Aboveground Tree Carbon Stock and Biomass Potential of Mixed Plantation Forests in Luot Mountain, Vietnam

Aboveground Tree Carbon Stock and Biomass Potential of Mixed Plantation Forests in Luot Mountain, Vietnam | 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 Case Report Aboveground Tree Carbon Stock and Biomass Potential of Mixed Plantation Forests in Luot Mountain, Vietnam Pervez Khan, Bui Manh Hung, Jishnu Panamoly Ayyappan, Amalu Shaju, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8823691/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Plantation forests consist primarily of planted or deliberately seeded trees and are intensively managed. It is expected that forests will play a more significant role in climate regulation in the future, as they are considered effective tools for combating climate change and absorbing carbon (C). To calculate the CO₂ uptake efficiency of planted forests at the Vietnam National University of Forestry (VNUF), this study estimated carbon capture and stock distribution in some planted forests in Luot Mountain. Random sampling was used to select a total of 20 rectangular plots of 500 square meters, with a dimension of 25 by 20 meters. Diameter at breast height (DBH) was measured by a diameter tape and caliper for trees with a diameter wider than 6 cm. The Blume-Leiss method was used to measure tree height. Overall biomass and carbon stocks aboveground in the study area were 62.4 tons/hectare and 31.2 tons/hectare, respectively. A carbon credit value of 91.55 USD/ha was assigned to the CO₂ and O₂ production and absorption potentials of 2288.94 (tons/ha) and 1670.92 (tons/ha), respectively. Forest conservation and management strategies should emphasize plantation preservation based on this study's findings because plantations store significant amounts of carbon. Above ground biomass carbon credit forest climate change global warming Figures Figure 1 Figure 2 1. Introduction Nowadays, the increase in the concentration of Carbon dioxide (CO 2 ) is the most important issue in the world, because CO 2 gas is the most important element of greenhouse gases which are caused by human activities and accelerate global warming and climate change. In the Globe climate change and global warming are the most pressing concerns, leading to environmental problems, such as thrilling weather actions, sea level rise, human health issues, wildlife starvation, plants growths, and agriculture production [ 1 , 2 ]. These climate events occur because of greenhouse gases, which are produced from human activities, such as fossil fuel burning, deforestation, burning of organic waste, and agricultural/ livestock activities [ 3 , 4 ]. As global wood and fiber demands rise, planted forests are essential, i.e., they provide almost 50.0% of industrial raw materials encompassing of timber, pulp, and fiber while occupying 7.0% of global forest land and reduce pressure on natural forests. These forest aids in restoring degraded lands, preventing soil erosion, maintaining soil fertility, and regulating water cycles. In addition to providing habitat for a variety of species, they also act as buffers for native species. By providing renewable resources, sequestering carbon to combat climate change, restoring degraded land, and protecting watersheds, they contribute to sustainable development. A forest has three main functions, including storing carbon in its constituent flora, also known as a "carbon store" or a "reservoir." Forests that absorb or reduce carbon dioxide from the atmosphere are called "vital carbon sinks." A forest that has been cleared, degraded, infested with diseases, pests, or burned is referred to as a "carbon source" that emits greenhouse gases. A significant amount of carbon is contained in forest biomass, with nearly 50% composed of carbon [ 5 ]. A tree's high carbon absorption capacity is influenced by its carbon stock, which in turn is influenced by the trunk diameter and density [ 6 ]. A forest ecosystem's aboveground biomass is a key parameter for describing its health. The aboveground biomass of a forest ecosystem is a key parameter that helps describe its functioning. It is crucial to investigate biomass carbonation in order to determine the storage of carbon and calculate the carbon cycle on a regional and global scale. Above–Ground Biomass (AGB) of dominant tree species in forest ecosystems and plant functional groups is crucial for understanding energy flow magnitudes and patterns. This organic matter is stored in tree trunks, branches, leaves, roots, and continuously circulates between the living and non-living components of the ecosystem. In order to understand the net value of AGB in forest, it is crucial to analyze how photosynthesis balances respiration, mortality, harvest, and herbivory [ 5 ]. Moreover, the estimation of the AGB is an essential aspect of studies of carbon stocks and global carbon balance [ 6 ]. Estimating AGB is a useful measure for comparing structural and functional attributes of forest ecosystems across a wide range of environmental conditions [ 7 ]. So far different studies have been conducted to estimate AGB and they have mostly used diameter and height [ 8 – 13 ]. AGB is thus of direct applied importance for estimating ecosystem carbon storage and fluxes [ 14 ]. Planted forests are defined as “forest predominantly composed of trees established through planting and deliberate seeding [ 15 ]. Globally, natural forests are disappearing at an alarming rate because of human intervention, which increases carbon dioxide emission in the atmosphere, causing global warming and climate change. In response to combat the climate change, an area 12.3 million hectares (ha) between 2010 and 2015 has been planted to enhance the total forest cover [ 15 ]. According to [ 18 ] of the global forest area, 7.0% forest area is composed of plantation forests, which is 291 million hectares. To counter climate change planted forest are effective tools due to carbon (C) absorption ability and an increasingly important role play in regulating climate in the future [ 19 ]. In Vietnam planted forests rapidly increased since 2000 from two million ha to about 4.2 million ha in 2018 [ 20 ] or more than 26.0% of the total forest area, with approximately two–thirds of the plantations area managed by smallholders [ 21 ]. This rapid expansion of plantations in recent years is due to the Government of Vietnam (GOV) implementing afforestation and reforestation programs that have been initiated from the 1980s in response to extensive deforestation and forest degradation during and after the American war [ 22 ]. Vietnam's approach to carbon sequestration integrates sustainable forest management practices and community–based conservation initiatives. While enhancing carbon storage capacities, forest governance and biodiversity conservation have improved through Forest Sector Support Partnership Programs [ 23 ]. These programs also aimed to increase rural populations' income, and fulfill industries' demands for timber [ 24 ]. Because of these programs, from 1990 to 2010, annually about 2.37% forest cover increased [ 25 ], and in Asia, Vietnam is one of few countries to achieve a forest transition [ 26 ]. These immature plantations show significant C sequestration potential [ 27 ]. In order to minimize atmospheric CO2 concentration accumulation, predict, and maintain long–term productivity of the system, relevant studies about carbon stocks in plantations will be especially helpful [ 28 ]. There is inadequate information about the tree carbon stock and its potential for sequestration in mixed plantation forests in Luot Mountain, Vietnam. The carbon stock and sequestration rate of planted forests, as well as their stability, have not been adequately quantified. A study has been conducted on aboveground biomass and carbon stock in six socio-economic regions of Vietnam [ 29 ]. Another study was also conducted on sustainably developing carbon stocks and Melaleuca forest growth in U Minh Thuong National Park in Vietnam after big fires [ 30 ]. Further, there were also studies on the effects of forest land use change on carbon stocks in Vietnam's northern mountainous regions [ 31 ] and Ba Vi's canopy structure and carbon stocks [ 32 ]. There are still gaps about the aboveground tree carbon stock as well as its potential for sequestering CO₂ in mixed plantation forests in Luot Mountain, Vietnam. Luot Mountain, Vietnam, there is still crucial needs to ascertain the comprehensive study to determine the tree carbon stock and its potential for sequestration in mixed plantation in order to prepare an effective and comprehensive management plan for future marketing. Hence, to identify the carbon sequestration rate of various ecosystems and their stability, uncertainty, and sustainability, it is inevitable to achieve carbon neutrality and carbon peaking [ 33 ]. As a consequence, this study was conducted with an eye towards the potential biomass, carbon, and environmental services of Luot Mountain for absorbing CO2, producing O2, and generating carbon credits. This study quantified the aboveground tree carbon stock and biomass of the Luot mountain forest for the purpose of valuing the carbon absorption capacity (carbon credits) of the mixed forest plantation. This study has specific objectives, including (1) determining the biomass and carbon stocks and biomass potential of mixed plantation forests Luot Mountain, (2) quantifying the value of mixed forest carbon credits, and (3) evaluating the environmental services provided by mixed forest plantations, such as the ability to absorb CO 2 , produce oxygen, and generate carbon credits. By determining the storage and cycling of carbon in tree components at the regional level, the findings of this study will contribute to the effective management and use of planted forests in the future. 2. Materials and Methods 2.1. Study Area This study was carried out within an experimental forest complex encompassing of mixed plantations at Luot Mountains is located in Xuan Mai town, Chuong My district of Ha Noi, at a latitude and longitude of 20°54'43" N 105°34'11" E (Fig. 1 ). It covers more than 150 ha and is characterized by a tropical monsoon climate. Originally native to the Poccafiarite parent rock, the soil is a brownish-yellowish feralit. Humus content in soil ranges from 2–3%, resulting in a pH of 7 due to the presence of humus. The soil accumulates a high level of aluminum and iron, is stable, and has a low phosphorus concentration. There is an average slope of 15 degrees, and the average temperature ranges from 20 to 25 0 C. The hottest month of the year is July. The average annual rainfall is 1753 millimeters. There are seven main forest types based on three main mature species: Eucalyptus urophylla, Acacia auriculiformis , and Pinus massoniana . Approximately 300 plant species are indigenous to the area [ 34 ]. 2.2. Data collection 2.2.1. Method of setting sample plots A total of 20 rectangular shaped sample plots in different land use types, with a plot dimension of (25×20m) 500 m 2 by following stratified random sampling method were taken. In each plot, the diameter tape and caliper were used to measure the tree diameter (cm) at breast height (DBH) greater than 6 cm. Blume–Leiss was used to measure height [ 35 ]. 2.2.2 Biomass Carbon calculation Stem volume (m 3 /ha) was calculated from DBH and tree height by using previous literature e.g [ 36 ]. Stem volume was calculated by using the following formula. V (m 3 /ha) = AH×FF---------------------------------- (1) Where , V = volume of stem (m 3 ), A = cross sectional area at BH point (m 2 ), H = tree height (m), FF = form factor From stem volume (m 3 /ha) and wood density (kg/m 3 ) Stem biomass (tones/ha) was calculated. From available literature, wood densities for all tree species were obtained. The following formula was used to determine the biomass of the stem. Stem biomass (tones/ha) = Stem volume (m 3 ) × Basic wood density (kg/m 3 ) ------------------- (2) The total tree biomass in (tones/ha) was determined using biomass expansion factors (BEF). Biomass expansion factors (BEF) was used to calculate total tree biomass (tones/ha), [ 33 ]. BEF of respective species was obtained and multiplied with stem biomass by using the following formula. Total biomass (tones/ha) = BEF×Stem biomass (tones/ha) ---------------------------------- (3) To get total carbon stock (tones/ha), total tree biomass (tones/ha) was multiplied with conversion factor of (0.5), which was sourced from Eq. (4) [ 37 , 41 ]. Carbon (tones/ha) = Biomass (tones/ha) × Carbon % (0.5) ---------------------------------- (4) 2.2.3. Environmental service potential The potential for environmental services is calculated using carbon credits, O 2 generation, and absorbed CO 2 . Eq. 5 can be used to examine the computation of the CO 2 absorption environmental service value [ 42 ]. CO 2 absorbed = Ct×3.67 ---------------------------------- (5) Where , Ct is the total amount of carbon stored (in tons/ha), CO2 absorbed is the amount of carbon dioxide absorbed (in tons/ha), and 3.67 is the equivalent number or conversion factor from carbon to carbon. To obtain carbon credits, the absorbed CO 2 was multiplied by the current carbon credit price, minus the transaction fees. In 2019, the World Bank set the price of carbon credits as USD 40/tones. Transaction costs include monitoring, administrative process fees, and verification of emission reduction services utilizing absorbed CO 2 . In the forestry sector, the transaction cost for reducing absorbed CO 2 emissions is $ 1.23 USD [ 43 , 44 ] ;. Thus, using Eq. 6, the environmental service value of carbon credits was calculated [ 45 ]. Carbon credits = HJ CO 2 × CO 2 absorbed ---------------------------------- (6) Where , Carbon credit – carbon dioxide compensation (tones/ha), HJCO 2 – Selling price of carbon credit (USD 40/tones), CO 2 absorbed – Carbon dioxide absorbed (tones/ha). The environmental service value of the O 2 production can be calculated using the CO 2 absorption development through Eq. 7 [ 46 ]. O 2 production = CO 2 × 0.73 ---------------------------------- (7) Where , O 2 production – oxygen production (tones/ha), CO 2 absorbed – absorbed carbon dioxide (tones/ha), 0.73 – equivalent number or conversion factor from CO 2 to O 2 . 2.3. Statistical analysis MS Excel 2016 and Sigma Plot version 12.5 (Systat Software Inc) were used for data analysis. For above–ground trees, descriptive statistics (min, max, and mean) were calculated for various parameters like tree height (m), diameter (cm), basal area (m 2 /ha), volume (m 3 ), biomass (tones/ha), and carbon stock (tones/ha). we developed linear regression models to investigate the relationship between tree diameters (cm) and height (m), diameter (cm) and volume (m 3 /ha), diameter (cm) and stem density (trees/ha), stem volume (m 3 /ha) and basal area (m 2 /ha), stem biomass (tones/ha) and basal area (m 2 /ha), total biomass (tones/ha) versus basal area (m 2 /ha) and total carbon stock (tones/ha) using Python version 3.12 [ 47 ] ( http://www.python.org ). 3. Results 3.1. Vegetation type status of mixed plantation forests of Luot Mountain The total area of Luot Mountain was more than 150 ha. These include pure pine plantation, pure white eucalyptus plantation, Acacia hybrid forest, Acacia auriculiformis and mixed forest species (about 30 years old). Among them, Acacia hybrid forest covered 32.02 ha (21.13%) of area, followed by Pine Forest 13.36 ha (8.81%), and mix forest 12.67 ha (8.42%) (Table 1 ). The least area was that of Pine–Acacia 0.96 ha (0.63%) and Eucalyptus 1.67 ha (1.10%). Other uses included a large military zone (25.25 ha); infrastructure (14.5ha), residential (17.71 ha) and electric pole line. Table 1 Vegetation type status of mixed plantation forests of Luot mountain Type of forest Pine forest Eucalyptus Acacia–hybrid forest Eucalyptus-Acacia Pine– Eucalyptus Pine– Acacia Mix forest Other Total area (ha) 13.36 1.67 32.02 2.16 1.95 0.96 12.67 86.72 Rate (%) 8.81 1.10 21.13 1.42 1.28 0.63 8.42 57.21 The growth and development of the shrub layer, as a fresh carpet was very dense. Pinus massoniana and Acacia auriculiformis were the dominant trees specie. 