Estimates Of Carbon Sequestration Research Articles

Importance, diversity and economic value of trees associated with cocoa trees in different agroforestry systems

The expansion of cocoa cultivation in Côte d'Ivoire, although crucial to the national economy, has been at the expense of forest cover, leading to massive deforestation, loss of biodiversity and degradation of essential ecosystem services. Cocoa-based agroforestry systems (SAFc), incorporating shade trees, are increasingly being promoted as a sustainable solution for reconciling agricultural productivity and environmental conservation. This study aimed to (1) characterise the floristic diversity of shade trees associated with cocoa trees in different SAFc in the Nawa region; (2) assess the structural characteristics of these trees; (3) estimate biomass and carbon sequestration of SAFc; and (4) compare the economic value of trees associated with SAFc. Sixteen (16) cocoa plantations representing four types of SAFc (full sun systems, shaded systems and two intermediate systems) were selected and floristic surveys were carried out. A total of 83 tree species in 62 genera and 32 botanical families were recorded, with higher species richness in shaded systems (52 species) and intermediate 2 (40 species). Structural analysis revealed a predominance of young trees (diameter class [10-20] cm), suggesting active regeneration. Overall, the results indicate that intermediate SAFc systems offer an optimal balance between cocoa productivity, biodiversity conservation and the provision of ecosystem services, particularly in terms of biomass accumulation and carbon sequestration. Promoting intermediate SAFc could therefore strengthen the sustainability of cocoa production in Côte d'Ivoire.

Carbon Sequestration Assessment Using Satellite Data and GIS at Chiang Mai Rajabhat University

This study conducted a project to assess carbon sequestration in the forest area of Chiang Mai Rajabhat University, Mae Rim Campus, covering a total area of approximately 5,600 rai, with about 75% consisting of dry dipterocarp forest. The Sentinel-2 satellite data from 2019 to 2023 were used to analyze and classify forest density using the Normalized Difference Vegetation Index (NDVI). It was classified into four NDVI levels: highest, high, moderate, and low. Then, eight sample plots were distributed across all density levels to collect field data on tree species, number of trees, height, and diameter. The biomass and carbon sequestration in the sample plots showed a strong correlation with vegetation density, with the highest average correlation in February, particularly on February 13, 2023, showing the highest correlation coefficient of 0.817. This relationship is described by the equation y=78.601x‒25.726, indicating that this model is effective for estimating carbon sequestration. The analysis revealed that the area with the highest NDVI level of dry dipterocarp forest had the highest above-ground carbon sequestration rate of 16.25 tons per rai, whereas the forest with the lowest NDVI level had an above-ground carbon sequestration rate of 0.21 tons per rai. In total, the above-ground carbon sequestration for the trees amounted to 50,907.35 tons. This preliminary assessment serves as a promising foundation for future efforts the conservation and restoration of the university’s forest area, contributing to sustainable strategies for mitigating global warming.

Carbon Sequestration and Landscape Influences in Urban Greenspace Coverage Variability: A High-Resolution Remote Sensing Study in Luohe, China

Urbanization has significantly altered urban landscape patterns, leading to a continuous reduction in the proportion of green spaces. As critical carbon sinks in urban carbon cycles, urban green spaces play an indispensable role in mitigating climate change. This study aims to evaluate the carbon capture and storage potential of urban green spaces in Luohe, China, and identify the landscape factors influencing carbon sequestration. The research combines on-site data collection with high-resolution remote sensing, utilizing the i-Tree Eco model to estimate carbon sequestration rates across areas with varying levels of greenery. The study reveals that the carbon sequestration capacity of urban green spaces in Luohe City is 1.30 t·C·ha−1·yr−1. Among various vegetation indices, the Enhanced Vegetation Index (EVI) explains urban green space carbon sequestration most effectively through an exponential model (R2 = 0.65, AIC = 136.5). At the city-wide scale, areas with higher greening rates, better connectivity, and more complex edge morphology exhibit superior carbon sequestration efficiency. The explanatory power of key landscape indices on carbon sequestration is 78% across the study area, with variations of 71.5%, 62%, and 84.9% for low, medium, and high greening rate areas, respectively. Moreover, when greening rates reach a certain threshold, maintaining and optimizing the quality of existing green spaces becomes more critical than simply expanding the green area. These insights provide valuable guidance for urban planners and policymakers on enhancing the ecological functions of urban green spaces during urban development.

