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Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 11 (2018) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2018.711.205 Growth and Carbon Storage Potential of Important Agroforestry Trees of North-West Himalaya S.R. Roshanzada, K.S. Pant* and S. Kar Department of Silviculture and Agroforestry, College of Forestry, Dr. YS Parmar University of Horticulture and Forestry, Nauni, Solan 173220, India *Corresponding author ABSTRACT Keywords Growth, Carbon storage, Allometric equation, Total biomass, Albizia chinensis, Albizia lebbeck, Acacia mollissima, Dalbergia sissoo, Toona ciliata, Melia composita and Ulmus villosa Article Info Accepted: 15 October 2018 Available Online: 10 November 2018 Growth, biomass, carbon storage and allometric relations for estimating stem volume and aboveground biomass on the basis of DBH and Height of tree and growth pattern curve, carbon storage and developed various allometric equations on selected Agroforestry trees. Total seven species including 210 trees were marked selected in the present study. The maximum adjust R2 found in; Albizia chinensis where quadratic function showed the highest adj R2 (0.993) on the basis of DBH and according to the height of tree (H), the best fit was also quadratic, which showed adj R2 in the value of (0.695), on the other hand for six species trees, power function was the best significant equation which modified the highest adj R2 for the following specieses, that are Albizia lebbeck (0.964), Acacia mollissima (0.992), Melia composita (0.990), Dalbergia sissoo (0.992), Toona ciliata (0.888) and Ulmus villosa (0.990) recorded on the basis of DBH, however, to the height of tree as an independent variable, the best equation was sigmoid which showed the adj R2 value in Albizia lebbeck (0.480), Acacia mollissima (0.530), Melia composita (0.598), Dalbergia sissoo (0.551), Toona ciliata (0.645) and Ulmus villosa (0.597). The total biomass (AGB + BGB) was calculated using specific gravity and root-shoot ratio. Branch and leaves biomass of each species was estimated using biomass expansion factor (BEF) of trees as per the guidelines of IPCC (2003). All biomass values were converted to tree biomass carbon by multiplying factor of 0.5. However, in this research, equation selection was based on adjust R2 and minimum standard error. Introduction Forestry play an important role in regional and global carbon (C) cycle because they store large quantities of C in vegetation and soil, exchange C with the atmosphere through photosynthesis and respiration and are source of atmospheric C when they are disturbed by human or natural causes, become atmospheric C sink during re-growth after disturbance, and can be managed to sequester or conserve significant quantities of C on the land (Brown et al., 1996; Sharma et al., 2011). This global importance of forest ecosystem emphasizes the need to accurately determine the amount of carbon stored in different forest ecosystem (Nizami, 2010). Forest ecosystems act as both source and sink of carbon and thus play a crucial role in global carbon cycles. Forests form an important aspect of active carbon pool 1804 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 as they account for 60 percent of terrestrial carbon storage (Wilson and Daff, 2003). Forest ecosystem is one of the most important carbon sinks of the terrestrial ecosystem. It uptakes the carbon dioxide by the process of photosynthesis and stores the carbon in the plant tissues, forest litter and soils. As more photosynthesis occurs, more CO2 is converted into biomass, reducing carbon in the atmosphere and sequestering it in plant tissue above and below ground (Gorte, 2009; IPCC, 2003) resulting in growth of different parts (Chavan and Rasal, 2010). Allometry, generally relates some non-easy to measure tree characteristics from easily collected data such as dbh (diameter at breast height), total height or tree age and provides relatively accurate estimates. Models for volume, biomass or nutrient content within the trees belong to the same class as methodologies for sampling trees and fitting and using the equations are similar. Despite their apparent simplicity, these models have to be built carefully, using the latest regression techniques. Tree growth parameters varies considerably with species, site quality, location, climatic regimes, altitude etc. and therefore becomes necessary to obtain accurate and precise tree allometric estimates in order to improve understanding of the role of these carbon sinks in global carbon cycle. An unsuitable application of allometric equation may lead to considerable bias in carbon stocks estimations (Henry et al., 2013). Solan between 30o 50 30 to 30o 52 0 N latitude and the longitude 77o8 30 and 77o11 30 E (Survey of India Toposheet No. 53F/1) with an elevation of about 900-1300 m above mean sea level. The minimum and maximum temperature varies from 3oC during winter (January) to 33oC during summer (June), whereas; mean annual temperature (MAT) is 19oC. Biomass sampling Seven species (each species 30 trees) were measured for their diameter at breast height (DBH) and height with tree calliper and Ravi’s altimeter, respectively. Biomass of the stem is determined by multiplying volume of stem with specific gravity. Local volume equation developed for specific tree species and region was used for calculating the volume of the forest trees, Branch and leaves biomass was estimated by multiplying the volume of trees of each species with their corresponding biomass expansion factors, The total aboveground biomass of the tree comprised of the sum of stem biomass, branch biomass and leaf biomass, The below ground biomass (BGB) calculated by multiplying above ground biomass taking 0.26 as the root: shoot ratio and for total biomass were calculated sum of above ground biomass and belowground biomass. Growth Materials and Methods To find the growth were calculated growth parameter (crown area, crown width, crown volume and height of the tree) Site description Crown area The study was conducted in out in, Dr Y S Parmar University of Horticulture and Forestry, Nauni area, Solan Himachal Pradesh, India. The area lies about 13 kilometres from Crown area will be assumed to be a circle, and it was calculated and used the formula given by Chaturvedi and Khanna (2000) and expressed in meter square. CA=π÷4D2. 1805 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 Crown width Adjusted R2 The crown width (m) was measured in two directions (North-south and East-west) and average was calculated as: Calculated as per following formula given by Gujrati, 1998. D1 + D2 CW = ------------2 R2 = 1 - [ ] Where: R = sample Rsquare, N= number of observations and K= number of parameter. Crown volume Standard residual error: (Mbow et al., 2013) 𝛔 For calculated, used the following formula (Balehegn et al., 2012): SRE CV=4ԉ÷3+(CW÷2+CD÷2)³. Height of trees Where: y = the average of the observed parameter, 𝛔 = the standard deviation and n= is the number of sample. It is the height from base to top of standing tree measured and used Ravi Millimeter and expressed in meters. Results and Discussion Determination of allometric among the tree components Carbon storage Biomass of each tree component converted to biomass-carbon by multiplying biomass with conversion factor of 0.50. Statistical procedure All the species compared for their morphological characters by using standard statistical procedure. equation The result on various linear and non-linear functions for tree volume as the dependent variable and DBH (diameter at breast height) and tree Height separately as independent variable for Albizia chinensis, Albizia lebbeck, Melia composita, Acacia mollissima, Toona ciliata, Dalbergia sissoo and Ulmus wallichiana and are present in Table 1. Albizia chinensis The allometric relationships among different tree components of an individual tree like height, dbh, biomass and volume developed by using linear and non-linear functions. Data processing and analysis The best linear and nonlinear relationship between tree components determined by determination of (Adj.R2) and standard residual error. The allometric relations for estimating stem volume with DBH and Height of tree , each taken independently , where quadratic 2 ̄ Function showed highest R (0.98) stem volume with DBH. In case of tree Height sigmoid function showed highest adj R̄2 (0.69). The allometric relationship of tree stem biomass with DBH and tree Height , each 1806 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 taken independently, where quadratic function showed R̄ 2 (0.99) for tree stem biomass with DBH. In case of Height of tree sigmoid function showed the highest adj R̄2 (0.69). Albizia chinensis showed significant allometric relationship for estimating of branch and leaves biomass (BB) with DBH as well as tree Height when used independently. The results revealed that quadratic function was strong with adj R̄2 (0.98). Similarly, stronger relationships were found for tree Height variable with maximum R̄2 values by sigmoid function (0.69). The allometric relationships of tree above ground biomass (AGB) with DBH and Height of tree , each taken independently , where quadratic Function showed R̄ 2 (0.99) and In case of tree Height sigmoid function showed R̄2 (0.69). Albizia lebbeck Albizia lebbeck were significant for DBH. The power function showed highest R̄2 (0.96) for volume with DBH and in case of Height of tree power function showed highest R̄2 (0.47). The allometric relations for estimating stem biomass with DBH and Height of tree , each taken independently , where power Function showed highest R̄ 2 (0.96) stem biomass with DBH and In case of tree Height power function showed highest adj R̄2 (0.47). Various allometric relationships used for DBH as well as tree Height for branch and leaves estimating of Albizia lebbeck. Trees were significant for DBH. The power function showed highest R̄2 (0.96) for branch and leaves with DBH and case of Height of tree power function showed highest R̄2 (0.48). Albizia lebbeck showed significant allometric relations for estimating aboveground biomass (ABG) based on DBH as well as tree Height when used independently. The results revealed that power function was strong with adj R̄2 (0.95) and similarly, stronger relationships were found for tree Height variable with maximum R̄2 values by power function (0.47). Acacia mollissima Among based on DBH, the allometric relations were significant, where power function reported highest R̄2 (0.99) and for tree Height variable, the significant relationships were stronger with maximum value of R̄2 (0.52) for sigmoid. Allometric relations for estimating stem biomass with DBH as well as tree Height separately for Acacia mollissima. The power function reported highest R̄2 (0.98) on the basis of DBH and for tree Height variable, the significant relationships were stronger with maximum value of R̄2 for sigmoid (0.51). Various linear and non-linear relationships used for DBH as well as tree Height for branch and leaves estimation of Acacia mollissima. Trees were significant for DBH. The power function showed highest R̄2 (0.96) for branch and leaves with DBH and however, in case of Height of tree sigmoid function showed highest R̄2 (0.45). Various linear and non-linear relationships used DBH as well as tree Height for stem volume estimation of Acacia mollissima. Trees were more significant for DBH. The power function showed highest R̄2 (0.97) and in case of Height of tree sigmoid function showed highest R̄2 (0.53). Toona ciliata Toona ciliata showed significant allometric relations for various linear and non-linear functions used for stem volume estimation 1807 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 with DBH as well as height when used independently. The results revealed that power function was strong with R̄2 (0.88) on the basis of DBH and similarly stronger relationships were found for tree Height variable with maximum value of R̄2 by sigmoid function (0.64). The allometric relations for estimating stem biomass with DBH, where power function was strong with R̄2 (0.87) and similarly stronger relationships were found for tree Height variable with maximum value of R̄2 by sigmoid function (0.64). Various linear and non linear relationships used for DBH as well as tree Height for branch and leaves estimation, trees were significant for DBH. The power function showed highest R̄2 (0.88) for branch and leaves with DBH and in case of Height of tree sigmoid function showed highest R̄2 (0.64). Allometric relations for estimating aboveground biomass (AGB) based on DBH. The results revealed that power function was strong with adj R̄2 (0.87) and also, stronger relationships were found for tree Height variable with maximum R̄2 values by sigmoid function (0.63). Dalbergia sissoo Various linear and non-linear equations used to find out stem volume of this tree with DBH as well as height independently were significant. The power function showed highest R̄2 (0.99) value based on DBH and In case of height of tree sigmoid function is the best fitted and highest R̄2 (0.54) value. Allometric relations for estimating stem biomass of Dalbergia sissoo trees with DBH showed The power function is best with highest R̄2 (0.98) value and In case of height of tree, sigmoid function is the best fitted and highest R̄2 (0.54) value. Various linear and non linear relationships for branch and leaves estimated based on DBH the power function showed highest R̄2 (0.98) and However, in case of Height of tree sigmoid function showed highest R̄2 (0.55). Table.1 Calculation of Aboveground biomass (AGB), belowground biomass (BGB), Total biomass (TB), aboveground carbon (AGC) and Total carbon storage TC of selected trees TREE SPECIES Albizia chinensis Albizia lebbeck Acacia mollissima Melia composita Toona ciliata Ulmus villosa Dalbergia sissoo Biomass (kg / Tree) Carbon (kg/tree) Aboveground Belowground Total Aboveground Total (AGB) (BGB) biomass (AGC) carbon TB TC ± 572 154 726 25 286 363 800 560 220 120 1020±12 680±23 400 280 510 340 950 260 1210±29 475 605 1030 650 770 280 180 160 1310±32 830±14 930±08 515 325 385 655 415 465 1808 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 Fig.1 Scatter diagrams from carbon storage of total biomass of Albizia chinensis (A), Albizia lebbeck (B), Melia composita (C), Acacia mollissima (D), Toona ciliata (E), Ulmus villosa (F) and Dalbergia sissoo (G) 1809 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 Fig.2 Scatter diagrams from carbon storage of aboveground biomass of Albizia chinensis (I), Albizia lebbeck (II), Melia composita (III), Acacia mollissima (IV), Toona ciliata (V), Ulmus villosa (VI) and Dalbergia sissoo (VII) 1810 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 Various linear and non linear relationships used based on DBH as well as tree Height for stem volume estimation of Dalbergia sissoo. Trees were more significant for DBH. The power function showed highest R̄2 (0.98) and, in case of Height of tree sigmoid function showed highest R̄2 (0.54). The