Aboveground Carbon Stocks Research Articles

Carbon stocks of Petungkriyono mixed forest as climate change mitigation

The Petungkriyono forest covers 53.88 km2 at Pekalongan Regency with 54.6% composition of mixed forest (29.43 km2). This study aimed to estimate above-ground biomass and carbon stocks from five villages; Tlogopakis, Tlogohendro, Kayupuring, Yosorejo and Kasimpar. Non-destructive samples of 30 plots were conducted by designing plots with 0.04 ha and stand inventory involving diameter at breast height, height and number of trees. The result showed that the total estimated biomass from five villages was 3,006.10 Mg ha-1 and carbon stocks were 1,442.93 Mg C ha-1. The averages of biomass and carbon stocks were 601.22 Mg Ha-1 and 288.59 Mg C ha-1. This indicates that 2,943 ha area of Petungkriyono mixed forest has carbon stocks capacity up to 1,769,390.46 Mg C. The highest above-ground biomass contribution 59% tree compared with 41% poles. The significantly higher above-ground biomass describes higher carbon stocks long term storage of CO2 to either mitigate or defer global warming. Climate change mitigation from carbon stocks can be obtained from CO2 equivalents if well managed. Petungkriyono mixed forest may have considerable potential for mitigating climate change by carbon sequestration.

High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA

The inclusion of forest carbon in climate change mitigation planning requires the development of models able to project potential future carbon stocks—a step beyond traditional monitoring, reporting and verification frameworks. Here, we updated and expanded a high-resolution forest carbon modelling approach previously developed for the state of Maryland to 11 states in the Regional Greenhouse Gas Initiative (RGGI) domain, which includes Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. In this study, we employ an updated version of the Ecosystem Demography (ED) model, an improved lidar initialization strategy, and an expanded calibration/validation approach. High resolution (90 m) wall-to-wall maps of present aboveground carbon, aboveground carbon sequestration potential, aboveground carbon sequestration potential gap (CSPG), and time to reach sequestration potential were produced over the RGGI domain where airborne lidar data were available, including 100% of eight states, 62% of Maine, 12% of New Jersey, and 0.65% of New York. For the eight states with complete data, an area of 228 552 km2, the contemporary forest aboveground carbon stock is estimated to be 1134 Tg C, and the forest aboveground CSPG is estimated to be larger at >1770 Tg C. Importantly, these estimates of the potential for added aboveground carbon sequestration in forests are spatially resolved, are further partitioned between continued growth of existing trees and new afforested/reforested areas, and include time estimates for realization. They are also assessed for sensitivity to potential changes in vegetation productivity and disturbance rate in response to climate change. The results from this study are intended as input into regional, state, and local planning efforts that consider future climate mitigation in forests along with other land-use considerations.

Not only exotic grasslands: The scattered trees in cultivated pastures of the Brazilian Cerrado

Cultivated pastures occupy 30% of the Brazilian Cerrado. Most pastures have low productivity, demanding intensification. Pasture intensification, as conventionally proposed, promises conservation by land sparing. However, it does not embrace silvopastoral systems, a type of intensification that enhances carbon balance and in situ biodiversity conservation. In the Cerrado, silvopastoral systems would be easily established because pastures with native trees are commonly found in the landscape. In this study, we estimated the density of scattered trees using RapidEye satellite data in 200 cultivated pastures (48,519 ha). We also identified tree species by establishing 93 field plots distributed along 15 ecoregions in the Cerrado biome. We expected that the density of trees would vary in function of farm size, age of the pasture, intensification of pasture management and biophysical variables. Mean scattered tree density was 3.52 tree ha−1 (± 2.93 SD), and it was higher in ecoregions with lower and more concentrated rainfall. The most frequent tree species were those with high commercial values, such as the Myracrodruon urundeuva timber tree (aroeira) and the Caryocar brasiliense fruit tree (pequi). The average above-ground carbon stock of native Cerrado trees in pastures was estimated in 1.2 Mg ha−1 (± 1.2 SD). Our study shows that there are productive pastures with high tree density and species richness, which could be used as models for sustainable intensification strategies in different ecoregions of the Cerrado.