Calculating carbon: The value of information in precision for blue carbon restoration projects

Coastal wetland restoration projects can receive payments for ecosystem services but often occur in regions with limited data, and additional data collection can be financially prohibitive. Value of Information analysis can quantify the difference between the expected value of an action before and after new information has been collected, aiming to understand how much data is required to make decisions that balance the costs of implementation versus the benefits of the project. The Australian carbon market provides a method that uses reintroduction of tidal flows to restore coastal wetland ecosystems for their carbon sequestration functions. The method requires a hydrological assessment of prospective sites, which is employed to estimate carbon sequestration potential. This research investigates how different amounts of data collection and different levels of complexity in the hydrological assessment influence the carbon abatement emissions estimated using the method. The results indicate that tidal restoration for blue carbon credits on grazing land may not be financially viable. We found that tidal data collected onsite were important for decision-making while complex hydrological models have low value compared to more simplistic approaches. While investing in data collection provides more value than increasing the complexity of modelling approaches, the value of information was still low. Additionally, restoration of coastal wetlands is unlikely to be financially attractive at current carbon prices, and the land would have to be unsuitable for cattle to become profitable for restoration. This work provides a framework for evaluating the financial benefit of collecting on-site data and using robust methods for estimating inundation, that can be used to guide decision-making to achieve optimal income.

451 Establishing producer research sites for the development of beef and bison climate-smart agriculture

Abstract Greenhouse gas (GHG) emissions and livestock production are topics that are increasingly intertwined. While livestock production is frequently presented as harmful to the environment, this perception fails to consider the carbon sequestration that takes place in livestock grazing systems and the role that grazing ruminants have in maintaining healthy grassland ecosystems. Grazing lands, which are often unsuited to row crop agriculture, are estimated to account for 25% of the global soil sequestration potential for soil carbon storage. Grazing livestock producers are often overlooked in the GHG reduction conversation, despite over 70% of beef GHG emissions being attributed to the cow-calf sector, which is primarily grazing. Furthermore, there is a relative lack of data surrounding the implementation of climate-smart agriculture practices on grazing operations and a lack of cost-effective methods to measure carbon/GHG sinks and sources on these landscapes. The potential climate benefits are considerable, with nearly 940 million acres of rangelands in the U.S. supporting forage-based livestock production. South Dakota State University recently received funding to support a large-scale climate-smart project focused on grazing beef and bison. For this project, we are utilizing the Cottonwood Field Station that has over 80 yr of historical grazing data, along with six grazing beef and bison ranching operations in the Northern Great Plains. The work on these ranches will focus on measuring and monitoring the impacts of climate-smart NRCS land practices, including cover crops, improved pasture and range seedings, prescribed grazing, and prescribed burning. A significant focus will be extensive, annual soil sampling across these operations to continuously monitor changes in soil organic carbon, bulk density, texture, pH, and soil microbiome community profiles. Each operation will have GreenFeed methane pasture units deployed for 5 yr to monitor changes in beef cattle and bison methane emissions in response to climate-smart practice adoption. We are also assessing biodiversity pre and post climate-smart practice adoption, as biodiversity improvements may be one of the most overlooked and yet most important responses to climate-smart land practice implementation. Over the duration of this project, a large-scale, comprehensive data collection will be achieved and used to refine GHG and carbon sequestration estimates associated with range livestock systems. Data resulting from this project will be used to inform research protocols and prediction models, fill knowledge gaps, and shape science-based discussions and marketing strategies for climate-smart agricultural commodities.

