||Approximately 13 million hectares of tropical forests are cut down annually, contributing
12-20% of global greenhouse gas emissions. REDD+ (Reduction in Emissions from Deforestation
and Degradation) is designed to tackle this challenge by providing economic incentives
for conservation, restoration and sustainable management of forests. In addition to
emissions reductions, REDD+ also has the capacity to deliver co-benefits including
biodiversity conservation and rural development by conserving species-rich forests
and providing poor forest communities with alternative livelihoods. The Philippines,
a biodiversity hotspot with the seventh highest deforestation rate in the world seeks
to maximize these co-benefits during project planning and site selection. The 2010
Philippine National REDD-plus Strategy outlines the rationale for targeting project
sites, however, a national-scale spatial prioritization assessment has yet to be conducted.
This study performs a multi-attribute utility theory (MAUT) analysis using five environmental
and socio-economic indicators (carbon stocks, deforestation rate, biodiversity, indigenous
community areas, and poverty incidence). The model is then applied in geographic information
system (GIS) to spatially identify potential priority areas (by province and municipality)
for REDD+ investment in the Philippines. Having a clear, publicly available prioritization
method ensures that REDD+ funds are allocated efficiently, and that the overall environmental
and social objectives of the program are being effectively conveyed on the ground.
It can also provide informed accounting of the trade-offs made between carbon, co-benefits
The results from the MAUT decision framework and subsequent spatial analysis show
four geographic scenarios coinciding with various possible stakeholder priorities.
Areas with high utility scores were located primarily in the uplands, with some scenarios
overlapping with the existing REDD+ pilot sites. While carbon, biodiversity and socioeconomic
indicators proved to be spatially correlated, deforestation rates were not and thus
require higher trade-offs. Additional, more detailed maps and studies on indicators
are needed for the Philippines, however, this spatial prioritization assessment represents
a compilation of the best available data and can be used as a stepping stone and resource
until more robust analyses can be completed.