Jurnal Manajemen Hutan Tropika
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Spatial Model of Deforestation in Sumatra Islands Using Typological Approach
Get PDFHigh rate of deforestation occurred in Sumatra Islands had been allegedly triggered by various factors. This study examined how the deforestation pattern was related to the typology of the area, as well as how the deforestation is being affected by many factors such as physical, biological, and socio-economic of the local community. The objective of this study was to formulate a spatial model of deforestation based on triggering factors within each typology in Sumatra Islands. The typology classes were developed on the basis of socio-economic factors using the standardized-euclidean distance measure and the memberships of each cluster was determined using the furthest neighbor method. The logistic regression method was used for modeling and estimating the spatial distribution of deforestation. Two deforestation typologies were distinguished in this study, namely typology 1 (regencies/cities with low deforestation rate) and typology 2 (regencies/cities with high deforestation rate). The study found that growth rate of farm households could be used to assign each regencies or cities in Sumatra Islands into their corresponding typology. The resulted spatial model of deforestation from logistic regression analysis were logit (deforestation) = 1.355 + (0.012*total of farm households) – (0.08*elevation) – (0.019*distance from road) for typology 1 and logit (deforestation) = 1.714 + (0.007*total of farm households) – (0.021*slope) – (0.051*elevation) – (0.038* distance from road) + (0.039* distance from river) for typology 2, respectively. The accuracy test of deforestation model in 2000–2006 showed overall accuracy of 68.52% (typology 1) and 74.49% (typology 2), while model of deforestation in 2006–2012 showed overall accuracy of 65.37% (typology 1) and 72.24% (typology 2), respectively
Spatial Model of Deforestation in Jambi Province for The Periode 1990–2011
Get PDFIn the last 2 decades, deforestation had been an international issue due to its effect to climate change. This study describes a spatial modelling for predicting deforestation in Jambi Province. The main study objective was to find out the best spatial model for predicting deforestation by considering the spatial contexts. The main data used for the analysis were multitemporal Landsat TM images acquired in 1990, 2000, and 2011, the existing land cover maps published by the Ministry of Forestry, statistical data and ground truth. Prior to any other analyses, all districts within the study area were classified into 2 typologies, i.e., low-rate and high-rate deforestation districs on the basis of social and economic factors by using clustering approaches. The spatial models of deforestation were developed by using least-square methods. The study found that the spatial model of deforestation for low-rate deforestation area is Logit (Deforestation) = -2.7046 – 0.000397*JH90(distance from forest edge) + 0.000002*JJ(distance from road) – 0.000111*JKBN90 (distance from estate crop edge) + 0.000096 *JP90(distance from agricultural crop edge) + 0.044227*PDK90(population density) + 0.148187 *E(elevation) – 0.131178*S(slope); while for the high-speed deforestation area is Logit (Deforestation) = 9.1727 – 0.000788*JH90(distance from forest edge) – 0.000065 *JJ(distance from road) – 0.000091*JKBN90(distance from estate crop edge) + 0.000005 *JP90(distance from agricultural crop edge) – 0.070372*PDK90(population density) + 11.268539*E(elevation) – 1.495198*S(slope). The low-rate and high-rate deforestation models had relatively good ROC (Relative Operating Characteristics) values of 91.32% and 99.08%, respectively. The study concludes that the deforestation rate was significantly affected by accessibility (distance from forest edge, distance from estate crop edge, edge from agricultural land), biophysical condition (elevation and slope) as well as population density.