3.2. Descriptive statistics on different parameters 3.2.1. Diameter, height, volume and basal area Table 2 below showed the key characteristics of the plots in the study area. The data showed that maximum diameter 51cm was investigated at plot 16, having plot elevation of 115m (15 0 ), while minimum diameter of 28cm at 17 plot with average of 38.06 (cm) of the whole plots. Maximum 29.8m tree height was found at plot 16 at 15 0 slope and 115m plot elevation, on the same way minimum height of 17.73m was investigated from plot 17 at plot elevation of 102m. The average height for the entire plots was 22.51m. The average basal area volume of the study area was 230.81m 3 /ha, which range from 117.8m 3 /ha to 410.9 m 3 /ha at plot 16; with plot height of 115m. In the present study average basal area was 25.6m 2 /ha. Highest basal area 36m 2 /ha was detected at plot 2 while the lowest basal area 14m 2 /ha was recorded from plot 1. There is a strong correlation between stem diameter (cm) and basal area (m²/ha), meaning the higher the stem diameter (cm), the higher the basal area (m²/ha). 3.2.2. Stem density, stem biomass, total biomass and total carbon stock The stem density refers the number of trees per hectare. In the present study maximum and minimum stem density of 860 and 420 trees/ha was investigated from plot 12 and 6 respectively. These plots had an average of 628 trees per hectare and an average stem biomass of 132.7 tons per hectare. Plot 16 had the highest biomass, 236.3 tons/ha, and Plot 1 had the lowest biomass of 67.72 tons/ha. It was determined that Lout Mountain had a mean biomass of 62.4 tons/ha. Total tree biomass was highest at plot 16 with 111.05 tons/ha and lowest at plot 1 with 31.89 tons/ha. Approximately 31.2 tons of carbon were accumulated on Luot Mountain in mixed forest. Plot 16 and 1 had minimum and maximum carbon stocks of 15.92 tons/ha and 55.52 tons/ha, respectively (Table 2 ). Table 2 Descriptive statistics on different growing stocks features Plot No Elevation (m) Slope Degree Height (m) DBH (cm) Basal Area m 2 /ha Volume m 3 /ha Stem Density trees/ha STBM tons/ha TTBM tons/ha Carbon tons/ha 1 48 8° 21.03 38.6 14.0 117.8 581 67.7 31.83 15.9 2 46 7° 20.73 36.1 36.0 298.5 532 171.6 80.7 40.3 3 47 2° 21.20 39.0 19.0 161.1 480 92.6 43.5 21.8 4 36 5° 24.8 42.0 22.0 217.8 514 125.2 58.9 29.4 5 65 7° 25.5 45.2 31.0 316.8 620 182.2 85.6 42.8 6 58 2° 23.9 43.0 28.0 268.01 420 154.1 72.4 36.2 7 56 5° 21.5 35.0 35.0 301.0 710 173.1 81.4 40.7 8 60 2° 20.1 31.0 27.0 216.8 679 124.6 58.6 29.3 9 63 2° 22.7 39.0 18.0 163.5 700 94.02 44.2 22.09 10 58 5° 28.8 47.0 23.0 265.2 780 152.5 71.7 35.8 11 85 4° 18.04 32.0 32.0 230.9 540 132.8 62.4 31.2 12 59 4° 18.2 29.0 29.0 211.4 860 121.5 57.12 28.6 13 54 3° 20.3 32.0 16.0 129.9 731 74.7 35.09 17.6 14 52 3° 24.03 41.0 21.0 201.9 604 116.06 54.6 27.3 15 55 8° 18.7 34.1 26.0 194.2 582 111.7 52.5 26.2 16 115 5° 29.4 51.0 35.0 410.9 734 236.3 111.05 55.5 17 102 3° 17.7 28.0 17.0 120.6 509 69.32 32.6 16.3 18 70 7° 25.7 37.5 24.0 246.2 639 141.6 66.6 33.3 19 50 4° 18.09 31.6 34.0 246.02 493 141.5 66.5 33.2 20 40 3° 29.8 49.0 25.0 297.7 714 171.2 80.4 40.2 Mean 22.5 38.06 25.6 230.81 621.10 132.7 62.4 31.2 Min 17.7 28.0 14.0 117.8 420 67.72 31.83 15.9 Max 29.8 51.0 36.0 410.9 860 236.3 111.05 55.5 STDV 3.86 6.7 6.85 74.1 115.24 42.6 20.02 10.01 St error 0.86 1.5 1.53 16.57 25.7 9.53 4.5 2.24 Variance 14.8 44.5 46.8 5487.8 13280.2 1814.8 400.8 100 CV% 17 17.5 26.7 32.09 18.55 32.10 32 32.07 3.2.3. Regression analysis of the variables A regression analysis revealed a strong positive linear correlation between (DBH) Diameter at Breast Height (cm) and height (m) with R 2 value 0.88. This indicates that tree diameter has a good correlation with tree height. A low p–value (p = 0.0000) explains the association between diameter and height of trees. The carbon stock of mixed forest is influenced by trees volume; understanding this relationship can help us determine its carbon sequestration potential. Based on an R 2 value of 0.35, the relationship between diameter and volume exhibited a moderate correlation, indicating that volume increases with increasing diameter. When the coefficient of determination is low, the diameter of trees is not an effective predictor of volume; other factors must also be taken into account. Furthermore, the relationship between diameter and stem density was not linear (weak negative relationship) with an R 2 value of 0.01, showing that the red line explains 1 percent of the variance (Fig. 2 ). Diameter doesn't predict stem density in this study because of its low coefficient of determination. There was a strong linear relation between basal area and volume, with R 2 = 0.67, indicating that basal area is a good predictor of volume. With R 2 value of 0.67, the relationship between basal area and total biomass was strong linear, showing that 67.0% of variance in total biomass can be attributed to basal area. In addition, basal area and carbon stock have a positive linear relationship with R 2 value of 0.67, which indicates that carbon stock increases by 1.19 tons per hectare for every square meter increase in basal area. As a result, more the basal area more will be the carbon stock. 3.2.4. Environmental service production Based on natural ecosystem processes, environmental services are the benefits obtained by humans and the environment from the concept of natural systems [ 39 , 40 ]. Luot Mountain mixed plantation forests were assessed for their environmental service production, such as capacity to absorption potential of CO 2 , O 2 production and carbon credits generation. The results demonstrated that mixed plantation forests Luot Mountain absorbed carbon dioxide (CO 2 ) 2288.94 tons per hectare, produced oxygen (O 2 ) 1670.92 tons per hectare, and generated carbon credit having value 91.55 US dollars per hectare (Table 3 ). Given the current enormous emissions issues, this trade has a lot of promise in the current global competitive environment [ 41 ]. Table 3 Environmental service output of the study area Environmental service potential of the Lout moutain CO 2 absorbed (tons/ha) O 2 production (tons/ha) Carbon credit (US$/ha) 623.69×3.67 = 2288.94 2288.94×0.73 = 1670.92 40×2288.94 = 91557.6/1000 = 91.55 4.0. Discussion 4.1. Tree Diameter, height, volume and basal area A forest is not just a green lung for our planet, but it is also a vital reservoir of carbon, so it is crucial to maintain it in the fight against climate change. It is, however, essential to have accurate information before we can transform that potential into measurable impact. Forest ecosystems not only play an important role in CO 2 sequestration, climate change mitigation and production bioenergy but also provide a livelihood to humans [ 45 ]. The global estimates reports confirmed that 12.0% of anthropogenic carbon emissions are sequestered by forests [ 46 ]. However, due to agriculture expansion, increase in deforestation rate land has alarmingly degraded into forest area and its carbon pool [ 47 ]. The forest ecosystem carbon storage capacity has been negatively affected because of an increase in global atmospheric CO 2 concentration and deforestation at alarm rate [ 48 ]. Through the Kyoto Protocol [ 49 ], these forest dynamics in the transformation of carbon dioxide from the atmosphere led to the management of carbon sequestration in natural forests, in which forest ecosystems generate sustainable production of various goods and services through carbon credits [ 50 ]. The outcome of diameter measurement indicated that the tree diameters ranged from a minimum 28 cm to 51 cm maximum, with average of 38.06 cm of the whole plots. [ 51 ] reported that diameter for northwest evergreen broadleaf forest ranged 54–83 cm in Vietnam. Likewise, [ 28 ] recorded tree diameter ranged from 20.76–22.87 cm with average of 21.78 cm in 11 years age Acacia mangium plantation in Chang Riec historical culture forest southeastern region, Vietnam. In other instance, trees diameter ranged from 13.8 − 17.8 cm was recorded for vegetation I and II for natural vegetation in Me Linh Biodiversity Station, Vinh Phuc province, Vietnam [ 65 ]. In Biological Station of La Selva, Costa Rica highest DBH of 25.5 cm was documented for pure V. guatemalensis planation, 30.5 cm for mix V. guatemalensis planation and 31.3 cm for mix T. Amazonia plantation respectively [ 57 ]. In addition, [ 53 ] stated that tree diameter range from 17–66 cm for Pinus sylvestris , 7.1–63.2 cm for Pinus sylvestris [ 58 ] and 20–52 cm for Picea orientalis [ 59 ]. Moreover, [ 61 ] recorded tree diamter 25.1 cm for V. guatemalensis and 26.80 cm for the mix forest with thinning, and 23.50 cm for V. koschnyi with thinning at Biological Station Costa Rica of La Selva. Tree heights results for mixed forests demonstrated that height ranged from 17.73 meters to 29.8 meters, with a mean height of 22.51 meters. Our measurements of height are coincident with [ 28 ], i.e., 18.9 m in a 12–year-old Acacia mangium forest in the change Riec historical culture forest in the southeastern region of Vietnam. In parallel, our tree heights are also closely related to the findings of [ 60 ]. For instance, we found 27.5 m height for polycultures of V. guatemalensis , 27.12 for mixed polycultures of J. copaia , and 22.03 for pure polycultures of J. copaia for La Selva Costa Rica Biological Station. Furthermore, the findings of our research are also consistent with [ 57 ], which documented that V. guatemalensis reaches a height of 24.4 m while V. ferruginea reaches 22.1 m, V. koschnyi reaches 21.7 m, and J. copaia species and 25.6 m for mixed plantation, respectively, for La Selva Biological Station Costa Rica. The average tree volume across the study was 230.81 m3/ha, ranging from 117.8 m3/ha (minimum) to 410.9 m3/ha (maximum). These findings are consistent with [ 56 ] r which estimated 115.2 (m 3 /ha) volume for C. brasiliense and 301.4 for V. guatemalensis , 331.6 for J. copaia at age of 10.3 years, 213 (m 3 /ha) for T. amazonia , 254.6 for mixture, and 280 (m 3 /ha) for V. koschnyi at the age of 10 years, 105.9 (m 3 /ha) for H. alchomeoides , 144 (m 3 /ha) for B. elegans , 194.7 (m 3 /ha) for mixture and 207.6 (m 3 /ha) V. ferruginea at the age of 9 years respectively in pure and mixed plantation at Costa Rica La Selva Biological Station. In other instance, [ 53 ] a tree volumes 176.6, 318.5 and 410.3 (m 3 /ha) were determined for C. brasiliense , J. copaia and V. guatemalensis species respectively at plantation I and 128.5, 232.7, 292.8 and 402.1 (m 3 /ha) tree volume for D. panamensis , T. amazonia , and V. koschnyi respectively mixed plantation II and tree volume 179.5, 207.9, 248.4 and 300.4 (m 3 /ha) for H. alchornoeides , B. elegans , and V. ferruginea respectively for plantation III at La Selva Biological Station Costa Rica. The mean basal area in mixed plantation forests was 25.6 m 2 /ha, and it ranged from 36 m 2 /ha highest to lowest 14 m 2 /ha to 25.6 m 2 /ha. The results of this study are closely related to the findings of [ 56 ], for example, 16.69 m 2 /ha, 28.85 m 2 /ha, 29.45 m 2 /ha, and 45.47 m 2 /ha basal areas for C. brasiliense, J. copaia , and V. guatemalensis for 10.3–years of plantation. Approximately 20.97 m 2 /ha, 26.39 m 2 /ha, and 28.55 m 2 /ha for T. amazonia , mixture, and V. koschnyi respectively, for a 10–year old plantation. At La Selva Biological Station Costa Rica, the area of pure and mixed plantations of H. alchomeoides, B. elegans , mixture, and V. ferruginea is 13.33 m 2 /ha, 18.54 m 2 /ha, 22.38 m 2 /ha, and 24.69 m 2 /ha, respectively. As for plantation I, basal areas of 20.0 m 2 /ha, 28.4 m 2 /ha, 35.1 m 2 /ha, and 38.1 m 2 /ha are allocated for C. brasiliense, J. copaia , and V. guatemalensis for 13 years of age. Further, 13–year-old plantation II contained 14.9 m 2 /ha, 22.7 m 2 /ha, 38.9 m 2 /ha, and 26.9% m 2 /ha of D. panamensis, T. amazonia, V. koschny i, and a mix of the three species. Plantation III at La Selva Biological Station Costa Rica accounted for 17.5 m 2 /ha, 23.8 m 2 /ha, 29.4 m 2 /ha, and 23.6 m 2 /ha basal area for H. alchornoeides, B. elegans , and V. ferruginea [ 57 ]. 4.2. Forest stand’s variables characteristics As a result of the present study, the maximum and minimum stem density was 860 trees/ha and 420 trees/ha, respectively, with a whole average of 628 trees/ha. There is a similar tree density detected in a undertaking at Me Linh Biodiversity Station in Vinh Phuc province, Vietnam, i.e., 577 trees/ha for vegetation II and natural vegetation. Furthermore, [ 70 ] reported 860 trees/ha, 800 trees/ha, and 680 trees/ha in rich forest areas which are consistent with our findings. Additionally, the findings of in Nam Mau communes, 800 trees/ha and 820 trees/ha were detected in damaged and rehabilitated forests, and 860 trees/ha in medium forests are closely associated with our findings. Similar densities, e.g., 820 trees/ha and 860 trees/ha were determined for medium forests in Quang Khe communes, 820 trees/ha and 840 trees/ha were determined for poor and rehabilitated forests in Nam Cuong communes, and 740 trees/ha, 780 trees/ha, and 840 trees/ha respectively for medium forests in Hoang Tri commune. The mid-Central Coast has a tree density of 708–749 trees/ha, and the Central Highland has a tree density of 573–918 trees/ha. Our findings of tree density are similar to those in [ 28 ], which documented 610 trees/ha, 728 trees/ha, and 888 trees/ha from 4–year–old, 7–year–old, and 11–year–old Acacia mangium plantations in the Riec historical culture forest in the southern region of Vietnam. In another study, 699.5 trees/ha, 721.7 trees/ha, and 803.7 trees/ha were reported for V. guatemalensis, C. brasiliense , and J. copaia after 10.3 years of plantation [ 56 ]. Our results are in alignment with those reported in [ 57 ], in which 543 trees are found per ha, 737 trees are found per ha, 766 trees/ha, and 781 trees/ha for T. amazonia , mixture, D. panamensis , and V. koschnyi , respectively, in pure and mixed plantations from 9 years old at La Selva Biological Station Costa Rica, 622 trees/ha, 721 trees/ha, 736 trees/ha, and 870 trees/ha for G. Americana, V. ferruginea, H. alchomeoides , and B. elegans . At plantation I of La Selva Biological Station Costa Rica, 612 trees/ha, 664 trees/ha, 684 trees per hectare, and 772 trees/ha were investigated for C. brasiliense, V. guatemalensis , and J. copaia , respectively. Additionally, there were 547 trees/ha, 752 trees/ha, 840 trees/ha, and 606 trees/ha for T. amazonia, D. panamensis , and V. koschnyi , along with a mixture of the three species. Similarly, for plantation III there were 723 trees/ha, 771 trees/ha, 781 trees/ha, and 713 trees/ha for V. ferruginea, H. alchornoeides , and B. elegans [ 57 ]. Based on the test results, mixed forest plantations had a biomass of 62.4 tons per hectare and range from 31.8 to 111.05 tons/ha. The findings are in agreement with those of a study by [ 30 ] that found an average trunk biomass per hectare (2.72–107.39 tons). In another study, tree layer biomass for vegetation types I and II for natural vegetation was 49.35 to 69.70 tones/ha at Me Linh Biodiversity Station, Vinh Phuc province, Vietnam. In a study conducted by [ 73 ], the amount of biomass varies from 55.72-130.18 tons/hectare, with an average of 84.54 tons/hectare in damaged and rehabilitated forest in Nam Mau communes. Moreover, they assessed that damaged and rehabilitated forests of Quang Khe communes produced biomass in the range of 54.96 tons per hectare to 137.5 tons per hectare, with an average of 84.9 tons per hectare. Furthermore, the biomass for damaged and rehabilitated forest in Nam Cuong communes ranged from 33.45 to 73.92 tons per hectare. Additionally, they detected biomass in Ba Be National Park Vietnam, which weighed 71.11 tons/ha in damaged and rehabilitated forests. As another example, [ 28 ] reported biomass of 55.08 