Can Payment for Environmental Services Save the Forest?
The Earth’s climate is changing. Global temperatures have risen at around 0.2°C per decade over the past 30 years, bringing the global mean temperature to the warmest level on record. There is a growing consensus that climate change is a result of greenhouse gases caused by human activity. It is thought that these changes will have effects on morbidity and mortality, and affect human migration.
Tropical deforestation is the second largest source of greenhouse gas emissions, accounting for 20 percent of the world’s carbon dioxide emissions. Reducing emissions from deforestation and degradation (REDD) is considered to be one of the fastest and cheapest ways of reducing carbon emissions.
REDD can be achieved only through changes in how humans interact with the forest. Avoided deforestation (AD) initiatives that attempt to influence these interactions have involved (1) the establishment of protected areas with greater monitoring and enforcement than in unprotected areas; and/or (2) the introduction of payments for environmental services, compensating individuals or communities for undertaking actions that contribute to environmental conservation. The (potential) contribution of reducing tropical deforestation for climate change mitigation depends on the amount of deforestation that is avoided. Despite the promises that AD initiatives hold for reducing CO2 emissions, little is known about how effective they are.
The goal of this project is to investigate the effectiveness of avoided deforestation initiatives. In particular, we will study the case of the Forest Allowance Program—also known as Programa Bolsa Floresta—an AD initiative implemented by the state government of Amazonas in Brazil that pays the local population a monthly allowance for environmental services and increases deforestation monitoring and enforcement. The initiative has so far been implemented in 15 protected areas in an area greater than 10 million hectares.
We will use geographically detailed longitudinal deforestation data constructed from rich satellite imagery to: (1) estimate the impact of the program on deforestation; and (2) investigate the existence of deforestation spillover effects to areas not included in the program.
Silvia Barcellos and Leandro Carvalho