THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY TRAN CONG PHONG DIRECT ESTIMATION OF CARBON STOCK FROM STANDING TREES AT CAMPUS FOREST INDERALAYA, SRIWIJAYA UNIVERSITY, SOUTH SUMATRA, INDONESIA BACHELOR THESIS Study Mode : Full-time Major : Environmental Science and Management Faculty : International Training and Development Center Batch : K44 - AEP (2012-2016) Thai Nguyen, 20/09/2016 DOCUMENTATION PAGE WITH ABSTRACT Thai Nguyen University of Agriculture and Forestry Degree Program Bachelor of Environment Science and Management Student Name Phong Tran Cong Student ID DTN1254140011 Thesis Tittle Supervisors “Direct estimation of carbon stock from standing trees at campus forest Inderalaya, Sriwijaya University, South Sumatra, Indonesia” Dr Iskhaq Iskandar1 Dr Duong Van Thao2 ABSTRACT A study of the CO2 stock in Sriwijaya University (Unsri), Inderalaya, South Sumatra, Indonesia was conducted by using direct measurement and supporting of Remote Sensing data to identify the plot location Forest plays an important role in carbon sequestration the global carbon cycle as carbon sinks of the terrestrial ecosystem The carbon sequestered or stored in the tree and forest mostly referred to the biomass of tree and biomass The Intergovernmental Panel on Climate Change identified five carbon pools of the terrestrial ecosystem involving biomass, namely the aboveground biomass, below-ground biomass, litter, woody debris and soil organic matter Among all the carbon pools, the aboveground biomass constitutes the major portion of the carbon pool Estimating the amount of forest biomass is very crucial for monitoring and estimating the amount of carbon is lost or emitted during anthropogenic activities, natural disaster as forest fire and it will also give us an idea of the forest’s potential to sequester and store carbon in the forest ecosystem Estimations Department of Physics, Faculty of Mathematics and Natural Science, University of Sriwijaya, Palembang, Indonesia The Advanced Education Program, Thai Nguyen University of Agriculture and Forestry, Vietnam i of forest carbon stocks are based upon the estimation of forest biomass This estimation will perform by direct field measurement In addition, with an area of approximately 712 hectares, Unsri campus is not larger area and accession It will be accurate and precise when using field measurement The study has successfully presented the storing of carbon in different types of vegetation in Unsri Campus and also reflecting the reality of vegetation in there Keywords Number of pages Date of Submission Above-ground biomass; Carbon stock; Biomass estimation; Field measurements; Unsri; Carbon pool 41 20/09/2016 Supervisor’s Signature ii ACKNOWLEDGMENT Fortunately, I have a precious internships opportunity to learning and professional development in Department of Biology in Sriwijaya University (UNSRI), Inderalaya and PPLH office in Palembang First and foremost, I would like to express my deepest gratitude and special thanks to my supervisor Dr Iskhaq Iskandar of Department of Physics, Faculty of Mathematics and Natural Science in Unsri and Dr Duong Van Thao of The Advanced Education Program, Thai Nguyen University of Agriculture and Forestry (TUAF), Vietnam, Who took time out to hear, guide, support and encourage me on the correct path and allowing me to carry out my study to have successful results Especially, their priceless advices are not a small contribution in orienting my career and future Moreover, I would like to acknowledge with much appreciation the crucial role of my advisers Agus Dwi Saputra and Guntur Pragustiadi for giving necessary advices and guidance, helping me during the experiment and completing my thesis, let me come out to know so many new things in Indonesia Additionally, I would like to thank all staff of PPLH office and Indonesian friends who has supported me and having the best moments while I was conducting my research in Palembang, Indonesia Last but not least, thanks to my parents and friends who always encourage and put me forward and offer support and love Sincerely, Tran Cong Phong iii TABLE OF CONTENT Error! Bookmark not defined iv LIST OF TABLES Page Table 3.1: Co-ordinate point of transects 19 Table 3.2: List of allometric equations used to estimate biomass of various 25 vegetations Table 4.1: Parameters of each forest types in the study site 28 LIST OF FIGURES Page Figure 2.1: Approximative values of the carbon content (tonnes per hectare) 11 for various vegetation types Figure 2.2: The carbon cycle in nature 13 Figure 3.1: Map of study area 18 Figure 3.2: The transect locations in Unsri campus 19 Figure 3.3: Sample plots for measurement of biomass and carbon stocks 20 Figure 3.4: Diagram of