A comparative study on the carbon storage and oxygen release capacity of Swietenia macrophylla king. and Eucalyptus camaldulensis Dehn. in northwest Bangladesh

A comparative study on the carbon storage and oxygen release capacity of Swietenia macrophylla king. and Eucalyptus camaldulensis Dehn. in northwest Bangladesh | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A comparative study on the carbon storage and oxygen release capacity of Swietenia macrophylla king. and Eucalyptus camaldulensis Dehn. in northwest Bangladesh Mohammed Mukhlesur Rahman, Mizanur Rahman, Md. Najmus Sayadat Pitol This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5348859/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Plantation sequesters atmospheric carbon and produces oxygen through photosynthesis and stores it as a reserve. Estimating the carbon sequestration capacity of forest tree species is essential for implementing massive plantation programs in developing countries such as Bangladesh. The present study was conducted on the carbon storage and release oxygen capacity of Swietenia macrophylla and Eucalyptu s camaldulensis which were planted forest tree species in the same ecological condition. Allometric equations were applied to estimate organic carbon in two species of trees. The diameter increased with increasing height and positive correlations were found in S. macrophylla and E. camaldulensis respectively ( p < 0.05). The maximum carbon storage of S. macrophylla and E. camaldulensis were 17.24 kg tree − 1 year − 1 and 21.73 kg tree − 1 year − 1 at twenty years old tree respectively. The lowest carbon storage of S. macrophylla and E. camaldulensis were 5.03 and 9.24 kg tree − 1 year − 1 at five years old, respectively. There was no significant difference (df = 11; p = 0.658) found between the DBH of the two species while their DBH were significantly different among their ages (df = 11; p = 0.000). Besides, the height of these two species was significantly difference (df = 11; p = 0.002) but not significant in their ages (df = 11; p = 0.694). The height and DBH growth became slower with the increase of the age of the plantations. The biomass, carbon stock, carbon-di-oxide storage and O 2 releasing potentiality were related to each other and significantly differed from their ages (p-value varied from 0.001 to 0.023). Comparatively higher growth performances were observed in E. camaldulensis than S. macrophylla in the same environmental conditions, management and equal ages. The findings indicated that S. macrophylla and E. camaldulensis both can be selected in the massive plantation programs in this area which will contribute to large carbon storage and play a vital role in mitigating climate change. Plantation non-destructive method biomass carbon global warming Figures Figure 1 Figure 2 Figure 3 Introduction Declination of biodiversity and increased CO 2 have been recognized as two major concerns nowadays (Kumar, 2011). One is the result, and another is the cause of global warming and climate change while the plantations are the most important tool for reducing their effects. We know only plants can seize the atmospheric CO 2 through photosynthesis, store it as biomass, and produce a massive quantity of oxygen (Lukito and Rohmatiah, 2013, Pitol and Mian, 2023). Plantation may lead to the enhancement of forestation though it reduces the diversity (Rahman et al. 2021). There are two types of plantations (such as artificial and natural plantations) (Menne, 2015) while the number of artificial plantations is increasing more rapidly than natural plantations in the tropical regions of the world. Artificial forests contribute to the declining pressure on timber extraction from natural forests and play a vital role in the conservation of forest resources (Kaul et al ., 2010). It is not possible to increase the forest and agriculture lands, but the production will be maximized by converting the traditional lands into sustainable uses like agroforestry home gardens, tea plantations and woodlot plantations (Nair and Kumar. 2006, Pitol et al. 2019). Plantation forests give us hope for sustainable use of forest resources. Approximately, the world has 187,086 (000 ha) plantation forests with a new planting rate of 4493(000 ha) per year (FAO 2010). Planted forests supply 35% of total wood demand with a projected increase to 44% by 2020 (FAO, 2010, ABARE & Jaakko Pöyry, 1999). Homestead forests have enormously increased in different parts of Bangladesh to fulfill the wood and fuel wood demand. They are increased based on special types of timber species which are fast growing and highly timber quality. The selection of plant species plays a vital role in mitigating global warming. In Bangladesh, the plantation forests increased from 238.81 (000 ha) to 278.11(000 ha) from 1990 to 2005 (FAO, 2010) while Jashimuddin and Inoue (2012) recorded that 48,420 ha of roadside plantations, 30,666 ha of woodlots and 8778 ha of agroforestry plantations during the last 30 years. However, the plantation activities are continuing without assessment of the carbon storage capacity of tree species in many regions of the world as well as Bangladesh. There is an urgent need to estimate biomass, carbon storage and released oxygen in different species for implementing massive plantation programs. Biomass is an important parameter to assess the assimilation of carbon by plants. Biomass and carbon storage play an important role in the global carbon cycle (Cairns et al ., 2003; Li et al ., 2011; Zhao et al ., 2014) and are now considered for creating any woodlot (Ekholm 2016; Gren and Zeleke 2016; Riutta et al. 2018; Nonini and Fiala 2019; Rinnamang et al. 2020). Normally, homestead forests are established with single tree species which is known as monoplantation. Monoplantations are increasing a geometrical rate in northern parts of Bangladesh to fulfill the local wood-related demands. Numerous experts recommended that the homestead flora of Bangladesh provides about 70% of all wood consumed and 90% of all fuel wood and bamboo (Alam et al ., 1990). Many kinds of exotic and indigenous forest tree species are planted in the homestead forests of Bangladesh while Swietenia macrophylla and Eucalyptus camaldulensis are the best choice for their fast-growing and well adaptable potentiality. Private landowners plant fast-growing tree species for local consumption such as fuel wood, poles, posts, and small wood and cottage industries (BBS, 2014). Moreover, the adaptation ability, growth performances and carbon storage capacity of planted tree species in most of the areas in Bangladesh have not been estimated yet. It is essential to know the role of plantation forests in carbon trade and ecosystem services (Nair, 2012). It improves the country’s negotiations for REDD + and carbon trade mechanisms (Nair, 2012; Jashimuddin and Inoue, 2012). Direct and indirect methods are mostly used for biomass calculation while indirect methods are based on allometric equations using measurable parameters (Salazar-Iglesias et al., 2010). This method is easy and suitable for the estimation of carbon storage in tropical forests (Razakamanarivo et al., 2012; Rahman, et al., 2019). Therefore, keeping this point in mind, an attempt was made to estimate a comparative study of the biomass, carbon storage and oxygen release between Swietenia macrophylla and Eucalyptus camaldulensis in the northern district of Bangladesh. The findings of the study will provide essential data on biomass, carbon storage and oxygen release which will be used for carbon monitoring at the national and international levels. Materials and Methods The study area The study was conducted on homestead forest areas at Natore Sadar upzila of Natore district in Bangladesh. Geographically, the study area is situated between 24 0 07ʹ to 24 0 43ʹ north latitudes and between 88 0 17ʹ to 88 0 58ʹ east longitudes (Fig. 1 ). This area falls under the tropical region, also known as Bangladesh's hottest district. The climatic condition is a hot-humid summer with moderate rainfall and a mild winter with foggy sometimes. The summer season is considered from April to the last of June. The rainy season starts at the end of June and stays up to September. The winter season comes from the middle of November and lasts up to the end of February. Temperature variation appears that the average annual temperature is about 26-36 0 C. The minimum and maximum mean temperature during winter varies from 9 0 to 14 0 C. The minimum and maximum mean temperatures vary from 25.50 0 C to 40.70 0 C during summer. The soil of the study area is rich in alluvium and clay texture with pH 7. 