This study was conducted to assess the species diversity and carbon sequestration potential of a natural mangrove stand in Botoc, Pinabacdao, Samar, the Philippines. Using the quadrat sampling technique, 12 plots with a size of 100 m 2 were established to facilitate inventory and measurement of trees. Shannon-Wiener index and allometric equations were used to determine species diversity, and biomass and tree carbon storage, respectively. The community's species diversity (H 0 ¼ 1.6365) was very low with a total of eight true mangrove species recorded, dominated by Avicennia officinalis with an importance value of 134.80%. Among the plots, a greater percentage of the total biomass was accounted to the aboveground biomass, corresponding to 74% (297.20 t ha À1 ), while the remaining 26% (103.87 t ha À1) was credited to the root biomass. The total carbon sequestered and stored in the biomass of the natural mangrove stand was 188.50 t C ha À1 equivalent to 691.81 t CO 2 ha À1 . The biomass and carbon density estimates acquired in this study suggest that natural mangrove forests in Botoc have the potential to sequester and store a huge amount of atmospheric carbon regardless of the very low species diversity.

The integrated remote sensing (RS) and geographic information system (GIS) approach was utilized in this study to classify land use and land cover (LULC), detect changes based over time, and identify transition trends in the Marikina subwatershed, Laguna de Bay watershed, Philippines. Landsat 5 Thematic Mapper (TM) imageries acquired in 1999 and 2006 were pre-processed and classified using a supervised classification technique with maximum likelihood classifier algorithm in RS and were used to develop maps of the sub-watershed and sub-subwatershed levels in a GIS platform. LULC change analysis revealed that, from 1999 to 2006, significant changes occurred in the sub-watershed as indicated by the increase of agricultural (11.76%) and orchard (4.52%) areas at the expense of brushland (16.56%) areas. Other LULC such as water bodies, built-up, forest, and grassland remain almost unchanged. In the sub-subwatershed level, Tayabasan experienced minimal change, whilst Tanay had the most transitions. Overall accuracy and kappa statistics were then derived using the confusion matrix, which resulted in 96.15% and 95.49% for 1999 imagery, and 93.82% and 92.73% for 2006 imagery, respectively. LULC persistence and transition trends were analyzed using land change modeler, while the Markov chain model has been utilized to predict the LULC distribution in 2020 pertinent to rates of change from 1999 to 2006. This study contributes not only to the understanding of the past and present landscape of the sub-watershed, but also provides an idea of the areas that need rehabilitation for the formulation of suitable mitigation measures and strategies toward the sustainable management of the sub-watershed.

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