Relationships between above- and below-ground carbon stocks in mangrove forests facilitate better estimation of total mangrove blue carbon

BackgroundAlthough great efforts have been made to quantify mangrove carbon stocks, accurate estimations of below-ground carbon stocks remain unreliable. In this study, we examined the distribution patterns of mangrove carbon stocks in China and other countries using our own field survey data and datasets from published literature. Based on these data, we investigated the possible relationships between above-ground carbon stock (AGC) and below-ground carbon stock (BGC) for mangrove forests, aiming to provide a scientific basis for estimation of total mangrove carbon stocks.ResultsThe average above-ground carbon stock in each region was sizeable (ranging from 12.0 to 150.2 Mg/ha), but average below-ground carbon stock was dominant (ranging from 46.6 to 388.6 Mg/ha), accounting for 69–91% of total carbon stock at the sites studied in China. Significant positive relationships were found between above-ground and below-ground mangrove carbon stocks, with the best fitting equation as BGC = 1.58 * AGC + 81.06 (Mg/ha, R2 = 0.62, p < 0.01, n = 122) for China. Such linear relationships vary for mangrove forests of different types and locations, from different geographical regions in China to other countries worldwide.ConclusionThe positive relationship we found between above- and below-ground carbon stocks of mangrove forests in China and worldwide can facilitate more accurate assessments of mangrove blue carbon stocks at regional or global scales using modern techniques including remote sensing.

Comparison of vegetation indices for estimating above-ground mangrove carbon stocks using PlanetScope image

Mangroves play a pivotal role in providing ecological benefits and services to reduce and adapt to climate change impact on coastal ecosystem. They are capable of absorbing carbon, which is crucial in controlling CO2 levels in the atmosphere. This research aims to assess the accuracy of selected vegetation indices for estimating above-ground carbon (AGC) stocks of mangroves using PlanetScope images in Bedul, Banyuwangi, East Java Province, Indonesia. A semi-empirical approach was used to assess and map mangrove AGC, starting with applying the allometric equation to calculate field-measured species-specific AGC stocks. Regression analyses were applied to develop a relationship between field AGC and vegetation indices derived from PlanetScope Image, including Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), and Enhanced Vegetation Index (EVI). The Standard Errors of Estimates (SE) were 31.41, 32.93, and 31.63 tons/ha for DVI, EVI, and NDVI, respectively. Thus, carbon stocks estimation, including DVI as an independent variable, is considered more accurate than other vegetation indices tested in this research

Ecosystem services trajectories in coffee agroforestry in Colombia over 40 years

Agroforestry interventions may act as catalysts for ecosystem service development and changes in supply and therefore may rehabilitate degraded land. This study investigates the trajectories of ecosystem services in coffee systems with a different time since transition to agroforestry in Colombia, the interactions among ecosystem services, and the biotic and abiotic factors that explain them. Therefore, we study a chronosequence of agroforestry coffee farms, with 1–40 years since planting of shade trees. We found that aboveground carbon stock, habitat provisioning, timber volume and coffee bean quality followed positive asymptotic trajectories. Erosion control and pest control did not change over time. Coffee yield tended to decrease as the shade trees matured, but this was not significant. We found consistent positive relationships between carbon stock, erosion control and epiphyte richness. A trade-off between aboveground carbon stock and coffee yield was found for the first 10 years, while a positive relation between coffee yield and erosion control was found for the long term (10–20 years). Canopy cover best explained ecosystem service supply, but also farm agrochemical input management, altitude and slope influenced the supply. This study demonstrated that agroforestry can be used to rehabilitate ecosystem service supply.