22 on average. This soil is perfect for agriculture and horticulture (BBS, 2022). The study area was covered by various planted timber tree species. The following planted species were dominant such as Mangifera indica, Azadirachta indica , Swietenia macrophylla, Albizia richardiana, Eucalyptus camaldulensis , Samanea saman, Artocarpus heterophyllus, Delonix regia, Caesalpinia pulcherrima and Citrus maxima etc. Homestead forests are accelerating at a geometrical rate to fulfill the demand for fuel wood and timber. Massive plantations have been started in the study area with the help of some selected forest tree species. Before plantation, the area was included in cultivation land and different types of agronomical and horticultural crops were grown such as Oryza sativa, Corchorus capsularis, Saccharum officinarum, Litchi chinensis, Manilkara zapota, Ziziphus mauritiana, Averrhoa carambola, Psidium guajava and Musa sapientum , etc. Sampling and measurements The study was carried out from January 2023 to December 2023. A systematic sampling method was used for the selection of plots. The geographical location of each plot was recorded using a global positioning system (GPS) and the size of each plot was 10 m×10 m. A total of land was 20 hectares for each species separately. Brown’s model (Brown et al ., 1989) was used to estimate the aboveground biomass of each tree of each experiment plot. Several scientists suggested that allometric equations are one of the most suitable methods for biomass estimation in tropical forests (Alves et al ., 1997; Schroeder et al. , 1997). Trees height and diameter at breast height (DBH > 5cm) from ground level (1.30 m) of all trees were measured using a clinometer and DBH tape respectively. Trees on the border were included in a plot if 50% of their basal area fell within the plots and excluded if 50% of their basal area fell outside the plot. Trees overhanging the plots were excluded, but with their trunk inside the sampling plots, and branches out were included. Care was taken to ensure the diameter tape was put on the stem exactly at the measurement point. Biomass, carbon stock, CO and release O estimation The study was conducted in planted forest areas and all trees were measured with the help of tape and a clinometer. It was impossible to cut all the trees to estimate of biomass and carbon of trees. Some models were developed by Brown (1997), Luckman et al . (1997), Negi et al . (1988) and Brown et al . (1989). Brown’s models (Brown et al ., 1989) was used to determine aboveground biomass because this method is the most suitable method for tropical forests (Alves et al . 1997; Brown 1997; Schroeder et al. 1997; Miah et al . 2011; Ullah and Al-Amin, 2012). This is the simplest method of estimating forest tree biomass in the tropics as it requires only tree diameter at breast height, total height and wood-specific gravity. While other models or regression equations require sectional diameter, this simply deals with diameter at breast height. The model is as follows: Y = exp. {-2.4090 + 0.9522 ln (D 2 HS)} Where Y = Aboveground biomass in kg, H = Height of the trees in meters, D = Diameter at breast height (1.30 m) in cm, and S = Wood density in units of tons m − 3 for a specific species (Brown 1997; Sattar et al . 1999). Using these models’ the aboveground biomass of each tree was estimated. From aboveground biomass of each individual’s tree was calculated and biomass was converted to tons ha − 1 and added to get the total aboveground biomass. Belowground biomass was calculated considering 15% of the aboveground biomass (MacDicken 1997; IPCC 2003; Miah et al. 2011). Belowground biomass was calculated for each tree. Aboveground and belowground biomass of trees was added to get the total biomass of trees. BGB = AGB X (20/100). The total carbon (TC) of the tree was determined by using the following formula. TC= (AGB + BGB) 🞨0.50 Where, 0.50 is the conversion factor (Schroeder, 1997). Besides, the carbon-di-oxide capturing (CO 2 ) was calculated by multiplying the total carbon stock by 3.67 (Kauffman and Donato, 2012) and then the released oxygen was calculated by multiplying the total carbon-di-oxide capturing by 0.727 (Pitol and Mian, 2022). Data analysis Biomass and carbon storage per tree were finally calculated using Xcel-365 software and figures were also made using Xcel and PowerPoint-365. Analysis of variance (ANOVA) was performed by using Statistical Package for Social Science (SPSS-20). Results Diameter and height of different ages plantations Diameter, height and wood density are the most important indicators for estimating biomass and carbon of trees. Biomass and carbon were calculated based on the diameter, height and wood density of planted forest tree species in the study area. The study revealed that the diameter and height were 27.78 cm and 29.65cm; and 17.44m and 9.55m were found in Eucalyptus camaldulensis and Swietenia macrophylla at 20 years old respectively (Fig. 2 ). There was no significant difference (df = 11; p = 0.658) found between the DBH of the two species ( Appendix 1 ) while their DBH were significantly different among their ages (df = 11; p = 0.000) ( Appendix 2 ). Moreover, the height of these two species was significantly difference (df = 11; p = 0.002) but not significant in their ages (df = 11; p = 0.694) ( Appendix 1 and Appendix 2 ). Comparatively higher growth performances were observed in E. camaldulensis than S. macrophylla in the same environmental conditions, management and equal ages (Fig. 1 ). Mean Annual increment of diameter, height, biomass, carbon stock, CO 2 capturing and O 2 releasing potentiality of different ages plantations The mean annual increment of DBH was insignificant (df = 11; p = 0.629) between these two species when they significantly varied among the ages (df = 11; p = 0.000). Besides, the mean annual height increment was significantly varied (df = 11; p = 0.034) between these two species when they were not considerably diverse among the ages (df = 11; p = 0.321). It was found that the mean annual diameter increments and mean annual height increments were 1. 93cm and 2. 06 cm; and 0.78m and 1. 24 m for S. macrophylla and E. camaldulensis respectively (Fig. 3 ). The present study revealed that the value of the mean annual diameter increments and mean yearly height increment of E. camaldulensis was comparatively higher than S. macrophylla. The height and DBH growth became slower with the increase of the age of the plantation. The aboveground biomass, belowground biomass, total biomass, aboveground carbon, belowground carbon, total carbon, carbon-di-oxide storage and O 2 releasing potentiality were related to each other and significantly differed from their ages (p-value varied from 0.001 to 0.023). The value was maximum for both species in 20-year-old plantations and minimum for 5-year-old plantations (Table 1 ). The highest aboveground biomass, belowground biomass and total biomass were 574.55 kg tree − 1 , 114.91 kg tree − 1 , 689.46 kg tree − 1 and 724.38 kg tree − 1 , 144.88 kg tree − 1 , 869.26 kg tree − 1 in S. macrophylla and E. camaldulensis at twenty years old respectively (Table 1 ). The lowest aboveground biomass, belowground biomass and total biomass were 41.94 kg tree − 1 , 8.39 kg tree − 1 , 50.33 kg tree − 1 and 76.99 kg tree − 1 , 15.40 kg tree − 1 , 92.39 kg tree − 1 in S. macrophylla and E. camaldulensis at five years old respectively (Table 1 ). Moreover, the maximum aboveground carbon, belowground carbon and total carbon were 287.28 kg tree − 1 , 57.46 kg tree − 1 , 344.73 kg tree − 1 and 362.19 kg tree − 1 , 72.44 kg tree − 1 , 434.63 kg tree − 1 in S. macrophylla and E. camaldulensis at twenty years old. The lowest aboveground carbon, belowground carbon and total carbon were 20.97 kg tree − 1 , 4.19 kg tree − 1 , 25.16 kg tree − 1 and 38.50 kg tree − 1 , 7.70 kg tree − 1 , 46.20 kg tree − 1 in S. macrophylla and E. camaldulensis at five years old (Table 1 ). However, the carbon storage varied from 5.03 to 17.24 kg tree − 1 year − 1 while capturing CO 2 varied from 18.46 to 63.26 kg tree − 1 year − 1 and releasing O 2 varied from 13.42 to 45.99 kg tree − 1 year − 1 for S. macrophylla . In addition, the carbon storage varied from 9.24 to 21.73 kg tree − 1 year − 1 while capturing CO 2 varied from 33.91 to 79.75 kg tree − 1 year − 1 and releasing O 2 varied from 24.65 to 57.98 kg tree − 1 year − 1 for E. camaldulensis (Table 1 ). Table 1 Aboveground biomass, belowground biomass, total biomass, aboveground carbon, belowground carbon, total carbon, carbon storage, CO 2 capturing and O 2 releasing potentiality of Swietenia macrophylla an d Eucalyptus camaldulensis in different ages Species Name Age of Plantation (years) AGB per tree (kg) BGB per tree (kg) TB per tree (kg) AGC per tree (kg) BGC per tree (kg) TC per tree (kg) Carbon storage kg tree − 1 year − 1 Capturing CO 2 kg tree − 1 year − 1 Releasing O 2 kg tree − 1 year − 1 Swietenia macrophylla 5 41.94 8.39 50.33 20.97 4.19 25.16 5.03 18,46 13.42 8 72.14 14.43 86.57 36.07 7.21 43.28 5.41 19,85 14.43 10 98.16 19.63 117.79 49.08 9.82 58.90 5.89 21,62 15.72 12 174.13 34.83 208.96 87.06 17.41 104.48 8.71 31,95 23.23 15 326.20 65.24 391.44 163.1 32.62 195.72 13.05 47,89 34.82 20 574.55 114.91 689.46 287.28 57.46 344.73 17.24 63,26 45.99 Eucalyptus camaldulensis 5 76.99 15.40 92.39 38.50 7.70 46.20 9.24 33,91 24.65 8 115.58 23.12 138.70 57.79 11.56 69.35 8.67 31,81 23.13 10 169.07 33.81 202.88 84.53 16.91 101.44 10.14 37,23 27.07 12 259.51 51.90 311.41 129.75 25.95 155.70 12.96 47,62 34.62 15 418.36 83.67 502.03 209.18 41.84 251.01 16.73 61,41 44.65 20 724.38 144.88 869.26 362.19 72.44 434.63 21.73 79,75 57.98 **AGB = Aboveground biomass, BGB = Belowground biomass, TB = Total biomass, AGC = Aboveground carbon, BGB = Belowground carbon and TC = Total carbon Discussion The basic two functions of trees are capturing carbon dioxide and producing oxygen for curbing climate change and survival of life on this earth respectively. Nowadays we are concerned about the carbon and carbon dioxide storage capacity of trees. In this study, we also checked the oxygen release potentiality of two widely used fast-growing species in Bangladesh. Comparatively higher growth performances were observed in E. camaldulensis than S. macrophylla in the same environmental conditions, management and equal ages. It revealed that the diameter and height were 27.78 cm and 29.65cm; and 17.44m and 9.55m in Eucalyptus camaldulensis and Swietenia macrophylla at 20-year-old plantations respectively. The height of S. macrophylla increased very slowly and E. camaldulensis was very fast while both showed similar dbh growth (Fig. 2 ). Normally growth parameters are mainly influenced by genetic criteria which is known as genotype. In this regard, the following equation may be regarded as phenotype = genotype + environment. The present findings indicated that growth performances varied between the two species due to the genotypic criteria. The phenotype depends on genotype and environmental factors. Several scientists worked on the estimation of the diameter and height of forest tree species in Bangladesh. Rahman (2022a) found that the dbh and height of Casuarina equisetifolia at Inani and Teknaf Forest Ranges 14.10 cm and 12.70 m; 17.10 cm and 17.10 m; and 23.54 cm and 20.33 m for 5-years, 10-years and 20-years old plantation separately. (Rahman, 2022b. Besides, the dbh and height of Acacia auriculiformis were 5.03 cm and 4.27 m; and 10.35 cm and 8.28 m for 5-year and 10-year plantations at Pomra, Hosnabad, Rajanagar and Parua Forest Ranges under the Chattogram North Forest Division in Bangladesh respectively (Rahman, 2022b). Dey et al. (2022) found the dbh and height of Eucalyptus camaldulensis were 10.6 m and 11.9 cm for a 5-year plantation, and 30.9 m and 42.7 cm for a 21-year plantation while Azad et al. (2021) found the dbh for 10.14 cm, 26.47 cm and 29.21cm for 5-year, 15-year, and 20-year plantations individually. It seemed that the height and dbh growth of E . camaldulensis was higher at every year plantations than the C . equisetifolia , A. auriculiformis and S. macrophylla and very close to Hevea brasiliensis plantations. In our study, the mean annual diameter increments and mean annual height increments were 1. 