measuring smaller tree diameter using d-tape (A) and 22 caliper (B) Figure 3.5: Guide for determining DBH for abnormal trees 22 Figure 3.6: Category deadwood considering the amount of carbon left 23 Figure 4.1 Carbon densities of six typical forests in UNSRI campus Vertical 30,31 bars are standard errors of the mean DEFINITION OF TERMS Allometric equation – the forest-biomass inventory technique for dry biomass determination It has been developed by establishing a relationship between the various physical parameters of the trees such as the diameter at breast height, height of the tree trunk, branch, total height of the tree, crown diameter, tree species Biomass – the total amount of living organic matter in trees expressed as oven dry tons per unit area Forest plantation – a forest established by planting or seeding in the process of afforestation and reforestation consisting of introduce or indigenous species Carbon stock – the absolute quantity of carbon held within a pool at a specified time In the study carbon stock is use to imply the amount of carbon stored by different types of standing vegetation that represent the flora of Sriwijaya University campus Carbon pool – a reservoir or a system which has the capacity to accumulate or release carbon Examples of carbon pools are forest biomass, wood products, soils and the atmosphere The units are kg ha-1 or Mg ha-1 LIST OF ABBREVIATIONS DBH Diameter at Breast Height IPCC Intergovermental Panel on Climate Change GIS Geographic Information System GHGs Green House Gases SOC Soil organic carbon Unsri Sriwijaya University tC Ton carbon tC/ha Ton carbon per hectare t/ha Tons per hectare PART 1: INTRODUCTION 1.1 Research rationale Global climate change in recent decades has occurred due to disruption of energy balance between the earth and the atmosphere as a result of increased concentrations of greenhouse gases (GHGs) emissions, including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) Especially, CO2 is the most abundant atmospheric gas related to the global warming CO2 is responsible for more than half of the radioactive forces associated with the greenhouse effect Atmospheric CO2 concentration increased by only 20 ppm over the 8000 years prior to industrialisation; multi-decadal to centennial-scale variations were less than 10 ppm and likely due mostly to natural processes However, since 1750, the carbon dioxide concentration in the atmosphere has increased from about 280 ppm to approximately 379 ppm in 2005 (IPPC, 2007) The rise in the carbon dioxide level in the atmosphere is mainly caused by anthropogenic activities Deforestation is having a considerable impact on the ability of the terrestrial biosphere to emit or remove carbon dioxide from the atmosphere Deforestation and degradation of forests lead to emission of carbon dioxide through the burning of forest biomass which is the most important carbon sinks of the terrestrial ecosystem Indonesia is on track to become the world's third-largest greenhouse gas polluter this year, surpassing India, as raging forest and land fires pump out huge volumes of carbon dioxide and thick smoke About 75 per cent of Indonesia's emissions come from deforestation, peatland clearance and peat fires every year (Fogarty, 2015) PART IV: RESULTS 4.1 Characteristics of the forests in the study areas The major characteristics of six forest types examined include alive and dead standing trees The variation in these characteristics not only distinguishes the different stands, but also improves understanding of their carbon stocks The stands of each typical plot that was measured variables: there were trees, trees, 10 trees, trees, 12 trees, 12 trees for plot 1, plot 2, plot 3, plot 4, plot 5, plot 6, respectively Within each study site, the tree diversity of arboretum forest (plot1), secondary forest (plot4) and regenerating forest (plot5) were significantly higher than oil palm plantation (plot 2) and rubber tree plantation (plot 3) and acacia forest (plot 6) The increased stand diversity of types: plot 1, plot was comprised of trees with a DBH ≥ cm and bigger while plot was comprised dominantly of trees with a 10 ≤ DBH ≤ 20 cm and bigger In contrast, plot and was dominated by trees with DBH ≥ 35 cm (accounting for 100%, 91.5%, respectively), with the balance of trees in plot having a 20 ≤ DBH < 35 cm, while plot was mostly dominated by trees with a 20 cm ≤ DBH < 35 cm (accounting for 80 %), with the balance having a 10 cm ≤ DBH < 20 cm (accounting for 20 %) Average DBH of all stand classes were 26.48 cm, 67.44 cm, 21.03 cm, 24.06 cm, 29.30 cm and 46.84 cm for plot 1, plot 2, plot 3, plot 4, plot 5, and plot 6, respectively (Table 4.1) There was a significant difference in