to 109.18 Mg/ha (60.7 and 120.3 tones/ha converted) in Acacia mangium plantations of 4 and 7 years old located in the change Riec historical culture forest in the southeastern region of Vietnam. Similar results were observed in dry deciduous and mixed deciduous forests in Madhya Pradesh of India (44.5 and 54.9 tons/ha). An assessment of the forest carbon stock of Balganga Reserved Forest (BRF) was conducted in Uttarakhand, India. Site III, in the 1800–2600 m elevation range, had the highest total biomass density (TBD) of 108.26 Mg/ha (119.3 tons/ha), followed by site II, in the 1600–1800 m elevation range (83.92 Mg/ha; 92.5 tons/ha), and site I, at 1000–1400 m elevation (57.22 Mg/ha; 63.07 tons/ha), with an average of 83.13 Mg/ha (91.6 tons/ha). As assessed by [ 60 ] for carbon sequestration potential, three forests of tropical dry deciduous in Haryana Gurgaon district accumulated 37.93 to 63.73 Mg/ha (41.8 to 70.2 tones/ha) AGB. Moreover, allometric equations [ 61 ] were used to determine biomass in Northeast India, Tripura tropical forest. Approximately 41.72 to 94.3 tons of biomass was collected per hectare. In an Indian community-managed forest in the Garhwal Himalayas, the total biomass was 132.74 Mg/ha (146.3 tons/ha) [ 62 ]. A study conducted by [ 63 ] used remote sensing satellites and GIS technology to calculate biomass and carbon in dry tropical forests in Chhattisgarh and established AGB 45.94–78.31 Mg/ha (50.64 to 86.32 tons). The same method of area weights was used by [ 64 ] in Gujarat, India's moist deciduous forest where 5.534–0.133 tons of biomass were recorded per hectare with a mean of 40.50 tons per hectare. As well as this, [ 65 ] determined the total biomass of 5–year–old Ceiba pentandra trees to be between 12.9 and 25 Mg/ha (14.21 and 27.6 tons/ha), Gmelina arborea to be between 9.9 and 21.4 Mg/ha, and Populus deltoides clones of Chhattisgarh, India, from 48.5 to 62.2 Mg/ha (53.4 to 68.56 tons/ha). Based on [ 66 ], the biomass productivity and carbon stocks of farm forestry and agroforestry systems in Andhra Pradesh were 62 Mg/ha (68.34 tons/ha) and 34 Mg/ha (37.47 tons/ha), respectively. Using biomass from five study sites in Tamil Nadu (four plantations and a natural forest), [ 67 ] analyzed the AGB of Coccus nucifera, Casuarina equisetifolia, Mangifera indica , and Anacardium occidentale , and found 143.2 tons, 38.0 tons, 121.1 tons, and 32.7 Mg/ha (157.85 tons per ha, 42.0 tons/ha, 133.4 tons/ha, and 36 tons per ha converted). In the Pachaimalai forest of the Eastern Ghats in India, [ 68 ] determined the annual biomass as 25.3x5.6 (tons/ha) with a range of 4.2x103.5 (tons/ha). From Luot Mountain mixed plantation forests, we estimated a mean carbon stock of 31.2 tons/ha, ranging from 15.9 tons/ha to 55.5 tons/ha. The results of our study are closely related to those of [ 34 ], in which they estimated a mean carbon stock of 23.04 tons/ha. Further, [ 69 ] estimated 24.63 ton/ha and 34.85 ton/ha average carbon stocks in natural vegetation in Vinh Phuc province, Me Linh Biodiversity Station, Vietnam. Additionally, [ 70 ] documented 11.5 tons/ha from A. mangium and Eucalypt plantations in Vietnam. Similarly, a study carried out by [ 71 ] estimated 38 Mg/ha C (41.9 tons/ha converted) in a Western Panama Teak plantation for ten–year–old teak. As well, a study was conducted in Indonesia by [ 72 ] on 46.32 tons per hectare for the production forest. In damaged and rehabilitated forests of Nam Mau communes, [ 73 ] documented 26.29 tons/ha, 32.44 tons/ha, 34.86 tons/ha, and 44.05 tons/ha of carbon. They also reported 18.32 tons/ha, 25.83 tons/ha, 44.31 tons/ha, 46.28 tons/ha, 64.83 tons/ha with a minimum to 137.5 tons/ha average for poor and rehabilitated forests in Quang Khe communes, 15.72 tons/ha, 16.81 tons/ha, 16.91 tons/ha, 19.0 tons/ha, 34.74 tons/ha, with an average of 20.64 tons/ha respectively for poor and rehabilitated forests in Nam Cuong communes. Additionally, [ 74 ] estimated 37.27 tons/ha of carbon stock in poor forest in Bach Ma National Park, Vietnam. The outcome of the results evidently demonstrated that, the carbon stock in the mixed forest plantation Luot Mountain is lower than the value for Asia, which ranges from 34.4–85.6 Mg/ha C (37.9–94.4 tons/ha converted), as well as that for global forests, 44.8–118.2 Mg/ha carbon stock (49.4–130.3 carbon tons/ha converted) [ 76 ]. Our results are almost equal to the findings of [ 77 ] estimated 31.7 and 29.2 tons of carbon in 2005 and 2015 for poor forests (evergreen broadleaves), and 21 and 23.6 tons/ha carbon in planted forests, respectively. Likewise, the outcome of our study is within the ranged of results of the study conducted in a 12–year–old mixed species cabinet timber plantation on the Atherton Tableland, north–east Australia, 51 tons of carbon was documented per hectare [ 78 ] and also [ 79 ] estimated 41 tons/ha carbon from 20–year–old cocoa trees and 45.3 tons/ha carbon for a 23–year–old plantation at Kade Agricultural Research Centre. Furthermore, similar findings were documented in J. copaia at plantation I in Costa Rica, 25.5 Mg/ha carbon (28.1 tons/ha converted) was measured, while for plantation II, 26.1, 36.8, 44.4, and 47.3 Mg/ha carbon (28.8 tons/ha, 40.6 tons/ha, 48.9 tons/ha, and 52.1 tons/ha converted) were measured for B. elegan, V. ferruginea, H. alchornoeides , and a mixture of these species [ 53 ]. Additionally, the results of current study are in parallel to research conducted by [ 80 ] in carbon pool sizes of Indian trees and forests ranged from 41 to 48 Mg/ha carbon (45.2 to 52.9 tons/ha converted) and from 39 to 47 Mg/ha carbon (43.0 to 51.8 tons/ha converted) for 1992 and 2002. As well, [ 59 ] estimated the carbon stock in Balganga Reserved Forest, Tehri Garhwal Uttarakhand India and reported the highest total biomass carbon density (TBD) at site III (elevation 1800–2600m) 53.45 Mg/ha (58.9 tons/ha converted), 42 Mg/ha carbon for site II (elevation 1600–1800m) (46 tons/ha converted), and 28.61 Mg/ha for site I (elevation 1000–1400 m) (31.5 tons/ha converted) with a mean of 41.6 Mg/ha (45.6 tons/hectare). Additionally, the findings of our study of carbon stock are aligned with previous study carried out in three protected forest types of tropical dry deciduous forests in Gurgaon district, southern Haryana [ 56 ] found that carbon was potentially sequestered in the forests, i.e., they documented 34.17 Mg/ha (37.7 tons/ha converted) carbon stock for Acacia leucophloea and Balanites aegyptiaca and 33.61 Mg/ha (37 tons/ha converted) for Anogeissus pendula and A. leucophloea in Yamunanagar and Saharanpur districts in northwestern India. The outcomes of our study are also closely related with study carried out by [ 81 ] estimated 27–32 tons of carbon per hectare for Poplar ( Populus deltoides ) agroforestry system and Poplar planting in boundary systems. As well, [ 59 ] used satellite remote sensing and GIS to estimate biomass and carbon in dry tropical forests in the Chhattisgarh region of India, resulting in 22.97 to 33.27 Mg/ha C (or 25.3 to 36.7 tons/ha converted). The findings of our study of carbon stock are aligned with previous study conducted in Madhya Pradesh, India, 13–42 Mg/ha (14.3–46.3 tons/ha converted) were recorded in non–teak forests and 33–53 Mg/ha (36.4–58.42 tons/ha converted) in teak–dominated forests [ 58 ]. However, our results are quite higher as compared to the results of a study conducted by [ 82 ] incorporated the sequestration and estimated 20.27 tons of carbon in natural plantation, Western Ghats. Our study results are higher than the study conducted in Karnataka, India, aboveground carbon stocks for dry deciduous forests 9 to 12 tons/ha by allometric volume equations [ 83 ] and also from Bodamalai hills tropical forests in Tamil Nadu 10.9 tons/ha [ 84 ]. Our findings are consistent with those of the study [ 58 ] which measured the above-ground biomass carbon density in a forest in Turkey at 32.44 grams per hectare (35.75 tons per hectare converted). The results of our study are also closely associated with those of [ 86 ] who found that the average biomass carbon density in European forests was 43.9 Mg/ha carbon (48.4 tons/ha converted). The same results were reported by [ 87 ] in Europe with 42.5 Mg/ha carbon (46.8 tons/ha converted). Further, such types of output have also been estimated by [ 82 ] in Europe at 43.9 Mg/ha carbon (48.4 tons/ha converted). Similar results were reported in another study in Europe [ 88 ] with 40.1 Mg/ha carbon (44.2 tons/ha converted). The results of this type were also documented by [ 89 ] in 1990, when 45 Mg/ha C (49.6 tons/ha converted) existed in 30 countries in Europe. Additionally, [ 90 ] estimated the carbon stock in Europe at 32 Mg/ha C (35.2 tons/ha converted), which is in line with our findings. A carbon stock of 45 Mg/ha (49.6 tones/ha converted) was reported by [ 91 ] in Turkey, which was the same as the output of our study. Comparatively, [ 92 ] recorded a lower carbon stock of 20.71 Mg/ha C (22.82 tons/ha converted). 4.3. Environmental service production To estimate the value of carbon dioxide that can be absorbed by a forest stand, carbon dioxide absorption potential is used. The amount of carbon that plants absorb is correlated with their carbon content because the carbon content is directly correlated with the plants' capacity to bind carbon dioxide from the atmosphere [ 91 , 92 ]. Absorption intensity of plant is indirectly affected by diameter and height of a plant, in relation to plants’ ability of carbon dioxide absorption [ 93 , 94 ]. The total carbon dioxide absorption potential of the present study was 2288.94 (tones/ha), O 2 production was 1670.92 (tones/ha), while carbon credit value was 91.55US $ /ha. [ 41 ] reported 1753.04 (tones/ha) total CO 2 absorption potential, 1279.72 (tones/ha) O 2 production and 70.12 US $ /ha total carbon credits value generated in Indonesia, Mount Bromo, Special Purpose Forest Area. India Himachal Pradesh region of middle Himalayan Kwalkhad watershed, Carbon sequestration and carbon credits were determined by [ 95 ]as 14.78 Mg/ha in Agri-horti-silviculture systems and 14.45 Mg/ha in agri-horti-silviculture systems, respectively. 4.4. Regression analysis of the variables in the forest stand In the study with R 2 value of 0.88 (dbh) diameter at breast height (cm) and height (m) have strong positive linear correlation. [ 35 ] conducted a study in the Kumrat valley of Pakistan and investigated polynomial Quadratic relationship between tree diameter (cm) and tree height (m) with R 2 value of 0.99. [ 96 ] investigated Quadratic type with R 2 value of 0.98 for diameter and height. While a study by [ 97 ] reported a linear relationship between stem height and diameter of P. roxburghii of subtropical pine forest of Pakistan. In the Northeastern India, Manipur semi-evergreen tropical forest a study was carried out to estimate AGB and net primary productivity, following harvest method and reported a positive correlation between AGB of trees, tree species and DBH [ 98 ]. Diameter and volume exhibited a moderate correlation with R 2 value of 0.35. [ 35 ] also showed direct relation between volume with basal area (m 3 ) having R 2 value of 0.90. Weak negative relation between diameter and stem density was found with R 2 value of 0.01. According to [ 31 ] with R 2 value of 0.81, stem density and tree diameter has direct relation in a study in Kumrat area of Pakistan. With R 2 = 0.78 and R 2 = 0.52, [ 99 ] reported for 15.0 and 25-year-old Douglas Fir trees, a significant correlation between aboveground biomass and tree density. [ 100 ] investigated a positive correlation between tree density and plant carbon storage. Basal area and volume showed strong linear relationship, with R 2 value of 0.67. A study by [ 97 ] in the subtropical pine (Pinus roxburghii) forest found a linear relationship between and basal area and stem volume. [ 35 ] investigated polynomial linear relationship with R 2 value of 0.90 between volume and basal area (m 2 /ha), in Pakistan’s Kumrat valley pure Pinus Wallichiana Forest. [ 7 ] investigated a strong positive correlation of AGB with tree basal cover of R 2 = 0.996, 0.989 and 0.990 in three plant functional types (dry mixed, sal mixed and teak plantation) in Katerniaghat wildlife Sanctuary (KWLS), India. Strong linear relationship was investigated between basal area and total biomass with R 2 value of 0.67. [ 31 ] discovered a polynomial linear relationship with a R 2 value of 0.90 between biomass (tones/ha) and basal area (m 2 /ha) in the stunning Kumrat Pakistani region. The study by [ 98 ] reported linear relationship with coefficient (R 2 ) of 0.92 between AGP and basal area in broad leaved and coniferous forest in temperate forests of Kashmir Valley, J&K, India. [ 99 ] also found a quadratic relationship between basal area and biomass in the coniferous forest of the Dir Kohistan with R 2 = 0.96. In Peninsular India's inland and costal tropical dry evergreen forests, a positive relationship was also found between AGB and basal area (BA) [ 100 ]. Finally, with R 2 value of 0.67 a strong positive linear relationship is shown between carbon stock and basal area. [ 35 ] with R 2 value of 0.90 positive linear relationship was investigated between basal area and carbon stock in Pakistan Kumrat region. A linear functional relation between basal area and biomass carbon with value of R 2 (0.99) was investigated by [ 101 ], which supports the arguments of the practical relation of biomass carbon and basal area. [ 102 ] observed that the product of crown area and biomass carbon per tree in the Pine savanna were positively correlated (R 2 = 0.95) for pine trees. 5.0. Conclusion The purpose of this study is to provide insight into how plantation forest ecosystem carbon sequestration affects environmental performance. Biomass and carbon stocks were derived from above–ground mixed tree plantations. Based on the results of this study, the biomass and carbon stocks in the Luot mountain plantation of the Vietnam National Forestry University experimental site ranged from 31.2 (tons/ha) to 62.4 (tons/ha). Carbon credits from the study area are valued at 91.55US $ /ha, which equates to 2288.94 (tones/ha) and 1670.92 (tones/ha), respectively. The findings emphasize the importance of plantation protection and management approaches that prioritize the preservation of plantations due to their substantial carbon storage capacity. As a result, carbon sequestration evaluation of Luot mountain ecosystems has great hypothetical and practical implications for assessing carbon sinks in plantations and establishing carbon sink forests. For the purpose of forest management, the data will be used for ecological assessment and planning. Declarations Ethical approval Not Applicable. Consent to participate Not Applicable Consent to publish Not Applicable. Funding The authors did not receive support from any organization for the submitted work Author Contribution All authors contributed equally to the study concept, design and writing this paper. All authors read and approved of the final manuscript. Data Availability The data supporting the results reported in this study, including all original data generated and any secondary data used in the analyses, are available from the corresponding author upon reasonable request. References Suryawan IWK, Lee CH. Community preferences in carbon reduction: unveiling the importance of adaptive capacity for solid waste management. Ecol Indic. 2023;157:111226. Koul B, Yakoob M, Shah MP. Agricultural waste management strategies for environmental sustainability. Environ Res. 2022;206:112285. Lee RP, Meyer B, Huang Q, Voss R. Sustainable waste management for zero waste cities in China: potential, challenges and opportunities. Clean Energy. 2020;4:169–201. Suryawan IWK, Rahman A, Lim JW, Helmy Q. 