scholarly journals ESTIMASI STOK KARBON PADA VEGETASI HUTAN RAWA GAMBUT DI KAWASAN LINDUNG IUPHHK-HTI PT. MUARA SUNGAI LANDAK KABUPATEN MEMPAWAH PROVINSI KALIMANTAN BARAT

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammad Taufiq Hidayat ◽  
Dwi Astiani ◽  
Iswan Dewantara
Keyword(s):  
Land Surface ◽  
Protected Area ◽  
Carbon Stock ◽  
Plant Biomass ◽  
Forest Degradation ◽  
Allometric Equation ◽  
Systematic Sampling ◽  
Entire Area ◽  
West Kalimantan ◽  
Non Destructive

Carbon stock is carbon stored both on the ground and land surface as plant biomass, dead plants (necromas), and in soil as soil organic matters. Change in carbon form becomes the basis for calculating emissions, where most of the carbon (C) elements that broken down into the air are usually bound to O2 and become CO2. Deforestation and degradation are the main threats on forest conservation in Indonesia. Deforestation and forest degradation that occur in Indonesia has led to the development of issues as a significant contributor to carbon emissions. The purpose of this study is to estimate carbon stocks in protected area at PT. Muara Sungai Landak Mempawah Regency, West Kalimantan Province. This study used non-destructive sampling. This method, was done by measuring the diameter of the tree and then using an allometric equation that is suitable for estimating biomass. The making of sample plots in this study is stratified on land cover condition and systematic sampling. The results show that carbon stock for the entire area/cover of the protected area of PT. Muara Sungai Landak is 25.970.08 tons. The highest carbon was in old shrubland cover with total of 15.425.15 tons, followed by young thicket 10.356.46 tons C. The smallest stock was in open peat land of 188.46 tons C. The calculation of vegetation in this study show the old shrub cover is 128.8 tons/ha. Keywords: Allometric Equation, Carbon Stock, Protected Area, Stratified Sampling.

scholarly journals CARBON STOCK ESTIMATION AT MINING RECLAMATION AREA: CASE STUDY PT NEWMONT NUSA TENGGARA

2017 ◽  
Author(s):  
Bambang Supriadi ◽  
JONI SAFAAT ADIANSYAH
Keyword(s):  
Carbon Stock ◽  
Plant Biomass ◽  
Initial Conditions ◽  
Total Carbon ◽  
Mining Operations ◽  
Forest Condition ◽  
Periodic Monitoring ◽  
Reclamation Area ◽  
Non Destructive

PT Newmont Nusa Tenggara (PTNNT) is one of mineral mining operations in Indonesia and located at West Sumbawa Regency of West Nusa Tenggara Province. In running its operation, PTNNT is conducting reclamation program to the area that are not disturbed by mining activities. Reclamation program is intended to restore the forest condition similar with the initial conditions and prevent from erosion. In addition, it is obvious that the reclamation forest has also a function as carbon stock. This study aims to determine carbon stock in the PTNNT’s reclamation area particularly in Pit. The method applied is non-destructive sampling methods with estimation of carbon stock using the equations developed by Katterings et al. Estimation of carbon stock is devided into some carbon pools which are biomass of tree, pole and stake, and plant biomass and litter. The research found that the average of total carbon stock in three locations of PTNNT’s reclamation forest (East Dump, Sejorong Dump, and Tongoloka Dump) planted in 2001-2008 is 3,965.95 tonnes carbon or 34.96 tonnes carbon/hectar. In addition, the number of tons of carbon/hectare is influenced by plant growth and it is evidenced by the highest result of carbon stock calculation in 2006 compared with the previous year. This is supported also by the result of periodic monitoring conducted by PTNNT if the growth of plants planted in 2006 is better that the previous year.

scholarly journals Potentials of Carbon Stored in Plant Biomass at Little Farmers Grassland Cisarua, West Bandung Regency