allometric relationships between stem volume and DBH were significant, where power function showed highest R̄2 (0.98), whereas, for tree Height, the relationships were significantly strong with highest R̄2 (0.59). The allometric relations for estimating stem biomass with DBH, where power function was strong with R̄2 (0.98) and similarly stronger relationships were found for tree Height variable with maximum value of R̄2 by sigmoid function (0.59). The power function showed highest R̄2 (0.98) for branch and leaves with DBH and however, in case of Height of tree sigmoid function showed highest R̄2 (0.58). Melia composita were more significant for DBH. The power function showed highest R̄2 (0.99) and However, in case of Height of tree sigmoid function showed highest R̄2 (0.59). Ulmus villosa The allometric relations for estimating stem volume of Ulmus villosa tree with DBH and Height of tree, each taken independently, resulted in highly significant R̄2 (0.96) which fitted by power function for stem volume with DBH and). In case of tree Height taken as predictor variable, sigmoid function showed highest R̄2 (0.60). The power function showed R̄ 2 (0.98) for tree stem biomass after estimating of the allometric relations for tree stem biomass of Ulmus villosa with DBH and In case of Height of tree sigmoid function showed the highest adj R̄2 (0.59) Ulmus villosa were significant for DBH. The power function showed highest R̄2 (0.98) for branch and leaves biomass and in case of Height of tree sigmoid function showed highest R̄2 (0.59). Ulmus villosa showed significant allometric relations for estimating of aboveground biomass (ABG) based on DBH. The results revealed that power function was strong with adj R̄2 (0.95) and similarly, stronger relationships were found for tree Height variable with maximum R̄2 values by sigmoid function (0.62). Growth pattern and relationship among trees components Albizia chinensis Growth curve pattern of morphological parameters of Albizia chinensis revealed that growth of crown area (Fig. 1) is best explained by sigmoid allometric equation (R̄2= 0.41, SEb0=0.57 and SEb1= 0.17). Albizia lebbeck Growth curve pattern of morphological parameters of Albizia lebbeck showed that growth of crown area, crown width, crown volume and height of tree are best explained by sigmoid curves with highest (R̄2= 0.59, SEb0=0.32 and SEb1= 0.04 Acacia mollissima Growth curve pattern of morphological parameters of Acacia mollissima revealed that is best explained by linear allometric equations with highest (R̄2= 0.19, SEb0=0.60 and SEb1= 3.69). 1811 Int.J.Curr.Microbiol.App.Sci (2018) 7(11): 1804-1818 Melia composita Growth curve pattern of morphological parameters of Melia composita showed that growth of crown area (Fig. 1) is best explained by sigmoid allometric equation (R̄2= 0.52, SEb0=0.54 and SEb1= 0.35). Toona ciliata Growth curve pattern of morphological parameters of Toona ciliata revealed that growth of crown area (Fig. 1) is best explained by quadratic allometric equation (R̄2= 0.23, SEb0=1.55 and SEb1= 0.13). Belowground biomass ranged from 280 kg/tree Toona ciliata to 120kg/tree Acacia mollissima. In case of total carbon storage potential Toona ciliata has a highest rate with (655 kg/tree). Allometric equations are useful to measure the biomass of trees in areas. This study provides allometric equations for DBH, height and tree biomass that can be used for forests ecosystems. It also shows that allometric equations integrating DBH and height of tree (H) independently were significant variable for the estimation of tree stem volume, stem biomass, branch and leaf biomass and aboveground biomass (Fig. 2). Dalbergia sissoo Growth curve pattern of morphological parameters of Albizia lebbeck showed that is the best explained by sigmoid curves with highest (R̄2= 0.44, SEb0=0.34 and SEb1= 0.08). Ulmus villosa Growth curve pattern of morphological parameters of Ulmus villosa revealed that is the best explained by sigmoid curves with highest (R̄2= 0.33, SEb0=0.34 and SEb1= 0.05). Determination of carbon storage The result revealed that biomass and carbon stored in different component trees decreased in the order: Toona ciliata ˃ Melia composita ˃ Albizia lebbeck ˃ Dalbergia sissoo ˃ Ulmus villosa ˃ Albizia chinensis ˃ Acacia mollissima. Aboveground biomass was maximum (1030 kg / tree) in Toona ciliata followed by Melia composita, (950 kg/tree), Albizia lebbeck (800 kg/tree), Dalbergia sissoo (770 kg/tree), Ulmus villosa (650 kg/tree), Albizia chinensis (572 kg/tree) and Acacia mollissima (560 kg /tree). It is evident from the present study that there is highly significant relation between DBH and crown area (CA), crown width (CW), crown volume (CV) and height of tree (H) growth parameters and these growth characteristics have strongly related to dbh of tree and they increase with the increase of DBH. Among various linear and non-linear functions, the sigmoid function was the best for that component which I mentioned above. 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