The State and the Development of Industrial Plantation Forest
Get PDFDevelopment of industrial plantation forest is a form of principal-agent relationship, in which the Ministry of Forestry as a principal gives utilization permit to the entrepreneur as an agent, known as the Forest Timber Product Exploitation Permit on Planted Forest. This utilization permit obtained by the agents is operationally conducted by other parties through a cooperative agreement. The purpose of this study is to obtain an information regarding to the state position in the development of industrial plantation forest. The study was conducted in Riau Province, using the constructivist paradigm with phenomenological method. Data were obtained through in-depth interviews to selected informants. Data were also obtained from the review of documents to complement the interview. Data analysis was conducted using property rights and principal agent theories. The phenomenon of multi-chain transfer of the management rights of plantation forest that occoured in the observed companies showed that the state was unable to effectively control to the forest plantation. The study recommends that state should issue regulation to decrease or stops further transfer of the management rights of plantation forest. However, further study needs to overcome the existing over accumulation of plantation forest in a few hands
Implication of Land-Use and Land-Cover Change into Carbon Dioxide Emissions in Karang Gading and Langkat Timur Wildlife Reserve, North Sumatra, Indonesia
Get PDFMangrove forest in the context of climate change is important sector to be included in the inventory of greenhouse gas (GHG) emissions. The present study describes land-use and land-cover change during 2006–2012 of a mangrove forest conservation area, Karang Gading and Langkat Timur Laut Wildlife Reserve (KGLTLWR) in North Sumatra, Indonesia and their implications to carbon dioxide emissions. A land-use change matrix showed that the decrease of mangrove forest due to increases of other land-use such as aquaculture (50.00%) and oil palm plantation (28.83%). Furthermore, the net cumulative of carbon emissions in KGLTLWR for 2006 was 3804.70 t CO2-eq year-1, whereas predicting future emissions in 2030 was 11,318.74 t CO2-eq year-1 or an increase of 33.61% for 12 years. Source of historical emissions mainly from changes of secondary mangrove forests into aquaculture and oil palm plantation were 3223.9 t CO2-eq year-1 (84.73%) and 959.00 t CO2-eq year-1 (25.21%), respectively, indicating that the KGLTLWR is still a GHG emitter. Mitigation scenario with no conversion in secondary mangrove forest reduced 16.21% and 25.8% carbon emissions in 2024 and 2030, respectively. This study suggested that aquaculture and oil palm plantation are drivers of deforestation as well as the largest of GHG emission source in this area
Spatial Model of Deforestation in Kalimantan from 2000 to 2013
Get PDFForestry sector is the biggest carbon emission contributor in Indonesia which is mainly caused by deforestation. In Kalimantan island one of the largest island in Indonesia has a significant area of forest cover still can be found although an alarming rates deforestation is also exist. This study was purposed to established spatial model of deforestation in Kalimantan island. This information is expected to provide options to develop sustainable forest management in Kalimantan trought optimizing environment and socio-economic purposes. This study used time-series land cover data from the Ministry of Environment and Forestry (2000 – 2013) and is validated by SPOT 5/6 images in 2013. The spatial model of deforestation were developed using binary logistic. The results of logistic regression analysis obtained spatial model of deforestation in Kalimantan = 1.1480714 – (0.033262*slope) – (0.002242*elevation) – (0.000413*distance from forest edge) + (0.000045*Gross Regional Domestic Product). Validation test showed overall accuracy about 79.64% and 77.01% for models of deforestation in 2000–2006 and 2006–2013 respectively.
High Risk Posture on Motor-Manual Short Wood Logging System in Acacia mangium Plantation
Get PDFMotor-manual logging has been considered as the most dominant logging system in Java Island, Indonesia. The system-which consisted of felling, delimbing, bucking, hauling, and transporting activities- involves a combination of stress factors e.q. difficult work postures, generation of force, and lifting techniques. In the other hand, combination of the three is well associated with high risk of work-related musculoskeletal injuries (MSIs), including musculoskeletal disorders. This research aimed to assess difficult work posture on felling, delimbing, bucking, and manually short wood hauling by employing rapid entire body assessment (REBA) technique and muscular pain scoring based on the worker\u27s perceive. It was revealed that felling and manual hauling were scored 4 in the REBA action level, indicated very high MSIs risk level, and categorized as “necessary now” for an injury risk preventive action. The workers\u27 pain scoring indicated that low back (spine in general) disorders resulting in low back pain has been considered to be the one of the leading safety issues in the felling and manual hauling. Regardless to complex mechanism of how the personal risk and environmental factors associated with manual material handling injuries, job-related factors approach should be underlined in the MSIs prevention initiative in motor-manual logging
Habitat Preferences, Distribution Pattern, and Root Weight Estimation of Pasak Bumi (Eurycoma longifolia Jack.)