Improving the precision of estimating carbon sequestration potential in four tree and shrub agroforestry species through the comparison of general and specific allometric equations in Côte d’Ivoire

Improving the precision of estimating carbon sequestration potential in four tree and shrub agroforestry species through the comparison of general and specific allometric equations in Côte d’Ivoire

Looking for the ecological transition of Mediterranean small ruminant sector. Characterization and main drivers of environmental performance of the Sardinian sheep farming systems

A Life Cycle Assessment (LCA) study was carried out to assess the environmental profile of the main Sardinian dairy sheep farming systems, with the scope to provide a detailed and robust baseline for the identification of effective mitigation solutions at farm level and to develop environmental strategies at regional scale. Both product- and area-based functional units (FUs) were adopted, considering sixteen impact categories and soil carbon sequestration estimates as well. Water Use, Climate Change, Land Use, Ecotoxicity Freshwater, Marine Eutrophication and Fossils Resource Use resulted the main impact categories, cumulatively contributing over 80% of the total environmental impact (single score). Environmental performances significantly varied according to the geo-pedological traits of the different sheep milk production areas and were driven by the farming systems’ structure and production level. The group of farms located in less fertile areas showed significantly worse environmental performance per kg of normalized milk for the impact categories Climate Change and Land Use, whereas no significant differences were observed for the remaining main impact categories. Considering the area-based FU, this farm group resulted less impacting for all main categories compared to the group of farms located in more plain and productive soils, with a significantly lower impact observed for Marine Eutrophication and Fossils Resource Use. Regardless of the FU used, feed supply management represented a key area of improvement, and soil carbon sequestration impact compensated the high GHG emission intensity of grassland-based farms despite the limited nutritional value of natural pasture. Regional strategies should be based on ecosystem services optimization and eco-innovative solutions tailored according to both the specific geo-pedological conditions and the production level of each farming system.

Air quality impact of natural protected areas: A case study of Sarayiçi Tavuk Forest, Edirne, Türkiye

This study investigated the regulatory ecosystem services of Sarayiçi Tavuk Forest, a natural protected urban forest in Edirne, Turkey, with a focus on its ability to improve air quality. The i-Tree Canopy Tool was used to categorise land-cover classes within the forest and assess air quality impacts using pollutant removal and carbon sequestration estimates. The results show that the Sarayiçi Tavuk Forest eliminates 5,014.68 kg/yr of pollutants, sequesters 183,000 kg/yr of carbon, and stores a total of 4,596,680 kg of carbon throughout the lifespan of its trees. The economic value of these regulatory ecosystem services is estimated at 864,177 USD annually and substantially improves air quality. The results of this study provide valuable insights for researchers, landscape managers, and policymakers involved in regional planning, decision-making, and green space improvement in cities. This study highlights the vital role of natural protected urban forests in improving air quality and underscores the need for their preservation and integration into landscape and urban planning strategies for sustainable development in response to 21st-century challenges.

Changes in productivity partitioning induced by precipitation extremes increase inaccuracy of grassland carbon estimation.

The fraction of net primary productivity (NPP) allocated to belowground organs (fBNPP) in grasslands is a critical parameter in global carbon cycle models; moreover, understanding the effect of precipitation changes on this parameter is vital to accurately estimating carbon sequestration in grassland ecosystems. However, how fBNPP responds to temporal precipitation changes along a gradient from extreme drought to extreme wetness, remains unclear, mainly due to the lack of long-term data of belowground net primary productivity (BNPP) and the fact that most precipitation experiments did not have a gradient from extreme drought to extreme wetness. Here, by conducting both a precipitation gradient experiment (100-500 mm) and a long-term observational study (34 years) in the Inner Mongolia grassland, we showed that fBNPP decreased linearly along the precipitation gradient from extreme drought to extreme wetness due to stronger responses in aboveground NPP to drought and wet conditions than those of BNPP. Our further meta-analysis in grasslands worldwide also indicated that fBNPP increased when precipitation decreased, and the vice versa. Such a consistent pattern of fBNPP response suggests that plants increase the belowground allocation with decreasing precipitation, while increase the aboveground allocation with increasing precipitation. Thus, the linearly decreasing response pattern in fBNPP should be incorporated into models that forecast carbon sequestration in grassland ecosystems; failure to do so will lead to underestimation of the carbon stock in drought years and overestimation of the carbon stock in wet years in grasslands.

