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GEOLOGY, ECOLOGY, AND LANDSCAPES 2019, VOL. 3, NO. 1, 29–36 INWASCON https://doi.org/10.1080/24749508.2018.1481656 State of research on carbon sequestration in Bangladesh: a comprehensive review a b a Sahadeb Chandra Majumder , Kamrul Islam and Mohammad Mosharraf Hossain a b Institute of Forestry and Environmental Sciences, University of Chittagong, Chittagong, Bangladesh; Department of Systems Innovation, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan ABSTRACT ARTICLE HISTORY Received 21 March 2018 A deep interest is evident in carbon sequestration modeling in Bangladesh from the devel- Accepted 22 May 2018 opment of several allometric equations to estimate carbon sequestration by plants. It is linked to the evolving carbon oﬀsetting approaches, for example, Clean Development Mechanism KEYWORDS (CDM) and the REDD+, which require certiﬁable estimate of carbon captured by trees and Carbon stock estimation; forests. This review compiled a snapshot of state of the art in carbon modeling in Bangladesh. allometric equations; CDM; More than half of the published research focused on the development of allometric equations REDD+; carbon and forest carbon estimation. The comparison among available studies was challenging due sequestration to the use of diﬀerent terminologies and assumptions and arbitrary combinations of para- meters including age, topography, season, slope, crown diameter, etc. The spatial distribution of reports indicated narrow geographical focus outside forests in Chittagong and Sundarbans. Surprisingly, no attempts were evident to explore carbon stocks at the Chittagong Hill Tracts (CHTs) where majority of pristine forest areas of the country occurs. Bangladesh is likely to reforest the vast deforested areas in CHTs under CDM and REDD+ projects which requires extensive carbon modeling. Majority of the reports used conversion factor to calculate soil carbon instead of analytical estimation which might cause inaccurate estimation of soil carbon. Blue carbon assessment and policy implication of carbon studies are two areas where insuﬃcient attention is evident. Bangladesh apparently needs to conduct wide-scale carbon modeling through the integration of GIS, remote sensing, etc to increase precision and accuracy of carbon stock assessments. . 1. Introduction reduce global carbon emissions by about 120 PgC between 2016 and 2100. As forests, trees, or vegeta- Climate change – the outcome of anthropogenic glo- tion acts as the carbon sink, these can be used in bal warming – is the single biggest environmental devising mechanisms to cope with the adverse impact crisis facing Earth, which may lead to unfathomable of global climate change (Rahman, Sarker, & Hossen, humanitarian disasters (Mal, Singh, Huggel, & 2013; Shin, Miah, & Lee, 2007). Achievement of full Grover, 2018; Milfont, Wilson, & Sibley, 2017; carbon mitigation potential requires estimation of O’Beirne et al., 2017; Xue et al., 2017). In the ﬁfth country-level carbon stocks through statistically vali- assessment (AR5) of 2014, the Intergovernmental dated methods (Mahmood, Siddique, & Akhter, Panel on Climate Change (IPCC) asserted increasing 2016). As a signatory of the Kyoto protocol, concentrations of greenhouse gases (GHG) mainly Bangladesh needs accurate estimations of existing from anthropogenic activities as the cause of global carbon stocks throughout the country to implement warming (IPCC, 2014). AR5 climate model projected carbon trading CDM projects (Saatchi et al., 2011). a rise of global surface temperature by 0.3–1.7°C and Now, the Government of Bangladesh is taking initia- 2.6–4.8°C, respectively, under the lowest and the tives to meet up nation-wide carbon stock data and highest emission scenarios (Stocker et al., 2013). prepared the REDD+ Readiness Roadmap (BFD, AR6 expected to limit global warming within 