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Carbon sequestration and soil fertility of tropical tree plantations and secondary forest established on degraded land. Plant Soil. 2013;362:187–200. Derwisch S, Schwendenmann L, Olschewski R, Hölscher D. Estimation and economic evaluation of aboveground carbon storage of Tectona grandis plantations in Western Panama. New For. 2009;37:227–40. Situmorang JP, Sugianto S. Estimation of carbon stock stands using EVI and NDVI vegetation index in production forest of Lembah Seulawah Sub-district, Aceh, Indonesia. Aceh Int J Sci Technol. 2016;5(3):126–39. Dong NT, Mai NTP, Lien NTH. Estimation of forest carbon stocks in Ba Be National Park, Bac Kan Province, Vietnam. Soc. 2020;4(1):195–208. Hai V, Trieu D, Tiep N, Bich N, Duong D. Research on carbon sequestration potential and commercial value of some major types of plantation forests in Vietnam. Final Project Report No. VAFS2009. Vietnam; 2009. p. 190. FAO. Global forest resources assessment 2010: main report. FAO Forestry Paper No. 163. Rome: Food and Agriculture Organization of the United Nations; 2010. Paudyal K, Samsudin YB, Baral H, Okarda B, Phuong VT, Paudel S, Keenan RJ. Spatial assessment of ecosystem services from planted forests in central Vietnam. Forests. 2020;11(8):822. Kanowski J, Catterall CP. Carbon stocks in above-ground biomass of monoculture plantations, mixed-species plantations and environmental restoration plantings in north-east Australia. Ecol Manag Restor. 2010;11. Kongsager R, Napier J, Mertz O. The carbon sequestration potential of tree crop plantations. Mitig Adapt Strateg Glob Change. 2013;18:1197–213. Kaul M, Mohren G, Dadhwal VK. Phytomass carbon pool of trees and forests in India. Clim Change. 2011;108:243–59. Rizvi R, Dhyani S, Yadav R, Singh R. Biomass production and carbon stock of poplar agroforestry systems in Yamunanagar and Saharanpur districts of northwestern India. Curr Sci. 2011;100(5):736–42. Kale MP, Ravan SA, Roy P, Singh S. Patterns of carbon sequestration in forests of Western Ghats and applicability of remote sensing in generating carbon credits through afforestation/reforestation. J Indian Soc Remote Sens. 2009;37:457–71. Devagiri G, Money S, Singh S, Dadhwal VK, Patil P, Khaple A, et al. Assessment of aboveground biomass and carbon pool in different vegetation types of south-western Karnataka, India using spectral modeling. Trop Ecol. 2013;54(2):149–65. Pragasan A. Tree carbon stock assessment from the tropical forests of Bodamalai Hills, India. J Earth Sci Clim Change. 2015;6(10):314. Tolunay D. Total carbon stocks and carbon accumulation in living tree biomass in forest ecosystems of Turkey. Turk J Agric For. 2011;35(3):265–79. UN-ECE/FAO. Global forest resources assessment 2005: global assessment of growing stock, biomass and carbon stock. Forestry Working Paper 106/E. Rome: FAO. 2006. p. 54. Fang J, Brown S, Tang Y, Nabuurs GJ, Wang X, Shen H. Overestimated biomass carbon pools of the northern mid- and high-latitude forests. Clim Change. 2006;74:355–68. Schelhaas MJ, Nabuurs GJ, Hočevar M. Spatial distribution of regional whole-tree carbon stocks and fluxes of forests in Europe. Wageningen: Alterra, Green World Research; 2001. Janssens IA, Freibauer A, Ciais P, Smith P, Nabuurs GJ, Folberth G, et al. Europe's terrestrial biosphere absorbs 7 to 12% of European anthropogenic CO₂ emissions. Science. 2003;300(5625):1538–42. Evrendilek F. An inventory-based carbon budget for forest and woodland ecosystems of Turkey. J Environ Monit. 2004;6(1):26–30. Garcia JA, Villen-Guzman M, Rodriguez-Maroto JM, Paz-Garcia JM. Technical analysis of CO₂ capture pathways and technologies. J Environ Chem Eng. 2022;10(5):108470. Godin J, Liu W, Ren S, Xu CC. Advances in recovery and utilization of carbon dioxide: a brief review. J Environ Chem Eng. 2021;9(4):105644. Khatoon S, Kim MH. Preliminary design and assessment of concentrated solar power plant using supercritical carbon dioxide Brayton cycles. Energy Convers Manag. 2022;252:115066. Zarbakhsh S, Shahsavar AR. Exogenous γ-aminobutyric acid improves photosynthetic efficiency, soluble sugars and mineral nutrients in pomegranate under drought and salinity stress. BMC Plant Biol. 2023;23(1):543. Goswami S, Verma K, Kaushal R. Biomass and carbon sequestration in different agroforestry systems of a Western Himalayan watershed. Biol Agric Hortic. 2014;30(2):88–96. Raqeeb A, Nizami SM, Saleem A, Hanif M. Characteristics and growing stock volume of forest stands in dry temperate forest of Chilas, Gilgit-Baltistan. Open J For. 2014. Nizami SM, Mirza SN, Livesley S, Arndt S, Fox JC, Khan IA, Mahmood T. Estimating carbon stocks in sub-tropical pine ( Pinus roxburghii ) forests of Pakistan. Pak J Agric Sci. 2009;46(4):266–70. Singh S, Patil P, Dadhwal VK, Banday J, Pant D. Assessment of aboveground phytomass in temperate forests of Kashmir Valley, J&K, India. Int J Ecol Environ Sci. 2012;38(2–3):47–58. Ahmad A, Mirza SN, Nizami S. Assessment of biomass and carbon stocks in coniferous forest of Dir Kohistan, KPK. Pak J Agric Sci. 2014;51(2). Mani S, Parthasarathy N. Above-ground biomass estimation in ten tropical dry evergreen forest sites of peninsular India. Biomass Bioenergy. 2007;31(5):284–90. Ahmad A, Amir M, Mannan A, Saeed S, Shah S, Ullah S, et al. Carbon sinks and mitigation potential of deodar ( Cedrus deodara ) forest ecosystem at different altitudes in Kumrat Valley, Pakistan. Open J For. 2018;8(4):553. Brown S, Pearson T, Slaymaker D, Ambagis S, Moore N, Novelo D, Sabido W. Application of multispectral three-dimensional aerial digital imagery for estimating carbon stocks in a tropical pine savanna. Report to the Nature Conservancy; 2004. pp. 12–22. Supriya Devi L, Yadava P. Aboveground biomass and net primary production of semi-evergreen tropical forest of Manipur, north-eastern India. J Res. 2009;20:151–5. Marziliano PA, Coletta V, Menguzzato G, Nicolaci A, Pellicone G, Veltri A. Effects of planting density on the distribution of biomass in a Douglas-fir plantation in southern Italy. Forest. 2015;8(3):368. Kindermann G, McCallum I, Fritz S, Obersteiner M. A global forest growing stock, biomass and carbon map based on FAO statistics. Silva Fenn. 2008;42(3):387–96. Additional Declarations No competing interests reported. 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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-8823691","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Case Report","associatedPublications":[],"authors":[{"id":627939840,"identity":"23a078b1-6f02-40ca-85f9-445c4bbd9504","order_by":0,"name":"Pervez Khan","email":"","orcid":"","institution":"Shaheed Benazir Bhutto University","correspondingAuthor":false,"prefix":"","firstName":"Pervez","middleName":"","lastName":"Khan","suffix":""},{"id":627939841,"identity":"58d7994f-27f3-4979-8ced-640499adb06d","order_by":1,"name":"Bui Manh Hung","email":"","orcid":"","institution":"Vietnam National University of Forestry","correspondingAuthor":false,"prefix":"","firstName":"Bui","middleName":"Manh","lastName":"Hung","suffix":""},{"id":627939842,"identity":"c043453f-1092-4856-985e-7663b3420b27","order_by":2,"name":"Jishnu Panamoly Ayyappan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYBAC9mYGNhQBORBx4AEeLYzoWozBWhLwaWlA05LYACLxamlnf/a4sO2OvMGN5GePC2rupM8PO/wQaIudnG4DLofxmBvPbHtmuOFGmrnxjGPPcjfeTjMAakk2NjuAUwubNG/bYcYNNxLMpHnYDudunJ0A0nIgcRtOLezPQFrsN9xI/ybN8+9wuuHs9A94tQg2M5iBtCRuuJEDZiTIS+fgt0WamQfonnPPkmeeeVNuPLPvsOEG6ZyCAwkGuP3Cx3/8mTRP2R3bvuPp2x4XfDssLz87ffOHDxV2cri0QMEBBoULCWzMIKYBWKUBXuUQLfL9ByBa5BsIqh4Fo2AUjIIRBgCKmWa0EJp+7AAAAABJRU5ErkJggg==","orcid":"","institution":"National Taiwan Ocean University","correspondingAuthor":true,"prefix":"","firstName":"Jishnu","middleName":"Panamoly","lastName":"Ayyappan","suffix":""},{"id":627939843,"identity":"ae6f3acd-f532-4c3e-b58e-040f30868326","order_by":3,"name":"Amalu Shaju","email":"","orcid":"","institution":"Mahatma Gandhi University","correspondingAuthor":false,"prefix":"","firstName":"Amalu","middleName":"","lastName":"Shaju","suffix":""},{"id":627939844,"identity":"5ce18d60-8a74-4300-9b82-84e8e1c01740","order_by":4,"name":"Nguyen Tuan Nam","email":"","orcid":"","institution":"Green C and B Consultant","correspondingAuthor":false,"prefix":"","firstName":"Nguyen","middleName":"Tuan","lastName":"Nam","suffix":""},{"id":627939847,"identity":"a586728a-e7c1-4d53-bac0-d80d36e9941d","order_by":5,"name":"Rajpar Nawaz Muhammad","email":"","orcid":"","institution":"Shaheed Benazir Bhutto University","correspondingAuthor":false,"prefix":"","firstName":"Rajpar","middleName":"Nawaz","lastName":"Muhammad","suffix":""},{"id":627939850,"identity":"fe735d66-d88f-4179-a6cd-dd13c5a5f125","order_by":6,"name":"Do Phu Tien","email":"","orcid":"","institution":"University of natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Do","middleName":"Phu","lastName":"Tien","suffix":""},{"id":627939851,"identity":"ef0abe45-a00e-4224-9724-5ae1bdfbd29b","order_by":7,"name":"Shiou Yih Lee","email":"","orcid":"","institution":"INTI International University","correspondingAuthor":false,"prefix":"","firstName":"Shiou","middleName":"Yih","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2026-02-08 18:53:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8823691/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8823691/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107832720,"identity":"98142203-2387-4882-8b94-996e9dd27c42","added_by":"auto","created_at":"2026-04-26 15:35:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":140955,"visible":true,"origin":"","legend":"\u003cp\u003ePlots setup in Luot Mountain. Vietnam map (right), Luot mountain map (left)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8823691/v1/0a0ef279b438316e1b1a2085.png"},{"id":107832721,"identity":"3f8ce7c2-6562-4690-9295-54bc4cb2194f","added_by":"auto","created_at":"2026-04-26 15:35:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28728,"visible":true,"origin":"","legend":"\u003cp\u003eRegression analysis graphs (a), BA vs Volume (b), BA vs Total Biomass (c), BA vs Carbon Stock (d), Dia vs Volume (e), Dia vs Stem Density (f), Dia vs Height\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8823691/v1/a1afd746cc497340c90036a3.png"},{"id":107870778,"identity":"09e0d369-cf06-4b9d-85ec-2b6174e00df1","added_by":"auto","created_at":"2026-04-27 07:40:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":791845,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8823691/v1/74c35ba6-8d86-4546-a127-7f5608d01b94.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Aboveground Tree Carbon Stock and Biomass Potential of Mixed Plantation Forests in Luot Mountain, Vietnam","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNowadays, the increase in the concentration of Carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) is the most important issue in the world, because CO\u003csub\u003e2\u003c/sub\u003e gas is the most important element of greenhouse gases which are caused by human activities and accelerate global warming and climate change. In the Globe climate change and global warming are the most pressing concerns, leading to environmental problems, such as thrilling weather actions, sea level rise, human health issues, wildlife starvation, plants growths, and agriculture production [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese climate events occur because of greenhouse gases, which are produced from human activities, such as fossil fuel burning, deforestation, burning of organic waste, and agricultural/ livestock activities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As global wood and fiber demands rise, planted forests are essential, i.e., they provide almost 50.0% of industrial raw materials encompassing of timber, pulp, and fiber while occupying 7.0% of global forest land and reduce pressure on natural forests. These forest aids in restoring degraded lands, preventing soil erosion, maintaining soil fertility, and regulating water cycles. In addition to providing habitat for a variety of species, they also act as buffers for native species. By providing renewable resources, sequestering carbon to combat climate change, restoring degraded land, and protecting watersheds, they contribute to sustainable development. A forest has three main functions, including storing carbon in its constituent flora, also known as a \"carbon store\" or a \"reservoir.\" Forests that absorb or reduce carbon dioxide from the atmosphere are called \"vital carbon sinks.\" A forest that has been cleared, degraded, infested with diseases, pests, or burned is referred to as a \"carbon source\" that emits greenhouse gases. A significant amount of carbon is contained in forest biomass, with nearly 50% composed of carbon [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. A tree's high carbon absorption capacity is influenced by its carbon stock, which in turn is influenced by the trunk diameter and density [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA forest ecosystem's aboveground biomass is a key parameter for describing its health. The aboveground biomass of a forest ecosystem is a key parameter that helps describe its functioning. It is crucial to investigate biomass carbonation in order to determine the storage of carbon and calculate the carbon cycle on a regional and global scale. Above\u0026ndash;Ground Biomass (AGB) of dominant tree species in forest ecosystems and plant functional groups is crucial for understanding energy flow magnitudes and patterns. This organic matter is stored in tree trunks, branches, leaves, roots, and continuously circulates between the living and non-living components of the ecosystem. In order to understand the net value of AGB in forest, it is crucial to analyze how photosynthesis balances respiration, mortality, harvest, and herbivory [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, the estimation of the AGB is an essential aspect of studies of carbon stocks and global carbon balance [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Estimating AGB is a useful measure for comparing structural and functional attributes of forest ecosystems across a wide range of environmental conditions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. So far different studies have been conducted to estimate AGB and they have mostly used diameter and height [\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. AGB is thus of direct applied importance for estimating ecosystem carbon storage and fluxes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePlanted forests are defined as \u0026ldquo;forest predominantly composed of trees established through planting and deliberate seeding [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Globally, natural forests are disappearing at an alarming rate because of human intervention, which increases carbon dioxide emission in the atmosphere, causing global warming and climate change. In response to combat the climate change, an area 12.3\u0026nbsp;million hectares (ha) between 2010 and 2015 has been planted to enhance the total forest cover [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. According to [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] of the global forest area, 7.0% forest area is composed of plantation forests, which is 291\u0026nbsp;million hectares. To counter climate change planted forest are effective tools due to carbon (C) absorption ability and an increasingly important role play in regulating climate in the future [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Vietnam planted forests rapidly increased since 2000 from two million ha to about 4.2\u0026nbsp;million ha in 2018 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] or more than 26.0% of the total forest area, with approximately two\u0026ndash;thirds of the plantations area managed by smallholders [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This rapid expansion of plantations in recent years is due to the Government of Vietnam (GOV) implementing afforestation and reforestation programs that have been initiated from the 1980s in response to extensive deforestation and forest degradation during and after the American war [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Vietnam's approach to carbon sequestration integrates