93cm and 2. 06 cm; and 0.78m and 1. 24 m for S. macrophylla and E. camaldulensis respectively (Fig. 3 ). The present study revealed that the value of the mean annual diameter increments and mean yearly height increment of E. camaldulensis was comparatively higher than S. macrophylla. Moreover, the height and DBH growth became slower with the increase of the age of the plantation. It exhibited that the tree grows faster at an early age. However, the mean annual diameter increment rate and mean annual height increment rate also varied from species to species and age to age. The mean annual diameter increment rates were 3.08 cm, 1.71 cm and 1.17 cm while the mean annual height increment rates were 2.54 m, 1.71 m and 1.02 m found in Casuarina equisetifolia at 5, 10 and 20-year trees (Rahman, 2022b). In addition, the mean annual diameter increment rates were 1.01 cm and 1.04 cm found in Acacia auriculiformis while the mean annual height increment rates were 0.94 m and 0.91 m found in Acacia auriculiformis at 5 and 10-year trees. There was a positive correlation between diameter and height, but the diameter and height rates varied from species to species. The biomass, carbon, carbon-dioxide storage and O 2 -releasing potentiality were related to each other and significantly differed from their ages (p-value varied from 0.001 to 0.023). There was a positive relation between the age and biomass, carbon, carbon-dioxide storage, and O 2 -releasing potentiality of trees. The present study was conducted in the northern parts of Bangladesh which is situated in the hottest tropical regions of Bangladesh. Normally, biomass and carbon storage vary in different regions of the world. Scientists observed that carbon storage capacity varied from species to species due to ecological and management conditions (Rahman et al., 2019, 2020). A study was conducted in the tropical forests of Badamalai hills in India and reported that the average carbon stock of single tree species was 0.04tC/tree. It was also reported that the maximum value was 0.68 t C/tree found in Ficus benghalensis , followed by Tamarindus indica, Spondias pinnata, Diospyros ebenum and Ficus beddomei 0.51 t C/tree, 0 46 t C/tree, 0.30 t C/tree, and 0.22 t C/tree respectively (Pragasan et al. , 2015). In this case, their findings were higher than the findings of the present study. However, wide variations in the biomass potential of a tree may occur due to differences in provenances, stand density, tree age, site characteristics, management, etc. Several scientists (observed that the total aboveground biomass in the range of 9.80 to 306.01 kg tree − 1 for Gmelina arborea and 7.25 to 314.61 kg tree − 1 for Swietenia Macrophylla (Kawahara et al ., 1981; Pitol et al. 2019; Pitol and Mian, 2022). On the other hand, Buante (1997) observed the total aboveground biomass of Acacia auriculiformis and Gmelina arborea in the ranges of only 15.71 to 49.08 kg tree − 1 and 9.18 to 68.58 kg tree − 1 . The following tree species were included such as Eucalyptus deglupta, paraserianthes falcataria, Swietenia macrophylla, Acacia auriculiformis and Gmelina arborea and their values were 365.70 kg tree − 1 , 90.70 kg tree − 1 , 156.30 kg tree − 1 , 248.20 kg tree − 1 and 114.80 kg tree − 1 respectively (Dey et al. 2022; Kawahara et al ., 1981; Pitol et al. 2019; Pitol and Mian, 2022. Generally, the total biomass and carbon were estimated based on aboveground and belowground biomass all over the world. Several scientists reported that total biomass and carbon varied from species to species and different ages such as 776.90 kg tree − 1 to 1574 kg tree − 1 biomass was found in Mangifera indica at 25 years old (Ganeshamurthy et al. , 2016). Carbon dioxide is the most effective greenhouse gas which traps heat and increases temperature in different levels of the atmosphere. The elevated temperature adversely affects biotic and abiotic components of all types of ecosystems which is the main obstacle to the sustainable development of the environment. In this case, plantations sequester carbon dioxide and produce oxygen from the atmosphere through photosynthesis and act as sinks which help to reduce global warming. Carbon storage capacity is the most important for the development of plantations based on species. The same species contained different amounts of carbon when grown in different regions. Scientists observed variations in carbon storage with the age of the forest, stand condition, species composition, climate condition, physiographical position and degree of disturbance (Kanime et al. , 2013 and Kumar et al ., 2016). Biomass, carbon storage, CO 2 and oxygen release assimilation vary with species. Scientists reported that higher values were found in Eucalyptus spp. while it was the lowest value in S. javanica (Ganeshamurthy et al. , 2019). Some species such as C. camphora, S. babylonica, P. roxburghii G. robusta and Diospyros sp. also have high values of carbon storage, and carbon assimilation. Some species particularly, M. koenigii, Mimosasp., F. auriculata, F. lacor and Dalbergia sp. have low values. Myrtaceae was the family with the highest carbon storage, carbon assimilation and followed by Lauraceae Salicaceae and Pinaceae (Kaul et al ., 2010). Maximum scientists (Chave et al ., 2014) opined that carbon sequestration depends on single or multiple factors such as age, size, density and climatic conditions, etc. However, our study was conducted in a narrow zone of the country. A massive survey is required to assess the feasibility and potentiality of plantation forests. It is also a prerequisite for our fair share in the global carbon trade mechanism. Conclusion Plantation sequesters carbon dioxide and acts as a carbon sink and oxygen source in the atmosphere. Elevated carbon dioxide in the atmosphere is harmful to all living organisms of the terrestrial environment. So, plantations should be increased to continue the equilibrium balance of the environment. The present findings of the study indicated that planted forests with fast-growing tree species play a vital role in sequestering carbon and generating oxygen and their utilization demands are also high for the quality of timber and fuel wood. It is also remarkable that the planted forest tree species are well adapted to the selected study areas. The socio-economic conditions can be easily developed through applying silviculture methods in the social plantation programs. Therefore, policymakers, administrators and planters can choose Swietenia macrophylla an d Eucalyptus camaldulensis for the massive plantations based on environmental conditions. Declarations Acknowledgment The authors would like to be grateful to the owners of the orchards in different locations. The orchard’s owners entirely help during the research period. The authors are highly thankful to the owners of the orchards for the permission to survey their areas during the survey. In addition, they provided the following information source of seeds, age of trees, plantation period and management techniques. Declaration of Interests The authors declare that there are no competing interests. Ethics and Biosecurity Statement We conducted our survey in private woodlands and home garden areas. We took the permission of the owner of the home gardens and woodlots. The authors also declared that no trees were damaged during the study. We did not use quarantine organisms or take any data from any protected areas. The scientific names of the two species we used followed the guidelines of the International Code of Nomenclature for algae, fungi, and plants. Data Availability Statement Data will be made accessible on request. 