quantity and distribution of carbon stored in our remaining wetlands or of the potential effects of human disturbance on these stocks. Here we use field data from the 2011 National Wetland Condition Assessment to provide unbiased estimates of soil carbon stocks for wetlands at regional and national scales. We find that wetlands in the conterminous United States store a total of 11.52 PgC, much of which is within soils deeper than 30 cm. Freshwater inland wetlands, in part due to their substantial areal extent, hold nearly ten-fold more carbon than tidal saltwater sites—indicating their importance in regional carbon storage. Our data suggest a possible relationship between carbon stocks and anthropogenic disturbance. These data highlight the need to protect wetlands to mitigate the risk of avoidable contributions to climate change.

Forest soil carbon stock estimates in a nationwide inventory: evaluating performance of the ROMULv and Yasso07 models in Finland

Abstract. Dynamic soil models are needed for estimating impact of weather and climate change on soil carbon stocks and fluxes. Here, we evaluate performance of Yasso07 and ROMULv models against forest soil carbon stock measurements. More specifically, we ask if litter quantity, litter quality and weather data are sufficient drivers for soil carbon stock estimation. We also test whether inclusion of soil water holding capacity improves reliability of modelled soil carbon stock estimates. Litter input of trees was estimated from stem volume maps provided by the National Forest Inventory, while understorey vegetation was estimated using new biomass models. The litter production rates of trees were based on earlier research, while for understorey biomass they were estimated from measured data. We applied Yasso07 and ROMULv models across Finland and ran those models into steady state; thereafter, measured soil carbon stocks were compared with model estimates. We found that the role of understorey litter input was underestimated when the Yasso07 model was parameterised, especially in northern Finland. We also found that the inclusion of soil water holding capacity in the ROMULv model improved predictions, especially in southern Finland. Our simulations and measurements show that models using only litter quality, litter quantity and weather data underestimate soil carbon stock in southern Finland, and this underestimation is due to omission of the impact of droughts to the decomposition of organic layers. Our results also imply that the ecosystem modelling community and greenhouse gas inventories should improve understorey litter estimation in the northern latitudes.

Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching

Abstract. Croplands are vital ecosystems for human well-being and provide important ecosystem services such as crop yields, retention of nitrogen and carbon storage. On large (regional to global)-scale levels, assessment of how these different services will vary in space and time, especially in response to cropland management, are scarce. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land-use-enabled dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator). Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land-use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. Our model experiments allow us to investigate trade-offs between these ecosystem services that can be provided from agricultural fields. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP (Representative Concentration Pathway) 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till management and cover crops proposed in previous studies is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C–N interactions in agricultural ecosystems under future environmental change and the effects these have on terrestrial biogeochemical cycles.

Permafrost Carbon: What soil science has to say about its distribution and fate

Permafrost Carbon: What soil science has to say about its distribution and fate

Neoformation of pedogenic carbonates by irrigation and fertilization and their contribution to carbon sequestration in soil

The impact of land use change and farming management on soil organic carbon (SOC) and soil inorganic carbon (SIC), particularly pedogenic carbonates (PC), was assessed in a semi-humid region of China. The SOC and SIC content and stocks were measured, and δ13C values were used to calculate the percentage of PC and lithogenic carbonates (LC) in the total SIC. Over the 39-year period, organic fertilizers at high and low rates (OFH and OFL), mineral fertilizers (MF), and a control site without fertilizers (CK) showed an increase of PC compared to a natural fallow plot (F). The main pathway of SIC accumulation was the neoformation of pedo-atmogenic carbonates contributing to C sequestration of at least 0.38, 0.27, 0.23, and 0.12MgCha−1yr−1 for the OFH, OFL, MF, and CK treatments, respectively. The LC stock remained similar in all treatments except for the CK, where LC was significantly lower than all of the other treatments which suggested dissolution. An increase in OC stocks in response to organic fertilization was not limited to the surface soil, but it continued down the soil profile to a depth of 160cm. The maximum potential for neoformation of PC depends on Ca2+ and Mg2+ availability; in this study these cations were provided by irrigation water. However, organic and mineral fertilizers modify this potential. Without organic and mineral fertilization, the PC formed at the expense of dissolution and re-precipitation of LC, even when substantial quantities of Ca2+ and Mg2+ were present in the soil. Our experimental results indicate that the neoformation of PC should be considered during estimation of soil carbon stocks and sequestration for the development of optimal fertilization, irrigation and land use practices.13

Estimation of soil carbon stocks in Pabitora Sanctuary and Manas National Park in Assam

North East India known for its rich flora and fauna, is covered by the mighty Brahmaputra-Barak river systems and their tributaries and comprises hilly terrain interspersed with valleys and plains. A field study was done to layout the soil carbon stock of Pabitora Wildlife Sanctuary and Manas National Park in Assam. Maximum average carbon stock in both was estimated in the upper layer of the soil sample, while least carbon stock was obtained at deepest layer (20-30 cm). The average carbon stock of the Manas National Park was higher than that of Pabitora Wildlife Sanctuary.

Towards cost-effective estimation of soil carbon stocks at the field scale

Accurate estimates of soil carbon stocks at the field scale are required to run market-based instruments for soil carbon, but the soil measurements required to make these estimates are expensive. Therefore, efficient sample designs are required. We explored the costs associated with estimating the mean soil carbon stocks within a 68-ha field on the old alluvial soils of the Macquarie River in central-west New South Wales (Red Chromosols or Red Luvisols). The sampling required to achieve a particular degree of accuracy depends upon the variability of soil carbon within the field. We conducted a 100-site geostatistical survey to estimate the variogram of soil carbon. We then used this variogram to consider the efficiency with which simple random and stratified sample designs can achieve a standard error &lt;2 t/ha for the mean carbon stock to 30 cm. The stratifications considered were either purely spatial or based upon auxiliary information such as landform or sensor data. The effectiveness of localised clustering or quadrats within designs was also considered. Formulae were devised to determine the costs of implementing the different designs, based upon our experience from conducting the geostatistical survey. Only weak correlations between carbon stocks and the auxiliary information were evident, and hence the stratifications were largely ineffective. Some benefits of using quadrats were evident, since analytical and field survey costs were reduced. However, the cost (AU$2500) required to achieve the target accuracy is still considerable. The sampled field has complex pedology, and we therefore expect that these costs are larger than average. Similar studies are required to calculate sampling requirements in different locations and to determine whether these requirements can be related to factors such as soil type, parent material, or land management history.