2020 ◽  
Vol 12 (1) ◽  
pp. 111-118
Author(s):  
Annas Dwitri Malik ◽  
Komang Yoga Zso Zsa Dewa ◽  
Parikesit Parikesit ◽  
Susanti Withaningsih ◽  
Ratna Wingit
Keyword(s):  
Carbon Sequestration ◽  
Carbon Storage ◽  
Carbon Stock ◽  
Plant Biomass ◽  
Animal Feed ◽  
Basal Area ◽  
Ground Cover ◽  
Co2 Concentration ◽  
Allometric Equation ◽  
Management Planning

Alternatives of vegetations to store carbon need to be encouraged considering that forests are threatened by widespread destructions. One such vegetation is grasslands which have the potential for carbon storage and to reduce CO2 concentration in the atmosphere. At present, many enterprises have designed grasslands for animal feed. Grassland at Little Farmers, Cisarua, West Bandung was established for many purposes, i.e. recreation, education, and animal feed. The purpose of this research was to study the potential of carbon stock in grassland vegetation at this location. Based on RaCSA method, the tree biomass was determined by nondestructive collection of density and basal area of trees, then calculated by an allometric equation. The ground cover biomass was determined by destructive collection of grass and roots. Total measured biomass was multiplied by 46% to obtain carbon storage. Based on the results, the potential of carbon stock in Little Farmers grassland is 6,506.23 kg/m2 with the potential for carbon storage below the ground (0.129 kg / m2) was slightly higher than the carbon stored above the ground  (0.101 kg / m2). Carbon stored in ground cover had been proven to be lower than woody plants (6,506 kg / m2). This study has pioneered in finding the carbon stocks potential of a man-made grassland, so it provides basis of an alternative land use that can be encouraged for carbon sequestration. For many enterprises, this study will aid in the conduct and management planning of grasslands with regards to ecosystem services preservation, such as carbon sequestration.

scholarly journals Estimasi Karbon Tersimpan Pada Hutan Rakyat Di Pekon Kelungu Kabupaten Tanggamus

2017 ◽  
Vol 5 (1) ◽  
pp. 128
Author(s):  
Liana Ristiara ◽  
Rudi Hilmanto ◽  
Duryat Duryat
Keyword(s):  
Carbon Stock ◽  
Forest Degradation ◽  
Agroforestry System ◽  
Allometric Equation ◽  
Total Carbon ◽  
Community Forest ◽  
Dead Tree ◽  
Tree Component ◽  
Important Value Index ◽  
The Village

The increasing rates of forest degradation and deforestation has been decreasing carbonstocks of forest. Pekon kelungu is one of the village that developing the community forestusing agroforestry system that is also has a function as a carbon stock. The research wasconducted to determine the dominant vegetation and to predict the amount of above groundcarbon stock at the community forest in Pekon Kelungu. The Important Value Index (IVI) wascalculated to measure plants domination.  Allometric equation was used to measure carbonstored for living and dead tree, volume formulas for necromass and Biomass ExpansionFactor formula for litter and seedlings. Durian, cacao and campaca is the dominat tree poleand seedling, respectively. The total carbon of above ground biomass of community forest inPekon Kelungu is amounted to 101,61 ton/ha. Carbon stored on tree component is amountedto 99,92 ton/ha, necromass is amounted to 0,81 ton/ha, litter is amounted to 0,87 ton/ha andseedling is amounted to 0,02 ton/ha.Keyword : carbon stock,community forest, IVI,

scholarly journals PENDUGAAN KARBON TERSIMPAN PADA TEGAKAN DI KAWASAN ARBORETUM SYLVA UNIVERSITAS TANJUNGPURA

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Priska Suryandari ◽  
Dwi Astiani ◽  
Iswan Dewantara
Keyword(s):  
Tropical Forests ◽  
Urban Areas ◽  
Carbon Stock ◽  
Development Programs ◽  
West Kalimantan ◽  
Landcover Change ◽  
The University ◽  
Destructive Measurement ◽  
Non Destructive ◽  
Initial Measurement

