scholarly journals Phytosociological assessment and carbon stock estimation and valuation in the tropical dry deciduous forest of Bihar

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saroni Biswas ◽  
Anirban Biswas ◽  
Arabinda Das ◽  
Saon Banerjee
Keyword(s):  
Carbon Stock ◽  
Deciduous Forest ◽  
Basal Area ◽  
Total Biomass ◽  
Content Type ◽  
Shorea Robusta ◽  
Sequestration Potential ◽  
Forest Division ◽  
C Stock ◽  
Stock Estimation

Purpose This study aims to assess the biodiversity of the study area and estimate the carbon stock of two dry deciduous forest ranges of Banka Forest Division, Bihar, India. Design/methodology/approach The phytosociological analysis was performed and C stock estimation based on volume determination through nondestructive methods was done. Findings Phytosociological analysis found total 18,888 [14,893 < 10 cm (diameter at breast height) dbh] and 2,855 (1,783 < 10 cm dbh) individuals at Banka and Bounsi range with basal area of 181,035.00 cm2 and 32,743.76 cm2, respectively. Importance value index was highest for Shorea robusta in both the ranges. Species diversity index and dominance index, 1.89 and 1.017 at Banka and 1.99 and 5.600 at Bounsi indicated the prevalence of biotic pressure. Decreased dbh and tree height resulted in a lowered growing stock volume as 59,140.40 cm3 ha−1 (Banka) and 71,306.37 cm3 ha−1 (Bounsi). Total C stock at Banka and Bounsi range was 51.8 t ha-1 and 12.56 t ha−1, respectively where the highest C stock is recorded for Shorea robusta in both the ranges (9.8 t ha−1 and 2.54 t ha-1, respectively). A positive correlation between volume, total biomass and basal area of tree species with C stock was observed. R2 value for Banka range was 0.9269 (volume-C stock), 1 (total biomass-C stock) and 0.647 (basal area-C stock). Strong positive correlation was also established at Bounsi range with R2 value of 1. Considering the total forest area enumerated, C sequestration potential was about 194.25 t CO2 (Banka) and 45.9 t CO2 (Bounsi). The valuation of C stock was therefore US$2,525.25 (Banka) and US$596.70 (Bounsi). Practical implications The research found the potentiality of the study area to sequester carbon. However, for future, the degraded areas would require intervention of management strategies for restoration of degraded lands and protection of planted trees to increase the carbon sequestration potential of the area. Originality/value Present study is the first attempt to assess the phytosociology and estimate the regulatory services of forest with respect to biomass and carbon stock estimation for the Banka forest division of Bihar.

Assessment of Biomass and Carbon Stock of planted teak forest in Terai region of Kumaun Himalaya, India

2018 ◽  
Vol 41 (4) ◽  
pp. 397-402
Author(s):  
Tanuja Gahlot ◽  
◽  
Prachi Joshi ◽  
Y.S. Rawat ◽  
◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Sequestration ◽  
Human Disturbance ◽  
Carbon Stock ◽  
Large Scale ◽  
Basal Area ◽  
Stand Density ◽  
Positive Contribution ◽  
Teak Plantation ◽  
Forest Division

The ability of forests in atmospheric carbon sequestration is increasingly gaining attention. Present study deals with the estimation of biomass and carbon stock of the teak plantation in the terai central forest division in Kumaun, Uttarakhand State of India. Very few scientific studies were done regarding the teak plantation and the estimation of its biomass in Kumaun. Therefore this study was carried out in this region to assess the role played by teak plantation in climate change. The information regarding the changes in pattern of carbon storage is vital and important because it can be used by government and policymakers to predict the deposit pattern for changing climate. Three sites i.e., Kamola block (Site I), Kamola beat (Site II) and East Gadappu beat (Site III) were selected for the study. Large scale variations in biomass and carbon stock were noted among all three sites. Site III (East Gadappu) showed the maximum biomass and carbon stock (297.03 tha-1 and 143.18 tha-1) followed by site I (Kamola block) (241.9 tha -1and 117.27 t ha-1) and site II ( Kamola beat ) (175.76 t ha-1and 85.79 t ha-1). Although stand density and total basal area of the forest showed almost similar value on all three sites, still the differences in biomass and carbon stock at all sites indicated the positive contribution of biodiversity as shown in the results and negative implications of human disturbance to the forest.

