Climate Change and Organic Carbon Storage in Bangladesh Forests

Alamgir, Mohammed; Turton, Stephen M.

doi:10.1002/9783527675265.ch33

Cited by 5 publications

(7 citation statements)

References 18 publications

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“…Mean biomass C stock estimated (46 Mg C ha -1 ) in our case was close to that found (54 Mg C ha -1 ) in homestead forests in northern Bangladesh [17]. This, however, is lower than that found in the mangrove (99 Mg C ha -1 ; [22]) and entire forests (49-121 Mg C ha -1 ; [12]) of Bangladesh. This disagreement could be explained by the lower overall species diversity and richness in our study, which indicates lower biomass C stock [15].…”

Section: Discussionsupporting

confidence: 79%

“…Bangladesh´s contribution to global emissions is very low; however, its carbon (C) rich forest ecosystems are highly affected by land-use change and adverse impacts of climate change [11], such as changes in precipitation and global sea level rise. Bangladesh has forest areas of about 2.53 million hectares, representing 17.5% of the total land area [12,13]. These tropical forests are consisted of hill, mangrove, sal forests, and coastal mangrove plantations, with semi-evergreen and deciduous tree coverage.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Tree Species Diversity and Stand Structure on Carbon Stocks of Homestead Forests in Maheshkhali Island, Southern Bangladesh

Baul

Chakraborty

Nandi

et al. 2020

Preprint

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BackgroundThis study aimed to estimate the carbon (C) stocks in homestead forest ecosystems (trees, litterfall, and soil) of Maheshkhali Island in Bangladesh and how tree species diversity and stand structural variation affected these C stocks. We randomly surveyed a total of 239 homestead forests proportionately allocating in hillside (67), beachside (69), and inland (103) in 2019 for measuring woody plants and sampling litterfall and C in soil at 0-30 cm depth. Tree (above- and below-ground) biomass was estimated by using pan-tropical allometric equations, and carbon of litterfall and soil were analyzed in a laboratory. ResultsWe found a total of 52 tree species, of which, 41, 42, and 48 species were in the hillside, beachside, and inland, respectively, corresponding to the individuals of 840, 540, and 1504 sampled. According to the results, species diversity, richness, stand density, basal area (BA), and tree diameter at breast height (DBH) and height were significantly (p ≤ 0.05) greater in the hillside and inland homestead forests, compared to the beachside. Most abundant species, for example, Mangifera indica, Samanea saman, and Artocarpus heterophyllus in the inland and hillside homestead forests stored most C in biomass, compared to the beachside forest. Tree biomass C stocks were 48-67% greater in the inland and hillside than on beachside forests due to significantly (p ≤ 0.05) greater stand density, BA, and DBH. The overall C stock of litterfall was 0.1% of the total biomass carbon. C stock in soil surface was greatest in the hillside homestead forests due to the greatest litterfall. The total soil C stock was also affected by tree species, stand density and species richness, and their interaction with soil properties. Total soil C stocks across the depths were greatest (51 Mg ha-1) in the inland homestead forests, with the greatest stand density and species richness. ConclusionsHomestead forest ecosystems across the area stored total 96 Mg C ha-1, which thus can contribute to climate change mitigation while generating C credit for small-scale homestead forests owners as well as conserving biodiversity in Bangladesh and countries alike.

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Section: Discussionsupporting

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Effects of Tree Species Diversity and Stand Structure on Carbon Stocks of Homestead Forests in Maheshkhali Island, Southern Bangladesh

Baul

Chakraborty

Nandi

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Mean biomass carbon stock estimated (46 Mg C ha −1 ) in our case was close to that found (54 Mg C ha −1 ) in homestead forests in northern Bangladesh [ 17 ]. This, however, is lower than that found in the mangrove (99 Mg C ha −1 ; [ 22 ]) and total forests (49–121 Mg C ha −1 ; [ 12 ]) of Bangladesh. This disagreement could be explained by the lower overall species diversity and richness in our study, which indicates lower biomass C stock [ 15 ].…”

Section: Discussionmentioning

confidence: 58%

Effects of tree species diversity and stand structure on carbon stocks of homestead forests in Maheshkhali Island, Southern Bangladesh