Short Communication: Estimation of aboveground biomass and carbon sequestration in KGPAA Mangkunagoro I Grand Forest Park, Central Java, Indonesia

Abstract. Indriyani S, Sari SP, Negari SIT, Prambudi SA, Nur AAI, Kusumaningrum L, Indrawan M, Sunarto, Sugiyarto, Budiharta S, Setyawan AD. 2024. Short Communication: Estimation of aboveground biomass and carbon sequestration in KGPAA Mangkunagoro I Grand Forest Park, Central Java, Indonesia. Biodiversitas 25: 2257-2263. Forests play an important role in climate change mitigation by absorbing carbon dioxide in the atmosphere and store it in the form of biomass. Valuation of carbon storage potential of a forest will provide insight on the importance of preserving it. This study aims to assess plant diversity and estimate aboveground biomass, carbon stocks, carbon dioxide sequestration potential, and the economic value of ecosystem services from carbon sequestration in KGPAA Mangkunagoro I Grand Forest Park, Central Java, Indonesia. We used a non-destructive method (i.e. allometric equation) in estimating aboveground biomass and carbon stock. We established 50 sampling plots to identify and measure trees (DBH >20 cm) and poles (10<DBH<20 cm). The results showed that there were 30 species from 20 families found in the observation plots. The potential aboveground biomass at the tree and pole level was 297.92 tons/ha and 57.22 tons/ha, respectively, while the total carbon stock for tree and pole was 140.02 tons/ha and 26.89 tons/ha, respectively. This was equivalent to carbon dioxide sequestration of 513.88 tons/ha and 98.70 tons/ha for trees and poles. The economic value of environmental services from carbon stock in the whole area of KGPAA Mangkunagoro I Grand Forest Park was estimated at IDR 21,289,040,253. The results of this research show that apart from playing a role in mitigating climate change by absorbing carbon, KGPAA Mangkunagoro I Grand Forest Park also has valuable economic value.

A new method of estimating carbon sequestration and its efficiency in coastal waters

The biological pump (BP) in oceans refers to the fraction of phytoplankton organic matter sinking out of the euphotic zone (surface layer) into below the pycnocline layer (bottom layer) in the water column. Currently, sediment traps are commonly used to estimate organic settlement and carbon sequestration in open oceans, but the installation of the sediment traps in the ocean requires special efforts, let alone the temporal and spatial discordance of particle sinking trajectory from the surface to the bottom. Net community production is used only for the euphotic zone. Thus, there has been a lack of a simple method to estimate the export flux of organic carbon from the surface to bottom layer and to quantify BP efficiency in the coastal areas. In this study, we develop a conceptual model to illustrate carbon sequestration processes from the surface to the pycnocline layer and the bottom layer. The idea is to examine an increase (the release) in dissolved inorganic carbon (DIC) and organic carbon (DOC) in the bottom layer. Based on this model, a new method was developed to estimate carbon sequestration (CS) and carbon sequestration efficiency (CSE). Two cruises in May and August in 2016 were conducted to establish a three-end-member mixing model of θ-S which is used to estimate biologically mediated DIC (ΔDIC = DICin-situ-DICmixed) in relation to the conservative mixing of DIC. Based on the density gradient threshold of 0.03 kg m-3m-1, the water column is separated into the surface mixed layer, the pycnocline layer and bottom layer and integrated ΔDIC (IntΔDIC) in the three layers are estimated. The same approach is applied to dissolved organic carbon (DOC) data which are used to make the same calculation with the mixing model to obtain the sequestrated DOC mass in the bottom layer. Carbon uptake and carbon sequestration (CS) can be calculated as the integrated ΔDIC in the surface mixed layer and bottom layers, respectively. Carbon sequestration efficiency (CSE), which is defined as sum of bottom layer Int ΔDIC + Int ΔDOC divided by the whole water column integrated ΔDIC can also be calculated. The results showed that during algal blooms driven by abundant nutrients from the Pearl River Estuarine water in May, little sinking carbon was observed due to the absence of the bottom layer, resulting in low CSE. In contrast, in August, even no significant algal bloom occurred, the strengthened water stratification, lead to a substantial increase in the CS(449.49 ± 366.14 mmol C m-2), leading to an increased CSE to a range of 0 ∼ 92.79 % (average 60.55 ± 25.07 %). The carbon sequestration rate was 55.61 ± 45.30 mg C m-2 d-1. The new method, based on vertical changes of DIC and DOC due to biological uptake or release in relation to the conservative mixing of water masses, provides an easy and direct tool to estimate carbon sequestration and carbon sequestration efficiency in the stratified water column in coastal waters.