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K., Singh, R., Singh, K., Rai, P., Pandey, C. B. and Sharma, D. K. (2016). Biomass estimation and carbon sequestration in Populus deltoids plantation in India. Journal of Soil Saline Water Quality , 8(1): 25-29. Kuyah, S., Dietz, J., Muthuri, C., Noordwijk, M. V. and Neufeldt, H. (2013). Allometry and partitioning of above and belowground biomass in farmed eucalyptus species dominant in western Kenya agricultural landscapes. Biomass and Bioenergy , 55: 276-284. Li, X., Yi, M. J., Son, y., Park, P.S., Lee, K. H. and et al . (2011). Biomass and carbon storage in an age sequence of Korean pine ( Pinus karaiensis ) plantation forests in central Korea. Journal of Plant Biology , 54(1): 33-42. Luckman, A., Baker, J., Mora, T., Corina-da-Costa, F. and Frery, C. A. (1997). A study of the relationships between radar backscatter and regeneration tropical forest biomass for space borne SAR instruments. Remote Sens Environ., 60: 1-13. Lukito, M., & Rohmatiah, A. (2013). Estimated biomass and carbon of teak 5-year (Case of Nusantara Superior Teak Plantation Forest (JUN) Krowe Village, Lembeyan District, Magetan Regency). Agritek J 14 (1), 1–23. https://doi.org/10.12988/asb.2017.7924. Mac Dicken, K. G. (1997). A guide to monitoring carbon storage in forestry and agro forestry projects USA. Winrock Int. Institute Agri. Development, P-19-99. Menne, W. (2015). Important differences between timber plantation and forests . World rainforest Movement, South Africa. Miah, M. D., Shin, M.Y. and Koike, M. (2011). Forests to climate change mitigation: clean development mechanism in Bangladesh. Springer-Verlag Berlin Heidelberg, ISBN 978-3-642-13252-0. Nair, P.K.R., & Kumar, B.M. (2006) Introduction. In: Kumar BM, Nair PKR (eds) Tropical homegardens: a time-tested example of sustainable agroforestry. Springer, Dordrecht, pp 1–10 Negi, J. D. S., Sharma, S. C. and Sharma, D. C. (1988). Comparative assessment of methods for estimating biomass in forest ecosystem. Indian For., 114: 136-146. Nonini, L., & Fiala, M. (2019). Estimation of carbon storage of forest biomass for voluntary carbon markets: preliminary results. J For Res 32 (1), 329–338. https://doi.org/10.1007/s11676-019-01074-w. Pitol, M.N.S, Khan, M.Z., & Khatun, R., (2019). Assessment of Total Carbon Stock in Swietenia macrophylla Woodlot at Jhenaidah District in Bangladesh. Asian J. Res. Agric. For. 2 (3), 1–10. https://doi.org/10.9734/AJRAF/2018/46922. Pitol, M.N.S., & Bachchu, M.M. (2023). High carbon storage and oxygen (O 2 ) release potential of Mahagony ( Swietenia macrophylla ) woodlot plantation in Bangladesh. Saudi Journal of Biological Sciences , 30 (1), 103498. doi: 10.1016/j.sjbs.2022.103498 Pragasan, L. A. (2015). Tree Carbon Stock Assessment from the Tropical Forests of Bodamalai Hills Located in India. Earth Science Climatic Change , 6(10): 314-319. Rahman, M. M. (2022a). Carbon sequestration capacity of Casuarina equisetifolia in the coastal areas of Cox’s Bazar, Bangladesh. International Journal of Advances in Engineering and Management , 4(8): 830-838. Rahman, M. M. (2022b). The ability of carbon storage of Acacia auriculiformis in different forest areas of Rangunia upzila under Chattogram district, Bangladesh. International Journal of Advances in Engineering and Management , 4(8): 815-822. Rahman, M.T., Gurung, D.B., & Pitol, M.N.S. (2020). Comparative study of understory between exotic monoculture plantation ( Acacia Sp. )and adjacent natural Sal ( Shorea Robusta ) forest. European Journal of agriculture and food science 2 (6).DOI: https://doi.org/10.24018/ejfood.2020.2.6.204 Rahman, R. R, Rahman. S, H. and Al-Amin, M. (2019). Carbon Stocks in Forest of the Kaptai National Park in Bangladesh. Indian Forester , 145(8): 699-706. Razakamanarivo, R. H., Razakavololona A., Razafindrakota, M. A., Vielledent, G. and Alberecht. A. (2012). Below ground biomass production and allometric relationship of eucalyptus coppice plantation in the central highlands of Madagascar . Biomass and bioenergy , 45: (1-10). Rinnamang, S., Sirirueang, K., Supavetch, S., Meunpong, P. (2020). Estimation of aboveground biomass using aerial photogrammetry from unmanned aerial vehicles in teak ( Tectona grandis ) plantation in Thailand. Biodiversitas 21 (6), 2369–2376. https://doi.org/10.13057/biodiv/d210605. Riutta, T., Malhi, Y., Kho, L.K., Marthews, T.R., Huasco, W.H., Khoo, M. (2018). Logging disturbance shift net primary productivity and its allocation in Bornean tropical forest. J. Glob Change Biol 24 (7), 2913–2928. https://doi.org/10.1111/gcb.14068. Salazar-Iglesia, S., Sanchez, L. E., Galinda, P. and Santa Regina, I. (2010). Aboveground tree biomass equations and nutrient pools for a para climax chestnut stand and for a climax oak stand in the Sierra de Francia Mountains, Salamanca Spain, Academic Journals , 5(11): 1294-1301. Sattar, M. A., Bhattacharjee, D. K. and Kabir, M. F. (1999). Physical and mechanical properties and uses of timber of Bangladesh. Report 57, Seasoning and Timber Division, Bangladesh Forest Research Institute Chittagong, Bangladesh. Schroeder, P., Brown, S., Mo, J., Birdsey, R. and Cieszewski, C. (1997). Biomass estimate for temperate broadleaf forests of the US using inventory data. Forest Science, 43(3): 424-434. Ullah, M.R., Al-Amin, M. (2012). Above- and below-ground carbon stock estimation in a natural forest of Bangladesh. J. For. Sci. 58: 372-379. Zhao, J., Kang, F., Wang, L. et al . (2014). Patterns of Biomass and Carbon Distribution across a Chrono sequence of Chines pine ( Pinus tabulaeformis ) forests. PLoS ONE, 9(7): e 94966. Additional Declarations No competing interests reported. Supplementary Files APPENDIX12.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5348859","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":398378350,"identity":"54b54250-4a11-4918-843a-e9b3e4af381a","order_by":0,"name":"Mohammed Mukhlesur Rahman","email":"","orcid":"","institution":"Bangladesh Forest Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"Mukhlesur","lastName":"Rahman","suffix":""},{"id":398378351,"identity":"5634cd19-261d-4a83-a5c5-7690beb7fb5f","order_by":1,"name":"Mizanur Rahman","email":"","orcid":"","institution":"Bangladesh Forest Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Mizanur","middleName":"","lastName":"Rahman","suffix":""},{"id":398378352,"identity":"9deb2664-4bf4-4f05-a8db-55045be0d6ea","order_by":2,"name":"Md. Najmus Sayadat Pitol","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYHCCBDhLgoHBBkgxNh4gQUtCGkhLAyEtCADUchjMwKvFnP3A0808fxjs+WckP7zx88d5u7Xth4G21NhE49Ji2ZOQdpu3jSFxxo00YyDndvK2M4lALcfSchtwaDE4ANLSAPTQjQQzCR6gFrMDQC2MDYdxazn/IO02yGHyN9K/Sf5JOJdsdv4hAS03gLbwsDEwbriRYybNk3DAzuwGIVtuPEi7ObdNInHjmTfF1jJpyQlmN4C2JODzy/mctBtv/tjYyx1P33jzjY2dvdn59IcPPtTY4NTCwMCTwACOd4EEMDcRrDIBp3IQYD8AofkhtD1exaNgFIyCUTAiAQAEv2juVLtt9AAAAABJRU5ErkJggg==","orcid":"","institution":"Bangladesh Forest Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Md.","middleName":"Najmus Sayadat","lastName":"Pitol","suffix":""}],"badges":[],"createdAt":"2024-10-28 17:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5348859/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5348859/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74267708,"identity":"9e0db3b2-500e-4fb5-8c2a-db7fbc94764a","added_by":"auto","created_at":"2025-01-20 13:20:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1281934,"visible":true,"origin":"","legend":"\u003cp\u003eNatore Sadar Upazila map, yellow line below shows the scale, the yellow circle upper right side shows the north sign, red circle and red shape on the left side shows the study area.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5348859/v1/4dec154d3f405b2317008543.png"},{"id":74268870,"identity":"52038106-95c7-44e1-894c-b73ac880bed8","added_by":"auto","created_at":"2025-01-20 13:28:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35532,"visible":true,"origin":"","legend":"\u003cp\u003eDiameter at breast height and height of\u003cem\u003e Swietenia\u003c/em\u003e \u003cem\u003emacrophylla \u003c/em\u003ean\u003cem\u003ed Eucalyptus camaldulensis \u003c/em\u003ein different ages.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5348859/v1/bb3299790da6556fd2450377.png"},{"id":74267711,"identity":"2cf4cdbb-5ffd-46b9-be70-bba6f23e99ea","added_by":"auto","created_at":"2025-01-20 13:20:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":52713,"visible":true,"origin":"","legend":"\u003cp\u003eMean annual diameter increment rate and mean annual height increment rate of \u003cem\u003eSwietenia macrophylla \u003c/em\u003ean\u003cem\u003ed Eucalyptus camaldulensis\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5348859/v1/0b18044a8b0797fe77a052e7.png"},{"id":80298472,"identity":"479778ec-3d83-4b04-8e47-4b263a15678c","added_by":"auto","created_at":"2025-04-10 08:53:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2921449,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5348859/v1/9418dc1e-ac47-4a5d-adac-e7857bd9cad4.pdf"},{"id":74267707,"identity":"5c86f120-5f82-43e1-9157-da5b0a63993c","added_by":"auto","created_at":"2025-01-20 13:20:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25967,"visible":true,"origin":"","legend":"","description":"","filename":"APPENDIX12.docx","url":"https://assets-eu.researchsquare.com/files/rs-5348859/v1/5a4c63df907fcf2b925f97d7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A comparative study on the carbon storage and oxygen release capacity of Swietenia macrophylla king. and Eucalyptus camaldulensis Dehn. in northwest Bangladesh","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDeclination of biodiversity and increased CO\u003csub\u003e2\u003c/sub\u003e have been recognized as two major concerns nowadays (Kumar, 2011). One is the result, and another is the cause of global warming and climate change while the plantations are the most important tool for reducing their effects. We know only plants can seize the atmospheric CO\u003csub\u003e2\u003c/sub\u003e through photosynthesis, store it as biomass, and produce a massive quantity of oxygen (Lukito and Rohmatiah, 2013, Pitol and Mian, 2023). Plantation may lead to the enhancement of forestation though it reduces the diversity (Rahman et al. 2021). There are two types of plantations (such as artificial and natural plantations) (Menne, 2015) while the number of artificial plantations is increasing more rapidly than natural plantations in the tropical regions of the world. Artificial forests contribute to the declining pressure on timber extraction from natural forests and play a vital role in the conservation of forest resources (Kaul \u003cem\u003eet al\u003c/em\u003e., 2010). It is not possible to increase the forest and agriculture lands, but the production will be maximized by converting the traditional lands into sustainable uses like agroforestry home gardens, tea plantations and woodlot plantations (Nair and Kumar. 