sustainable forest management practices and community\u0026ndash;based conservation initiatives. While enhancing carbon storage capacities, forest governance and biodiversity conservation have improved through Forest Sector Support Partnership Programs [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These programs also aimed to increase rural populations' income, and fulfill industries' demands for timber [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Because of these programs, from 1990 to 2010, annually about 2.37% forest cover increased [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and in Asia, Vietnam is one of few countries to achieve a forest transition [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These immature plantations show significant C sequestration potential [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In order to minimize atmospheric CO2 concentration accumulation, predict, and maintain long\u0026ndash;term productivity of the system, relevant studies about carbon stocks in plantations will be especially helpful [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere is inadequate information about the tree carbon stock and its potential for sequestration in mixed plantation forests in Luot Mountain, Vietnam. The carbon stock and sequestration rate of planted forests, as well as their stability, have not been adequately quantified. A study has been conducted on aboveground biomass and carbon stock in six socio-economic regions of Vietnam [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Another study was also conducted on sustainably developing carbon stocks and Melaleuca forest growth in U Minh Thuong National Park in Vietnam after big fires [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Further, there were also studies on the effects of forest land use change on carbon stocks in Vietnam's northern mountainous regions [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] and Ba Vi's canopy structure and carbon stocks [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are still gaps about the aboveground tree carbon stock as well as its potential for sequestering CO₂ in mixed plantation forests in Luot Mountain, Vietnam. Luot Mountain, Vietnam, there is still crucial needs to ascertain the comprehensive study to determine the tree carbon stock and its potential for sequestration in mixed plantation in order to prepare an effective and comprehensive management plan for future marketing. Hence, to identify the carbon sequestration rate of various ecosystems and their stability, uncertainty, and sustainability, it is inevitable to achieve carbon neutrality and carbon peaking [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. As a consequence, this study was conducted with an eye towards the potential biomass, carbon, and environmental services of Luot Mountain for absorbing CO2, producing O2, and generating carbon credits. This study quantified the aboveground tree carbon stock and biomass of the Luot mountain forest for the purpose of valuing the carbon absorption capacity (carbon credits) of the mixed forest plantation. This study has specific objectives, including (1) determining the biomass and carbon stocks and biomass potential of mixed plantation forests Luot Mountain, (2) quantifying the value of mixed forest carbon credits, and (3) evaluating the environmental services provided by mixed forest plantations, such as the ability to absorb CO\u003csub\u003e2\u003c/sub\u003e, produce oxygen, and generate carbon credits. By determining the storage and cycling of carbon in tree components at the regional level, the findings of this study will contribute to the effective management and use of planted forests in the future.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Area\u003c/h2\u003e \u003cp\u003eThis study was carried out within an experimental forest complex encompassing of mixed plantations at Luot Mountains is located in Xuan Mai town, Chuong My district of Ha Noi, at a latitude and longitude of 20\u0026deg;54'43\" N 105\u0026deg;34'11\" E (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It covers more than 150 ha and is characterized by a tropical monsoon climate. Originally native to the Poccafiarite parent rock, the soil is a brownish-yellowish feralit. Humus content in soil ranges from 2\u0026ndash;3%, resulting in a pH of 7 due to the presence of humus. The soil accumulates a high level of aluminum and iron, is stable, and has a low phosphorus concentration. There is an average slope of 15 degrees, and the average temperature ranges from 20 to 25\u003csup\u003e0\u003c/sup\u003eC. The hottest month of the year is July. The average annual rainfall is 1753 millimeters. There are seven main forest types based on three main mature species: \u003cem\u003eEucalyptus urophylla, Acacia auriculiformis\u003c/em\u003e, and \u003cem\u003ePinus massoniana\u003c/em\u003e. Approximately 300 plant species are indigenous to the area [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data collection\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Method of setting sample plots\u003c/h2\u003e \u003cp\u003eA total of 20 rectangular shaped sample plots in different land use types, with a plot dimension of (25\u0026times;20m) 500 m\u003csup\u003e2\u003c/sup\u003e by following stratified random sampling method were taken. In each plot, the diameter tape and caliper were used to measure the tree diameter (cm) at breast height (DBH) greater than 6 cm. Blume\u0026ndash;Leiss was used to measure height [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Biomass Carbon calculation\u003c/h2\u003e \u003cp\u003eStem volume (m\u003csup\u003e3\u003c/sup\u003e/ha) was calculated from DBH and tree height by using previous literature e.g [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Stem volume was calculated by using the following formula.\u003c/p\u003e \u003cp\u003eV (m\u003csup\u003e3\u003c/sup\u003e/ha)\u0026thinsp;=\u0026thinsp;AH\u0026times;FF---------------------------------- (1)\u003c/p\u003e \u003cp\u003e \u003cem\u003eWhere\u003c/em\u003e, V\u0026thinsp;=\u0026thinsp;volume of stem (m\u003csup\u003e3\u003c/sup\u003e), A\u0026thinsp;=\u0026thinsp;cross sectional area at BH point (m\u003csup\u003e2\u003c/sup\u003e), H\u0026thinsp;=\u0026thinsp;tree height (m), FF\u0026thinsp;=\u0026thinsp;form factor\u003c/p\u003e \u003cp\u003eFrom stem volume (m\u003csup\u003e3\u003c/sup\u003e/ha) and wood density (kg/m\u003csup\u003e3\u003c/sup\u003e) Stem biomass (tones/ha) was calculated. From available literature, wood densities for all tree species were obtained. The following formula was used to determine the biomass of the stem.\u003c/p\u003e \u003cp\u003eStem biomass (tones/ha) = Stem volume (m\u003csup\u003e3\u003c/sup\u003e) \u0026times; Basic wood density (kg/m\u003csup\u003e3\u003c/sup\u003e) ------------------- (2)\u003c/p\u003e \u003cp\u003eThe total tree biomass in (tones/ha) was determined using biomass expansion factors (BEF). Biomass expansion factors (BEF) was used to calculate total tree biomass (tones/ha), [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. BEF of respective species was obtained and multiplied with stem biomass by using the following formula.\u003c/p\u003e \u003cp\u003eTotal biomass (tones/ha)\u0026thinsp;=\u0026thinsp;BEF\u0026times;Stem biomass (tones/ha) ---------------------------------- (3)\u003c/p\u003e \u003cp\u003eTo get total carbon stock (tones/ha), total tree biomass (tones/ha) was multiplied with conversion factor of (0.5), which was sourced from Eq.\u0026nbsp;(4) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCarbon (tones/ha) = Biomass (tones/ha) \u0026times; Carbon % (0.5) ---------------------------------- (4)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Environmental service potential\u003c/h2\u003e \u003cp\u003eThe potential for environmental services is calculated using carbon credits, O\u003csub\u003e2\u003c/sub\u003e generation, and absorbed CO\u003csub\u003e2\u003c/sub\u003e. Eq.\u0026nbsp;5 can be used to examine the computation of the CO\u003csub\u003e2\u003c/sub\u003e absorption environmental service value [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e absorbed\u0026thinsp;=\u0026thinsp;Ct\u0026times;3.67 ---------------------------------- (5)\u003c/p\u003e \u003cp\u003e \u003cem\u003eWhere\u003c/em\u003e, Ct is the total amount of carbon stored (in tons/ha), CO2 absorbed is the amount of carbon dioxide absorbed (in tons/ha), and 3.67 is the equivalent number or conversion factor from carbon to carbon.\u003c/p\u003e \u003cp\u003eTo obtain carbon credits, the absorbed CO\u003csub\u003e2\u003c/sub\u003e was multiplied by the current carbon credit price, minus the transaction fees. In 2019, the World Bank set the price of carbon credits as USD 40/tones. Transaction costs include monitoring, administrative process fees, and verification of emission reduction services utilizing absorbed CO\u003csub\u003e2\u003c/sub\u003e. In the forestry sector, the transaction cost for reducing absorbed CO\u003csub\u003e2\u003c/sub\u003e emissions is \u003cspan\u003e$\u003c/span\u003e1.23 USD [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] ;. Thus, using Eq.\u0026nbsp;6, the environmental service value of carbon credits was calculated [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCarbon credits\u0026thinsp;=\u0026thinsp;HJ CO\u003csub\u003e2\u003c/sub\u003e\u0026times; CO\u003csub\u003e2\u003c/sub\u003e absorbed ---------------------------------- (6)\u003c/p\u003e \u003cp\u003e \u003cem\u003eWhere\u003c/em\u003e, Carbon credit \u0026ndash; carbon dioxide compensation (tones/ha), HJCO\u003csub\u003e2\u003c/sub\u003e \u0026ndash; Selling price of carbon credit (USD 40/tones), CO\u003csub\u003e2\u003c/sub\u003e absorbed \u0026ndash; Carbon dioxide absorbed (tones/ha).\u003c/p\u003e \u003cp\u003eThe environmental service value of the O\u003csub\u003e2\u003c/sub\u003e production can be calculated using the CO\u003csub\u003e2\u003c/sub\u003e absorption development through Eq.\u0026nbsp;7 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e production\u0026thinsp;=\u0026thinsp;CO\u003csub\u003e2\u003c/sub\u003e\u0026times; 0.73 ---------------------------------- (7)\u003c/p\u003e \u003cp\u003e \u003cem\u003eWhere\u003c/em\u003e, O\u003csub\u003e2\u003c/sub\u003e production \u0026ndash; oxygen production (tones/ha), CO\u003csub\u003e2\u003c/sub\u003e absorbed \u0026ndash; absorbed carbon dioxide (tones/ha), 0.73 \u0026ndash; equivalent number or conversion factor from CO\u003csub\u003e2\u003c/sub\u003e to O\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical analysis\u003c/h2\u003e \u003cp\u003eMS Excel 2016 and Sigma Plot version 12.5 (Systat Software Inc) were used for data analysis. For above\u0026ndash;ground trees, descriptive statistics (min, max, and mean) were calculated for various parameters like tree height (m), diameter (cm), basal area (m\u003csup\u003e2\u003c/sup\u003e/ha), volume (m\u003csup\u003e3\u003c/sup\u003e), biomass (tones/ha), and carbon stock (tones/ha). we developed linear regression models to investigate the relationship between tree diameters (cm) and height (m), diameter (cm) and volume (m\u003csup\u003e3\u003c/sup\u003e/ha), diameter (cm) and stem density (trees/ha), stem volume (m\u003csup\u003e3\u003c/sup\u003e/ha) and basal area (m\u003csup\u003e2\u003c/sup\u003e/ha), stem biomass (tones/ha) and basal area (m\u003csup\u003e2\u003c/sup\u003e/ha), total biomass (tones/ha) versus basal area (m\u003csup\u003e2\u003c/sup\u003e/ha) and total carbon stock (tones/ha) using Python version 3.12 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.python.org\u003c/span\u003e\u003cspan address=\"http://www.python.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.1. Vegetation type status\u003c/b\u003e of \u003cb\u003emixed plantation forests of Luot Mountain\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe total area of Luot Mountain was more than 150 ha. These include pure pine plantation, pure white eucalyptus plantation, Acacia hybrid forest, \u003cem\u003eAcacia auriculiformis\u003c/em\u003e and mixed forest species (about 30 years old). Among them, Acacia hybrid forest covered 32.02 ha (21.13%) of area, followed by Pine Forest 13.36 ha (8.81%), and mix forest 12.67 ha (8.42%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The least area was that of Pine\u0026ndash;Acacia 0.96 ha (0.63%) and Eucalyptus 1.67 ha (1.10%). Other uses included a large military zone (25.25 ha); infrastructure (14.5ha), residential (17.71 ha) and electric pole line.\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\u003eVegetation type status of mixed plantation forests of Luot mountain\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of forest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePine forest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEucalyptus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAcacia\u0026ndash;hybrid forest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEucalyptus-Acacia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePine\u0026ndash; Eucalyptus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePine\u0026ndash; Acacia\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMix forest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal area (ha)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e12.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e86.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e57.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe growth and development of the shrub layer, as a fresh carpet was very dense. \u003cem\u003ePinus massoniana\u003c/em\u003e and \u003cem\u003eAcacia auriculiformis\u003c/em\u003e were the dominant trees specie.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Descriptive statistics on different parameters\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Diameter, height, volume and basal area\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below showed the key characteristics of the plots in the study area. The data showed that maximum diameter 51cm was investigated at plot 16, having plot elevation of 115m (15\u003csup\u003e0\u003c/sup\u003e), while minimum diameter of 28cm at 17 plot with average of 38.06 (cm) of the whole plots. Maximum 29.8m tree height was found at plot 16 at 15\u003csup\u003e0\u003c/sup\u003e slope and 115m plot elevation, on the same way minimum height of 17.73m was investigated from plot 17 at plot elevation of 102m. The average height for the entire plots was 22.51m. The average basal area volume of the study area was 230.81m\u003csup\u003e3\u003c/sup\u003e/ha, which range from 117.8m\u003csup\u003e3\u003c/sup\u003e/ha to 410.9 m\u003csup\u003e3\u003c/sup\u003e/ha at plot 16; with plot height of 115m. In the present study average basal area was 25.6m\u003csup\u003e2\u003c/sup\u003e/ha. Highest basal area 36m\u003csup\u003e2\u003c/sup\u003e/ha was detected at plot 2 while the lowest basal area 14m\u003csup\u003e2\u003c/sup\u003e/ha was recorded from plot 1. There is a strong correlation between stem diameter (cm) and basal area (m\u0026sup2;/ha), meaning the higher the stem diameter (cm), the higher the basal area (m\u0026sup2;/ha).