1.5°C 2018). The reliable quantiﬁcation of carbon seques- (IPCC, 2018) by keeping GHG emission under check tration by vegetation will help the policy makers, through internationally binding instruments researchers, and entrepreneurs of developing coun- (Mehling, Metcalf, & Stavins, 2018; Weitzman, tries like Bangladesh to sell Certiﬁed Emission 2017) including carbon quota, Clean Development Reduction to developed countries (Ahammad, Mechanism (CDM), and REDD+. Houghton and Hossain, & Husnain, 2014; Ahmed & Glaser, 2016) Nassikas (2018) emphasized on arresting deforesta- in global carbon markets under REDD+ and CDM tion and allowing the secondary forests to grow to (Al-Amin, 2016; Shin, Miah, & Lee, 2008) as they CONTACT Kamrul Islam firstname.lastname@example.org; email@example.com Department of Systems Innovation, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan Supplementary data for this article can be accessed here. © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 30 S. C. MAJUMDER ET AL. need to oﬀset their higher per capita carbon emission. (BFD) with 10.20%, 4.08%, and 2.04%, respectively. Carbon estimation is also necessary for Bangladesh to Lead authors in published studies from BFD are unex- implement climate change mitigation policies (Miah pectedly low, though BFD is the government-accre- & Shin, 2009; Saatchi et al., 2011). Carbon stock dited organization to deal with such matters. Detailed estimation includes quantiﬁcation of soil organic car- information regarding the lead and co-authors’ institu- bon, carbon in living trees, understory vegetation, tion has been added in the Supplementary material 1. woody debris, and litters of forest ﬂoor in form of above-ground carbon and below-ground carbon 3.2. Focus of carbon sequestration-related (Gibbs, Brown, Niles, & Foley, 2007; Patra et al., research in Bangladesh 2013). In Bangladesh, researchers have estimated car- bon stocks in diﬀerent forms at diﬀerent parts of the Analysis of existing carbon sequestration-related stu- country and have developed allometric models. dies in Bangladesh (Figure 2) showed that majority, However, most of the available estimation is limited around 51.02%, focused on biomass carbon estima- to application of few variables that miss the vast pools tion. Mahmood et al. (2016) also reported similar of ecosystem carbon (Donato et al., 2011; Miah & ﬁndings in their study that covered the period Shin, 2009). Again, most of the works reﬂect allo- between 2011 and 2016. These studies included esti- metric equation of some common tree species, palm, mation of mainly above-ground biomass, while only a and shrub species (Mahmood et al., 2016). This study handful of studies included the below-ground bio- was undertaken in the pretext that it is now necessary mass estimation with speciﬁc equations. Majority of to review the geographic distribution of these studies the researchers just estimated below-ground carbon to check the coverage of diﬀerent forest types, carbon as 15% of the above-ground carbon. Species diversity pools, and robustness of models in terms of inclusion and forest fragmentation were considered for better of pertinent variables. Considering the above back- estimation of carbon stocks (Islam, Deb, & Rahman, drop, this review intends to specify the state of art in 2017). About 25% of the studies were on soil carbon carbon sequestration-related studies in Bangladesh. estimation which included gross estimation of soil carbon by using wet oxidation method and highlights of approaches to improve soil carbon stock. The 2. Analytical methodology other areas of studies were policy analysis and review (10.20%), blue carbon (10.20%), and GIS and remote- Current study is based mainly on the published lit- sensing application (4.08%). More detailed informa- erature related to carbon estimation in Bangladesh tion on major highlights of existing