2006, Pitol et al. 2019). Plantation forests give us hope for sustainable use of forest resources. Approximately, the world has 187,086 (000 ha) plantation forests with a new planting rate of 4493(000 ha) per year (FAO 2010). Planted forests supply 35% of total wood demand with a projected increase to 44% by 2020 (FAO, 2010, ABARE \u0026amp; Jaakko P\u0026ouml;yry, 1999).\u003c/p\u003e \u003cp\u003eHomestead forests have enormously increased in different parts of Bangladesh to fulfill the wood and fuel wood demand. They are increased based on special types of timber species which are fast growing and highly timber quality. The selection of plant species plays a vital role in mitigating global warming. In Bangladesh, the plantation forests increased from 238.81 (000 ha) to 278.11(000 ha) from 1990 to 2005 (FAO, 2010) while Jashimuddin and Inoue (2012) recorded that 48,420 ha of roadside plantations, 30,666 ha of woodlots and 8778 ha of agroforestry plantations during the last 30 years. However, the plantation activities are continuing without assessment of the carbon storage capacity of tree species in many regions of the world as well as Bangladesh. There is an urgent need to estimate biomass, carbon storage and released oxygen in different species for implementing massive plantation programs. Biomass is an important parameter to assess the assimilation of carbon by plants. Biomass and carbon storage play an important role in the global carbon cycle (Cairns \u003cem\u003eet al\u003c/em\u003e., 2003; Li \u003cem\u003eet al\u003c/em\u003e., 2011; Zhao \u003cem\u003eet al\u003c/em\u003e., 2014) and are now considered for creating any woodlot (Ekholm 2016; Gren and Zeleke 2016; Riutta et al. 2018; Nonini and Fiala 2019; Rinnamang et al. 2020).\u003c/p\u003e \u003cp\u003eNormally, homestead forests are established with single tree species which is known as monoplantation. Monoplantations are increasing a geometrical rate in northern parts of Bangladesh to fulfill the local wood-related demands. Numerous experts recommended that the homestead flora of Bangladesh provides about 70% of all wood consumed and 90% of all fuel wood and bamboo (Alam \u003cem\u003eet al\u003c/em\u003e., 1990). Many kinds of exotic and indigenous forest tree species are planted in the homestead forests of Bangladesh while \u003cem\u003eSwietenia macrophylla\u003c/em\u003e and \u003cem\u003eEucalyptus camaldulensis\u003c/em\u003e are the best choice for their fast-growing and well adaptable potentiality. Private landowners plant fast-growing tree species for local consumption such as fuel wood, poles, posts, and small wood and cottage industries (BBS, 2014). Moreover, the adaptation ability, growth performances and carbon storage capacity of planted tree species in most of the areas in Bangladesh have not been estimated yet. It is essential to know the role of plantation forests in carbon trade and ecosystem services (Nair, 2012). It improves the country\u0026rsquo;s negotiations for REDD\u0026thinsp;+\u0026thinsp;and carbon trade mechanisms (Nair, 2012; Jashimuddin and Inoue, 2012). Direct and indirect methods are mostly used for biomass calculation while indirect methods are based on allometric equations using measurable parameters (Salazar-Iglesias et al., 2010). This method is easy and suitable for the estimation of carbon storage in tropical forests (Razakamanarivo et al., 2012; Rahman, et al., 2019). Therefore, keeping this point in mind, an attempt was made to estimate a comparative study of the biomass, carbon storage and oxygen release between \u003cem\u003eSwietenia macrophylla\u003c/em\u003e and \u003cem\u003eEucalyptus camaldulensis\u003c/em\u003e in the northern district of Bangladesh. The findings of the study will provide essential data on biomass, carbon storage and oxygen release which will be used for carbon monitoring at the national and international levels.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe study area\u003c/h2\u003e \u003cp\u003eThe study was conducted on homestead forest areas at Natore Sadar upzila of Natore district in Bangladesh. Geographically, the study area is situated between 24\u003csup\u003e0\u003c/sup\u003e 07ʹ to 24\u003csup\u003e0\u003c/sup\u003e 43ʹ north latitudes and between 88\u003csup\u003e0\u003c/sup\u003e 17ʹ to 88\u003csup\u003e0\u003c/sup\u003e 58ʹ east longitudes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This area falls under the tropical region, also known as Bangladesh's hottest district. The climatic condition is a hot-humid summer with moderate rainfall and a mild winter with foggy sometimes. The summer season is considered from April to the last of June. The rainy season starts at the end of June and stays up to September. The winter season comes from the middle of November and lasts up to the end of February. Temperature variation appears that the average annual temperature is about 26-36\u003csup\u003e0\u003c/sup\u003eC. The minimum and maximum mean temperature during winter varies from 9\u003csup\u003e0\u003c/sup\u003e to 14\u003csup\u003e0\u003c/sup\u003eC. The minimum and maximum mean temperatures vary from 25.50 \u003csup\u003e0\u003c/sup\u003eC to 40.70 \u003csup\u003e0\u003c/sup\u003eC during summer. The soil of the study area is rich in alluvium and clay texture with pH 7. 22 on average. This soil is perfect for agriculture and horticulture (BBS, 2022). The study area was covered by various planted timber tree species. The following planted species were dominant such as \u003cem\u003eMangifera indica, Azadirachta indica\u003c/em\u003e, \u003cem\u003eSwietenia macrophylla, Albizia richardiana, Eucalyptus camaldulensis\u003c/em\u003e, \u003cem\u003eSamanea saman, Artocarpus heterophyllus, Delonix regia, Caesalpinia pulcherrima\u003c/em\u003e and \u003cem\u003eCitrus maxima\u003c/em\u003e etc. Homestead forests are accelerating at a geometrical rate to fulfill the demand for fuel wood and timber. Massive plantations have been started in the study area with the help of some selected forest tree species. Before plantation, the area was included in cultivation land and different types of agronomical and horticultural crops were grown such as \u003cem\u003eOryza sativa, Corchorus capsularis, Saccharum officinarum, Litchi chinensis, Manilkara zapota, Ziziphus mauritiana, Averrhoa carambola, Psidium guajava\u003c/em\u003e and \u003cem\u003eMusa sapientum\u003c/em\u003e, etc.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSampling and measurements\u003c/h3\u003e\n\u003cp\u003eThe study was carried out from January 2023 to December 2023. A systematic sampling method was used for the selection of plots. The geographical location of each plot was recorded using a global positioning system (GPS) and the size of each plot was 10 m\u0026times;10 m. A total of land was 20 hectares for each species separately. Brown\u0026rsquo;s model (Brown \u003cem\u003eet al\u003c/em\u003e., 1989) was used to estimate the aboveground biomass of each tree of each experiment plot. Several scientists suggested that allometric equations are one of the most suitable methods for biomass estimation in tropical forests (Alves \u003cem\u003eet al\u003c/em\u003e., 1997; Schroeder \u003cem\u003eet al.\u003c/em\u003e, 1997). Trees height and diameter at breast height (DBH\u0026thinsp;\u0026gt;\u0026thinsp;5cm) from ground level (1.30 m) of all trees were measured using a clinometer and DBH tape respectively. Trees on the border were included in a plot if 50% of their basal area fell within the plots and excluded if 50% of their basal area fell outside the plot. Trees overhanging the plots were excluded, but with their trunk inside the sampling plots, and branches out were included. Care was taken to ensure the diameter tape was put on the stem exactly at the measurement point.\u003c/p\u003e\n\u003ch3\u003eBiomass, carbon stock, CO and release O estimation\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in planted forest areas and all trees were measured with the help of tape and a clinometer. It was impossible to cut all the trees to estimate of biomass and carbon of trees. Some models were developed by Brown (1997), Luckman \u003cem\u003eet al\u003c/em\u003e. (1997), Negi \u003cem\u003eet al\u003c/em\u003e. (1988) and Brown \u003cem\u003eet al\u003c/em\u003e. (1989). Brown\u0026rsquo;s models (Brown \u003cem\u003eet al\u003c/em\u003e., 1989) was used to determine aboveground biomass because this method is the most suitable method for tropical forests (Alves \u003cem\u003eet al\u003c/em\u003e. 1997; Brown 1997; Schroeder \u003cem\u003eet al.\u003c/em\u003e 1997; Miah \u003cem\u003eet al\u003c/em\u003e. 2011; Ullah and Al-Amin, 2012). This is the simplest method of estimating forest tree biomass in the tropics as it requires only tree diameter at breast height, total height and wood-specific gravity. While other models or regression equations require sectional diameter, this simply deals with diameter at breast height. The model is as follows:\u003c/p\u003e \u003cp\u003eY\u0026thinsp;=\u0026thinsp;exp. {-2.4090\u0026thinsp;+\u0026thinsp;0.9522 ln (D\u003csup\u003e2\u003c/sup\u003eHS)}\u003c/p\u003e \u003cp\u003eWhere Y\u0026thinsp;=\u0026thinsp;Aboveground biomass in kg, H\u0026thinsp;=\u0026thinsp;Height of the trees in meters, D\u0026thinsp;=\u0026thinsp;Diameter at breast height (1.30 m) in cm, and S\u0026thinsp;=\u0026thinsp;Wood density in units of tons m\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e for a specific species (Brown 1997; Sattar \u003cem\u003eet al\u003c/em\u003e. 1999).\u003c/p\u003e \u003cp\u003eUsing these models\u0026rsquo; the aboveground biomass of each tree was estimated. From aboveground biomass of each individual\u0026rsquo;s tree was calculated and biomass was converted to tons ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and added to get the total aboveground biomass. Belowground biomass was calculated considering 15% of the aboveground biomass (MacDicken 1997; IPCC 2003; Miah \u003cem\u003eet al.\u003c/em\u003e 2011). Belowground biomass was calculated for each tree. Aboveground and belowground biomass of trees was added to get the total biomass of trees.