scholarly journals Carbon stock estimation of mangrove forest in Sulaman Lake Forest Reserve, Sabah, Malaysia

2020 ◽  
Vol 21 (12) ◽  
Author(s):  
Normah Awang Besar ◽  
NURUL SYAKILAH SUHAILI ◽  
JIM LIEW JUN FEI ◽  
FAUZAN WAJDI SHA’ARI ◽  
MUHAMMAD IZZUDDIN IDRIS ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Mangrove Forest ◽  
Carbon Stock ◽  
Total Carbon ◽  
Climate Mitigation ◽  
Total Biomass ◽  
Forest Reserve ◽  
Soil Carbon Stock ◽  
Stock Estimation ◽  
Total Carbon Stock

Abstract. Besar NA, Suhaili NS, Fei JLJ, Sha’ari FW, Idris MI, Hatta SH, Kodoh J. 2020. Carbon stock estimation of Sulaman Lake Forest Reserve in Sabah, Malaysia. Biodiversitas 21: 5657-5664. Mangrove forest has a significant role in sequestering carbon gases from the atmosphere but there are lesser literature has been made on it. This research was conducted to quantify the aboveground, belowground and soil carbon stock in Sulaman Lake Forest Reserve, Sabah, Malaysia. Nine transect lines with 125 m length were established and a circle with 7 m radius was set in every 25 m. Forest inventory was done to get the diameter breast height of standing trees and soil sampling with four different depths (0-15 cm, 15-30 cm, 30-50 cm and 50-100 cm) were taken for soil analysis and bulk density. Allometric equation was used to calculate aboveground and belowground biomass then its carbon stock was estimated as 50% from its total biomass. The result shows the total carbon stock in the study area was 441.72 Mg C ha-1, and soil has the highest value of carbon stock (351.98 ± 11.73 Mg C ha-1) followed by aboveground carbon (67.30 ± 20.55 Mg C ha-1) and belowground carbon (22.44 ± 0.17 Mg C ha-1). This study found that soil carbon stock made up almost 80% of the total carbon stock in the mangrove forest. This ecosystem also shows a higher value of carbon stock compared to other locations hence emphasized the importance of prioritizing a mangrove forest in any climate mitigation efforts.

scholarly journals Variability Assessment for Volume, Biomass and Carbon Stock in Cedrus deodara (Roxb) G.Don. Forests of Garhwal Himalaya

2020 ◽  
pp. 93-103
Author(s):  
Rathod Digvijaysinh ◽  
Yogesh Kumar ◽  
Gaurav Chand Ramola ◽  
Dhaval Prajapati ◽  
C. S. Dhanai ◽  
...  
Keyword(s):  
Carbon Stock ◽  
Canopy Cover ◽  
Basal Area ◽  
Stand Density ◽  
Total Carbon ◽  
Total Biomass ◽  
Timber Species ◽  
Biomass Density ◽  
Cedrus Deodara ◽  
Ground Biomass

Deodar is typically gregarious and is usually found in pure stands. It is one of the most important timber species in the forests of North Indian Himalayas. The objective of the present study was the assessment of variation in volume and biomass along with the carbon holding capacity of different deodar forests. The present study was undertaken in ten different forests sites, assessed by laying out three 0.1 ha sample plots randomly on each location. Total enumeration of trees within the sample plot was done by measuring girth and height of all the trees. Further, data collected from stand were computed for dbh, basal area, volume, stand density and canopy cover. The above ground biomass densities (AGBD), below ground biomass density (BGBD), total biomass density (TBD), total carbon density (TCD) were examined for variation of biomass and carbon stock. The results derived from field data during the study revealed that the values range from 42.10 to 57.07 cm (diameter at breast height), 1.37 to 2.84 m2 trees-1 (basal area), 19.68 to 37.64 m (height), 1.44 m3 tree-1 to 4.27 m3 tree-1 (volume), 227 to 407 individual ha-1 (stand density) and 57.91% to 80.60% (canopy cover) respectively. The values of AGBD (428.57 to 1279.51 Mg ha-1), BGBD (97.41 to 256.14 Mg ha-1), TBD (525.98 to 1535.65 Mg ha-1), and TCD (767.83 to 262.99 Mg ha-1) were recorded in different study sites and highest values was observed in Kanasar-I site. On the basis of above results it can be concluded that the healthy stand growth means presence of trees in all diameter classes. The Kanasar-I has more prominent capacity to storage biomass and carbon stock. Deodar being a slow growing conifer will provide a long term and high carbon storage than broadleaf species forest. Therefore, protecting deodar forest would have the largest impact, per unit area, on reducing carbon emission from deforestation.

