The rate, extent and spatial predictors of forest loss (2000-2012) in the terrestrial protected areas of the Philippines

- Terrestrial protected areas are generally effective in reducing forest loss.
- Some protected areas have phenomenal forest cover loss in terms of extent and rate.
- Spatial predictor variables have weak or no relationships with forest cover.
- Maps included in this study are not reliable inputs for forest loss modelling.
- Assessments at finer spatio-temporal scales are better for conservation planning.

While studies on deforestation of protected areas (PAs) have been conducted in many parts of the world, no comparative study has been done over an entire country in the tropics. Thus, we conducted a country-wide assessment of forest cover loss in all terrestrial protected areas of the Philippines, covering 198 PAs with a total area of 4.68 million ha. This study utilised Hansen's Landsat-derived global maps of forest cover change from 2000 to 2012, with tree canopy cover data for 2000 as the base year. Correlation and logistic regression analyses were employed to determine the significance and magnitude of the relationships between forest cover and 11 predictor variables. The assessment of forest loss reveals that the terrestrial protected areas are generally effective in reducing forest loss. Over the 12-year period, the average rate (2.59%) of forest clearing in protected areas is marginally lower by 0.1% than the entire country (2.69%). Within the same duration, the average forest loss rate within the 2-km buffer zones of selected protected areas is 1.4 times of those inside PAs. However, there was a significant number of PAs with phenomenal forest cover loss in terms of extent (48,583 ha over 12 years) and rate (up to 21%). We found that spatial predictor variables included in this study have weak or no relationships with forest cover, and hence they are not reliable inputs for predictive modelling. Comprehensive assessments of deforestation are needed at the micro-scale (e.g. single PA level) level and relatively shorter historical timeframe (e.g. less than a decade), to generate useful information for policy formulation, planning, and management.