\u003c/p\u003e \u003cp\u003eBGB\u0026thinsp;=\u0026thinsp;AGB X (20/100).\u003c/p\u003e \u003cp\u003eThe total carbon (TC) of the tree was determined by using the following formula.\u003c/p\u003e\n\u003ch3\u003eTC= (AGB + BGB) 🞨0.50\u003c/h3\u003e\n\u003cp\u003eWhere, 0.50 is the conversion factor (Schroeder, 1997).\u003c/p\u003e \u003cp\u003eBesides, the carbon-di-oxide capturing (CO\u003csub\u003e2\u003c/sub\u003e) was calculated by multiplying the total carbon stock by 3.67 (Kauffman and Donato, 2012) and then the released oxygen was calculated by multiplying the total carbon-di-oxide capturing by 0.727 (Pitol and Mian, 2022).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eBiomass and carbon storage per tree were finally calculated using Xcel-365 software and figures were also made using Xcel and PowerPoint-365. Analysis of variance (ANOVA) was performed by using Statistical Package for Social Science (SPSS-20).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDiameter and height of different ages plantations\u003c/h2\u003e \u003cp\u003eDiameter, height and wood density are the most important indicators for estimating biomass and carbon of trees. Biomass and carbon were calculated based on the diameter, height and wood density of planted forest tree species in the study area. The study revealed that the diameter and height were 27.78 cm and 29.65cm; and 17.44m and 9.55m were found in \u003cem\u003eEucalyptus camaldulensis\u003c/em\u003e and \u003cem\u003eSwietenia macrophylla\u003c/em\u003e at 20 years old respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). There was no significant difference (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.658) found between the DBH of the two species (\u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003eAppendix 1\u003c/span\u003e) while their DBH were significantly different among their ages (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.000) (\u003cspan refid=\"Sec13\" class=\"InternalRef\"\u003eAppendix 2\u003c/span\u003e). Moreover, the height of these two species was significantly difference (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.002) but not significant in their ages (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.694) (\u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003eAppendix 1\u003c/span\u003e and \u003cspan refid=\"Sec13\" class=\"InternalRef\"\u003eAppendix 2\u003c/span\u003e). Comparatively higher growth performances were observed in \u003cem\u003eE. camaldulensis\u003c/em\u003e than \u003cem\u003eS. macrophylla\u003c/em\u003e in the same environmental conditions, management and equal ages (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eMean Annual increment of diameter, height, biomass, carbon stock, CO\u003c/b\u003e \u003csub\u003e \u003cb\u003e2\u003c/b\u003e \u003c/sub\u003e \u003cb\u003ecapturing and O\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003ereleasing potentiality of different ages plantations\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe mean annual increment of DBH was insignificant (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.629) between these two species when they significantly varied among the ages (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.000). Besides, the mean annual height increment was significantly varied (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.034) between these two species when they were not considerably diverse among the ages (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.321). It was found that the mean annual diameter increments and mean annual height increments were 1. 93cm and 2. 06 cm; and 0.78m and 1. 24 m for \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The present study revealed that the value of the mean annual diameter increments and mean yearly height increment of \u003cem\u003eE. camaldulensis\u003c/em\u003e was comparatively higher than \u003cem\u003eS. macrophylla.\u003c/em\u003e The height and DBH growth became slower with the increase of the age of the plantation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe aboveground biomass, belowground biomass, total biomass, aboveground carbon, belowground carbon, total carbon, carbon-di-oxide storage and O\u003csub\u003e2\u003c/sub\u003e releasing potentiality were related to each other and significantly differed from their ages (p-value varied from 0.001 to 0.023). The value was maximum for both species in 20-year-old plantations and minimum for 5-year-old plantations (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The highest aboveground biomass, belowground biomass and total biomass were 574.55 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 114.91 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 689.46 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 724.38 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 144.88 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 869.26 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e at twenty years old respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The lowest aboveground biomass, belowground biomass and total biomass were 41.94 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 8.39 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 50.33 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 76.99 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 15.40 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 92.39 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e at five years old respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Moreover, the maximum aboveground carbon, belowground carbon and total carbon were 287.28 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 57.46 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 344.73 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 362.19 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 72.44 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 434.63 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e at twenty years old. The lowest aboveground carbon, belowground carbon and total carbon were 20.97 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 4.19 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 25.16 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 38.50 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 7.70 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 46.20 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e at five years old (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, the carbon storage varied from 5.03 to 17.24 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e while capturing CO\u003csub\u003e2\u003c/sub\u003e varied from 18.46 to 63.26 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and releasing O\u003csub\u003e2\u003c/sub\u003e varied from 13.42 to 45.99 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for \u003cem\u003eS. macrophylla\u003c/em\u003e. In addition, the carbon storage varied from 9.24 to 21.73 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e while capturing CO\u003csub\u003e2\u003c/sub\u003e varied from 33.91 to 79.75 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and releasing O\u003csub\u003e2\u003c/sub\u003e varied from 24.65 to 57.98 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for \u003cem\u003eE. camaldulensis\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAboveground biomass, belowground biomass, total biomass, aboveground carbon, belowground carbon, total carbon, carbon storage, CO\u003csub\u003e2\u003c/sub\u003e capturing and O\u003csub\u003e2\u003c/sub\u003e releasing potentiality of \u003cem\u003eSwietenia macrophylla\u003c/em\u003e an\u003cem\u003ed Eucalyptus camaldulensis\u003c/em\u003e in different ages\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge of Plantation (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGB\u003c/p\u003e \u003cp\u003eper tree (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBGB per tree (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTB\u003c/p\u003e \u003cp\u003eper tree (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAGC per tree (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBGC\u003c/p\u003e \u003cp\u003eper tree (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTC per tree (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCarbon storage kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCapturing CO\u003csub\u003e2\u003c/sub\u003e kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eReleasing O\u003csub\u003e2\u003c/sub\u003e kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cem\u003eSwietenia macrophylla\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e25.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e18,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e13.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e43.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e19,85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e14.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e117.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e58.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e21,62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e15.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e174.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e208.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e87.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e104.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e31,95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e23.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e326.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e391.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e163.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e195.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e13.