Mapping Above-Ground Carbon Stock of Secondary Peat Swamp Forest Using Forest Canopy Density Model Landsat 8 OLI-TIRS: A Case Study in Central Kalimantan Indonesia

Mapping the above-ground carbon potential by using a non-destructive method has been a serious challenge for researchers in the effort to improve the performance of natural forest management in Indonesia, particularly in the ex-Mega Rice Project (MRP) area in Central Kalimantan Province. Nevertheless, the rapid and dynamic changes in secondary peat swamp forests are currently mapped effectively with the remote sensing technology using the Forest Canopy Density (FCD) model. FCD analysis as done by integrating vegetation index, soil index, temperature index and shadow index of Landsat 8 OLI images. The result was an FCD class map. In each class, parameter measurements were established for seedling, sapling, poles and tree stages. Above-ground carbon stock was calculated using three allometric equations. The results revealed that the values of carbon stock in ±16,147.26 ha dense secondary peat swamp forest, ±1,509.66 ha moderately dense scrub swamp forest, and ±632.07 ha sparse scrub swamp forest were, respectively, 79.28-122.96; 74.06-113.06; and 40.48-63.60 ton/ha. These results show that FCD application could be used to classify forest density effectively and in line with the variety of their attributes such us aboveground biomass and carbon stock potential.

The allometric relationships for estimating above-ground biomass and carbon stock in an abandoned traditional garden in East Kalimantan, Indonesia

Abstract. Karyati, Widiati KY, Karmini, Mulyadi R. 2021. The allometric relationships for estimating aboveground biomass and carbon stock in an abandoned traditional garden in East Kalimantan, Indonesia. Biodiversitas 22: 751-762. The existence of traditional gardens after abandonment process has a role based on ecological and economic aspects. To estimate the biomass and carbon stock in the abandoned traditional gardens, specific allometric equations are required. The aim of this study was to develop allometric equations to estimate biomass of plant parts (leaf, branch, trunk, and aboveground biomass (AGB)) through tree dimensions variables (diameter at breast height (DBH), total tree height, and tree bole height). The relationships between stem biomass, AGB and tree dimensions were very strong indicated by the relatively high adjusted R2 value. The moderately strong relationships were shown between branch biomass and tree dimensions, meanwhile, the relationship between leaf biomass and tree dimensions was very weak. The specific allometric equations for estimating biomass and carbon stocks that are suitable for tree species and/or forest stands at a particular site are very useful for calculating the carbon stocks and sequestration. The appropriate biomass and carbon stock calculation are needed to determine policies related to global climate change.

Estimating above-ground biomass of subtropical forest using airborne LiDAR in Hong Kong

Seventy-percent of the terrestrial area of Hong Kong is covered by vegetation and 40% is protected as the Country Park. The above-ground biomass (AGB) acts as reliable source of carbon sink and while Hong Kong has recognized the importance of carbon sink in forest and urged for forest protection in the latest strategic plan, yet no study has been conducted on assessing the baseline of terrestrial AGB and its carbon storage. This study compared and estimated the AGB by the traditional allometric modeling and the Light Detection and Ranging (LiDAR) plot metrics at plot-level in a subtropical forest of Hong Kong. The study has tested five allometric models which were developed from pantropical regions, subtropical areas and locally. The best model was then selected as the dependent variable to develop the LiDAR-derived AGB model. The raw LiDAR point cloud was pre-processed to normalized height point cloud and hence generating the LiDAR metric as independent variables for the model development. Regression models were used to estimate AGB at various plot sizes (i.e., in 10-m, 5-m and 2.5-m radius). The models were then evaluated statistically and validated by bootstrapping and leave-one-out cross validation (LOOCV). The results indicated the LiDAR metric derived from larger plot size outperformed the smaller plot size, with model R2 of 0.864 and root-mean-square-error (RMSE) of 37.75 kg/ha. It also found that pantropical model was comparable to a site-specific model when including the bioclimatic variable in subtropical forests. This study provides the approach for delineating the baseline of terrestrial above-ground biomass and carbon stock in subtropical forests upon an appropriate plot size is being deployed.