carbon studies in with investigation into some associated secondary Bangladesh is included in Supplementary material 2. data. The documents were collected exhaustively through online literature databases including Google Scholar, Nature, Springer Link, Science Direct, Plos, 3.3. Estimate of carbon by forest types Wiley online library, Tandfonline, and Cabdirect. Resource person consultation along with literature Carbon estimation at national scale for Bangladesh review from diﬀerent books, blogs, newspapers, thesis requires allometric models for all major forest types papers, term papers, essays, and statistical yearbook of the country and for the major species. The models has also been taken into consideration. A total of 49 also need to cover all possible carbon pools by taking studies were found relevant and considered for cur- ecosystem complexity into consideration. Researchers rent study. ISI indexing of research papers for choos- have been estimating carbon sequestration or stock ing them for current study was not considered, as for diﬀerent parts of the country by using diﬀerent only limited number of carbon studies exist for allometric equations as summarized in Table 1.It Bangladesh in ISI indexed journals. 2.04% Academic Institution 3. Findings and discussion 4.08% 10.20% Foreign Organizaiton 3.1. Source of carbon study researchers in Bangladesh Other Government Organizaiton 55.10% It is evident from current study (Figure 1)thatlead 28.57% NGO authors of published carbon studies focusing on Bangladesh Forest Department Bangladesh are mainly from academic institutions (55.10%). Surprisingly, second largest chunk in the pie (28.57%) is occupied by lead authors from foreign institutions, followed by other government organiza- Figure 1. Institutional attachments of lead researchers of tions, NGOs, and Bangladesh Forest Department carbon studies of Bangladesh. GEOLOGY, ECOLOGY, AND LANDSCAPES 31 Figure 2. Major focal areas of carbon sequestration related-studies in Bangladesh. shows the rates of carbon sequestration for diﬀerent rapid ﬂuctuations. The estimated total carbon forest types of the country according to the available stocks in Bangladesh forest ecosystems were literature. Contrary to the intuition, roadside planta- 251.8 million Mg in 2014 (Mukul et al., 2014), of tions showed the highest above-ground carbon which they estimated that a whopping 49.4% was −1 sequestration rate (165.81 Mg C ha ) among planta- stored solely at the Sundarbans mangrove forest. tion forests in Bangladesh followed by institutional Comparing to other mangrove-holding countries, −1 plantations (150.00 Mg C ha ). Among the natural Bangladesh lacks equivalent mangrove carbon −1 forests, protected areas (195.8 Mg C ha ) accumu- stocks. Hamilton and Friess (2018) found that lated the highest amount of above-ground carbon Bangladesh ranks three places lower globally if −1 followed by mangroves (76.80 Mg C ha ). Again, ranked upon mangrove carbon stocks in mangrove the estimated below-ground carbon for fast-growing area holding. −1 species (100.84 Mg C ha ) was compared to the −1 above-ground carbon (110.25 Mg C ha ). These 3.4. Forest areas covered: spatial distribution of anomalies dictate the necessity of developing more existing studies rational estimates and revisiting the counterintuitive results. Bangladesh has 2.56 million hectares of forestland Zomer et al. (2016) found around 20% of the including the hill forests in south-eastern and north- international studies suggested increasing rate in eastern hill forests, west and central Sal forests, total carbon stocks in Bangladesh. Interestingly, south-western and coastal mangrove forests with local studies showed the opposite trend with diverse plant species (BFD, 2018). We have found ﬁvearticles forthewholecountry emphasizingon carbon policy implications. Region-wise distribu- tionsofthestudiesareshownin