Land Use and Land Cover Scenarios for Optimum Water Yield and Sediment Retention Ecosystem Services in Klong U-Tapao Watershed, Songkhla, Thailand

The Klong U-Tapao watershed is the main source of water supply for agriculture, industry, and household consumption of the Songkhla province and it frequently contributes serious problems to lowland areas, particularly flood and soil erosion. Therefore, land use and land cover (LULC) scenario identification for optimum water yield and sediment retention ecosystem services are necessary. In this study, LULC data in 2010 and 2017 were firstly classified from Landsat data using random forests classifiers, and they were then used to predict LULC change during 2018 −2024 under three different scenarios by CLUE-S model. Later, actual LULC data in 2017 and predictive LULC data of three scenarios were further used to estimate water yield and sediment retention services under the InVEST and LULC scenario for optimum water yield and sediment retention ecosystem services were finally identified using the ecosystem service change index (ESCI). The result of the study showed the major increasing areas of LULC types during 2010−2017 were rubber plantation and urban and built-up area while the major decreasing areas of LULC classes were evergreen forest and miscellaneous land. In addition, the derived LULC prediction of three different scenarios could provide realistic results as expected. Likewise, water yield and sediment retention estimation of three different scenarios could also provide expected results according to characteristics of scenarios’ definitions and climates, soil and terrain, and LULC factors. Finally, LULC of Scenario II was chosen for optimum water yield and sediment retention ecosystem services. In conclusion, the integration of remote sensing technology with advanced classification methods and geospatial models can be used as proficient tools to provide geospatial data on water yield and sediment retention ecosystem services from different scenarios

Above-ground carbon stock and REDD+ opportunities of community-managed forests in northern Thailand

This study aimed to investigate the structure of two deciduous forests and assess their above-ground carbon stock in order to promote community forest management (CFM) for REDD+ opportunities in the Ban Mae Chiang Rai Lum Community Forest in northern Thailand. A systematic sampling method was used to establish twenty-five sample plots of 40 m x 40 m (0.16 ha) each that were used to survey the entire 3,925 ha area of the community forest. Cluster analysis identified two different forest types: dry dipterocarp forest and mixed deciduous forest. It was determined that the above-ground carbon stock did not vary significantly between them. An analysis of carbon sequestration in the community forest indicates that carbon stock increased under CFM from 2007 to 2018 by an estimated 28,928 t C and participation in the carbon market would have yielded approximately US $339,730.43 or US$8.66 /ha/year to the community for that 10-year period. Projections for 2028 reflect that carbon stock will experience continual growth which indicates that maintaining CFM can increase carbon sequestration and reduce CO2 emissions. However, though further growth of carbon stock in the community forest is expected into 2038, that growth would be at a lesser rate than during the preceding decade. This suggests that CFM management should address forest utilization practices with a focus on maintaining long term carbon stock growth. Additional measures to address the impact of drought conditions and to safeguard against forest fires are required to sustain tree species' growth and expansion in order to increase their carbon accumulation potential. Thailand's community forest involvement in REDD+ and participation in its international carbon market could create more economic opportunities for local communities.Y

Ecological Structure of a Tropical Urban Forest in the Bang Kachao Peninsula, Bangkok

Rapid urbanization has changed the structure and function of natural ecosystems, especially floodplain ecosystems in SE Asia. The ecological structure of vegetation stands and the usefulness of satellite images was investigated to characterize a disturbed tropical urban forest located in the Chao Phraya River lower floodplain, Thailand. Nine sample plots were established on the Bang Kachao Peninsula (BKP) within 4 tropical forest types in an urban area: rehabilitation forest, home-garden agroforestry, mangrove and park. The tree habitats were beach forest, swamp forest, moist evergreen forest, dry evergreen forest, mangrove forest and abandoned orchard or home-garden. Normalized difference vegetation index (NDVI) values obtained from Landsat 7 satellite images were correlated with plant structure from field surveys. NDVI had the highest relationship with stand factors for number of families, number of species, Shannon-Weiner index and total basal area. Linear regression predicted well the correlation between NDVI and stand factors for families and basal area. NDVI trends reflected urban tropical forest typing and biodiversity, being high in rehabilitation and mangrove forests, moderate in home-gardens and low in parks. We suggest that the application of NDVI for assessments can be useful for future planning, monitoring and management of the BKP and hence may contribute for increasing biodiversity and complexity of these urban forests