Indonesia's tropical forests have an important large amounts of carbon and biodiversity land. The landcover change of the forest for other uses such as agriculture or plantations, particularly in the carbon-rich peat land, making Indonesia become one of the biggest greenhouse gas emitters in the world. Along with the increase of the earth's temperature that rising quite sharply in recent years, Arboretum storage development programs are important in reducing air pollution. Arboretum storage created as a buffer area for water needs, natural environment and carbon storage as well as a have for the flora and fauna in urban areas. One of the Arboretum in the province of West Kalimantan is the area Arboretum Sylva Faculty of forestry Universitas of Tanjungpura Pontianak. The area is an planted with trees and other vegetation forming a structure resembling a forests and an area for the conservation of forest germplasm. It is needed to do re-measurement to search for the growth of the carbon stock in the Arboretum Sylva Tanjungpura University during a period of six years after the initial measurement. This research aims to register total value of (carbon stock) in the area of the Arboretum of the University of Tanjungpura Sylva. The method used for the research was survey sampling with non destructive measurement assesment for tree stage. Data collection was done by census/sampling intensity (100%). While  for the level of sapling, pole stage, stake and necromass were done by nested plots. The results show carbon stock stored for the per unit area was 255.55 tons/Ha and the value of carbon stored whole area was 817.76 Tons.  Keywords: stored carbon, tropical forests, Urban forests

scholarly journals Short Communication: Carbon sequestration by young Rhizophora apiculata plants in Kubu Raya District, West Kalimantan, Indonesia

2019 ◽  
Vol 20 (2) ◽  
pp. 311-315
Author(s):  
RINTO WIARTA ◽  
YULIATI INDRAYANI ◽  
FAIRUZ MULIA ◽  
DWI ASTIANI
Keyword(s):  
Carbon Sequestration ◽  
Carbon Stock ◽  
Short Communication ◽  
Allometric Equation ◽  
Mangrove Species ◽  
West Kalimantan ◽  
Rhizophora Apiculata ◽  
Harvesting Method ◽  
Stock Values ◽  
Change Mitigation

Wiarta R, Indrayani Y, Mulia F, Astiani D. 2019. Short Communication: Carbon sequestration by young Rhizophora apiculata plants in Kubu Raya District, West Kalimantan, Indonesia. Biodiversitas 20: 311-315. Mangrove forest ecosystem has been known for its roles in buffering coastal abrasions and being a reservoir for seafood production. However, very little information is available on its role in sequestering carbon and how its annual growth ability can benefit climate change mitigation. This study aims to determine carbon storage and sequestration by one, three and five-year-old Rhizophora apiculata Blume planted in PT. Ovivipari Bina Semesta (PT. BIOS). This study was conducted for over five months during 2015-2016, in purposively selected mangrove rehabilitation area. It used both harvestings as well as non-harvesting methods for estimation of carbon stock and carbon sequestration. The results show that the mangrove species has a very high ability to sequester carbon per unit area. The amount of carbon stored in plants aged 1 year, 3 years and 5 years were 0.363 tonnes ha-1, 5,591 tonnes ha-1 and 7,240 tons ha-1, respectively. The study also indicated that the carbon stock values obtained by non-harvesting method using allometric equation were higher than the values obtained by harvesting method.

scholarly journals The use of radiocarbon <sup>14</sup>C to constrain carbon dynamics in the soil module of the land surface model ORCHIDEE (SVN r5165)

2018 ◽  
Author(s):  
Marwa Tifafi ◽  
Marta Camino-Serrano ◽  
Christine Hatté ◽  
Hector Morras ◽  
Lucas Moretti ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Land Surface ◽  
Carbon Stock ◽  
Land Surface Model ◽  
Carbon Dynamics ◽  
Total Carbon ◽  
Soil Parameters ◽  
Surface Model