Baul

Chakraborty

Nandi

et al. 2021

Carbon Balance Manage

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Background The homestead forests of Bangladesh occupy 0.27 million hectares (10% of the total forested area) and have potential to store carbon (C) and conserve biodiversity. Small scale forestry practices, however, are lacking reliable estimation of C stocks and tree species diversity. This may hinder successful implementation of REDD + and similar mechanisms as they concentrate on large-scale forests. This study aimed to estimate the above- and below-ground carbon stocks in homestead forests of Maheshkhali Island in Bangladesh and how tree species diversity and stand structural variation affect these C stocks. We randomly surveyed a total of 239 homestead forests in the hillside, beachside, and inland in 2019. Results Tree biomass C stocks were 48–67% greater in the inland and hillside forests than in the beachside due to significantly greater stand density, basal area, tree diameter. In total we found 52 tree species, but most abundant species in the inland and hillside forests, Mangifera indica, Samanea saman, and Artocarpus heterophyllus stored the most C in tree biomass. Greater tree species richness and diversity index in the inland and hillside forests indicated greater above- and below-ground tree biomass C stocks. An increase in tree species richness and diversity index by one unit was found to increase the tree biomass C stock by 22 and 30 Mg C ha−1, respectively. The total soil C stock was also affected by tree species diversity, stand density, and their interaction with soil properties. Total soil C stocks were greatest (51 Mg ha−1) in the inland forests, having also the greatest stand density and tree species richness. C stock in soil surface was greatest in the hillside forests due to the greatest litterfall, but the average share of litterfall from the total biomass C was only 0.1%. Conclusions Homestead forest ecosystems could store 96 Mg C ha−1 in total, which can contribute to climate change mitigation by generating C credits for small-scale homestead forests owners. Above- and below-ground tree biomass C stocks were found to correlate with tree species diversity, which may also contribute to biodiversity conservation in the REDD + in Bangladesh and countries alike.

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“…Bangladesh Forest Department in the forest and tree resources assessment (BFD 2007) reported that Bangladesh forests were containing on average 96 tC/ha. Ground-based studies like Alamgir and Turton (2014) reported that Bangladesh forest carbon density was 49-121 tC/ha depending on the vegetation type, where our estimate for Raghunandan falls in that range. Rahman et al (2014) reported that the average (median) above ground carbon density of Sundarbans mangrove forest was nearly 97 tC/ha.…”

Section: Estimation Of Biomass-carbon Dynamics Emission Factors and mentioning

confidence: 48%

“…using remotely sensed data. A number of studies provided a ground-based estimate of biomass-carbon for several forests or forest species in Bangladesh(Alamgir & Al-Amin 2007;Alamgir & Turton 2014;Rahman et al 2014;Shin, Miah & Lee 2008;Ullah & Al-Amin 2012). Studies concerning the estimation of biomass-carbon/emission using satellite image are rare in Bangladesh (Nishorgo Network 2011;Rahman, Csaplovics & Koch 2008).…”

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confidence: 99%

Mapping forest dynamics in Bangladesh from satellite images: implications for the global REDD+ program

Redowan¹

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Reducing emissions from deforestation and forest degradation (REDD+) is a global climate change mitigation initiative under negotiation by the United Nations Framework Convention on Climate Change (UNFCCC). This initiative provides financial incentives to developing countries for enhancing carbon stocks in their forests by abstaining from deforestation and forest degradation, which would lead to emission of CO2 into the atmosphere. To implement a REDD+ project, developing countries need to measure and monitor anthropogenic changes in their forests and as well as forest carbon to account for CO2 emissions and removals from such changes. It is also important to predict future scenarios of forest/landuse changes and to identify the areas at risk of changes so that appropriate conservation initiatives can be taken. Bangladesh is steadily progressing through its REDD+ roadmap. However, several key research issues still to address include: using remote sensing technology to detect deforestation, forest degradation and associated changes in forest carbon stock, and predict future forest/land-use pattern at local environmental setting. This study developed and evaluated approaches to detect the extent of historic (1995-2015) deforestation and forest degradation (Objective 1), to estimate the emissions of forest aboveground carbon due to deforestation and degradation activities (Objective 2), and to assess the future scenarios, driving forces and risk of deforestation and forest degradation (Objective 3) at Raghunandan Hill Reserve in northeastern Bangladesh using a combination of satellite and field-level data employing various geospatial, statistical and modeling tools. The thesis comprises seven chapters. The significance and background of the research along with aim, objectives, research questions and available literature on the topic were described in chapter 1, 2 and 3. Chapter 4 dealt with the first objective, where changes of forest areas to non-forest areas and one forest strata to another during 1995-2015 were detected with high accuracy (>90%) by applying Monte-Carlo spectral unmixing algorithm to Landsat images, followed by knowledge-based classification approach. The classification was verified using independent randomly drawn reference sample points using high-resolution Google Earth images. A post-classification comparison method was applied to quantify the spatial extent, location and rate of changes of forest classes by generating transition matrices. In chapter 5, emissions of carbon (t CO2e yr-1) from deforestation and forest degradation activities during 1995-2005 and 2005-2015 periods at Raghunandan forest were estimated using Landsat satellite and field-level biomass-carbon data applying regression analysis and geospatial techniques with acceptable accuracy. The accuracy of the estimate was verified using root mean square error iii (RMSE) of estimated carbon with field reference carbon. Results indicated that, during 1995-2005, the total estimated emission was 4589 tonnes (t) CO2e yr-1 from deforesta...

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Climate Change and Organic Carbon Storage in Bangladesh Forests

Cited by 5 publications

References 18 publications

Effects of Tree Species Diversity and Stand Structure on Carbon Stocks of Homestead Forests in Maheshkhali Island, Southern Bangladesh

Effects of Tree Species Diversity and Stand Structure on Carbon Stocks of Homestead Forests in Maheshkhali Island, Southern Bangladesh

Effects of tree species diversity and stand structure on carbon stocks of homestead forests in Maheshkhali Island, Southern Bangladesh

Mapping forest dynamics in Bangladesh from satellite images: implications for the global REDD+ program

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