DEVELOPING SITE-SPECIFIC ALLOMETRIC EQUATIONS FOR ABOVE-GROUND BIOMASS ESTIMATION IN PEAT SWAMP FORESTS OF ROKAN HILIR DISTRICT, RIAU PROVINCE, INDONESIA

In forest biomass assessment studies, the selection or development of reliable allometric biomass equations is an essential step which determines largely the accuracy of the resulted biomass estimates. Unfortunately, only few studies on allometric biomass equations have been conducted for peat swamp forests and the results are usually not publicly accessible or well documented. Thus, the objective of this study was to develop site-specific allometric equations for above-ground biomass (AGB) estimations in tropical peat swamp forests in Indonesia. These equations were developed based on 51 destructively sampled trees. The results indicated that the developed site-specific allometric equations have coefficient of determination (R2) greater than 95%. The R2 values ranged from 97.0% to 98.7%, where the lowest R2 value resulted from the simplest model which used only DBH as a predictor. Model 5, which used DBH, H and ρ as predictive variables, provided best performance when estimating the AGB of the study area. Hence, as long as reliable data are available as input, Model 5 is recommended. The accuracy and applicability of the allometric equations for peat swamp forests could be improved further by adding more sampled trees from different tree species and/or with a wider DBH range. Considering the importance of wood density in the estimation of the AGB and the lack of this information for peat swamp forest tree species, research should be dedicated to analysing the wood density of the dominant tree species comprising the majority of the AGB density in the study area

RELATIONSHIPS BETWEEN TOTAL TREE HEIGHT AND DIAMETER AT BREAST HEIGHT FOR TROPICAL PEAT SWAMP FOREST TREE SPECIES IN ROKAN HILIR DISTRICT, RIAU PROVINCE

Reliable information on total tree height (H) is fundamental in forest resource management and forest ecological studies, including in forest biomass assessment. Adding an H variable can improve the performance of the biomass allometric equations by reducing the average deviation significantly. However, measuring H is relatively complex, less accurate, time consuming, and expensive. Thus, H is only measured for sampled trees within the plots, whilst diameter at breast height (DBH) is commonly measured for each tree during the forest inventory. The missing H information is usually estimated based on a stand-specific allometric relationship between H and DBH (H-D model) constructed from sampled trees. Despite extensive studies on H-D model for boreal forests and for single-species/plantation forests, few studies have focused on tropical forests. Furthermore, relationships for peat swamp forest tree species, and especially those in Indonesia, have not been widely published. Thus, the objective of this study was to develop site-specific H-D models for tropical peat swamp forests using linearized and non-linear regression functions. The results indicated that the non-linear models outperformed the linearized models based on the statistical parameters and the biological criteria. The modified logistic function (Model 7) is recommended for estimating H in the study area as it has comparable model performances to the exponential function (Model 6) and passed the point diameter-height of (0, 1.3). However, all five non-linear models performed equally well and the differences between them were trivial. Further improvements are needed to improve the accuracy, the predictive ability and the geographical applicability of the models by grouping the species, adding stand variables and (or) using advanced techniques of mixed-effect modelling. In addition, model validation should be carried out prior to their application by collecting a new dataset from the forest being studied

RELATIONSHIPS BETWEEN TOTAL TREE HEIGHT AND DIAMETER AT BREAST HEIGHT FOR TROPICAL PEAT SWAMP FOREST TREE SPECIES IN ROKAN HILIR DISTRICT, RIAU PROVINCE

Reliable information on total tree height (H) is fundamental in forest resource management and forest ecological studies, including in forest biomass assessment. Adding an H variable can improve the performance of the biomass allometric equations by reducing the average deviation significantly. However, measuring H is relatively complex, less accurate, time consuming, and expensive. Thus, H is only measured for sampled trees within the plots, whilst diameter at breast height (DBH) is commonly measured for each tree during the forest inventory. The missing H information is usually estimated based on a stand-specific allometric relationship between H and DBH (H-D model) constructed from sampled trees. Despite extensive studies on H-D model for boreal forests and for single-species/plantation forests, few studies have focused on tropical forests. Furthermore, relationships for peat swamp forest tree species, and especially those in Indonesia, have not been widely published. Thus, the objective of this study was to develop site-specific H-D models for tropical peat swamp forests using linearized and non-linear regression functions. The results indicated that the non-linear models outperformed the linearized models based on the statistical parameters and the biological criteria. The modified logistic function (Model 7) is recommended for estimating H in the study area as it has comparable model performances to the exponential function (Model 6) and passed the point diameter-height of (0, 1.3). However, all five non-linear models performed equally well and the differences between them were trivial. Further improvements are needed to improve the accuracy, the predictive ability and the geographical applicability of the models by grouping the species, adding stand variables and (or) using advanced techniques of mixed-effect modelling. In addition, model validation should be carried out prior to their application by collecting a new dataset from the forest being studied