Carbon stock potential in Pinus roxburghii forests of Indian Himalayan regions

Chir pine (Pinus roxburghii) is the most important tree species used for afforestation programs in the Himalayan regions. In the present study, fourteen forest stands were selected in four different altitudes, i.e., 1801 masl in Garhwal Himalayan of Uttarakhand, India, to assess carbon stock potential of the forest. The study was conducted during 2013–2015. Among the study sites, the maximum tree density (575 ± 90.14 ind. ha−1) was reported in New Tehri (altitude: > 1801 masl) and minimum (135 ± 5.00 ind. ha−1) in Daddi (altitude: 1001–1400 masl). The highest (96 ± 18.36 t ha−1) above-ground carbon stock was estimated in Kandikhal where bole, branch, and foliage contribute 89.93 ± 19.47, 5.17 ± 1.04 and 0.90 ± 0.14 t ha−1, respectively, while lowest (26.68 ± 9.48 t ha−1) was in Gumkhal, and contribution from the same component was found as 20.72 ± 7.84, 4.50 ± 1.58, and 1.47 ± 0.11 t ha−1, respectively. Further, highest value of below-ground carbon was in Kandikhal (28.58 ± 4.81 t ha−1) with an altitude range between 1001 and 1400 masl and the lowest in Gumkhal (9.19 ± 2.87 t ha−1) between 1401 and 1800 masl. Besides, litter production was found higher in the summer season followed by winter and rainy seasons. The study concluded that the density, height, basal area, and volume of Pinus roxburgii varied with altitude, but it was not directional. However, growth patterns and tree density were the key factors in estimating total carbon stocks and further to know the behavior of carbon dynamics (source/sink). Litter production had an inverse relation with altitude; however, increase in litter biomass at > 1801 masl was observed due to new plantations of pine. This study will be highly helpful to the forester and policy-makers in planning carbon mitigation strategies (e.g., catchment area treatment, afforestation activities) at regional and global scales.

Estimation of aboveground biomass and carbon stock in a pine-mahogany mixture stands at specific purpose forest area of Gunung Bromo, Karanganyar

Forest plays an important role on reducing the impact of global warming as carbon sink. Forest has an ability to absorb carbon on large scale and store it as biomass. This research was aim to determine the potential of aboveground biomass and carbon stock in pine-mahogany mixture stands in Specific Purpose Forest Area (SPFA) of Gunung Bromo. The systematic sampling with random start was used to determine the plot, and the distance between plots were 100 m. In total, there were 35 square plots, 20 × 20 m in size, that had been set up under the pine-mahogany mixture stands. This research was conducted by using non-destructive sampling method by measuring the tree volume. The pine-mahogany stands dominated by the trees with diameter class 20-30 cm. The tree density and stand volume were 431 trees/ha and 229.4 m3/ha. Estimated aboveground biomass, carbon stock, and CO2 equivalent in pine stands were 136.53 ton/ha, 64.17 ton C/ha, and 235.29 ton/ha, while for mahogany stands were 33.01 ton/ha, 15.56 ton C/ha, and 57.04 ton/ha, respectively. Thus, the total biomass and carbon stock in pine-mahogany mixture stands were 169.63 ton/ha and 79.73 ton C/ha. Meanwhile, total CO2-equivalent was 292.23 ton/ha.

Evaluation of the Aerial Biomass of Three Sahelian Species in the Ferlo (North Senegal): &amp;lt;i&amp;gt;Acacia tortilis&amp;lt;/i&amp;gt; (Forsk.) Hayn essp. Raddiana (Savi) Brenan, &amp;lt;i&amp;gt;Acacia senegal&amp;lt;/i&amp;gt; (L.) Willd and &amp;lt;i&amp;gt;Balanites aegyptiaca&amp;lt;/i&amp;gt; (L.) Del