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Stem density, stem biomass, total biomass and total carbon stock\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe stem density refers the number of trees per hectare. In the present study maximum and minimum stem density of 860 and 420 trees/ha was investigated from plot 12 and 6 respectively. These plots had an average of 628 trees per hectare and an average stem biomass of 132.7 tons per hectare. Plot 16 had the highest biomass, 236.3 tons/ha, and Plot 1 had the lowest biomass of 67.72 tons/ha. It was determined that Lout Mountain had a mean biomass of 62.4 tons/ha. Total tree biomass was highest at plot 16 with 111.05 tons/ha and lowest at plot 1 with 31.89 tons/ha. Approximately 31.2 tons of carbon were accumulated on Luot Mountain in mixed forest. Plot 16 and 1 had minimum and maximum carbon stocks of 15.92 tons/ha and 55.52 tons/ha, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics on different growing stocks features\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlot No\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElevation (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSlope Degree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHeight (m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDBH (cm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBasal Area m\u003csup\u003e2\u003c/sup\u003e/ha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003cp\u003em\u003csup\u003e3\u003c/sup\u003e/ha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStem Density trees/ha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSTBM\u003c/p\u003e \u003cp\u003etons/ha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTTBM\u003c/p\u003e \u003cp\u003etons/ha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eCarbon\u003c/p\u003e \u003cp\u003etons/ha\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e117.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e67.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e298.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e171.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e161.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e92.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e43.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e217.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e125.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e58.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e316.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e182.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e85.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e268.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e154.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e72.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e301.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e173.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e81.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e216.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e124.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e58.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e163.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e94.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e44.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e265.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e152.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e71.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e35.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e230.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e132.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e62.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e 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align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e201.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e116.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e54.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e 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align=\"left\" colname=\"c10\"\u003e \u003cp\u003e111.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e55.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e120.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e69.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e246.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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align=\"left\" colname=\"c7\"\u003e \u003cp\u003e297.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e171.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e230.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e621.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e132.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e62.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e117.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e67.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e410.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e236.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e111.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e55.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSTDV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e115.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e42.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSt error\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eVariance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5487.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13280.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1814.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e400.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCV%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e32.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3. Regression analysis of the variables\u003c/h2\u003e \u003cp\u003eA regression analysis revealed a strong positive linear correlation between (DBH) Diameter at Breast Height (cm) and height (m) with R\u003csup\u003e2\u003c/sup\u003e value 0.88. This indicates that tree diameter has a good correlation with tree height. A low p\u0026ndash;value (p\u0026thinsp;=\u0026thinsp;0.0000) explains the association between diameter and height of trees. The carbon stock of mixed forest is influenced by trees volume; understanding this relationship can help us determine its carbon sequestration potential. Based on an R\u003csup\u003e2\u003c/sup\u003e value of 0.35, the relationship between diameter and volume exhibited a moderate correlation, indicating that volume increases with increasing diameter. When the coefficient of determination is low, the diameter of trees is not an effective predictor of volume; other factors must also be taken into account. Furthermore, the relationship between diameter and stem density was not linear (weak negative relationship) with an R\u003csup\u003e2\u003c/sup\u003e value of 0.01, showing that the red line explains 1 percent of the variance (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Diameter doesn't predict stem density in this study because of its low coefficient of determination.\u003c/p\u003e \u003cp\u003eThere was a strong linear relation between basal area and volume, with R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.67, indicating that basal area is a good predictor of volume. With R\u003csup\u003e2\u003c/sup\u003e value of 0.67, the relationship between basal area and total biomass was strong linear, showing that 67.0% of variance in total biomass can be attributed to basal area. In addition, basal area and carbon stock have a positive linear relationship with R\u003csup\u003e2\u003c/sup\u003e value of 0.67, which indicates that carbon stock increases by 1.19 tons per hectare for every square meter increase in basal area. As a result, more the basal area more will be the carbon stock.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.4. Environmental service production\u003c/h2\u003e \u003cp\u003eBased on natural ecosystem processes, environmental services are the benefits obtained by humans and the environment from the concept of natural systems [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Luot Mountain mixed plantation forests were assessed for their environmental service production, such as capacity to absorption potential of CO\u003csub\u003e2\u003c/sub\u003e, O\u003csub\u003e2\u003c/sub\u003e production and carbon credits generation. The results demonstrated that mixed plantation forests Luot Mountain absorbed carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) 2288.94 tons per hectare, produced oxygen (O\u003csub\u003e2\u003c/sub\u003e) 1670.92 tons per hectare, and generated carbon credit having value 91.55 US dollars per hectare (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Given the current enormous emissions issues, this trade has a lot of promise in the current global competitive environment [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEnvironmental service output of the study area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eEnvironmental service potential of the Lout moutain\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eabsorbed (tons/ha)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e \u003cb\u003eproduction (tons/ha)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCarbon credit (US$/ha)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e623.69\u0026times;3.67\u0026thinsp;=\u0026thinsp;2288.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2288.94\u0026times;0.73\u0026thinsp;=\u0026thinsp;1670.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u0026times;2288.94\u0026thinsp;=\u0026thinsp;91557.6/1000\u0026thinsp;=\u0026thinsp;91.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4.0. Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Tree Diameter, height, volume and basal area\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eA forest is not just a green lung for our planet, but it is also a vital reservoir of carbon, so it is crucial to maintain it in the fight against climate change. It is, however, essential to have accurate information before we can transform that potential into measurable impact. Forest ecosystems not only play an important role in CO\u003csub\u003e2\u003c/sub\u003e sequestration, climate change mitigation and production bioenergy but also provide a livelihood to humans [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The global estimates reports confirmed that 12.0% of anthropogenic carbon emissions are sequestered by forests [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, due to agriculture expansion, increase in deforestation rate land has alarmingly degraded into forest area and its carbon pool [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The forest ecosystem carbon storage capacity has been negatively affected because of an increase in global atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentration and deforestation at alarm rate [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Through the Kyoto Protocol [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], these forest dynamics in the transformation of carbon dioxide from the atmosphere led to the management of carbon sequestration in natural forests, in which forest ecosystems generate sustainable production of various goods and services through carbon credits [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The outcome of diameter measurement indicated that the tree diameters ranged from a minimum 28 cm to 51 cm maximum, with average of 38.06 cm of the whole plots. [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] reported that diameter for northwest evergreen broadleaf forest ranged 54\u0026ndash;83 cm in Vietnam. Likewise, [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] recorded tree diameter ranged from 20.76\u0026ndash;22.87 cm with average of 21.78 cm in 11 years age \u003cem\u003eAcacia mangium\u003c/em\u003e plantation in Chang Riec historical culture forest southeastern region, Vietnam. In other instance, trees diameter ranged from 13.8 \u0026minus;\u0026thinsp;17.8 cm was recorded for vegetation I and II for natural vegetation in Me Linh Biodiversity Station, Vinh Phuc province, Vietnam [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. In Biological Station of La Selva, Costa Rica highest DBH of 25.5 cm was documented for pure \u003cem\u003eV. guatemalensis\u003c/em\u003e planation, 30.5 cm for mix \u003cem\u003eV. guatemalensis\u003c/em\u003e planation and 31.3 cm for mix \u003cem\u003eT. Amazonia\u003c/em\u003e plantation respectively [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. In addition, [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] stated that tree diameter range from 17\u0026ndash;66 cm for \u003cem\u003ePinus sylvestris\u003c/em\u003e, 7.1\u0026ndash;63.2 cm for \u003cem\u003ePinus sylvestris\u003c/em\u003e [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] and 20\u0026ndash;52 cm for \u003cem\u003ePicea orientalis\u003c/em\u003e [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Moreover, [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] recorded tree diamter 25.1 cm for \u003cem\u003eV. guatemalensis\u003c/em\u003e and 26.80 cm for the mix forest with thinning, and 23.50 cm for \u003cem\u003eV. koschnyi\u003c/em\u003e with thinning at Biological Station Costa Rica of La Selva.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eTree heights results for mixed forests demonstrated that height ranged from 17.73 meters to 29.8 meters, with a mean height of 22.51 meters. Our measurements of height are coincident with [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], i.e., 18.9 m in a 12\u0026ndash;year-old \u003cem\u003eAcacia mangium\u003c/em\u003e forest in the change Riec historical culture forest in the southeastern region of Vietnam. In parallel, our tree heights are also closely related to the findings of [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. For instance, we found 27.5 m height for polycultures of \u003cem\u003eV. guatemalensis\u003c/em\u003e, 27.12 for mixed polycultures of \u003cem\u003eJ. copaia\u003c/em\u003e, and 22.03 for pure polycultures of \u003cem\u003eJ. copaia\u003c/em\u003e for La Selva Costa Rica Biological Station. Furthermore, the findings of our research are also consistent with [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], which documented that \u003cem\u003eV. guatemalensis\u003c/em\u003e reaches a height of 24.4 m while \u003cem\u003eV. ferruginea\u003c/em\u003e reaches 22.1 m, \u003cem\u003eV. koschnyi\u003c/em\u003e reaches 21.7 m, and \u003cem\u003eJ. copaia\u003c/em\u003e species and 25.6 m for mixed plantation, respectively, for La Selva Biological Station Costa Rica.\u003c/p\u003e \u003cp\u003eThe average tree volume across the study was 230.81 m3/ha, ranging from 117.8 m3/ha (minimum) to 410.9 m3/ha (maximum). These findings are consistent with [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] r which estimated 115.2 (m\u003csup\u003e3\u003c/sup\u003e/ha) volume for \u003cem\u003eC. brasiliense\u003c/em\u003e and 301.4 for \u003cem\u003eV. guatemalensis\u003c/em\u003e, 331.6 for \u003cem\u003eJ. copaia\u003c/em\u003e at age of 10.3 years, 213 (m\u003csup\u003e3\u003c/sup\u003e/ha) for \u003cem\u003eT. amazonia\u003c/em\u003e, 254.6 for mixture, and 280 (m\u003csup\u003e3\u003c/sup\u003e/ha) for \u003cem\u003eV. koschnyi\u003c/em\u003e at the age of 10 years, 105.9 (m\u003csup\u003e3\u003c/sup\u003e/ha) for \u003cem\u003eH. alchomeoides\u003c/em\u003e, 144 (m\u003csup\u003e3\u003c/sup\u003e/ha) for \u003cem\u003eB. elegans\u003c/em\u003e, 194.7 (m\u003csup\u003e3\u003c/sup\u003e/ha) for mixture and 207.6 (m\u003csup\u003e3\u003c/sup\u003e/ha) \u003cem\u003eV. ferruginea\u003c/em\u003e at the age of 9 years respectively in pure and mixed plantation at Costa Rica La Selva Biological Station. In other instance, [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] a tree volumes 176.6, 318.5 and 410.3 (m\u003csup\u003e3\u003c/sup\u003e/ha) were determined for \u003cem\u003eC. brasiliense\u003c/em\u003e, \u003cem\u003eJ. copaia\u003c/em\u003e and \u003cem\u003eV. guatemalensis\u003c/em\u003e species respectively at plantation I and 128.5, 232.7, 292.8 and 402.1 (m\u003csup\u003e3\u003c/sup\u003e/ha) tree volume for \u003cem\u003eD. panamensis\u003c/em\u003e, \u003cem\u003eT. amazonia\u003c/em\u003e, and \u003cem\u003eV. koschnyi\u003c/em\u003e respectively mixed plantation II and tree volume 179.5, 207.9, 248.4 and 300.4 (m\u003csup\u003e3\u003c/sup\u003e/ha) for \u003cem\u003eH. alchornoeides\u003c/em\u003e, \u003cem\u003eB. elegans\u003c/em\u003e, and \u003cem\u003eV. ferruginea\u003c/em\u003e respectively for plantation III at La Selva Biological Station Costa Rica.