Landscape scale carbon stock assessment of tropical peat swamp forests using an integrated field measurement and remote sensing technique : a case study in pt diamond raya timber, Rokan Hilir district, Riau province, Indonesia

Indonesia's tropical peatland ecosystems constitute one of the largest terrestrial carbon pools in the world. However, anthropogenic and natural disturbances can convert the peatland ecosystems' status from carbon sinks and stores to sources. Huge amounts of carbon are released to the atmosphere as CO2 through peat decomposition and fire. When these emissions are taken into account, Indonesia became one of the largest CO2 emitter worldwide. Despite their significant role in the global climate change, tropical peatland ecosystems (particularly peat swamp forests) are inadequately studied. Thus, the main objectives of this research are to fill the gap in knowledge regarding peat swamp forests and to develop a practical framework for assessing carbon stock at landscape level in peat swamp forests under an active logging company. Site-specific allometric equations for above-ground biomass and carbon (AGB and AGC) were developed based on 51 and 31 destructively sampled trees, respectively, and the results were compared to the published equations commonly used in the tropical forest biomass studies. The carbon fraction used to develop AGC equations were analysed based on 362 subsamples from 31 sampled trees using the Walkley-Black method. The relationship between total tree height (H) and diameter at breast height (DBH) were constructed based on 286 sampled trees using linearized and non-linear functions. A total of 150 measurement plots were used to analyse the impacts of selective logging on forest community composition, structure and biomass. The stand attributes comparison between logged and unlogged plots was conducted using non-parametric tests. The landscape level carbon stock estimates were calculated based on a published biomass-backscatter algorithm and ALOS-PALSAR images. The results indicated that the developed site-specific allometric equations have determination coefficient of greater than 95%. The model which used DBH, H and wood density has the best performance, thus is recommended when reliable data on these variables are available. The site-specific outperformed the published equations in estimating AGB and AGC. The non-linear function provided better H-D models than the linearized function based on the statistical parameters and the biological criteria with the fit index of ~91% and the standard error of 3.6 m. The model based on the modified logistic function is recommended. The species composition, structure and biomass between selectively logged and unlogged forest plots were statistically significantly different, but there are indications that the differences decrease with time since harvest. The generated landscape level AGB map depicts logically the spatial pattern of AGB density distribution, thus is useful for management purposes, particularly in allocating the resources efficiently for further ground-based investigations. The landscape level AGB per ha ranged from 12.5 to 390.6 t with an average of 213.4 t. The carbon fraction obtained in this study was 0.473, which was slightly lower than the generic value of 0.5. Despite the limitations, this study has provided a practical framework for assessing carbon stocks and the impacts of selective logging at the landscape level

Alokasi Pengeluaran Rumah Tangga Penyadap Getah Pinus Di Desa Somagede Kabupaten Kebumen, Jawa Tengah

The Pine forest has contributed of local people economy, especially of the resin tappers. Increasing income will raise the household expenditure both of consumptive and productive needs. This research was aimed to find out the expenditure allocations of resin tappers\u27 household and to identify the factors affecting them. Survey method was adopted in this research to collect the primary data of 30 respondents. The collected data was analyzed both quantitatively and qualitatively. Multiple linear regression model was applied to figure out the factors affecting the expenditure allocations of resin tappers\u27 household. The result of the research indicated that the expenditure of resin tappers\u27 household reacted Rp 2,366,459 per annum and 58,08% of it was food and beverage expenditure. The expenditure allocations were affected significantly by tappers\u27 age, food and beverage expenditure, and land area. The tappers\u27 age, food and beverage expenditure had a positive effect whereas the land area had a negative effect on the household expenditure. Keywords: The expenditure allocations, resin tappers\u27 household, household expenditure, pine, resin tapper

Alokasi Pengeluaran Rumah Tangga Penyadap Getah Pinus di Desa Somagede, Kabupaten Kebumen Jawa Tengah

Expenditure Allocation of Resin Tapper`Households in Somagede Village, Kebumen Regency, Central JavaPine forest has contributed to local people economy, especially the resin tappers. Increasing income will raise the household expenditure both of consumptive and productive needs. This research was aimed to assess the expenditure allocations of resin tappers’ household and to identify the factors affecting them.Survey method was adopted in this research to collect the primary data of 30 respondents. The collected data was analyzed both quantitatively and qualitatively. Multiple linear regression model was applied to figure out the factors affecting the expenditure allocations of resin tappers’ household.The results of the study indicated that the expenditure of resin tappers’ household reached to Rp 2,366,459 per annum and 58,08% of it was food and beverage expenditure. The expenditure allocations were affected significantly by tappers’ age, food and beverage expenditure, and farm land size. The tappers’ age, food and beverage expenditure had a positive effect whereas farm land size had a negative effect on the household expenditure.