In a context of climate change characterized by rising temperatures, increased greenhouse gases and frequent droughts, the Sahel is presented as one of the most vulnerable areas to the adverse effects of climate change. The Sahel is presented as one of the most vulnerable areas to the adverse effects of climate change. The objective of this study is to assess the above-ground biomass and carbon stock of three Sahelian species: Acacia raddiana tortilis (Forsk.) hayne ssp. raddiana (savi) Brenan, Acacia senegal (L.) Willd and Balanites aegyptiaca (L.). The study was carried out in northern Senegal commonly known as Ferlo. Biomasses of the populations of the three target species were first assessed by harvesting the entire epigenetic part of the species and then modelled by correlation using dendrometric parameters measured on each individual of the sample. Two models, mono-specific and multi-species, were used. The results obtained showed that the diameter at breast height (x) and the parameter best correlated to the epigeal biomass (y). The dry biomass of woody plants was 31.4 ± 15.2 kg/tree for B. aegyptiaca, 30.6 ± 13.2 kg/tree for A. senegal and 26.2 ± 11.1 kg/tree for A. raddiana; i.e. carbon equivalents of 14.75 - 14.38 - 12.31 kg/tree respectively. The amount of carbon contained in the above-ground woody biomass is estimated at 4.48 t/ha. The carbon equivalent, atmospheric CO2 is estimated at 16.44 tons of CO2/ha and based on the actual density of Ferlo (108.08 ± 49.79 ind/ha) the sequestered carbon of the area is estimated at 1777.008 tons of CO2. The comparison between the models developed in this study and the multispecific or mono-specific models from the literature showed substantial differences. This study contributes to a better understanding of the contribution of Sahelian woody species to carbon sequestration and the results could be used in the framework of adaptation to climate change.

Escalating the small-sized community green spaces’ role as the carbon storage in the coastal town

The community green space type is well-known as a public place with a superior aesthetic value. In contrast, this green space type can also have the principal ecological value because of the vegetation cover. This study was estimated the above-ground biomass and carbon stock of each tree species within the community green spaces in both coastal and terrestrial habitat to select some potential species to be more developed within both community green spaces in order to escalate the ecological value of the green spaces (carbon storage in a town area). All woody plants with a diameter at breast height (dbh) ≥ 20 cm were identified by the census method within three sampling plots in both Laman Brenda Park (Site 1) and Pamedan Ahmad Yani Park (Site 2). This study found that the tree community in Site 2 stores a higher carbon stock (15,433 kg/ha) than in Site 1 (1,744 kg/ha). The number of individual trees is the main driving factor of the amount of carbon stock on both sites. Some species from Lauraceae, Fabaceae, and Meliaceae that are incredibly tolerant of small mineral content soils, salinity, and lack of water content should be more developed in Site 1, specifically.

Ratios between aboveground net primary production, litterfall and carbon stocks in scots pine stands (Russia)

Background: Forests are the main terrestrial regulators of greenhouse gas concentrations. However, estimates of carbon fluxes in them are characterized by large uncertainties. Therefore, the derivation of predictors for their assessment is an urgent task. The aim was to assess the carbon stocks in the biomass to characterize the intensity of aboveground net production and the amount of litterfall in Scots pine forests of different types on the North-East of the Europe. We estimated biomass and aboveground net primary production (ANPP) of stands using sample trees. For vegetation of ground cover biomass and primary production evaluating, we cut off all aboveground organs on an area of 625 cm2 and removed the first-year parts. Litterfall was collected over 3-6 years using litter traps. Results: Most of the carbon in the biomass of pine forests is concentrated in trees (Cstand) with dominating role of stem wood. However, in boggy forests, ground vegetation plays a significant role in carbon stocks, both in absolute and relative values. We estimated carbon fluxes in ANPP and stand litterfall. High contribution of needles was detected for these flows. The ratio between ANPP and Cstand varied from 0.018 to 0.056 but between Litterfal and Cstand ranged from 0.008 to 0.024. Conclusion: The biomass, ANPP and litterfall depended form forest type. Obtained ratios between them can be used for assessing carbon fluxes in large regions using remote data collection of forest biomass.

The Neglected Carbon Sink: Above-Ground Carbon Stock Estimates of Urban Forests and Their Variations by Land Use Type in Zomba City, Malawi

The Neglected Carbon Sink: Above-Ground Carbon Stock Estimates of Urban Forests and Their Variations by Land Use Type in Zomba City, Malawi

Assessment of The Above-Ground Carbon Stock and Soil Physico-Chemical Properties of an Arboretum within The University of Port Harcourt, Nigeria

Assessment of The Above-Ground Carbon Stock and Soil Physico-Chemical Properties of an Arboretum within The University of Port Harcourt, Nigeria

Integrating high resolution drone imagery and forest inventory to distinguish canopy and understory trees and quantify their contributions to forest structure and dynamics.