scholarly journals Regeneration Status and Carbon Accumulation Potential in Community Managed Sal (Shorea robusta) Forests of Far-Western Terai Region, Nepal

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Rajeev Joshi
Keyword(s):  
Carbon Sequestration ◽  
Carbon Stock ◽  
Carbon Accumulation ◽  
Developmental Phase ◽  
Community Forest ◽  
Carbon Sequestration Potential ◽  
Community Forests ◽  
Shorea Robusta ◽  
Regeneration Status ◽  
Sequestration Potential

Regeneration patterns of species population can address climate change by adaptive evolution or by migrating association to survival in their favorable climate and finally decide the particular forest future. This research examined the status of regeneration and carbon sequestration potential in tropical Sal (Shorea robusta) forest of Kanchanpur district, Nepal. For the study, a total of 63 concentric sample plots were investigated by using systematic sampling with 0.5% sampling intensity. Regeneration status of forest was estimated by calculating the density of each species in each developmental phase. The above-ground carbon stock of trees species were estimated using allometric equations. The studied forests had good regeneration status and Shorea robusta was the dominant species in terms of regeneration and carbon stock. Ramnagar community forest had greater number of seedling, sapling and tree than that of the Ganesh community forest. Reverse J-shaped population curves were recorded at both the study sites. This study provided information about the regeneration status, structure, composition and carbon sequestration potential of tree species which is very necessary for conservation and sustainable management of community forests. Studies indicate that community management has increased the carbon stock of forests and also has promoted the productivity of forests by altering the structure and composition of the community forests.

CONTRIBUTION OF AGROFORESTS IN ADAPTATION OF CLIMATE CHANGE EFFECTS: ESTIMATING THE PHYTODIVERSITY AND C SEQUESTRATION POTENTIAL IN 8-, 16- AND 24-YEAR-OLD OF PINUS SYLVESTRIS AGROFORESTS IN NORTHERN CAMEROON (TROPICAL AFRICA)

2021 ◽  
pp. 2050010
Author(s):  
V. NOIHA NOUMI ◽  
P. KOUAM KAMNING ◽  
C. KAMDOUM DEMGUIA ◽  
L. ZAPFACK
Keyword(s):  
Aboveground Biomass ◽  
Basal Area ◽  
Allometric Equation ◽  
Shannon Index ◽  
Nondestructive Method ◽  
Total Carbon ◽  
Total Biomass ◽  
Importance Value Index ◽  
Importance Value ◽  
Sequestration Potential

The study aims at assessing the agrobiodiversity and carbon stocks by the pine agroforests in the Sudano-Guinean zone of Cameroon. Five [Formula: see text][Formula: see text]m sampling transects were established in each chronosequence, it was undertaken to assess the growth characteristics and biomass. Estimates of stocks of carbon in aboveground biomass, belowground biomass (BGB), total biomass (TB) and CO2 equivalent stock were incorporated in allometric equation based on nondestructive method. A total of 24 species from 23 genera and 17 families were inventoried. Annona senegalensis, Syzygium guineensis and Hymenocardia acida contributed the most to the importance value index (IVI). Density ranged between [Formula: see text]–[Formula: see text] stems/ha; basal area between [Formula: see text]–[Formula: see text][Formula: see text]m2/ha; Shannon index between [Formula: see text]–[Formula: see text] with the highest value for 8-year-old stands; Pielou’s evenness between [Formula: see text]–[Formula: see text] with the lowest value in 24-year-old stands. Aboveground biomass ranged between [Formula: see text]–[Formula: see text] Mg C/ha with the highest value in 16-year-old stands; belowground carbon from [Formula: see text] Mg C/ha to [Formula: see text] Mg C/ha and total carbon from [Formula: see text] Mg C/ha to [Formula: see text] Mg C/ha. The sequestration potential ranged from [Formula: see text] Mg CO[Formula: see text]/ha to [Formula: see text] Mg CO[Formula: see text]/ha. The sequestration rates were 84.77, 49.7 and 28.6 Mg CO[Formula: see text].ha[Formula: see text]yr[Formula: see text] in 8-, 16- and 24-year-old stands, respectively. Although our data reported that pine stands hosted a few number of species; they are true carbon sinks and useful to the REED[Formula: see text] community.