\u003c/p\u003e \u003cp\u003eThe mean basal area in mixed plantation forests was 25.6 m\u003csup\u003e2\u003c/sup\u003e/ha, and it ranged from 36 m\u003csup\u003e2\u003c/sup\u003e/ha highest to lowest 14 m\u003csup\u003e2\u003c/sup\u003e/ha to 25.6 m\u003csup\u003e2\u003c/sup\u003e/ha. The results of this study are closely related to the findings of [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], for example, 16.69 m\u003csup\u003e2\u003c/sup\u003e/ha, 28.85 m\u003csup\u003e2\u003c/sup\u003e/ha, 29.45 m\u003csup\u003e2\u003c/sup\u003e/ha, and 45.47 m\u003csup\u003e2\u003c/sup\u003e/ha basal areas for \u003cem\u003eC. brasiliense, J. copaia\u003c/em\u003e, and \u003cem\u003eV. guatemalensis\u003c/em\u003e for 10.3\u0026ndash;years of plantation. Approximately 20.97 m\u003csup\u003e2\u003c/sup\u003e/ha, 26.39 m\u003csup\u003e2\u003c/sup\u003e/ha, and 28.55 m\u003csup\u003e2\u003c/sup\u003e/ha for \u003cem\u003eT. amazonia\u003c/em\u003e, mixture, and \u003cem\u003eV. koschnyi\u003c/em\u003e respectively, for a 10\u0026ndash;year old plantation. At La Selva Biological Station Costa Rica, the area of pure and mixed plantations of \u003cem\u003eH. alchomeoides, B. elegans\u003c/em\u003e, mixture, and \u003cem\u003eV. ferruginea\u003c/em\u003e is 13.33 m\u003csup\u003e2\u003c/sup\u003e/ha, 18.54 m\u003csup\u003e2\u003c/sup\u003e/ha, 22.38 m\u003csup\u003e2\u003c/sup\u003e/ha, and 24.69 m\u003csup\u003e2\u003c/sup\u003e/ha, respectively. As for plantation I, basal areas of 20.0 m\u003csup\u003e2\u003c/sup\u003e/ha, 28.4 m\u003csup\u003e2\u003c/sup\u003e/ha, 35.1 m\u003csup\u003e2\u003c/sup\u003e/ha, and 38.1 m\u003csup\u003e2\u003c/sup\u003e/ha are allocated for \u003cem\u003eC. brasiliense, J. copaia\u003c/em\u003e, and \u003cem\u003eV. guatemalensis\u003c/em\u003e for 13 years of age. Further, 13\u0026ndash;year-old plantation II contained 14.9 m\u003csup\u003e2\u003c/sup\u003e/ha, 22.7 m\u003csup\u003e2\u003c/sup\u003e/ha, 38.9 m\u003csup\u003e2\u003c/sup\u003e/ha, and 26.9% m\u003csup\u003e2\u003c/sup\u003e/ha of \u003cem\u003eD. panamensis, T. amazonia, V. koschny\u003c/em\u003ei, and a mix of the three species. Plantation III at La Selva Biological Station Costa Rica accounted for 17.5 m\u003csup\u003e2\u003c/sup\u003e/ha, 23.8 m\u003csup\u003e2\u003c/sup\u003e/ha, 29.4 m\u003csup\u003e2\u003c/sup\u003e/ha, and 23.6 m\u003csup\u003e2\u003c/sup\u003e/ha basal area for \u003cem\u003eH. alchornoeides, B. elegans\u003c/em\u003e, and \u003cem\u003eV. ferruginea\u003c/em\u003e [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Forest stand\u0026rsquo;s variables characteristics\u003c/h2\u003e \u003cp\u003eAs a result of the present study, the maximum and minimum stem density was 860 trees/ha and 420 trees/ha, respectively, with a whole average of 628 trees/ha. There is a similar tree density detected in a undertaking at Me Linh Biodiversity Station in Vinh Phuc province, Vietnam, i.e., 577 trees/ha for vegetation II and natural vegetation. Furthermore, [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] reported 860 trees/ha, 800 trees/ha, and 680 trees/ha in rich forest areas which are consistent with our findings. Additionally, the findings of in Nam Mau communes, 800 trees/ha and 820 trees/ha were detected in damaged and rehabilitated forests, and 860 trees/ha in medium forests are closely associated with our findings. Similar densities, e.g., 820 trees/ha and 860 trees/ha were determined for medium forests in Quang Khe communes, 820 trees/ha and 840 trees/ha were determined for poor and rehabilitated forests in Nam Cuong communes, and 740 trees/ha, 780 trees/ha, and 840 trees/ha respectively for medium forests in Hoang Tri commune. The mid-Central Coast has a tree density of 708\u0026ndash;749 trees/ha, and the Central Highland has a tree density of 573\u0026ndash;918 trees/ha. Our findings of tree density are similar to those in [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], which documented 610 trees/ha, 728 trees/ha, and 888 trees/ha from 4\u0026ndash;year\u0026ndash;old, 7\u0026ndash;year\u0026ndash;old, and 11\u0026ndash;year\u0026ndash;old \u003cem\u003eAcacia mangium\u003c/em\u003e plantations in the Riec historical culture forest in the southern region of Vietnam. In another study, 699.5 trees/ha, 721.7 trees/ha, and 803.7 trees/ha were reported for \u003cem\u003eV. guatemalensis, C. brasiliense\u003c/em\u003e, and \u003cem\u003eJ. copaia\u003c/em\u003e after 10.3 years of plantation [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Our results are in alignment with those reported in [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], in which 543 trees are found per ha, 737 trees are found per ha, 766 trees/ha, and 781 trees/ha for \u003cem\u003eT. amazonia\u003c/em\u003e, mixture, \u003cem\u003eD. panamensis\u003c/em\u003e, and \u003cem\u003eV. koschnyi\u003c/em\u003e, respectively, in pure and mixed plantations from 9 years old at La Selva Biological Station Costa Rica, 622 trees/ha, 721 trees/ha, 736 trees/ha, and 870 trees/ha for \u003cem\u003eG. Americana, V. ferruginea, H. alchomeoides\u003c/em\u003e, and \u003cem\u003eB. elegans\u003c/em\u003e. At plantation I of La Selva Biological Station Costa Rica, 612 trees/ha, 664 trees/ha, 684 trees per hectare, and 772 trees/ha were investigated for \u003cem\u003eC. brasiliense, V. guatemalensis\u003c/em\u003e, and \u003cem\u003eJ. copaia\u003c/em\u003e, respectively. Additionally, there were 547 trees/ha, 752 trees/ha, 840 trees/ha, and 606 trees/ha for \u003cem\u003eT. amazonia, D. panamensis\u003c/em\u003e, and \u003cem\u003eV. koschnyi\u003c/em\u003e, along with a mixture of the three species. Similarly, for plantation III there were 723 trees/ha, 771 trees/ha, 781 trees/ha, and 713 trees/ha for \u003cem\u003eV. ferruginea, H. alchornoeides\u003c/em\u003e, and \u003cem\u003eB. elegans\u003c/em\u003e [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBased on the test results, mixed forest plantations had a biomass of 62.4 tons per hectare and range from 31.8 to 111.05 tons/ha. The findings are in agreement with those of a study by [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] that found an average trunk biomass per hectare (2.72\u0026ndash;107.39 tons). In another study, tree layer biomass for vegetation types I and II for natural vegetation was 49.35 to 69.70 tones/ha at Me Linh Biodiversity Station, Vinh Phuc province, Vietnam. In a study conducted by [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], the amount of biomass varies from 55.72-130.18 tons/hectare, with an average of 84.54 tons/hectare in damaged and rehabilitated forest in Nam Mau communes. Moreover, they assessed that damaged and rehabilitated forests of Quang Khe communes produced biomass in the range of 54.96 tons per hectare to 137.5 tons per hectare, with an average of 84.9 tons per hectare. Furthermore, the biomass for damaged and rehabilitated forest in Nam Cuong communes ranged from 33.45 to 73.92 tons per hectare. Additionally, they detected biomass in Ba Be National Park Vietnam, which weighed 71.11 tons/ha in damaged and rehabilitated forests. As another example, [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] reported biomass of 55.08 to 109.18 Mg/ha (60.7 and 120.3 tones/ha converted) in Acacia mangium plantations of 4 and 7 years old located in the change Riec historical culture forest in the southeastern region of Vietnam. Similar results were observed in dry deciduous and mixed deciduous forests in Madhya Pradesh of India (44.5 and 54.9 tons/ha). An assessment of the forest carbon stock of Balganga Reserved Forest (BRF) was conducted in Uttarakhand, India. Site III, in the 1800\u0026ndash;2600 m elevation range, had the highest total biomass density (TBD) of 108.26 Mg/ha (119.3 tons/ha), followed by site II, in the 1600\u0026ndash;1800 m elevation range (83.92 Mg/ha; 92.5 tons/ha), and site I, at 1000\u0026ndash;1400 m elevation (57.22 Mg/ha; 63.07 tons/ha), with an average of 83.13 Mg/ha (91.6 tons/ha). As assessed by [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] for carbon sequestration potential, three forests of tropical dry deciduous in Haryana Gurgaon district accumulated 37.93 to 63.73 Mg/ha (41.8 to 70.2 tones/ha) AGB.\u003c/p\u003e \u003cp\u003eMoreover, allometric equations [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] were used to determine biomass in Northeast India, Tripura tropical forest. Approximately 41.72 to 94.3 tons of biomass was collected per hectare. In an Indian community-managed forest in the Garhwal Himalayas, the total biomass was 132.74 Mg/ha (146.3 tons/ha) [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. A study conducted by [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] used remote sensing satellites and GIS technology to calculate biomass and carbon in dry tropical forests in Chhattisgarh and established AGB 45.94\u0026ndash;78.31 Mg/ha (50.64 to 86.32 tons). The same method of area weights was used by [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] in Gujarat, India's moist deciduous forest where 5.534\u0026ndash;0.133 tons of biomass were recorded per hectare with a mean of 40.50 tons per hectare. As well as this, [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] determined the total biomass of 5\u0026ndash;year\u0026ndash;old \u003cem\u003eCeiba pentandra\u003c/em\u003e trees to be between 12.9 and 25 Mg/ha (14.21 and 27.6 tons/ha), \u003cem\u003eGmelina arborea\u003c/em\u003e to be between 9.9 and 21.4 Mg/ha, and \u003cem\u003ePopulus deltoides\u003c/em\u003e clones of Chhattisgarh, India, from 48.5 to 62.2 Mg/ha (53.4 to 68.56 tons/ha). Based on [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], the biomass productivity and carbon stocks of farm forestry and agroforestry systems in Andhra Pradesh were 62 Mg/ha (68.34 tons/ha) and 34 Mg/ha (37.47 tons/ha), respectively. Using biomass from five study sites in Tamil Nadu (four plantations and a natural forest), [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] analyzed the AGB of \u003cem\u003eCoccus nucifera, Casuarina equisetifolia, Mangifera indica\u003c/em\u003e, and \u003cem\u003eAnacardium occidentale\u003c/em\u003e, and found 143.2 tons, 38.0 tons, 121.1 tons, and 32.7 Mg/ha (157.85 tons per ha, 42.0 tons/ha, 133.4 tons/ha, and 36 tons per ha converted). In the Pachaimalai forest of the Eastern Ghats in India, [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] determined the annual biomass as 25.3x5.6 (tons/ha) with a range of 4.2x103.5 (tons/ha).\u003c/p\u003e \u003cp\u003eFrom Luot Mountain mixed plantation forests, we estimated a mean carbon stock of 31.2 tons/ha, ranging from 15.9 tons/ha to 55.5 tons/ha. The results of our study are closely related to those of [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], in which they estimated a mean carbon stock of 23.04 tons/ha. Further, [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] estimated 24.63 ton/ha and 34.85 ton/ha average carbon stocks in natural vegetation in Vinh Phuc province, Me Linh Biodiversity Station, Vietnam. Additionally, [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] documented 11.5 tons/ha from \u003cem\u003eA. mangium\u003c/em\u003e and \u003cem\u003eEucalypt plantations\u003c/em\u003e in Vietnam. Similarly, a study carried out by [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e] estimated 38 Mg/ha C (41.9 tons/ha converted) in a Western Panama Teak plantation for ten\u0026ndash;year\u0026ndash;old teak. As well, a study was conducted in Indonesia by [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] on 46.32 tons per hectare for the production forest. In damaged and rehabilitated forests of Nam Mau communes, [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] documented 26.29 tons/ha, 32.44 tons/ha, 34.86 tons/ha, and 44.05 tons/ha of carbon. They also reported 18.32 tons/ha, 25.83 tons/ha, 44.31 tons/ha, 46.28 tons/ha, 64.83 tons/ha with a minimum to 137.5 tons/ha average for poor and rehabilitated forests in Quang Khe communes, 15.72 tons/ha, 16.81 tons/ha, 16.91 tons/ha, 19.0 tons/ha, 34.74 tons/ha, with an average of 20.64 tons/ha respectively for poor and rehabilitated forests in Nam Cuong communes. Additionally, [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] estimated 37.27 tons/ha of carbon stock in poor forest in Bach Ma National Park, Vietnam.\u003c/p\u003e \u003cp\u003eThe outcome of the results evidently demonstrated that, the carbon stock in the mixed forest plantation Luot Mountain is lower than the value for Asia, which ranges from 34.4\u0026ndash;85.6 Mg/ha C (37.9\u0026ndash;94.4 tons/ha converted), as well as that for global forests, 44.8\u0026ndash;118.2 Mg/ha carbon stock (49.4\u0026ndash;130.3 carbon tons/ha converted) [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Our results are almost equal to the findings of [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] estimated 31.7 and 29.2 tons of carbon in 2005 and 2015 for poor forests (evergreen broadleaves), and 21 and 23.6 tons/ha carbon in planted forests, respectively. Likewise, the outcome of our study is within the ranged of results of the study conducted in a 12\u0026ndash;year\u0026ndash;old mixed species cabinet timber plantation on the Atherton Tableland, north\u0026ndash;east Australia, 51 tons of carbon was documented per hectare [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e] and also [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e] estimated 41 tons/ha carbon from 20\u0026ndash;year\u0026ndash;old cocoa trees and 45.3 tons/ha carbon for a 23\u0026ndash;year\u0026ndash;old plantation at Kade Agricultural Research Centre. Furthermore, similar findings were documented in \u003cem\u003eJ. copaia\u003c/em\u003e at plantation I in Costa Rica, 25.5 Mg/ha carbon (28.1 tons/ha converted) was measured, while for plantation II, 26.1, 36.8, 44.4, and 47.3 Mg/ha carbon (28.8 tons/ha, 40.6 tons/ha, 48.9 tons/ha, and 52.1 tons/ha converted) were measured for \u003cem\u003eB. elegan, V. ferruginea, H. alchornoeides\u003c/em\u003e, and a mixture of these species [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Additionally, the results of current study are in parallel to research conducted by [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e] in carbon pool sizes of Indian trees and forests ranged from 41 to 48 Mg/ha carbon (45.2 to 52.9 tons/ha converted) and from 39 to 47 Mg/ha carbon (43.0 to 51.8 tons/ha converted) for 1992 and 2002. As well, [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] estimated the carbon stock in Balganga Reserved Forest, Tehri Garhwal Uttarakhand India and reported the highest total biomass carbon density (TBD) at site III (elevation 1800\u0026ndash;2600m) 53.45 Mg/ha (58.9 tons/ha converted), 42 Mg/ha carbon for site II (elevation 1600\u0026ndash;1800m) (46 tons/ha converted), and 28.61 Mg/ha for site I (elevation 1000\u0026ndash;1400 m) (31.5 tons/ha converted) with a mean of 41.6 Mg/ha (45.6 tons/hectare).\u003c/p\u003e \u003cp\u003eAdditionally, the findings of our study of carbon stock are aligned with previous study carried out in three protected forest types of tropical dry deciduous forests in Gurgaon district, southern Haryana [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] found that carbon was potentially sequestered in the forests, i.e., they documented 34.17 Mg/ha (37.7 tons/ha converted) carbon stock for \u003cem\u003eAcacia leucophloea\u003c/em\u003e and \u003cem\u003eBalanites aegyptiaca\u003c/em\u003e and 33.61 Mg/ha (37 tons/ha converted) for \u003cem\u003eAnogeissus pendula\u003c/em\u003e and \u003cem\u003eA. leucophloea\u003c/em\u003e in Yamunanagar and Saharanpur districts in northwestern India. The outcomes of our study are also closely related with study carried out by [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e] estimated 27\u0026ndash;32 tons of carbon per hectare for Poplar (\u003cem\u003ePopulus deltoides\u003c/em\u003e) agroforestry system and Poplar planting in boundary systems. As well, [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] used satellite remote sensing and GIS to estimate biomass and carbon in dry tropical forests in the Chhattisgarh region of India, resulting in 22.97 to 33.27 Mg/ha C (or 25.3 to 36.7 tons/ha converted). The findings of our study of carbon stock are aligned with previous study conducted in Madhya Pradesh, India, 13\u0026ndash;42 Mg/ha (14.3\u0026ndash;46.3 tons/ha converted) were recorded in non\u0026ndash;teak forests and 33\u0026ndash;53 Mg/ha (36.4\u0026ndash;58.42 tons/ha converted) in teak\u0026ndash;dominated forests [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. However, our results are quite higher as compared to the results of a study conducted by [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e] incorporated the sequestration and estimated 20.27 tons of carbon in natural plantation, Western Ghats.