Temperature variations impacting leaf senescence initiation pathways alter leaf fall timing patterns in northern deciduous forests

Simulating the timing of leaf fall in large scale is crucial for accurate estimation of ecosystem carbon sequestration. However, the limited understanding of leaf senescence mechanisms often impedes the accuracy of simulation and prediction. In this study, we employed the advanced process-based models to fit remote sensing-derived end dates of the growing season (EOS) across deciduous broadleaf forests in the Northern Hemisphere, and revealed the spatial pattern associated with two leaf senescence pathways (i.e., either photoperiod- or temperature- initiated leaf senescence) and their potential effects on EOS prediction. The results show that the pixel-specific optimum models effectively fitted all EOS time series. Leaf senescence in 67.6 % and 32.4 % of pixels was initiated by shortening daylength and declining temperature, respectively. Shortening daylength triggered leaf senescence occurs mainly in areas with shorter summer daylength and/or warmer autumns, whereas declining temperature induced leaf senescence appears primarily in areas with longer summer daylength and/or colder autumns. The strong dependence of leaf senescence initiation cues on local temperature conditions implies that the ongoing increase in autumn temperature has the potential to alter the leaf senescence initiation, shifting from temperature cues to photoperiod signals. This shift would occur in 26.2–49.6 % of the areas where leaf senescence is initiated by declining temperature under RCP 4.5 and 8.5 scenarios, while forest areas where leaf senescence is induced by shortening daylength may expand northward. The overall delaying of the currently predicted EOS would therefore slow down by 4.5–10.3 % under the two warming scenarios. This implies that the adaptive nature of plants will reduce the overestimation of changes in carbon exchange capacity between ecosystems and atmosphere. Our study offers novel insights into understanding the mechanism of leaf senescence and improving the estimation of autumn phenology and ecosystem carbon balance in the deciduous broadleaf forests.

Estimation of potential carbon sequestration in Thai reforestation from mining, based on the integrated spatial analysis

Mining, an activity that dates to the earliest stages of human civilization, has played a vital role in fulfilling human requirements for an extended period of time. Nevertheless, it is worth noting that this particular activity accounts for a significant proportion, ranging from 4% to 7% of the overall world greenhouse gas emissions. These emissions mostly consist of carbon dioxide, methane, and nitrogen oxides, which are released because of fuel burning, on-site energy generation, and many other sources. The mining industry, as a constituent of industrial process and product use (IPPU) sector in Thailand, makes a substantial contribution to these emissions. Thailand is now engaged in the implementation of carbon sequestration strategies, specifically focusing on the reclamation and replanting of post-mining zones. This initiative aims to tackle the various issues associated with small-scale operations within the country’s mining sector. The objective of this study is to analyse the carbon sequestration potential of Thailand’s mining area through the utilization of satellite pictures obtained from LANDSAT 8 OLI and Geographic Information System (GIS) applications. This study assesses the present carbon storage capacity, establishes the appropriate carbon pricing, and investigates the potential for reforestation in mining areas inside the nation. Based on the findings, it is evident that the northern region of Thailand has the most substantial potential for carbon sequestration, mostly due to the presence of vegetated land. Furthermore, it is projected that the overall carbon sequestration capacity in Thailand will amount to 14.68 MtCO2e in 2023 and 28.02 MtCO2e in 2030.