Cartographie de la variabilité spatiale du stock de carbone forestier dans la Réserve de Biosphère Transfrontalière du W au Nord-Bénin.

2021 ◽  
Vol 2 (1) ◽  
pp. 47-60
Author(s):  
Ousséni AROUNA ◽  
◽  
Issiaka SARE WARA ◽  
DJAOUGA Mama ◽  
ZAKARI Soufouyane ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Spatial Distribution ◽  
Carbon Stock ◽  
Biosphere Reserve ◽  
Total Biomass ◽  
Entire Study ◽  
Carbon Sequestration Potential ◽  
Distribution Spatiale ◽  
Sequestration Potential ◽  
Entire Study Area

La cartographie du stock de carbone permet d’enrichir les connaissances mais aussi la comparaison des diverses transformations du couvert végétal sur l’évolution du stock. La présente recherche vise à cartographier la variabilité spatiale du stock de carbone forestier dans la Réserve de Biosphère Transfrontalière du W au Nord-Bénin. Le modèle de régression non linéaire a permis de prédire la distribution spatiale de la biomasse et du carbone à partir des valeurs de NDVI. Il résulte de cette méthode que la biomasse totale produite dans les unités de végétation de la RBTW a été estimée à 39 988 935,73 tonnes. La quantité totale de carbone correspondante est de 19 474 611,70 tonnes. Concernant la quantité de dioxyde de carbone accumulée, elle a été évaluée à 71 471 824,94 tonnes. Par ailleurs, la quantité de biomasse estimée par placeau oscille entre 2,71 et 172,82 t/ha. Le potentiel de séquestration de carbone dans les savanes boisées et arborées fait respectivement 1,81 et 1,24 fois celui enregistré en moyenne dans la RBTW. Les savanes arbustives et les friches sont les unités qui piègent le moins de dioxyde de carbone soit 18 % et 2 % du total de CO2. Sur l’ensemble du secteur d’étude, la quantité de carbone enregistrée varie de 35,80 à 54,32 t/ha avec une moyenne de 41,24 ± 4,08 t/ha. La quantité moyenne dans le Parc est de 40,42 ± 2,85 t/ha alors qu’elle est de 41,95 ± 4,78 t/ha pour la périphérie. La distribution spatiale de la biomasse et du carbone montre que les fortes quantités de biomasse et de carbone sont enregistrées particulièrement au sud-ouest de la RBTW. Mapping of carbon stock allows for a better understanding but also for the comparison of various vegetation cover transformations on the evolution of the stock. The present research aims to map the spatial variability of forest carbon stock in the W Transboundary Biosphere Reserve in northern Benin. The non-linear regression model was used to predict the spatial distribution of biomass and carbon from NDVI. As a result of this method, the total biomass produced in the RBTW vegetation units was estimated to be 39,988,935.73 tons. The corresponding total amount of carbon is 19,474,611.70 tons. Regarding the amount of carbon dioxide accumulated, it was estimated at 71,471,824.94 tons. Furthermore, the estimated amount of biomass per plot varies between 2.71 and 172.82 t/ha. The carbon sequestration potential of these two units in woodlands and shrub savannahs is respectively 1.81 and 1.24 times that recorded on average in the RBTW. Shrub savannahs and wastelands are the units that sequestrate the least carbon dioxide at 18% and 2% of total CO2. Over the entire study area, the amount of carbon recorded ranges from 35.80 to 54.32 t/ha with an average of 41.24 ± 4.08 t/ha. The average amount in the Park is 40.42 ± 2.85 t/ha while it is 41.95 ± 4.78 t/ha for the periphery. The spatial distribution of biomass and carbon shows that high amounts of biomass and carbon are recorded in the south and particularly in the southwest of the RBTW.