Tree growth and survival differ strongly between canopy trees (those directly exposed to overhead light), and understory trees. However, the structural complexity of many tropical forests makes it difficult to determine canopy positions. The integration of remote sensing and ground-based data enables this determination and measurements of how canopy and understory trees differ in structure and dynamics. Here we analyzed 2 cm resolution RGB imagery collected by a Remotely Piloted Aircraft System (RPAS), also known as drone, together with two decades of bi-annual tree censuses for 2 ha of old growth forest in the Central Amazon. We delineated all crowns visible in the imagery and linked each crown to a tagged stem through field work. Canopy trees constituted 40% of the 1244 inventoried trees with diameter at breast height (DBH) > 10 cm, and accounted for ~70% of aboveground carbon stocks and wood productivity. The probability of being in the canopy increased logistically with tree diameter, passing through 50% at 23.5 cm DBH. Diameter growth was on average twice as large in canopy trees as in understory trees. Growth rates were unrelated to diameter in canopy trees and positively related to diameter in understory trees, consistent with the idea that light availability increases with diameter in the understory but not the canopy. The whole stand size distribution was best fit by a Weibull distribution, whereas the separate size distributions of understory trees or canopy trees > 25 cm DBH were equally well fit by exponential and Weibull distributions, consistent with mechanistic forest models. The identification and field mapping of crowns seen in a high resolution orthomosaic revealed new patterns in the structure and dynamics of trees of canopy vs. understory at this site, demonstrating the value of traditional tree censuses with drone remote sensing.

Analysis of Floristic Diversity and Quantification of Diameter Class Aboveground Biomass (AGB) and Carbon Stocks of Afromontane Vegetation of Nkoanenkole Forest Reserve (NCFR) in Northern Tanzania

Nkoanenkole Forest Reserve (NCFR) is such a potential area in floristic diversity within a relatively small area of 370.2 ha. The study was conducted in 2018 to analyze the floristic diversity and quantify the tree species aboveground biomass and carbon stocks of Nkoanenkole Catchment Forest Reserve (NCFR) in Arumeru District, Arusha-Tanzania. Systematic random sampling was applied, whereby a 24 with a 15 m radius (706.5 m2) were set at an inter plot and transect distance of 350 m. The plant species were identified by their botanical names, determined for abundance, and trees with ≥5cm DBH were measured. Shannon Wiever (H’), and Simpson indices were applied to calculate the index of diversity. Also, density and relative density were calculated. The AGB and AGC mg ha-1 were calculated using allometric models. 147 plant species were identified from the 24 sample plots, of which 54 were trees, 31 shrubs and lianas, 48 herbs, 3 sedges, 6 grass species, and 6 belonged to the ferns. The calculate H’ was 3.3316 for trees with an index of dominance of 0.053, and 2.449 for shrubs and lianas, sedges, herbs, and ferns with an index of dominance of 0.00.3135. The families of Euphorbiaceae, Rubiaceae, Fabaceae, and Asteraceae were determined to be the most dominant in terms of the number species. The identified tree seedlings were 14 with an abundance of 136, the density of 16.513±0.590, and a relative density of 20.14±0.73. Bersama abyssinica and Psychotria riparia were the most dominant tree seedlings. The DBH-class of 15±5 had the highest AGB (kg) and AGC mg ha-1, followed by 25±15, 55±45, 65±55, and the rest. NCFR is latent for its biodiversity, hence recommending further study on biological diversity, the possibility for upgrading the NCFR to the nature reserve, encourage beekeeping as potential pollinators, discourage illegal human activities through education and regular patrols.