The dissolution of olivine added to soil at 32°C: the fate of weathering products and its implications for enhanced weathering at different temperatures

The amendment of agricultural soils by crushed silicate minerals has been proposed to enhance weathering rates and facilitate carbon dioxide (CO2) removal from the atmosphere. Laboratory dissolution experiments typically provide weathering rates that are significantly higher than those observed under natural conditions, while field studies are limited in the nature of data they can collect. This study uses an experimental setup that aims to emulate natural field conditions in a controlled setting using soil cores retrieved from UK cropland amended with crushed olivine at 32°C. Results are compared to enhanced weathering experiments run at 4°C and 19°C under otherwise identical conditions. The data reveal temperature-dependent variations in the behaviour of different elements, most importantly Mg and Si, with silicon being retained at moderate temperatures and magnesium being retained at higher temperatures. These patterns are most likely due to different retention mechanisms, notably Si reprecipitation (e.g. as cation-depleted Si-enriched mineral surface coatings) and cation exchange (affecting Mg, but to a lesser degree Si), such that the influence of cation exchange should be accounted for when interpreting enhanced weathering field data. We therefore recommend that estimates of carbon sequestration should not be based on the behaviour of individual elements. A temperature effect on the weathering rate of olivine added to soil columns is observed with the weathering rate being higher at 32°C than at 19°C and 4°C, and significantly lower than laboratory experiment-derived weathering rates. This further emphasises the need for enhanced weathering field trials, as simple laboratory-derived rates cannot be used to assess the feasibility of enhanced weathering measures. The carbon dioxide capture potential at 32°C is conservatively estimated at ~115 t CO2 km-2 yr-1 assuming an olivine amendment rate of 12.7 kg m-2. Our data suggests that soil accumulation of heavy metals like Cu and Cr at high temperatures (hence high weathering rates) is non-dangerous, however, Ni concentrations in the effluent solution are close to EU guidelines while Cr and Cu are considerably lower than guidelines. All of these conclusions have implications for the application of enhanced weathering for carbon dioxide removal from the atmosphere.

Estimating carbon sequestration potential and optimizing management strategies for Moso bamboo (Phyllostachys pubescens) forests using machine learning

Estimating the carbon sequestration potential of Moso bamboo (Phyllostachys pubescens) forests and optimizing management strategies play pivotal roles in enhancing quality and promoting sustainable development. However, there is a lack of methods to simulate changes in carbon sequestration capacity in Moso bamboo forests and to screen and optimize the best management measures based on long-term time series data from fixed-sample fine surveys. Therefore, this study utilized continuous survey data and climate data from fixed sample plots in Zhejiang Province spanning from 2004 to 2019. By comparing four different algorithms, namely random forest, support vector machine, XGBoost, and BP neural network, to construct aboveground carbon stock models for Moso bamboo forests. The ultimate goal was to identify the optimal algorithmic model. Additionally, the key driving parameters for future carbon stocks were considered and future aboveground carbon stocks were predicted in Moso bamboo forests. Then formulated an optimal management strategy based on these predictions. The results indicated that the carbon stock model constructed using the XGBoost algorithm, with an R2 of 0.9895 and root mean square error of 0.1059, achieved the best performance and was considered the optimal algorithmic model. The most influential driving parameters for vegetation carbon stocks in Moso bamboo forests were found to be mean age, mean diameter at breast height, and mean culm density. Under optimal management measures, which involve no harvesting of 1–3 du bamboo, 30% harvesting of 4 du bamboo, and 80% harvesting of bamboo aged 5 du and above. Our predictions show that aboveground carbon stocks in Moso bamboo forests in Zhejiang Province will peak at 36.25 ± 8.47 Tg C in 2046 and remain stable from 2046 to 2060. Conversely, degradation is detrimental to the long-term maintenance of carbon sequestration capacity in Moso bamboo forests, resulting in a peak aboveground carbon stock of 29.50 ± 7.49 Tg C in 2033, followed by a continuous decline. This study underscores the significant influence of estimating carbon sequestration potential and optimizing management decisions on enhancing and sustaining the carbon sequestration capacity of Moso bamboo forests.