Figure 3.The Table 1. Reported rates of above- and below-ground carbon highest number of studies (15 studies) was con- sequestration at diﬀerent forest types in Bangladesh. ducted on forests in Chittagong followed by 13 stu- Carbon stock sta- −1 tus (Mg C ha ) dies on Sundarbans mangrove forest. However, one Above Below of the main forest stock of the country in Chittagong Category ground ground Reference Hill Tracts remained unexplored in terms of carbon Mangrove 76.80 41.10 (Kamruzzaman, Ahmed, Paul, estimation. The rapid loss of vegetation cover in all Rahman, & Osawa, 2018) Bamboo 50.44 2.52 (Sohel, Alamgir, Akhter, & forest types may result in an estimated annual GDP Rahman, 2015) loss of 0.5–1.5% annually (Rahman et al., 2013). An Palm 22.35 (Dey, Islam, & Masum, 2014) Institutional 150.00 24.23 (Islam, 2013) intensiﬁed research on carbon stock estimation in plantation these forests is needed to ensure funding from car- Roadside 165.81 26.99 (Rahman, Kabir, Akon, & Ando, plantation 2015) bon oﬀsetting mechanisms to maintain the existing Fragmented 16.30 17.26 (Islam et al., 2017) vegetation with elevated reforestation eﬀorts (Shin forest Contiguous 31.21 21.62 (Islam et al., 2017) et al., 2007). The analysis in this review indicates the forest need for more elaborate geographic coverage of car- Home garden 44.29 8.00 (Jaman, Hossain, Islam, Helal, & bon estimation studies in the future. Detailed data Jamil, 2016) Fast growing 110.25 100.84 (Ullah, Banik, & Banik, 2014) on district-wise spatial distribution of existing car- species bon studies have been provided in Supplementary Protected 195.8 37 (BFD, 2018) areas material 3. 32 S. C. MAJUMDER ET AL. Figure 3. Spatial distribution of published studies on carbon estimation in Bangladesh. 3.5. Carbon estimation methods used compounded when someone used 0.50 (Dey et al., 2014; Islam, 2013; Shin et al., 2007) as the carbon Selection of rational allometric equations is the key to conversion factor from biomass and some other used objective estimation of carbon stock. Table 2 sum- 0.58 (Akter, Rahman, & Al-Amin, 2013; Sohel et al., marizes the commonly used equations in Bangladesh. 2015). Similarly, Rahman et al. (2013) subtracted 1.87 Though the number of allometric equations speciﬁc from loss on ignition during carbon percentage cal- to Bangladesh has increased, half of the models lack culation, while Sohel et al. (2015) subtracted 1.47. statistical validity. Mahmood et al. (2016) concluded that only 5% tree species and shrubs in Bangladesh have allometric equation to estimate the biomass. 3.6. Variables considered National Forest Assessment in Bangladesh in 2005– The allometric models depict relationship between 2007 used allometric equations developed for other diﬀerent variables related to trees including diameter countries as were in the Sundarbans carbon inventory at breast height (DBH), height of the tree trunk, total 2009–2010 (Chanda et al., 2016). Even though species height of the tree, crown diameter, height–diameter richness limits the use of species-speciﬁc allometric ratio (H/D), tree species richness, etc. (Hossain et al., equations (Mizanur, Khan, Hoque, & Ahmed, 2015), 2016a; Islam et al., 2017). The choice of these vari- the use of common equations of other countries will ables varied among diﬀerent studies. Also, some yield unreasonable estimates which posed doubt on reports considered hill slopes which deﬁnitely aﬀect the accuracy of national estimation (Ahiduzzaman the biomass yield (Haque & Karmakar, 2009; Shin and Islam, 2016; Mizanur et al., 2015). Carbon et al., 2007). Few papers considered the age to esti- sequestration rate under the same environment solely mate carbon stock for trunk, litter, and soil of planta- depends on the species (Nahiyan, Baidya, Dip, Sultan, tion species to get more accurate results (Shin et al., & Ahmed, 2017) which dictates the need to develop 