DBH in the six forest types (p = 5.649e-09) However, post-hoc test shows that there is no significant difference in tree DBH between plot 1, plot 3, plot and plot 27 Table 4.1: Parameters of each forest types in the study site Number Biomass (ton/ha) Average of trees diameter (cm) Alive Dead Total Plot 26.48 ± 13.62 85.08 ± 10.59 0.00 85.08 ± 10.59 Plot 67.44 ± 3.24 76.93 ± 7.20 0.00 76.93 ± 7.20 Plot 10 21.03 ± 1.85 54.77 ± 2.54 0.00 54.77 ± 2.54 Plot 24.06 ± 3.21 22.31 ± 0.95 28.63 ± 2.79 50.93 ± 2.94 Plot 12 29.30 ± 1.97 65.60 ± 1.22 52.48 ± 1.64 118.09 ± 2.05 Plot 12 46.84 ± 3.59 97.42 ± 1.48 4.45 ± 0.00 101.87 ± 1.48 Total 59.00 402.11 ± 13.23 85.56 ± 3.23 487.67 ± 13.62 As table 4.1, the highest value of biomass was in regenerating forest (plot 5) (accounting for 118.09 ± 2.05 t/ha) However, 44.44% of the biomass in plot contained by dead trees Beside of plot with high value of biomass from dead trees that was secondary forest (plot has the lowest amount of biomass) with 56% biomass of dead trees, while arboretum forest and acacia forest have high value of biomass from living stand for 85.08 t/ha and 97.42 t/ha, respectively The value of tree biomass was affected by the tree diameter as well as the diversity of tree species (variable density) Comparing plot and with plot 3, the diversity of tree species and high variability of tree diameter was cause of significant difference in value of biomass while plot has only 54.77 ± 2.54 t/ha, plot and have 85.08 ± 10.59 t/ha and 118.09 ± 2.05 t/ha, respectively According to Adi Nugroho et al (2006: 30), the 28 biomass of each tree parts is positively correlated with diameter and total height of the tree The positive correlation can be interpreted that increase in the tree diameter will be followed by an increase in biomass in each part of the tree If comparing plot and plot 4, while plot has trees, plot has trees, but the amount of biomass in plot was significantly higher than plot (by 35 t/ha) Meanwhile, plot and plot also have low diversity of tree species (dominating of one species) but plot contained 101.87 t/ha with twice times of diameter larger than plot that contained only 54.77 t/ha Therefore, in conclude the number of individual trees not significantly affect the amount of biomass of trees on a plot, but also influenced by the size of the diameter of a tree As explained above, oil palm plantation (plot 2) that has biggest diameter at all Tree species were not mentioned at all above in comparing about biomass correlating diameter and diversity of tree Because oil palm has a different structure of wood and covered outside in addition to this study using a non-destructive method so oil palm have largest by diameter but was not contained the highest amount of biomass 4.2 Carbon stock in UNSRI stands The carbon densities of six typical forests in Sriwijaya University campus were from range of 38.29-46.79 tC/ha, 34.62-42.31 tC/ha, 24.65-30.12 tC/ha, 22.92-28.01 tC/ha, 53.14-64.95 tC/ha, and 45.84-56.03 tC/ha, respectively, for arboretum forest (plot 1), oil palm plantation (plot 2), rubber trees plantation (plot 3), secondary forest (plot 4), regenerating forests (plot 5), and acacia forest (plot 6) (Figure 4.1a) There is a significant difference in carbon densities between the forest types (p = 0.0187) On stands plantations with dominant of one species, the carbon density of plot was 29 significantly greater (1.86 times and 1.32 times) than plot and plot 2, respectively Acacia forests are likely to have higher carbon densities, although further research would help establish the validity of this claim Seeing from total carbon densities, after disturbance carbon densities of plot was still higher 1.39 times than plot (Arboretum forest) but plot was lower than plot (1.67 times) Seeing from the categories, alive stands were fullly contributor of carbon densities of plot 1, plot and plot While plot 4, plot and plot were contributors of both alive and dead stands As alive stands, plot and plot were lead the carbon densities with 42.54 tC/ha, 48.71tC/ha respectively when 11.15 tC/ha were the lowest carbon densities as plot As dead trees, those were distributed almost in plot and plot (accounting for 56.21 % and 44.44 %, respectively) which were disturbing by hard weather and forest fire while plot had a small amount of dead stand biomass as the natural dead (Figure 4.1b) A 30 B Figure 4.1: Carbon densities of six typical forests in Unsri campus Vertical bar are standard errors of the mean 4.3 Variability of carbon stocks in different types of forests This study investigated the carbon stocks of two components: dead and alive stands for six types of forests in UNSRI campus The carbon stocks of six plots that represent