Estimation of Corn Net Primary Productivity and Carbon Sequestration Based on the CASA Model: A Case Study of the Fen River Basin

The utilization of remote sensing technology to assess changes in crop net primary productivity (NPP), biomass, and carbon sequestration within the Fen River Basin, a crucial agricultural region in China, is important for achieving agricultural modernization, enhancing ecological environment quality, and obtaining carbon neutrality objectives. This study employed satellite remote sensing and the Carnegie–Ames–Stanford approach (CASA) model as research methods to investigate the temporal and spatial distribution characteristics of corn NPP in the Fen River Basin. Correlation analysis was conducted to examine the response of corn NPP to various environmental factors in the region, while aboveground biomass and carbon sequestration of corn were estimated using a biomass inversion model driven by NPP and principles of photosynthesis in green plants. The findings revealed that, from a temporal perspective, corn NPP in the Fen River Basin exhibited a unimodal variation pattern, with an average value of 368.65 gC/m2. Spatially, the corn NPP displayed a discernible differentiation pattern, with the highest values primarily observed in the middle reaches of the Fen River Basin. Throughout the spatial and temporal variations in corn NPP during 2011–2020, the carbon sequestration capacity of corn exhibited an upward trend, particularly since 2017. The corn NPP displayed a positive correlation with temperature and precipitation. The response to solar radiation was mildly negative and a mildly positive correlation. In 2020, the aboveground biomass and carbon sequestration of corn followed a normal distribution, with the highest values concentrated in the northwestern part of the lower Fen River.

Estimation on Individual-Level Carbon Sequestration Capacity of Understory Perennial Herbs

The carbon sequestration capacity of plants has been used as a nature-based solution to reduce carbon emissions. Perennial herbs potentially contribute to carbon sequestration by allocating carbon to belowground parts as well as trees. As individual-level estimations have mainly been carried out for tree species, individual-level carbon sequestration for understory perennial herb species is poorly understood. To estimate the below- and aboveground carbon sequestration capacity, ten perennial herb species were planted for field experiment. Individual carbon sequestration by biomass was calculated by measuring the aboveground- and estimating belowground biomass gain at harvest. We further measured non-destructive aboveground parameters, such as photosynthesis and leaf area, to estimate the belowground biomass. Four species (Aconitum jaluense Kom., Aquilegea oxysepala Trautv. & C.A.Mey., Disporum smilacinum A.Gray, and Polygonatum odoratum var. pluriflorum (Miq.) Ohwi) showed the positive belowground carbon sequestration level during the experimental period. Correlation analyses indicated that the aboveground biomass and leaf area at senescence stage could be used as non-destructive estimates of belowground carbon sequestration. The perennial herb species habitat suitability for use as additional carbon sinks in urban forests and for forest restoration should be assessed based on the increase in belowground biomass.

Coupling remote sensing and eDNA to monitor environmental impact: A pilot to quantify the environmental benefits of sustainable agriculture in the Brazilian Amazon.