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e47,89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e34.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e574.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e114.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e689.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e287.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e57.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e344.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e17.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e63,26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e45.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cem\u003eEucalyptus camaldulensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e9.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e33,91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e24.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e115.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e138.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e69.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e8.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e31,81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e23.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e202.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e84.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e101.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e37,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e27.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e259.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e311.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e129.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e155.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e12.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e47,62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e34.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e418.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e502.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e209.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e251.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e16.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e61,41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e44.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e724.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e144.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e869.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e362.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e72.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e434.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e21.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e79,75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e57.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e**AGB\u0026thinsp;=\u0026thinsp;Aboveground biomass, BGB\u0026thinsp;=\u0026thinsp;Belowground biomass, TB\u0026thinsp;=\u0026thinsp;Total biomass, AGC\u0026thinsp;=\u0026thinsp;Aboveground carbon, BGB\u0026thinsp;=\u0026thinsp;Belowground carbon and TC\u0026thinsp;=\u0026thinsp;Total carbon\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe basic two functions of trees are capturing carbon dioxide and producing oxygen for curbing climate change and survival of life on this earth respectively. Nowadays we are concerned about the carbon and carbon dioxide storage capacity of trees. In this study, we also checked the oxygen release potentiality of two widely used fast-growing species in Bangladesh. Comparatively higher growth performances were observed in \u003cem\u003eE. camaldulensis\u003c/em\u003e than \u003cem\u003eS. macrophylla\u003c/em\u003e in the same environmental conditions, management and equal ages. It revealed that the diameter and height were 27.78 cm and 29.65cm; and 17.44m and 9.55m in \u003cem\u003eEucalyptus camaldulensis\u003c/em\u003e and \u003cem\u003eSwietenia macrophylla\u003c/em\u003e at 20-year-old plantations respectively. The height of \u003cem\u003eS. macrophylla\u003c/em\u003e increased very slowly and \u003cem\u003eE. camaldulensis\u003c/em\u003e was very fast while both showed similar dbh growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Normally growth parameters are mainly influenced by genetic criteria which is known as genotype. In this regard, the following equation may be regarded as phenotype\u0026thinsp;=\u0026thinsp;genotype\u0026thinsp;+\u0026thinsp;environment. The present findings indicated that growth performances varied between the two species due to the genotypic criteria. The phenotype depends on genotype and environmental factors. Several scientists worked on the estimation of the diameter and height of forest tree species in Bangladesh. Rahman (2022a) found that the dbh and height of \u003cem\u003eCasuarina equisetifolia\u003c/em\u003e at Inani and Teknaf Forest Ranges 14.10 cm and 12.70 m; 17.10 cm and 17.10 m; and 23.54 cm and 20.33 m for 5-years, 10-years and 20-years old plantation separately. (Rahman, 2022b. Besides, the dbh and height of \u003cem\u003eAcacia auriculiformis\u003c/em\u003e were 5.03 cm and 4.27 m; and 10.35 cm and 8.28 m for 5-year and 10-year plantations at Pomra, Hosnabad, Rajanagar and Parua Forest Ranges under the Chattogram North Forest Division in Bangladesh respectively (Rahman, 2022b). Dey et al. (2022) found the dbh and height of \u003cem\u003eEucalyptus camaldulensis\u003c/em\u003e were 10.6 m and 11.9 cm for a 5-year plantation, and 30.9 m and 42.7 cm for a 21-year plantation while Azad et al. (2021) found the dbh for 10.14 cm, 26.47 cm and 29.21cm for 5-year, 15-year, and 20-year plantations individually. It seemed that the height and dbh growth of \u003cem\u003eE\u003c/em\u003e. \u003cem\u003ecamaldulensis\u003c/em\u003e was higher at every year plantations than the \u003cem\u003eC\u003c/em\u003e. \u003cem\u003eequisetifolia\u003c/em\u003e, \u003cem\u003eA. auriculiformis\u003c/em\u003e and \u003cem\u003eS. macrophylla\u003c/em\u003e and very close to \u003cem\u003eHevea brasiliensis\u003c/em\u003e plantations.\u003c/p\u003e \u003cp\u003eIn our study, the mean annual diameter increments and mean annual height increments were 1. 93cm and 2. 06 cm; and 0.78m and 1. 24 m for \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The present study revealed that the value of the mean annual diameter increments and mean yearly height increment of \u003cem\u003eE. camaldulensis\u003c/em\u003e was comparatively higher than \u003cem\u003eS. macrophylla.\u003c/em\u003e Moreover, the height and DBH growth became slower with the increase of the age of the plantation. It exhibited that the tree grows faster at an early age. However, the mean annual diameter increment rate and mean annual height increment rate also varied from species to species and age to age. The mean annual diameter increment rates were 3.08 cm, 1.71 cm and 1.17 cm while the mean annual height increment rates were 2.54 m, 1.71 m and 1.02 m found in \u003cem\u003eCasuarina equisetifolia\u003c/em\u003e at 5, 10 and 20-year trees (Rahman, 2022b). In addition, the mean annual diameter increment rates were 1.01 cm and 1.04 cm found in \u003cem\u003eAcacia auriculiformis\u003c/em\u003e while the mean annual height increment rates were 0.94 m and 0.91 m found in \u003cem\u003eAcacia auriculiformis\u003c/em\u003e at 5 and 10-year trees. There was a positive correlation between diameter and height, but the diameter and height rates varied from species to species.\u003c/p\u003e \u003cp\u003eThe biomass, carbon, carbon-dioxide storage and O\u003csub\u003e2\u003c/sub\u003e-releasing potentiality were related to each other and significantly differed from their ages (p-value varied from 0.001 to 0.023). There was a positive relation between the age and biomass, carbon, carbon-dioxide storage, and O\u003csub\u003e2\u003c/sub\u003e-releasing potentiality of trees. The present study was conducted in the northern parts of Bangladesh which is situated in the hottest tropical regions of Bangladesh. Normally, biomass and carbon storage vary in different regions of the world. Scientists observed that carbon storage capacity varied from species to species due to ecological and management conditions (Rahman et al., 2019, 2020). A study was conducted in the tropical forests of Badamalai hills in India and reported that the average carbon stock of single tree species was 0.04tC/tree. It was also reported that the maximum value was 0.68 t C/tree found in \u003cem\u003eFicus benghalensis\u003c/em\u003e, followed by \u003cem\u003eTamarindus indica, Spondias pinnata, Diospyros ebenum\u003c/em\u003e and \u003cem\u003eFicus beddomei\u003c/em\u003e 0.51 t C/tree, 0 46 t C/tree, 0.30 t C/tree, and 0.22 t C/tree respectively (Pragasan \u003cem\u003eet al.\u003c/em\u003e, 2015). In this case, their findings were higher than the findings of the present study. However, wide variations in the biomass potential of a tree may occur due to differences in provenances, stand density, tree age, site characteristics, management, etc. Several scientists (observed that the total aboveground biomass in the range of 9.80 to 306.01 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for \u003cem\u003eGmelina arborea\u003c/em\u003e and 7.25 to 314.61 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for \u003cem\u003eSwietenia Macrophylla\u003c/em\u003e (Kawahara \u003cem\u003eet al\u003c/em\u003e., 1981; Pitol et al. 2019; Pitol and Mian, 2022). On the other hand, Buante (1997) observed the total aboveground biomass of \u003cem\u003eAcacia auriculiformis\u003c/em\u003e and \u003cem\u003eGmelina arborea\u003c/em\u003e in the ranges of only 15.71 to 49.08 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 9.18 to 68.58 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The following tree species were included such as \u003cem\u003eEucalyptus deglupta, paraserianthes falcataria, Swietenia macrophylla, Acacia auriculiformis\u003c/em\u003e and \u003cem\u003eGmelina arborea\u003c/em\u003e and their values were 365.70 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 90.70 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 156.30 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 248.20 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 114.80 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively (Dey et al. 2022; Kawahara \u003cem\u003eet al\u003c/em\u003e., 1981; Pitol et al. 2019; Pitol and Mian, 2022. Generally, the total biomass and carbon were estimated based on aboveground and belowground biomass all over the world. Several scientists reported that total biomass and carbon varied from species to species and different ages such as 776.90 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 1574 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003ebiomass was found in \u003cem\u003eMangifera indica\u003c/em\u003e at 25 years old (Ganeshamurthy \u003cem\u003eet al.