\u003c/p\u003e \u003cp\u003eOur study results are higher than the study conducted in Karnataka, India, aboveground carbon stocks for dry deciduous forests 9 to 12 tons/ha by allometric volume equations [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e] and also from Bodamalai hills tropical forests in Tamil Nadu 10.9 tons/ha [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. Our findings are consistent with those of the study [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] which measured the above-ground biomass carbon density in a forest in Turkey at 32.44 grams per hectare (35.75 tons per hectare converted). The results of our study are also closely associated with those of [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e] who found that the average biomass carbon density in European forests was 43.9 Mg/ha carbon (48.4 tons/ha converted). The same results were reported by [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e] in Europe with 42.5 Mg/ha carbon (46.8 tons/ha converted). Further, such types of output have also been estimated by [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e] in Europe at 43.9 Mg/ha carbon (48.4 tons/ha converted). Similar results were reported in another study in Europe [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e] with 40.1 Mg/ha carbon (44.2 tons/ha converted). The results of this type were also documented by [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e] in 1990, when 45 Mg/ha C (49.6 tons/ha converted) existed in 30 countries in Europe. Additionally, [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e] estimated the carbon stock in Europe at 32 Mg/ha C (35.2 tons/ha converted), which is in line with our findings. A carbon stock of 45 Mg/ha (49.6 tones/ha converted) was reported by [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e] in Turkey, which was the same as the output of our study. Comparatively, [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e] recorded a lower carbon stock of 20.71 Mg/ha C (22.82 tons/ha converted).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Environmental service production\u003c/h2\u003e \u003cp\u003eTo estimate the value of carbon dioxide that can be absorbed by a forest stand, carbon dioxide absorption potential is used. The amount of carbon that plants absorb is correlated with their carbon content because the carbon content is directly correlated with the plants' capacity to bind carbon dioxide from the atmosphere [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. Absorption intensity of plant is indirectly affected by diameter and height of a plant, in relation to plants\u0026rsquo; ability of carbon dioxide absorption [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. The total carbon dioxide absorption potential of the present study was 2288.94 (tones/ha), O\u003csub\u003e2\u003c/sub\u003e production was 1670.92 (tones/ha), while carbon credit value was 91.55US\u003cspan\u003e$\u003c/span\u003e/ha. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] reported 1753.04 (tones/ha) total CO\u003csub\u003e2\u003c/sub\u003e absorption potential, 1279.72 (tones/ha) O\u003csub\u003e2\u003c/sub\u003e production and 70.12 US\u003cspan\u003e$\u003c/span\u003e/ha total carbon credits value generated in Indonesia, Mount Bromo, Special Purpose Forest Area. India Himachal Pradesh region of middle Himalayan Kwalkhad watershed, Carbon sequestration and carbon credits were determined by [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]as 14.78 Mg/ha in Agri-horti-silviculture systems and 14.45 Mg/ha in agri-horti-silviculture systems, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Regression analysis of the variables in the forest stand\u003c/h2\u003e \u003cp\u003eIn the study with R\u003csup\u003e2\u003c/sup\u003e value of 0.88 (dbh) diameter at breast height (cm) and height (m) have strong positive linear correlation. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] conducted a study in the Kumrat valley of Pakistan and investigated polynomial Quadratic relationship between tree diameter (cm) and tree height (m) with R\u003csup\u003e2\u003c/sup\u003e value of 0.99. [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e] investigated Quadratic type with R\u003csup\u003e2\u003c/sup\u003e value of 0.98 for diameter and height. While a study by [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e] reported a linear relationship between stem height and diameter of \u003cem\u003eP. roxburghii\u003c/em\u003e of subtropical pine forest of Pakistan. In the Northeastern India, Manipur semi-evergreen tropical forest a study was carried out to estimate AGB and net primary productivity, following harvest method and reported a positive correlation between AGB of trees, tree species and DBH [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiameter and volume exhibited a moderate correlation with R\u003csup\u003e2\u003c/sup\u003e value of 0.35. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] also showed direct relation between volume with basal area (m\u003csup\u003e3\u003c/sup\u003e) having R\u003csup\u003e2\u003c/sup\u003e value of 0.90. Weak negative relation between diameter and stem density was found with R\u003csup\u003e2\u003c/sup\u003e value of 0.01. According to [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] with R\u003csup\u003e2\u003c/sup\u003e value of 0.81, stem density and tree diameter has direct relation in a study in Kumrat area of Pakistan. With R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.78 and R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.52, [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e] reported for 15.0 and 25-year-old Douglas Fir trees, a significant correlation between aboveground biomass and tree density. [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e] investigated a positive correlation between tree density and plant carbon storage.\u003c/p\u003e \u003cp\u003eBasal area and volume showed strong linear relationship, with R\u003csup\u003e2\u003c/sup\u003e value of 0.67. A study by [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e] in the subtropical pine \u003cem\u003e(Pinus roxburghii)\u003c/em\u003e forest found a linear relationship between and basal area and stem volume. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] investigated polynomial linear relationship with R\u003csup\u003e2\u003c/sup\u003e value of 0.90 between volume and basal area (m\u003csup\u003e2\u003c/sup\u003e/ha), in Pakistan\u0026rsquo;s Kumrat valley pure \u003cem\u003ePinus Wallichiana\u003c/em\u003e Forest. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] investigated a strong positive correlation of AGB with tree basal cover of R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.996, 0.989 and 0.990 in three plant functional types (dry mixed, sal mixed and teak plantation) in Katerniaghat wildlife Sanctuary (KWLS), India.\u003c/p\u003e \u003cp\u003eStrong linear relationship was investigated between basal area and total biomass with R\u003csup\u003e2\u003c/sup\u003e value of 0.67. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] discovered a polynomial linear relationship with a R\u003csup\u003e2\u003c/sup\u003e value of 0.90 between biomass (tones/ha) and basal area (m\u003csup\u003e2\u003c/sup\u003e/ha) in the stunning Kumrat Pakistani region. The study by [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e] reported linear relationship with coefficient (R\u003csup\u003e2\u003c/sup\u003e) of 0.92 between AGP and basal area in broad leaved and coniferous forest in temperate forests of Kashmir Valley, J\u0026amp;K, India. [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e] also found a quadratic relationship between basal area and biomass in the coniferous forest of the Dir Kohistan with R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.96. In Peninsular India's inland and costal tropical dry evergreen forests, a positive relationship was also found between AGB and basal area (BA) [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFinally, with R\u003csup\u003e2\u003c/sup\u003e value of 0.67 a strong positive linear relationship is shown between carbon stock and basal area. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] with R\u003csup\u003e2\u003c/sup\u003e value of 0.90 positive linear relationship was investigated between basal area and carbon stock in Pakistan Kumrat region. A linear functional relation between basal area and biomass carbon with value of R\u003csup\u003e2\u003c/sup\u003e (0.99) was investigated by [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e], which supports the arguments of the practical relation of biomass carbon and basal area. [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e] observed that the product of crown area and biomass carbon per tree in the Pine savanna were positively correlated (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.95) for pine trees.\u003c/p\u003e \u003c/div\u003e"},{"header":"5.0. Conclusion","content":"\u003cp\u003eThe purpose of this study is to provide insight into how plantation forest ecosystem carbon sequestration affects environmental performance. Biomass and carbon stocks were derived from above\u0026ndash;ground mixed tree plantations. Based on the results of this study, the biomass and carbon stocks in the Luot mountain plantation of the Vietnam National Forestry University experimental site ranged from 31.2 (tons/ha) to 62.4 (tons/ha). Carbon credits from the study area are valued at 91.55US\u003cspan\u003e$\u003c/span\u003e/ha, which equates to 2288.94 (tones/ha) and 1670.92 (tones/ha), respectively. The findings emphasize the importance of plantation protection and management approaches that prioritize the preservation of plantations due to their substantial carbon storage capacity. As a result, carbon sequestration evaluation of Luot mountain ecosystems has great hypothetical and practical implications for assessing carbon sinks in plantations and establishing carbon sink forests. For the purpose of forest management, the data will be used for ecological assessment and planning.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical approval\u003c/h2\u003e \u003cp\u003eNot Applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate\u003c/strong\u003e \u003cp\u003eNot Applicable\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to publish\u003c/strong\u003e \u003cp\u003eNot Applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors did not receive support from any organization for the submitted work\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed equally to the study concept, design and writing this paper. All authors read and approved of the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting the results reported in this study, including all original data generated and any secondary data used in the analyses, are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSuryawan IWK, Lee CH. Community preferences in carbon reduction: unveiling the importance of adaptive capacity for solid waste management. Ecol Indic. 2023;157:111226.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoul B, Yakoob M, Shah MP. Agricultural waste management strategies for environmental sustainability. Environ Res. 2022;206:112285.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee RP, Meyer B, Huang Q, Voss R. Sustainable waste management for zero waste cities in China: potential, challenges and opportunities. 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Silva Fenn. 2008;42(3):387\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"discover-forests","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Forests](https://link.springer.com/journal/44415)","snPcode":"44415","submissionUrl":"https://submission.nature.com/new-submission/44415/3","title":"Discover Forests","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Above ground biomass, carbon credit, forest, climate change, global warming","lastPublishedDoi":"10.21203/rs.3.rs-8823691/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8823691/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePlantation forests consist primarily of planted or deliberately seeded trees and are intensively managed. It is expected that forests will play a more significant role in climate regulation in the future, as they are considered effective tools for combating climate change and absorbing carbon (C). To calculate the CO₂ uptake efficiency of planted forests at the Vietnam National University of Forestry (VNUF), this study estimated carbon capture and stock distribution in some planted forests in Luot Mountain. Random sampling was used to select a total of 20 rectangular plots of 500 square meters, with a dimension of 25 by 20 meters. Diameter at breast height (DBH) was measured by a diameter tape and caliper for trees with a diameter wider than 6 cm. The Blume-Leiss method was used to measure tree height. Overall biomass and carbon stocks aboveground in the study area were 62.4 tons/hectare and 31.2 tons/hectare, respectively. A carbon credit value of 91.55 USD/ha was assigned to the CO₂ and O₂ production and absorption potentials of 2288.94 (tons/ha) and 1670.92 (tons/ha), respectively. Forest conservation and management strategies should emphasize plantation preservation based on this study's findings because plantations store significant amounts of carbon.\u003c/p\u003e","manuscriptTitle":"Aboveground Tree Carbon Stock and Biomass Potential of Mixed Plantation Forests in Luot Mountain, Vietnam","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-26 15:35:36","doi":"10.21203/rs.3.rs-8823691/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-30T11:00:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33782971255897859034589905227289579757","date":"2026-04-22T18:01:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25577930838588285245542954025836925011","date":"2026-04-21T11:41:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T15:35:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204557060714102262879545180711757270242","date":"2026-04-16T14:31:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-16T11:17:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-16T10:24:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-09T17:00:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Forests","date":"2026-04-09T15:56:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-forests","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Forests](https://link.springer.com/journal/44415)","snPcode":"44415","submissionUrl":"https://submission.nature.com/new-submission/44415/3","title":"Discover Forests","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5afe76f5-5cd9-4924-bd06-c9c053c480c3","owner":[],"postedDate":"April 26th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-04-30T11:00:19+00:00","index":71,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-26T15:35:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-26 15:35:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8823691","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8823691","identity":"rs-8823691","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}