Spatial-Temporal Dynamics Land Use/Land Cover Change and Flood Hazard Mapping in the Upstream Citarum Watershed, West Java, Indonesia

This study presents the information on the dynamics of changes in land use/land cover (LULC) spatially and temporally related to the causes of flooding in the study area. The dynamics of LULC changes have been derived based on the classification of Landsat imagery for the period between 1990 and 2016. Terrain surface classification (TSC) was proposed as a micro-landform classification approach in this study to create flood hazard assessment and mapping that was produced based on the integration of TSC with a probability map for flood inundation, and flood depth information derived from field observation. TSC as the micro-landform classification approach was derived from SRTM30 DEM data. Multi-temporal Sentinel-1 data were used to construct a pattern of historical inundation or past flooding in the study area and also to produce the flood probability map. The results of the study indicate that the proposed flood hazard mapping (FHM) from the TSC as a micro-landform classification approach has the same pattern with the results of the integration of historical inundation or previous floods, as well as field investigations in the study area. This research will remain an important benchmark for planners, policymakers and researchers regarding spatial planning in the study area. In addition, the results can provide important input for sustainable land use plans and strategies for mitigating flood hazards

Lake and Stream Buffer Zone Widths' Effects on Nutrient Export to Lake Rawapening, Central Java, Indonesia: A Simple Simulation Study

Lake ecosystems in Indonesia face serious environmental problems. One of those problems is eutrophication caused by excessive plant nutrients, particularly nitrogen (N) and phosphorus (P). Water quality degradation and biodiversity loss are the effects of eutrophication. The government of Indonesia (GoI) has issued a regulation on determining lake and stream buffer zones, but it has not been fully implemented in the field. Additionally, the data related to the effects of each buffer zone width is not available. This study aims to begin to fill this gap. It simulates the effect of lake and stream buffer zone widths on nutrient export to Rawapening Lake. The Nutrient Retention sub-model, which is part of InVEST (Integrated Valuation of Environmental Services and Tradeoffs) software, has been used for this research to analyse information from several data sources, including a Digital Elevation Model (DEM) and measurements of soil depth, annual rainfall, land cover/use, watershed/sub-watershed boundaries, and biophysical conditions. Several studies of eutrophication in Rawapening Lake have measured the magnitude of eutrophication but have not discussed the effects of buffer zone widths. Therefore, this study accommodates the updated data on how much effect of buffer zone widths on the reduction of nutrient export. Five scenarios of buffer zone width are considered:  30 m., 90 m., and 150 m, where the lake buffer zone widths and the stream buffer zone width are 30 m. The results indicated that the maximum nutrient export reduction of lake buffer zones was only 2.63% (for N) and 3.56% (for P). On the other hand, the 30 m stream buffer zone width reduced the nutrient export to Rawapening Lake by up to 43.05% for N and by 44.90% for P. A 30 m combined lake and stream buffer zone width slightly increases the nutrient export reduction effectiveness, i.e., 0.41% and 0.56% for N and P, respectively

Spatial-temporal dynamics land use/land cover change and flood hazard mapping in the upstream citarum watershed, west Java, Indonesia

This study presents the information on the dynamics of changes in land use/land cover (LULC) spatially and temporally related to the causes of flooding in the study area. The dynamics of LULC changes have been derived based on the classification of Landsat imagery for the period between 1990 and 2016. Terrain surface classification (TSC) was proposed as a micro-landform classification approach in this study to create flood hazard assessment and mapping that was produced based on the integration of TSC with a probability map for flood inundation, and flood depth information derived from field observation. TSC as the micro-landform classification approach was derived from SRTM30 DEM data. Multi-temporal Sentinel-1 data were used to construct a pattern of historical inundation or past flooding in the study area and  also to produce the flood probability map. The results of the study indicate that the proposed flood hazard mapping (FHM) from the TSC as a micro-landform classification approach has the same pattern with the results of the integration of historical inundation or previous floods, as well as field investigations in the study area. This research will remain an important benchmark for planners, policymakers and  researchers regarding spatial planning in the study area. In addition, the results can provide important input for sustainable land use plans and strategies for mitigating flood hazards