No full textPasak bumi (Eurycoma longifolia Jack) is one of non timber forest products with “indeterminate” conservation status and commercially traded in West Kalimantan. The research objective was to determine the potential of pasak bumi root per hectare and its ecological condition under natural habitat. Root weight of E. longifolia Jack was estimated using simple linear regression and exponential equation with stem diameter and height as independent variables. The results showed that the individual number of the population was 114 with the majority in seedling stage with 71 individuals (62.28%). The distribution was found in clumped pattern. Conditions of the habitat could be described as follows: daily average temperature of 25.6oC, daily average relative humidity of 73.6%, light intensity of 0.9 klx, and red-yellow podsolic soil with texture ranged from clay to sandy clay. The selected estimator model for E. longifolia Jack root weight used exponential equation with stem height as independent variable using the equation of Y= 21.99T0,010 and determination coefficient of 0.97. After height variable was added, the potential of E. longifolia Jack minimum root weight that could be harvested per hectare was 0.33 kg
Carbon Stored on Seagrass Community in Marine Nature Tourism Park of Kotania Bay, Western Seram, Indonesia
Get PDFCurrently, the function of seagrass community as carbon storage has been discussed in line with “blue carbon” function of that seagrass has. Seagrass bed are a very valuable coastal ecosystem, however, seagrass bed is threatened if compared to other coastal ecosystems, such as mangroves and coral reefs. The threatened seagrass experienced also contributes to its capacity in absorbing CO2 emission from greenhouse gasses such as CO2 emission Temporal estimation shows that CO2 emission will increase in the coming decade. On the other side, efforts to decrease climate change can be influenced by the existence of seagrass. Informations about existence of seagrass as carbon storage are still very rare or limited. This study was aimed to estimate carbon storage on seagrass community in Marine Nature Tourism Park of Kotania Bay Area, Western Seram, Maluku Province. The quadrat transect method of 0.25 m2 for each plot was used to collect seagrass existence. The content of carbon in the sample of dry biomass of seagrass was analyzed in the laboratory using Walkley & Black method. The results showed that total carbon stored was higher in both Osi and Burung Islands of Kotania Bay than other studied areas (Buntal and Tatumbu Islands, Marsegu Island, Barnusang Peninsula, Loupessy and Tamanjaya Village). The average carbon stored in Kotania Bay waters was 2.385 Mg C ha-1, whereas the total of carbon stored was 2054.4967 Mg C
Growth Model of Pine (Pinus merkusii Jungh. Et de Vriese) Stand on Community Forest in Tana Toraja Regency
Get PDFGrowth modeling and yield simulation of forest is a very important aspect in forest management including community forests. Stand growth model is an abstraction of the dynamic nature of a forest stand, including growth, ingrowths, mortality, and other changes in the structure and composition of the stand. In forest management, growth estimation plays an important role in supporting the sustainability of the benefits value of the community forests. The objectives of the research were to find out the stand growth model and the potential of community\u27s pine forest. The study was conducted at the location of the community pine forests in District Mengkendek Tana Toraja Regency. Sample location, as representative of stand age classes that distribute on some villages in Mengkendek District, were selected by purposive sampling.The study results indicate that the most suitable model for upper trees mean height (H) is Weibull Model, for growth diameter and growth volume is Logistic Model . The stand mean height (h) can be presented as a function of H and Relative Spacing Ratio (Sr) on the basis of function log Sr = 0,197 – 0,653 log H, then the tree volume, can be estimated on the basis of function log V = -1,70 + 0,94logD + 1,50logh, and then the growth function of volume on the basis of function V = 1.008 / 1 + 251.322 exp(-0.373t. Further, the maximum value of stand Annual Increment was 18 m3ha-1year-1, attained at the age of 20 years
Policy Adoption of Forest Management Unit: A Knowledge Diffusion Analysis
Get PDFWithin the policy adoption process of Forest Management Unit (FMU) concept, there has been disagreement of stakeholders on FMUs concept. This disagreement is caused by the exchange of knowledge, information, and perception among stakeholders involved. The results of these interactions could speed up, slow down, and prevent the adoption process of FMU policy. The study objective was analyzing process of knowledge diffusion of FMUs development policy and stakeholders interaction in PFMU Batutegi and PFMU Kotaagung Utara, Indonesia. Adoption process was analyzed by the logical diffusion technique based on knowledge time of FMUs concept received and its interaction space. Social interaction among stakeholders was analyzed using method developed by International Development Studies analysis, i.e. interaction among discourse/narrative, actors/networks and politics/interests. The results showed that knowledge diffusion of FMUs concept in both PFMU tends to cascade diffusion. Factors was affecting of it process were network, role of opinion leaders, willingness to know, and understand on FMUs concept. Indicative strategy is needed as anticipating and overcoming an obstacle in its internalization process, i.e. harmonization of legislative and executive relationship, building an opinion the importance of FMU, and optimalizing network for bureaucratic problems