Monitoring is essential to ensure that environmental goals are being achieved, including those of sustainable agriculture. Growing interest in environmental monitoring provides an opportunity to improve monitoring practices. Approaches that directly monitor land cover change and biodiversity annually by coupling the wall-to-wall coverage from remote sensing and the site-specific community composition from environmental DNA (eDNA) can provide timely, relevant results for parties interested in the success of sustainable agricultural practices. To ensure that the measured impacts are due to the environmental projects and not exogenous factors, sites where projects have been implemented should be benchmarked against counterfactuals (no project) and control (natural habitat) sites. Results can then be used to calculate diverse sets of indicators customized to monitor different projects. Here, we report on our experience developing and applying one such approach to assess the impact of shaded cocoa projects implemented by the Instituto de Manejo e Certificação Florestal e Agrícola (IMAFLORA) near São Félix do Xingu, in Pará, Brazil. We used the Continuous Degradation Detection (CODED) and LandTrendr algorithms to create a remote sensing-based assessment of forest disturbance and regeneration, estimate carbon sequestration, and changes in essential habitats. We coupled these remote sensing methods with eDNA analyses using arthropod-targeted primers by collecting soil samples from intervention and counterfactual pasture field sites and a control secondary forest. We used a custom set of indicators from the pilot application of a coupled monitoring framework called TerraBio. Our results suggest that, due to IMAFLORA's shaded cocoa projects, over 400 acres were restored in the intervention area and the community composition of arthropods in shaded cocoa is closer to second-growth forests than that of pastures. In reviewing the coupled approach, we found multiple aspects worked well, and we conclude by presenting multiple lessons learned.

Estimation of seagrass blue carbon stocks in Ahmad Rhang Manyang and Ujung Pancu Waters, Aceh Besar District

The blue carbon was concepted by the United Nations Environment Program (UNEP) in 2009, refers to the ability of marine and coastal ecosystems such as mangrove, seagrass, and tidal marshes to capture and store carbon dioxide through photosynthesis. This study aims to analyze the estimation of seagrass blue carbon stock and sequestration in Ahmad Rhang Manyang and Ujung Pancu. Data were collected using the plot transect method to assess cover, density, biomass and use model calculations called Seagrass Carbon Converter (SCC) to assess seagrass carbon stocks. Three species of seagrass were found at four research stations are Halodule pinifolia, Halophila ovalis, Halophila minor. The result showed that seagrass cover in Ahmad Rhang Manyang waters was 27.95% in the poor category and in Ujung Pancu waters was 39.4% in the medium category.. The seagrass carbon stock in Ahmad Rhang Manyang 123.93 gram C/m2 and in Ujung Pancu was 231.43 gram C/m2. The seagrass carbon absorption value in Ahmad Rhang Manyang was 4.16 TC/Ha/year (tons of carbon per hectare per year) and Ujung Pancu is 15.5 TC/Ha/year.

Differences in organic carbon accumulation in mangrove soils due to foraging by herbivorous crabs

Crabs in mangroves could enhance the transfer of organic carbon (OC) from leaf litter to soils, whose variation with the difference in crab size is, however, not well known. A 32-day laboratory feeding experiment was conducted to explore the effects of different sizes of the crabs Parasesarma plicatum foraging on leaf litter of Kandelia obovata on OC accumulation in mangrove soils. Mean rates of soil OC accumulation due to leaf foraging by large, medium, and small crabs were 21.11, 16.11, and 0.77 mg C ind−1 d−1, corresponding to the rates of OC removal from leaf litter of 62.60%, 51.37%, and 2.19%, respectively. Large and medium crabs ingested larger amounts of leaf litter, and soil OC accumulation rates resulting from leaf foraging by large and medium crabs were approximately 8 times higher than those by leaf litter decomposition and triple those by non-leaf foraging. Small crabs ingested the smallest amount of leaf litter, which was almost used for their growth and metabolism. These results underline the key ecological roles of leaf foraging by crabs, especially those with large and medium sizes, in OC accumulation in mangrove soils, which is conducive to estimating carbon sequestration in mangrove soils.