scholarly journals CARBON SEQUESTRATION POTENTIAL OF ROAD SIDE STANDING TREES IN KAMAREDDY MUNICIPALITY, TELANGANA, INDIA

2021 ◽  
Vol 21 (2) ◽  
Author(s):  
Anil Ragula ◽  
Shyam Mukandam ◽  
Suryakiran Banoth
Keyword(s):  
Carbon Sequestration ◽  
Carbon Stock ◽  
Total Carbon ◽  
Total Biomass ◽  
Carbon Sequestration Potential ◽  
The Road ◽  
Plot Size ◽  
Sequestration Potential ◽  
Standing Trees

In our study of Kamareddy Municipality area, we laid out a 27 sample plots linearly along the road side. 27 sample plots covered about 2.7 ha of land that means each plot size is 0.1 ha. We enumerated 229 number of tree individuals in sampled area. In the 27 sample plots, we calculated 53.5 M3 0f tree volume, mean volume per plot is 1.98 M3 . Total biomass (AGB+BGB) is about 44.7 tones; mean biomass per plot is around 1.65 tones. Total carbon calculated 1.3 tons, mean carbon is 0.78 tones per plot. The total Carbon sequestration potential is 77.9 tones, mean carbon sequestration potential per plot is about 2.88 tones. By the calculations we assumed per hectare volume is 19.81 M3 , biomass is 16.5 tones, carbon stock is 7.88 tones and carbon sequestration potential is 28.85 tons per hectare.

scholarly journals Estimating Aboveground Carbon Stock at the Scale of Individual Trees in Subtropical Forests Using UAV LiDAR and Hyperspectral Data

2021 ◽  
Vol 13 (24) ◽  
pp. 4969
Author(s):  
Haiming Qin ◽  
Weiqi Zhou ◽  
Yang Yao ◽  
Weimin Wang
Keyword(s):  
Carbon Stock ◽  
Explanatory Power ◽  
Hyperspectral Data ◽  
Tree Level ◽  
Accurate Estimation ◽  
Lidar Data ◽  
Aboveground Carbon ◽  
Sequestration Potential ◽  
Stock Estimation ◽  
Individual Trees

Accurate estimation of aboveground carbon stock for individual trees is important for evaluating forest carbon sequestration potential and maintaining ecosystem carbon balance. Airborne light detection and ranging (LiDAR) data has been widely used to estimate tree-level carbon stock. However, few studies have explored the potential of combining LiDAR and hyperspectral data to estimate tree-level carbon stock. The objective of this study is to explore the potential of integrating unmanned aerial vehicle (UAV) LiDAR with hyperspectral data for tree-level aboveground carbon stock estimation. To achieve this goal, we first delineated individual trees by a CHM-based watershed segmentation algorithm. We then extracted structural and spectral features from UAV LiDAR and hyperspectral data respectively. Then, Pearson correlation analysis was conducted to assess the correlation between LiDAR features, hyperspectral features, and tree-level carbon stock, based on which, features were selected for model development. Finally, we developed tree-level carbon stock estimation models based on the Schumacher–Hall formula and stepwise multiple regression. Results showed that both LiDAR and hyperspectral features were strongly correlated to tree-level carbon stock. Both tree height (H, r = 0.75) and Green index (GI, r = 0.83) had the highest correlation coefficients with tree-level carbon stock in LiDAR and hyperspectral features, respectively. The best model using LiDAR features alone includes the metrics of H, the 10th height percentile of points (PH10), and mean height of points (Hmean), and can explain 74% of the variations in tree-level carbon stock. Similarly, the best model using hyperspectral data includes GI and modified normalized differential vegetation index (mNDVI), and has similar explanatory power (r2 = 0.75). The model that integrates predictors, namely, GI and the 95th height percentile of points (PH95) from hyperspectral and LiDAR data, substantially improves the explanatory power (r2 = 0.89). These results indicated that while either LiDAR data or hyperspectral data alone can estimate tree-level carbon stock with reasonable accuracy, combining LiDAR and hyperspectral features can substantially improve the explanatory power of the model. Such results suggested that tree-level carbon stock estimation can greatly benefit from the complementary nature of LiDAR-detected structural characteristics and hyperspectral-captured spectral information of vegetation.

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