for six types of Unsri forests are very varied The forest at the research site is not primary forest It all was disturbing and serving for educational activities and agriculture However, it still presents of all types of vegetation as seedlings, saplings, poles, and small trees Large trees are rarely found in the plot location, dominating by small-diameter trees and undergrowth types of herbs/shrubs Those were under the influence of many internal and external factors Internal factors such as the condition concerning the tissue/organ photosynthetic, chlorophyll, the age of the network, the other physiological activities such as transpiration, respiration and other physiological 31 adaptations that are intertwined While external factors such as climatic factors such as temperature, humidity, wind speed, rain, and also the light factor, the concentration of CO2, O2, competitors, and pathogenic organisms (Campbell, Reece, & Mitchell, 2004) Plot that is located in an area near the swamp has the largest tree biomass by 118,09 t/ha and simultaneously has the largest carbon density in the range from 53,14 to 64,95 tC/ha The high values of those paramaters on this plot due to high species diversity (4 species) and high species density that was found by the presence of all trees in a range of diameter was measured Several authors have reported positive relationships between species diversity and biomass in forest ecosystems (Vila`, et al., 2007) The floras are dominated in this plot by several species as Melaleuca leucadendra, and Acacia mangium Likewise, with species and high species density plot that is located in arboretum could contain 85.08 t/ha and simultaneously has the third largest carbon density in the range from 38.29 to 46.79 tC/ha The values of biomass in the plot were measured in all live trees, but in the plot that values were contributed by nearly 45% of dead trees While the other plots have only a small amount of biomass from dead trees, even none, plot that is located in secondary forest and plot in regenerating forest have a larger amount of biomass from dead trees with 28.63 t/ha (56,2%) and 52.48 t/ha (45%), respectively Those are consequence of external affection as El Nino, drought, infertility soil, forest fire In plot 2, 3, 6, there are only one species in each plot, such as plot is Elaeis guineesis Carbon estimated data in plot is located within oil palm plantations, so the tree stand consists only of Elaeis guineensis This is because of the campus Unsri 32 Inderalaya is dominated by palm oil (together with rubber, arboretum and campground area) covering an area of 167,545.05 m2 Biomass of trees in this plot has been estimated at 76,93 t/ha and carbon density was in the range from 34,62 to 42,31 tC/ha The value of carbon biomass in accordance with the conditions of oil palm plantations in Indonesia, considering has done some research on the estimation of carbon stocks of palm oil on a variety of different types of land According to Sitompul et al (2000) in Yulianti (2009: 50) explained that the backup Carbon biomass in oil palm plantations in Indonesia ranges from 31 to 101 tC/ha Plot and plot have the different values of tree biomass and carbon density that seems to be abnormal and against the positive correlation between diameter and biomass value which are not greater biomass value of plot (by 76,93 t/ha) than plot (by 101,87 t/ha) while diameter of plot is bigger than plot There was easy to explain that they have different trees shape and structure such as oil palm is unbranched tree while Acacia mangium is branched trees so they will apply by different allometric equation Plot is located behind the clinic Unsri that is the area of plantation as Acacia sp, because this flora is relatively fast growing According to (Purwitasari, 2011), Acacia mangium belongs to the family Fabaceae This plant is one of rapidly growing species and easy to grow (adaptive) on land conditions had lower levels of fertility Acacia is also one that has the high carbon absorption capacity The rapid growth of Acacia mangium is directly proportional to the diameter of the tree In every part of the tree Acacia mangium store carbon reserves, but the amount of carbon stored each different part of the tree According to Fadhli (2009), the average carbon content in the biggest Acacia tree types found on the stem that is equal to 49.30%, the stump of 43.31% and 33 the branches irregularly 42.55% , section 42.15% irregular branches and twigs parts of 37.78% while the smallest one is the carbon content in the leaf that is equal to 37.73% Seeing to plot and plot 6, the values of biomass and diameter in those plots were built up to the positive relationship between biomass and