Accounting for Greenhouse Gas Emissions from Forest Edge Degradation: Gold Mining in Guyana as a Case Study

Background and Methods: Degradation of forests in developing countries results from multiple activities and is perceived to be a key source of greenhouse gas emissions, yet there are not reliable methodologies to measure and monitor emissions from all degrading activities. Therefore, there is limited knowledge of the actual extent of emissions from forest degradation. Degradation can be either in the forest interior, with a repeatable defined pattern within areas of forest, as with timber harvest, or on the forest edge and immediately bounding areas of deforestation. Forest edge degradation is especially challenging to capture with remote sensing or to predict from proxy factors. This paper addresses forest edge degradation and: (1) proposes a low cost methodology for assessing forest edge degradation surrounding deforestation; (2) using the method, provides estimates of gross carbon emissions from forest degradation surrounding and caused by alluvial mining in Guyana, and (3) compares emissions from mining degradation with other sources of forest greenhouse gas emissions. To estimate carbon emissions from forest degradation associated with mining in Guyana, 100 m buffers were located around polygons pre-mapped as mining deforestation, and within these buffers rectangular transects were established. Researchers collected ground data to produce estimates of the biomass damaged as a result of mining activities to apply to the buffer area around the mining deforestation. Results: The proposed method to estimate emissions from forest edge degradation was successfully piloted in Guyana, where 61% of the transects lost 10 Mg C ha−1 or less in trees from mining damage and 46% of these transects lost 1 Mg C ha−1 or less. Seventy percent of the damaged stems and 60% of carbon loss occurred in the first 50 m of the transects. The median loss in carbon stock from mining damage was 2.2 Mg C ha−1 (95% confidence interval: 0.0–10.2 Mg C ha−1). The carbon loss from mining degradation represented 1.0% of mean total aboveground carbon stocks, with emissions from mining degradation equivalent to ~2% of all emissions from forest change in Guyana. Conclusions: Gross carbon emissions from forest degradation around mining sites are of little significance regardless of persistence and potential forest recovery. The development of cost- and time-effective buffers around deforestation provides a sound approach to estimating carbon emissions from forest degradation adjacent to deforestation including surrounding mining. This simple approach provides a low-cost method that can be replicated anywhere to derive forest degradation estimates.

Characteristics of mangrove ecosystems in Weda Bay: Environment, Vegetation, and Aboveground Carbon Stocks

Weda Bay is one of the largest mangrove habitat in North Maluku and one of mega-biodiversity spots in Indonesia. However, data and information of mangrove vegetation and its ecosystem services particularly carbon stocks were limited. Mangroves were mapped using GIS-remote sensing and vegetation were sampled using transects in five sites of mangroves across Weda Bay. Tansects were extended from seaward to landward to cover all vegetation variation and hydrodynamic conditions. Environmental data (water and substrate): temperature, pH, Dissolved Oxygen (DO), particle size of sediment, and nutrient (phosphate and nitrate) were collected. The objective is to identify characteristics of mangrove landscape and vegetation, it is environment, and it ecosystem services in term of aboveground carbon stocks. The study showed that the characteristics of landscape and vegetation of mangrove varied among hydrodynamic conditions. The bay is important habitat for 8.5% (17 species) of mangrove species in Indonesia. Rhizophora apiculata and Bruguiera gymnorrhiza were the most dominant mangroves. The environmental conditions of Weda Bay particularly northern part of the bay were suitable for mangrove growth. Substrate of mangrove did not vary significantly with distance from the seaward which was mainly dominated by mud and clay (3.9 - 63 μm). Mean water temperature in the mangrove area was 29.3°C, salinity 34.1 psu, mean water suspension was 46 mg l−1, mean dissolved oxygen was 3.2 mg l−1, and water current was 10 m s−1. Aboveground carbon stock was considerable (752 ± 17.6 Mg C ha−1). Change in aboveground carbon stocks over the distance from the seaward edge to landward edge was not significantly different. In contrast, aboveground carbon stocks varied among hydrodynamic conditions: estuarine, delta, and riverine mangroves. Delta mangrove contained the highest carbon stock (993 ± 27.7 Mg C ha−1), followed by estuarine mangroves (645 ± 12.2 Mg C ha−1) and riverine mangroves (244 ± 8.6 Mg C ha−1). However, this ecosystem faced some threats such as mangrove extraction and plastic pollution. Better mangrove management e.g. reducing mangrove extraction and pollution are required to protect the functions and ecosystem services of mangroves. In addition, conserving mangrove forests will allow the government to achieve blue economy goals and to mitigate climate change through carbon sequestration.