2007). There are reports where herb, shrub, trees, and species-speciﬁc localized allometric equations (Aysha grass species were included in total carbon estimation et al., 2015; Mukul et al., 2014). In majority of the (Ullah & Al-Amin, 2012). Some researchers estimated studies, below-ground carbon stock was calculated as the carbon stock solely based on DBH (Dey et al., 15% of above-ground carbon stock (Miah, Uddin, 2014; Hossain et al., 2016a), while few one considered Bhuiyan, Koike, & Shin, 2009; Ullah & Al-Amin, 10–12 parameters (Rahman, 2004). Mizanur et al. 2012), but in another study, it was found 14% in (2015) found that dominant mangrove species are real ﬁeld (Rahman et al., 2015) which added further the key indicator of ecosystem carbon stock. Soil errors into the estimates. In addition, confusion GEOLOGY, ECOLOGY, AND LANDSCAPES 33 Table 2. Commonly used equations in carbon studies in Bangladesh. Name Expression Speciﬁcation Reference Above-ground biomass logY = logβ +β log X X = physical parameter of trees (Hossain et al., 2016b) 0 1 (e.g., height, DBH) Y = exp(−β +β In(D HS)) H = height (Akter et al., 2013; Alamgir & Al- 0 1 D = diameter Amin, 2007; Islam et al., 2017; S = oven dry density Shin et al., 2007; Ullah & Al-Amin, 2012; Ullah et al., 2014) Y= β +β X +β X Y = total carbon stock (Dey et al., 2014; Hossain, Saha, 0 1 1 2 2 X = physical parameter of trees Abdullah, Saha, & Siddique, 2016a; (e.g., height, DBH) Hossain & Banik, 2005; Ullah et al., 2014) Y= ρ.exp(−β +β InX+β InX ρ = wood density (Islam, 2013; Jaman et al., 2016; 0 1 2 −β InX ) X = physical parameter of trees Kamruzzaman et al., 2018; (e.g., height, DBH) Mizanur et al., 2015) β1 β2 Below-ground biomass BGB = β ρ D BGB = below-ground biomass (Kamruzzaman et al., 2018; Mizanur ρ = wood density et al., 2015) D = DBH BGB = exp(−β +β InAGB) AGB = above-ground biomass (Islam, 2013; Jaman et al., 2016) 0 1 BGB = 15% of the total above- (Islam et al., 2017; Miah et al., 2009; ground biomass Ullah & Al-Amin, 2012; Ullah et al., 2014) BGB = 20% of the total above- (Hanif, Bari, & Rahman, 2015) ground biomass Moisture content Moisture content (%) = (W2 W1 = weight of Petri dish (Akter et al., 2013; Alamgir & Al- −W3/W3−W1)×100 W2 = weight of Petri dish with Amin, 2007; Rahman et al., 2013; moist soil Sohel et al., 2015; Ullah & Al-Amin, W3 = weight of Petri dish with dry 2012) soil Loss on ignition (LOI) LOI (%) = (W1/W2)×100 W1 = loss in weight W2 = weight (Rahman et al., 2013; Sohel et al., of oven dry soil 2015) Carbon (%) from LOI Carbon (%) = 0.476×(%LOI–1.87) (Rahman et al., 2013) Carbon (%) = 0.476×(%LOI–1.47) (Sohel et al., 2015) Carbon in the stand by using GIS and Carbon, C = ƒ(D,A,L,R,H, O,S,F,P, D = average tree diameter at (Al-Amin, 2016; Rahman, 2004) remote sensing Cr,B,W) breast height A = stand age L = leaf area index H = canopy height O = canopy cover R = total area of the stand S = stems per unit area F = forest type P = species Cr = crown height B = bole height W = crown width Cl = leaf cluster index organic carbon content is inﬂuenced by microbial 3.8. Prospects ahead: carbon market activity (Rasid, Chowdhury, & Osman, 2016), pH Global carbon markets are either “ﬁnancing to maintain (Bangladesh Rice Research Institute, 2014; Hossain, compliance” or “voluntary forest carbon markets.” CDM 2016), soil depth (Saha, Rahman, Khatun, Hossain, & projects exemplify the former, while Bio-Carbon Fund Saleque, 2014), and applied fertilizer type (Rahman, managed by the World Bank exempliﬁes the latter. On 2015; Rahman et al., 2016). Again, type of forest the other hand, REDD+ has a broader domain of applic- whether it is fragmented or continuous inﬂuences ability (Ahmed & Glaser, 2016)asitmainlyfocuses to the carbon content signiﬁcantly (Islam et al., 2017). conserve the tropical forests through carbon payment. Holistic models are therefore necessary which take