Estimates Of Carbon Sequestration Research Articles

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.

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.

The importance of terrestrial carbon sequestration during Termination 1

ABSTRACTDuring the transition from the Last Glacial Maximum (LGM) to the Holocene, terrestrial carbon sequestration occurred primarily in boreal forests and forest soils largely on landscapes that had been covered by ice sheets. Major processes operating during this period included radiative warming from rising concentrations of atmospheric CO2 (degassing oceans and oxidation of permafrost); increased seasonal warming associated with axial precession; melting of alpine glaciers and ice sheets; exposure of new land surfaces; and sequestration of carbon in expanding terrestrial vegetation and soils. We examine mechanisms of warming that melted glacial ice; temporal and spatial availability of newly exposed landscapes; rates at which plant colonization and soil development occurred; estimates of terrestrial carbon sequestration; and how those processes interacted with one another. Data from the West Antarctic Ice Sheet Divide ice core show that from 18 to 11 cal ka bp the concentration of atmospheric CO2 rose by ≈80 ppmv (≈170 Gt C); published estimates of net terrestrial carbon sequestration (following photosynthesis) are considerably higher (450–1250 Gt C). Thus, accumulation of carbon in terrestrial vegetation and soils played an important role in modulating atmospheric CO2 and, indirectly, Earth's climate during Termination 1, and possibly during earlier Quaternary ice ages.

Estimation of aboveground biomass and carbon stocks of Quercus ilex L. saplings using UAV-derived RGB imagery

Key messageCrown area, sapling height, and biovolume extracted from UAV-acquired RGB images provided accurate estimates of aboveground biomass and carbon stocks in a 5-year-old holm oak (Quercus ilex L.) plantation. Our models regressing UAV-derived sapling variables against ground-based measurements exhibited high R2 values (0.78–0.89), thereby reflecting that RGB data can be used as an effective tool for measuring young individuals.ContextThe monitoring of tree sapling performance from the early stages of reforestation is of particular importance in the context of the global efforts to restore forests. Yet, most models to estimate carbon sequestration are developed for adult trees. Thus, the few models specifically developed for young trees rely on ground-based field sampling of tree growth parameters, which is time-consuming and difficult to implement at large spatial scales.AimsOur objectives were as follows: (1) to study the potential of UAV-based RGB imagery to detect and extract sapling variables (e.g., crown area, height, and biovolume) by comparing ground-based sapling measurements with UAV-derived data and (2) to compare the accuracy of the data estimated from RGB imagery with existing traditional field-based allometric equations.MethodsWe used a 5-year-old holm oak (Quercus ilex L. subsp. ballota (Desf.) Samp.) plantation (N = 617 plants), and their crown area, height, and biovolume were estimated from RGB imagery. Subsequently, the plants were harvested and the UAV-derived data were compared with field-measured sapling height and aboveground biomass values. Carbon content in leaves and stems was measured in a subsample of the saplings to estimate carbon stocks.ResultsThe models fitted with UAV-derived variables displayed high performance, with R2 values from 0.78 to 0.89 for height, leaf and stem biomass, total aboveground biomass, and carbon stocks. Moreover, aboveground biomass outputs calculated with field height and UAV-derived height using allometric equations exhibited R2 values from 0.65 to 0.68.ConclusionsGiven the affordable cost of RGB cameras and the versatility of drones, we suggest that UAV-based models may be a cost-effective method to estimate the biomass and carbon stocks of young plantations. However, further studies conducting drone flights in different conditions are needed to make this approach more scalable.

Estimation and simulation of carbon sequestration in typical dryland areas of China under future climate change scenarios

Climate anomalies and human disturbances exert complex effects on regional carbon sequestration (CS), causing ecosystem CS to either increase or decrease due to factors such as vegetation greening, climate extremes, land use/land cover (LULC) changes, and farming systems. This study employs the patch-level land use simulation model to forecast changes in various land-use types in the Xinjiang Uyghur Autonomous Region, China, between 2020 and 2060 under different climatic conditions. The Intergovernmental Panel on Climate Change has proposed shared socioeconomic pathways (SSPs) as potential socioeconomic and environmental trajectories that might influence the region’s future land-use patterns. Three salient findings emerged: (1) LULC displayed considerable variation across future climate scenarios, with a notable rise in forest and grassland cover and a marked decrease in cropland areas under the SSP126 scenario. Conversely, the SSP585 scenario witnessed a substantial cropland expansion, paralleled by a decrease in forest and grassland areas; (2) CS exhibited significant disparities across different future climate scenarios. Xinjiang achieved a peak CS of 9.81 Pg between 2020 and 2060 under the SSP126 scenario, marking an increase of 335.22 Tg in 2060 compared to that in 2020. The SSP585 scenario registered the lowest CS at 9.41 Pg, indicating a decline of 50.07 Tg in 2060 relative to 2020; (3) The impacts of longitude and latitude on CS in Xinjiang predominantly arose from shifts in forest area and vegetation cover based on latitude, which positively influenced CS. In contrast, a decrease in vegetation cover and a subsequent decline in CS were evident with increasing longitude, particularly in the Altai, Tianshan, and Kunlun Mountains. These findings hold significant implications for formulating CS management strategies for terrestrial ecosystems and enhancing ecological preservation in Xinjiang.

