Geosimulation of riverine type mangrove in Palawan, Philippines using cellular automata - Manalili, Michael Andrew G.
Mangroves of the Philippines has been in a hotspot due to rapid decrease in the extent as a result of combined environmental, anthropogenic and socio-economic stresses at the local, landscape, and regional levels. Although there had been numerous rehabilitation efforts by the government, still there was a failure in understanding and implementation of site-species suitability for mangrove rehabilitation and majority of mangrove rehabilitation in the Philippines has failed. Palawan province has long been known as the Philippines' biodiversity hotpot for mangroves. The dynamic interactions of man and environment from upland to coast has made it more difficult to implement single solution in addressing coastal issues. Many environmental models have been developed to understand processes that are unique in space and in time. However, information is lost in transition when studying high temporal phenomena and spatial details are generally aggregated. This study focused on identifying geomorphologic and bioclimatic variables that is highly correlated with mangrove area on a regional scale using 183 catchment areas for the mainland Palawan. A statistical random forest regression model revealed that geomorphologic variables (i.e., extent of tidally inundated floodplain, main river channel width, presence of neighbouring mangroves, and main river channel length) correlates to 67% of the variability in mangrove extent. The same model also revealed that longitudinal position of mangrove, precipitation during wettest month, and area of agriculture within the watershed correlates to 50.49% of the regional variability of mangrove decline based on a 24-year mangrove observations. Geosimulation using Cellular Automata approach was implemented in this study to model spatially explicit interactions of different land uses within the watershed which captured spatial and temporal interactions of six land uses. Event-based Markov chain model was able to simulate temporally dynamic land use transitions as to how the mangroves are affected by land use allocations. Finally, local geosimulation model presented multiple future scenarios and use cases of mangrove mortality and growth which implements spatial and time-dependent parameters that mimics both natural and spatial patterns and processes. The modelled projection for the state of mangrove in Iwahig, Bataraza mangrove is threatened to be more fragmented if no immediate local and holistic interventions are implemented.