diameter Plot is in rubber tree plantation that is in the young state That is the reason why it has lowest diameter average value and also seems to have lowest biomass value However, the biomass in these plots will be increasing day by day due to developmental stages Many other studies have found a similar increasing trend for both aboveground and belowground C stocks that addresses age dependence of forest biomass and C stocks (Taylor, Wang, & Chen, 2007) (Peichl & Arain, 2006) As a result, forest developmental stages play a determining role in the distribution of C pools for different forest ecosystems (Pregitzer & Euskirchen, 2004) University of Sriwijaya Campus in Inderalaya has an area of ± 712 hectares, including all faculty buildings, auditorium, rector, language institutions, libraries, Puskom, student center, a sports center, terminal, hospital, worship, swamps, etc with a total area 516.94 hectares The remaining parks, urban forests, green open spaces, and estates (including rubber plantations, oil palm plantations, arboretum and campground area) with an area of 195.061 hectares So the real study site is narrower with 195,061 hectares Thus, potential total carbon stocks in Unsri campus are in the range from 7134.39 to 8719.80 tC As a comparison the results of the estimation of carbon stocks in multiple locations in Palembang and surrounding areas in 2012 The carbon stored in the forest near the city of SMB II Palembang Airport with an area of 30 hectares recorded 1380.9 tC (Agus, 2012), while other estimation of total biomass and carbon content 34 stored within the Pulokerto Island (112 ha) of 1962.24 tons and C-stock amounted to 981.12 tC (Wibowo, 2011), the content of carbon stocks stored in Pulokerto Island neighborhood was relatively lower than the urban forest near Airport SMB II Palembang And this shows that the content of the carbon stocks stored in standing trees depending on the location of the region and the structure of the composition of the vegetation component in the region This indicated that the carbon stocks stored in the Unsri campus, Inderalaya quite high compared to some of the research department in Palembang making it potentially as carbon storage area and open green spaces for Ogan Ilir 35 PART V: DISCUSSION AND CONCLUSION 5.1 Discussion There are significant different biomass and carbon density value of each type of stands in Unsri campus, Inderalaya, Indonesia That difference was making may be under the external and internal affection, each sample plot had own feature affection such as plot the biomass value was effected by internal affection while plot and were affected by external affection like soil, climatic conditions Standing trees are really important in absorbing carbon and sequester them In the other hand, stands could store carbon in long-term than the other flora that is extremely necessary and suitable information for policy maker, who could be headache to find out a great solution for reducing greenhouse gases Reforestation as a great solution in reducing the amount of carbon in the atmosphere was considered Carbon was storing in the stands is important as aboveground pool However, there are still have other pool can store carbon as belowground pool, debris, litter, organic soil and peat soil, even aboveground biomass as herb and shrub and the carbon they can store is still unaware 5.2 Conclution Based on the results that have been done, it can be drawn to some conclusions as follows: The total amount of carbon in standing trees in Sriwijaya University campus, Inderalaya is in the range from 7134.39 to 8719.80 (tons C) 36 With dominant sapling and low density, plot has the lowest carbon stock value by 25.47 (tC/ha) With high density and diversity, plot has the highest carbon stock value by 59.04 (tC/ha) However, potential carbon stock is plot 37 REFERENCES Agus, M (2012) Estimasi Cadangan Karbon Pohon Di Kawasan Hutan Kota Sultan Mahmud Badaruddin I Talang Betutu Palembang Inderalaya: FMIPA Unsri Archibald, S., & Bond, W J (2003) Growing tall vs growing wide: tree architecture 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Supervisors Direct estimation of carbon stock from standing trees at campus forest Inderalaya, Sriwijaya University, South Sumatra, Indonesia Dr Iskhaq Iskandar1 Dr Duong Van Thao2 ABSTRACT A study of. .. Mathematics and Natural Science, University of Sriwijaya, Palembang, Indonesia The Advanced Education Program, Thai Nguyen University of Agriculture and Forestry, Vietnam i of forest carbon stocks... ability of the terrestrial biosphere to emit or remove carbon dioxide from the atmosphere Deforestation and degradation of forests lead to emission of carbon dioxide through the burning of forest