Some studies suggested the possibility of reforestation of into account all pertinent variables in carbon Bangladesh’s large area of degraded land under CDM estimation. and REDD+ (Miah & Shin, 2009; Saatchi et al., 2011; Shin et al., 2007). There are other approaches as Dey et al. (2014)showedthe signiﬁcance of palm trees, and Sohel 3.7. Anomalies in units et al. (2015) showed the applicability of bamboo in Researchers used diﬀerent units to show carbon carbon sequestration, while Ahiduzzaman and Islam −1 stocks including “Metric ton ha ” (Dey et al., (2016) showed the possibility of using rice husk energy −1 2014), “Mg C h ” (Barua & Haque, 2013; Islam, to substitute 4.66 million ton wood fuel annually to save −1 2013; Rahman et al., 2015), and “Ton h ” (Islam 24.14 thousand hectares of forest equivalent that may et al., 2017; Sohel et al., 2015; Ullah et al., 2014), sequester 7.45 million ton of CO per annum. Similarly, while “ton-year” was a more suitable unit in consid- Islam (2013) showed the signiﬁcance of institutional eration of CDM (Shin et al., 2007). plantation in carbon sequestration. Few researchers 34 S. C. MAJUMDER ET AL. proposed using REDD+ to check blue carbon emission References duetotheshrinkageofmangroves andextension of Ahammad, R., Hossain, M. K., & Husnain, P. (2014). coastal aquaculture (Ahmed, Cheung, Thompson, & Governance of forest conservation and co-beneﬁts for Glaser, 2017;Ahmed &Glaser, 2016;Ahmed, Bangladesh under changing climate. Journal of Forestry Thompson, & Glaser, 2018;Hussain,Failler,Karim,& Research, 25,29–36. Ahiduzzaman, M., & Islam, A. K. M. S. (2016). Assessment Alam, 2018;Islam, 2016). Roads and community-based of rice husk briquette fuel use as an alternative source of home gardens were promoted in few reports to ensure woodfuel. International Journal of Renewable Energy reforestation by Payment for Environmental Services Research, 6, 1602–1611. (PES) under UNFCCC’s carbon mitigation strategies Ahmed, N., Cheung, W. W. L., Thompson, S., & Glaser, M. (IPCC, 2018; Mehling et al., 2018; Stocker et al., 2013). (2017). Solutions to blue carbon emissions: Shrimp cul- tivation, mangrove deforestation and climate change in coastal Bangladesh. Marine Policy, 82,68–75. Ahmed, N., & Glaser, M. (2016). Coastal aquaculture, 4. Conclusion and policy recommendations mangrove deforestation and blue carbon emissions: Is REDD+ a solution? Marine Policy, 66,58–66. There are anomalies in the estimates of carbon Ahmed, N., Thompson, S., & Glaser, M. (2018). Integrated among published reports due to the variations in mangrove-shrimp cultivation: Potential for blue carbon the models and assumptions used for the estimation sequestration. Ambio, 47, 441–452. of carbon stock. Accordingly, global studies showed Akter, S., Rahman, M., & Al-Amin, M. (2013). Chittagong increasing carbon stock trend in Bangladesh, while university campus: Rich in forest growing stock of valu- local studies showed the opposite. On the other hand, able timber tree species in Bangladesh. Journal of Forest and Environmental Science, 29, 157–164. the concentration of studies did not represent all Alamgir, M., & Al-Amin, M. (2007). Organic carbon sto- important forest areas, and there is a general lack of rage in trees within diﬀerent Geopositions of Chittagong species- and ecosystem-speciﬁc carbon estimation (south) forest division, Bangladesh. Journal of Forestry models, while available models lack in stringent sta- Research, 18, 174. tistical validation. Bangladesh needs more studies to Al-Amin, M. (2016). Forest carbon stock measurement to management: Perspective REDD+ in Bangladesh. 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Geology Ecology and Landscapes – Taylor & Francis
Published: Jan 2, 2019
Keywords: Carbon stock estimation; allometric equations; CDM; REDD+; carbon sequestration
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