Sensationalized soil carbon sequestration estimates excuse further climate inaction.

Sensationalized soil carbon sequestration estimates excuse further climate inaction.

Biomass production, carbon stock and sequestration potential of prominent agroforestry systems in north-western Himalaya, India

Agroforestry is an age-old practise of integrating farming with practises, preferably on the same unit of land on sustainable basis. There is tremendous scope for Agroforestry because India has achieved self-sufficiency in food production. Now its attention is becoming more focused on the ecological problems and shortage of fuel, fodder and other outputs as well as unemployment. So, agroforestry land use systems offer a better option by serving as carbon sinks and contributing in attaining food safety, subsistence income, and habitat amelioration. The current study was conducted in this context in the south Kashmir area of India with the objective of recognising the capability of various agroforestry systems for biomass estimation and carbon sequestration assessment for mitigating climate variation. The present study entitled “Biomass production, carbon stock and sequestration potential of prominent agroforestry systems in North-western Himalaya, India” was carried out, during 2018–2019. The study site is located between 33° 72’N and 75° 14’E at an altitude ranging from 2,900 to 5,900 M (amsl). Multistage random sampling technique was used for selection of sampled tehsils, blocks, villages and farmers in Anantnag district. The first stage was the random sampling of six tehsils namely Anantnag, Shangus, Kokernag, Dooru, Sallar, and Larnu and blocks per tehsil namely, viz.; Anantnag, Shangus, Sagam, Shahabad, Pahalgam and Larnu. Then four villages within each block like Anantnag (Ruhoo, Dialgam, Wanihama and Donipawa), Shangus (Shangus, Nowgam, Kutheir and Andoora), Sagam (Hiller, Khalhar, Sagam and Bidder), Shahabad (Larkipora, Shankerpora, Nathipora and Bragam), Pahalgam (Yanner, Charigam, Movra and Wahdan) and Larnu (Leesu, Dandipora, Bidhard and Larnu). Ten farmers within each village were selected, thus making a total of 240 farmers, which accounts 25% sampling intensity. Four agroforestry systems including horti-agriculture, agrisilviculture, (boundary planting), agri-horti-silviculture and horti-silvipasture were chosen for the study as the experimental configuration. Maximum biomass was found in horti-silvipastoral contributing 66.55 t ha−1 followed by agri-horti-silviculture as 50.18 t ha−1, horti-agriculture as 36.22 t ha−1 and agri-silviculture as 34.87 t ha−1. The maximum mean biomass of fruit trees (30.54 t ha−1), forest trees (25.19 t ha−1), grass (7.18 t ha−1) during the first cut and 3.64 t ha−1 during the second cut, was calculated in horti-silvipasture system. The overall biomass output of diverse agroforestry systems goes along with the sequence: horti-silvipasture > agri-horti-silviculture > horti-agriculture > boundary plantation, respectively. As a result, estimates of carbon stocks and carbon sequestration for all systems showed the same trend as values for biomass since they are both directly related to the capacity for biomass generation of various plant components. By providing for rural livelihoods and serving as an efficient carbon sink through carbon sequestration, these agroforestry systems in the Himalayas can significantly increase total production and productivity. The results of the current study could have a big impact on how alternative agroforestry systems and tree combinations are chosen for efficient carbon budget management in delicate Himalayan ecosystems.

Carbon Sequestration Assessment in Kazakhstan’s Forests: Analytical Review

Climate change processes are occurring on a global scale, accompanied by the emission of substantial greenhouse gas quantities into the atmosphere, with carbon monoxide and dioxide as their predominant components. The analytical review presents the results of assessing the current state of existing research on carbon sequestration in forests. Forest ecosystems play a crucial role in climate change mitigation by absorbing substantial amounts of carbon dioxide from the atmosphere, making woodlands the most important carbon sink. Forest biomass and productivity determine the level of carbon accumulation in forest ecosystems. The methods for estimating carbon sequestration are based on various models such as InVEST, CO2FIX, CBM-CFS3, etc. It has been observed that forests accumulate, absorb, and emit carbon dioxide, constituting a trifecta in climate change dynamics. The limited research on carbon sequestration by forests in Kazakhstan substantiates further targeted scientific investigation. The recommendations for enhancing the carbon sequestration potential of domestic woodlands include afforestation and commercial forestry. Progress in these sectors will not only improve the efficiency but also foster the sustainable development of forest resources as a means of climate change adaptation.