\u003c/em\u003e, 2016).\u003c/p\u003e \u003cp\u003eCarbon dioxide is the most effective greenhouse gas which traps heat and increases temperature in different levels of the atmosphere. The elevated temperature adversely affects biotic and abiotic components of all types of ecosystems which is the main obstacle to the sustainable development of the environment. In this case, plantations sequester carbon dioxide and produce oxygen from the atmosphere through photosynthesis and act as sinks which help to reduce global warming. Carbon storage capacity is the most important for the development of plantations based on species. The same species contained different amounts of carbon when grown in different regions. Scientists observed variations in carbon storage with the age of the forest, stand condition, species composition, climate condition, physiographical position and degree of disturbance (Kanime \u003cem\u003eet al.\u003c/em\u003e, 2013 and Kumar \u003cem\u003eet al\u003c/em\u003e., 2016). Biomass, carbon storage, CO\u003csub\u003e2\u003c/sub\u003e and oxygen release assimilation vary with species. Scientists reported that higher values were found in \u003cem\u003eEucalyptus spp.\u003c/em\u003e while it was the lowest value in \u003cem\u003eS. javanica\u003c/em\u003e (Ganeshamurthy \u003cem\u003eet al.\u003c/em\u003e, 2019). Some species such as \u003cem\u003eC. camphora, S. babylonica, P. roxburghii G. robusta\u003c/em\u003e and \u003cem\u003eDiospyros\u003c/em\u003e sp. also have high values of carbon storage, and carbon assimilation. Some species particularly, \u003cem\u003eM. koenigii, Mimosasp., F. auriculata, F. lacor\u003c/em\u003e and \u003cem\u003eDalbergia\u003c/em\u003e sp. have low values. Myrtaceae was the family with the highest carbon storage, carbon assimilation and followed by Lauraceae Salicaceae and Pinaceae (Kaul \u003cem\u003eet al\u003c/em\u003e., 2010). Maximum scientists (Chave \u003cem\u003eet al\u003c/em\u003e., 2014) opined that carbon sequestration depends on single or multiple factors such as age, size, density and climatic conditions, etc. However, our study was conducted in a narrow zone of the country. A massive survey is required to assess the feasibility and potentiality of plantation forests. It is also a prerequisite for our fair share in the global carbon trade mechanism.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePlantation sequesters carbon dioxide and acts as a carbon sink and oxygen source in the atmosphere. Elevated carbon dioxide in the atmosphere is harmful to all living organisms of the terrestrial environment. So, plantations should be increased to continue the equilibrium balance of the environment. The present findings of the study indicated that planted forests with fast-growing tree species play a vital role in sequestering carbon and generating oxygen and their utilization demands are also high for the quality of timber and fuel wood. It is also remarkable that the planted forest tree species are well adapted to the selected study areas. The socio-economic conditions can be easily developed through applying silviculture methods in the social plantation programs. Therefore, policymakers, administrators and planters can choose \u003cem\u003eSwietenia macrophylla\u003c/em\u003e an\u003cem\u003ed Eucalyptus camaldulensis\u003c/em\u003e for the massive plantations based on environmental conditions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Acknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to be grateful to the owners of the orchards in different locations. The orchard’s owners entirely help during the research period. The authors are highly thankful to the owners of the orchards for the permission to survey their areas during the survey. In addition, they provided the following information source of seeds, age of trees, plantation period and management techniques.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and Biosecurity Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted our survey in private woodlands and home garden areas. We took the permission of the owner of the home gardens and woodlots. The authors also declared that no trees were damaged during the study. We did not use quarantine organisms or take any data from any protected areas. The scientific names of the two species we used followed the guidelines of the International Code of Nomenclature for algae, fungi, and plants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made accessible on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors’ self-fund was used for data collection.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll Authors participate equally.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eABARE -Jaakko Poyry., (1999). Global Outlook for Plantations, ABARE Research Report 99.9, Canberra.\u003c/li\u003e\n\u003cli\u003eAlam, M. S. and Masum, K. M. (2005). 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Patterns of Biomass and Carbon Distribution across a Chrono sequence of Chines pine (\u003cem\u003ePinus tabulaeformis\u003c/em\u003e) forests.\u003cem\u003e PLoS ONE,\u003c/em\u003e \u003cstrong\u003e9(7):\u003c/strong\u003e e 94966.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Plantation, non-destructive method, biomass, carbon, global warming","lastPublishedDoi":"10.21203/rs.3.rs-5348859/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5348859/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePlantation sequesters atmospheric carbon and produces oxygen through photosynthesis and stores it as a reserve. Estimating the carbon sequestration capacity of forest tree species is essential for implementing massive plantation programs in developing countries such as Bangladesh. The present study was conducted on the carbon storage and release oxygen capacity of \u003cem\u003eSwietenia macrophylla\u003c/em\u003e and \u003cem\u003eEucalyptu\u003c/em\u003es \u003cem\u003ecamaldulensis\u003c/em\u003e which were planted forest tree species in the same ecological condition. Allometric equations were applied to estimate organic carbon in two species of trees. The diameter increased with increasing height and positive correlations were found in \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e respectively (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The maximum carbon storage of \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e were 17.24 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 21.73 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at twenty years old tree respectively. The lowest carbon storage of \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e were 5.03 and 9.24 kg tree\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e year\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at five years old, respectively. There was no significant difference (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.658) found between the DBH of the two species while their DBH were significantly different among their ages (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.000). Besides, the height of these two species was significantly difference (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.002) but not significant in their ages (df\u0026thinsp;=\u0026thinsp;11; p\u0026thinsp;=\u0026thinsp;0.694). The height and DBH growth became slower with the increase of the age of the plantations. The biomass, carbon stock, carbon-di-oxide storage and O\u003csub\u003e2\u003c/sub\u003e releasing potentiality were related to each other and significantly differed from their ages (p-value varied from 0.001 to 0.023). Comparatively higher growth performances were observed in \u003cem\u003eE. camaldulensis\u003c/em\u003e than \u003cem\u003eS. macrophylla\u003c/em\u003e in the same environmental conditions, management and equal ages. The findings indicated that \u003cem\u003eS. macrophylla\u003c/em\u003e and \u003cem\u003eE. camaldulensis\u003c/em\u003e both can be selected in the massive plantation programs in this area which will contribute to large carbon storage and play a vital role in mitigating climate change.\u003c/p\u003e","manuscriptTitle":"A comparative study on the carbon storage and oxygen release capacity of Swietenia macrophylla king. and Eucalyptus camaldulensis Dehn. in northwest Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-20 13:20:43","doi":"10.21203/rs.3.rs-5348859/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"11a7ab76-77fa-4686-92b1-431db57e5eac","owner":[],"postedDate":"January 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-10T08:53:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-20 13:20:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5348859","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5348859","identity":"rs-5348859","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}