Abstract. Despite the importance of soil as a large component of the terrestrial ecosystems, the soil compartments are not well represented in the Land Surface Models (LSMs). Indeed, soils in current LSMs are generally represented based on a very simplified schema that can induce a misrepresentation of the deep dynamics of soil carbon. Here, we present a new version of the IPSL-Land Surface Model called ORCHIDEE-SOM, incorporating the 14C dynamic in the soil. ORCHIDEE-SOM, first, simulates soil carbon dynamics for different layers, down to 2 m depth. Second, concentration of dissolved organic carbon (DOC) and its transport are modeled. Finally, soil organic carbon (SOC) decomposition is considered taking into account the priming effect. After implementing the 14C in the soil module of the model, we evaluated model outputs against observations of soil organic carbon and 14C activity (F14C) for different sites with different characteristics. The model managed to reproduce the soil organic carbon stocks and the F14C along the vertical profiles. However, an overestimation of the total carbon stock was noted, but was mostly marked on the surface. Then, thanks to the introduction of 14C, it has been possible to highlight an underestimation of the age of carbon in the soil. Thereafter, two different tests on this new version have been established. The first was to increase carbon residence time of the passive pool and decrease the flux from the slow pool to the passive pool. The second was to establish an equation of diffusion, initially constant throughout the profile, making it vary exponentially as a function of depth. The first modifications did not improve the capacity of the model to reproduce observations whereas the second test showed a decrease of the soil carbon stock overestimation, especially at the surface and an improvement of the estimates of the carbon age. This assumes that we should focus more on vertical variation of soil parameters as a function of depth, mainly for diffusion, in order to upgrade the representation of global carbon cycle in LSMs, thereby helping to improve predictions of the future response of soil organic carbon to global warming.

scholarly journals Estimation on the Change of Above-Ground Carbon Stock in Arboretum University of Lampung

2018 ◽  
Vol 6 (2) ◽  
pp. 51
Author(s):  
Kristian Gomos Banjarnahor ◽  
Agus Setiawan ◽  
Arief Darmawan
Keyword(s):  
Carbon Stock ◽  
The Body ◽  
Total Carbon ◽  
Biomass Estimation ◽  
Total Biomass ◽  
Biomass Carbon ◽  
Process Plants ◽  
Carbon Dioxide Co2 ◽  
Non Destructive ◽  
Earth Temperature

Carbon dioxide (CO2) is a greenhouse gas that could increase earth temperature. Through the photosynthesis process, plants absorb CO2 then convert it into carbohydrates, then sequester it in the body of plants. The purpose of the study is to estimate the changes in the carbon stock at the Arboretum University of Lampung. The methods used were stock difference by counting the carbon changes or difference between carbon stored in 2010 and 2016. While the stand biomass estimation measured by trees general allometric equations with non-destructive sampling. The results showed that the total carbon was 46% of the total biomass. Carbon stock in 2016 were about 226.75 ton/ha, showing an increase of 59.72% or 84.78 ton/ha compared to in 2010’s. The increase was due to additional growth of 804 trees as a result of plantation activity and natural regeneration. Keywords: Arboretum, biomass, carbon, necromass, University of Lampung.

scholarly journals ABOVE GROUND TREES BIOMASS OF LORE LINDU NATIONAL PARK-CENTRAL SULAWESI : A STUDY COMBINING FIELD MEASUREMENT AND REMOTE SENSING

Agromet ◽  
2010 ◽  
Vol 24 (1) ◽  
pp. 33
Author(s):  
Naimatu Solicha ◽  
Tania June ◽  
M. Ardiansyah ◽  
Antonius B. W.
Keyword(s):  
Remote Sensing ◽  
Carbon Stock ◽  
Field Data ◽  
Forest Cover ◽  
Satellite Image ◽  
Forest Biomass ◽  
Allometric Equation ◽  
Natural Forest ◽  
Forest Cover Type ◽  
Cover Type

Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.

scholarly journals Spatial distribution pattern of Tarsius Lariang in lore lindu national park

2019 ◽  
Vol 13 (2) ◽  
pp. 606 ◽  
Author(s):  
Abdul Rosyid ◽  
Yanto Santosa ◽  
I Nengah Surati Jaya ◽  
M. Bismark ◽  
Agus P. Kartono
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
Land Surface ◽  
National Park ◽  
Spatial Distribution Pattern ◽  
Systematic Sampling ◽  
Affecting Factors ◽  
Factors Affecting ◽  
Insect Abundance ◽  
Lore Lindu National Park

<p><span>Tarsius lariang (T. lariang) is an endemic species in Lore Lindu National Park (LLNP). Available information regarding T. lariang is limited to only morphological, anatomical, cytogenetic, and voices issues. Knowledge for its geospatial characteristics such as spatial preferences and spatial distribution is rare. The main objective of this study is to identify the spatial distribution pattern of T. lariang in LLNP. An additional objective is to identify the environmental factors affecting its spatial distribution patterns. Field observation for distribution pattern was done at the observation plot that were using systematic sampling with random start. Furthermore, the density estimation in each point was calculated using Triangle Count and Concentration Count method, while insect abundance was estimated using light traps sample data. Finally, spatial pattern was estimated using nearest neighbor index, while the environmental affecting factors were identified by using spatial analysis and correlation analyses. From 45 observation points, the T. lariang distribution pattern was clumped. It is also recognized that the significant factors affecting the spatial distribution were insect abundance, proximity from the commercially utilized land, and land surface temperature.</span></p><p> </p>

scholarly journals ANALYSIS OF FIELD SEAGRASS PERCENT COVER AND ABOVEGROUND CARBON STOCK DATA FOR NON-DESTRUCTIVE ABOVEGROUND SEAGRASS CARBON STOCK MAPPING USING WORLDVIEW-2 IMAGE

2021 ◽  
Vol XLVI-4/W6-2021 ◽  
pp. 321-327
Author(s):  
P. Wicaksono ◽  
P. Danoedoro ◽  
U. Nehren ◽  
A. Maishella ◽  
M. Hafizt ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Stock ◽  
Stepwise Regression ◽  
Species Level ◽  
Measured Parameter ◽  
Support Vector ◽  
Percent Cover ◽  
Svm Classification ◽  
Aboveground Carbon ◽  
Non Destructive

Abstract. Remote sensing can make seagrass aboveground carbon stock (AGCseagrass) information spatially extensive and widely available. Therefore, it is necessary to develop a rapid approach to estimate AGCseagrass in the field to train and assess its remote sensing-based mapping. The aim of this research is to (1) analyze the Percent Cover (PCv)-AGCseagrass relationship in seagrass at the species and community levels to estimate AGCseagrass from PCv and (2) perform AGCseagrass mapping at both levels using WorldView-2 image and assess the accuracy of the resulting map. This research was conducted in Karimunjawa and Kemujan Islands, Indonesia. Support Vector Machine (SVM) classification was used to map seagrass species composition, and stepwise regression was used to model AGCseagrass using deglint, water column corrected, and principle component bands. The results were a rapid AGCseagrass estimation using an easily measured parameter, the seagrass PCv. At the community level, the AGCseagrass map had 58.79% accuracy (SEE = 5.41 g C m−2), whereas at the species level, the accuracy increased for the class Ea (64.73%, SEE = 6.86 g C m−2) and EaThCr (70.02%, SEE = 4.32 g C m−2) but decreased for ThCr (55.08%, SEE = 2.55 g C m−2). The results indicate that WorldView-2 image reflectance can accurately map AGCseagrass in the study area in the range of 15–20 g C m−2 for Ea, 10–15 g C m−2 for EaThCr, and 4–8 g C m−2 for ThCr. Based on our model, the AGCseagrass in the study area was estimated at 13.39 t C.

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