USING REMOTE SENSING TO DETECT FOREST COVER CHANGE IN SAM HOUSTON NATIONAL FOREST, TEXAS

Abstract. The Sam Houston National Forest is a large, forested area in Texas that has experienced significant land-use changes over the past few decades. The study area replicates plentiful climatic, physiographic, and edaphic differences in the country and this forest faces a serious problem of degradation and disturbance of different nature. In this study, we utilized remote sensing technology specifically Landsat 4 ETM and Landsat 8 from USGS Earth Explorer with spatial resolution 30 m, to analyze forest cover change in Sam Houston National Forest from 2001 to 2020. We also employed the Hansen Global Forest Cover Data from the Google Earth Engine Catalogue to assess the forest cover loss and gain within the study period. Also, the i-Tree software was used to estimate carbon sequestration in the forest and assess the potential benefits of forest management practices. Results of the study showed that the Sam Houston National Forest has experienced a net loss of forest cover over the past few decades, primarily due to agricultural expansion and urbanization. However, the forest has also shown signs of regrowth and recovery in certain areas, highlighting the potential for effective forest management practices to promote carbon sequestration and conservation. Overall, our study highlights the importance of remote sensing technology for understanding forest cover change and its implications for carbon sequestration and climate change mitigation.

Environmental Consequences of Intensive Aquaculture Practices at Moyna Purba Medinipur West Bengal India with Special Reference to Carbon Footprint and Carbon Sequestration.

Moyna of Purba Medinipur district is widely known as an aquaculture hub of West Bengal, India. Though very good production is achievable from this fish culture system, management practices are inappropriate, which could create the sustainability problem of this culture system. The present study was thus undertaken for the estimation of plankton population, water quality, carbon footprint and carbon sequestration of this intensive aquaculture practices. Information on spawn to fry, fry to fingerlings and grow-out culture were collected through the structured questionnaire from the fish farmers. The plankton density, primary productivity, carbon footprint and carbon sequestration were analyzed using standard procedures. The phytoplankton, zooplankton and primary productivity were maximum at the stocking period and minimum during the middle of culture period. The lowest feed conversion ratio (FCR) was noticed with the minimum amount of feed applied in the pond. The CO2-e emission ranged from 0.56 to 4.89kg CO2-e/kg fish (av. 2.13) for the production levels of 5.0 to 10.7 t/ha/yr. The pond water developed salinity and ammonium-N increased from 0.01 to 0.50mg/l. The ponds with high feed loading (28 to 32 t/ha/yr) had the highest average sediment accumulation rate (11.0 ± 3.0cm/yr) and carbon sequestration (704 ± 30g C/m2/yr).

Regionalized life cycle inventory data collection and calculation for perennial forage production in Canada: methodological best practices and limitations

Abstract Purpose In Canada, 95–99% of produced forages are consumed domestically each year, mainly by beef cattle. Despite their importance, their contribution to the Canadian livestock industry and associated ecosystem services has not been investigated. This study developed a life cycle inventory (LCI) of perennial forage production in Canada averaged from 2009 to 2018. Methods LCI data were sourced or calculated from up-to-date, regionally resolved sources and models. Inputs to perennial forage production included the following: concrete, steel, and plastic usage; machinery fuel consumption; electricity, natural gas, and water use for irrigation; and synthetic and organic fertilizer, lime, and herbicide use. Assessed emissions included ammonia and nitrous oxide (N2O); carbon dioxide from energy use; herbicide, nitrate, and phosphate losses; and soil carbon accumulation. Results were expressed per metric tonne of harvested perennial forage dry matter at provincial and regional scales—Western Canada [British Columbia (BC), Alberta (AB), Saskatchewan (SK), Manitoba (MB)] and Eastern Canada [Ontario (ON), Québec (QC)]. Results and discussion Rates of inputs varied, with generally lower nutrient but higher herbicide application in West vs. East. Irrigation was highest in BC, followed by AB and SK; energy consumption was highest in BC and lowest in QC. Higher N2O losses and nutrient losses via leaching and runoff in the East were partially due to greater soil moisture. Although total harvested perennial forage area declined from 6.43 to 5.23 million hectares from 2009 to 2018, these lands continued to accumulate soil carbon. The time period used to calculate average yields affected LCI estimates, as prairie yields were lower 1994–2003/1999–2008 due to drought. Furthermore, soil carbon sequestration estimates were affected by the annual change coefficients employed, underscoring the need for careful interpretation of LCI outputs. Results were compared to other studies and highlighted the importance of the choice of data and methods in creating LCI, and the need for transparency. Conclusions This first national LCI of perennial forage production in Canada provides a baseline for LCI inputs and outputs associated with this sector, highlighting provincial and regional differences. Outputs can be used to conduct future life cycle assessments to assess the environmental impacts of forage production and generate recommendations to improve sustainability, and for education and marketing purposes. This study demonstrates methodological best practices for LCI data mining and calculations, within available data and model limitations, thereby identifying gaps and providing a roadmap for other countries or sectors to develop detailed forage LCI.