Cycle 1 (2011 Deadline)
REDD based forest expansion, food consumption, and reduced emissions agricultural policies (REAP) in the Ecuadorian Amazon
PI: Carlos Mena, Universidad San Francisco de Quito (USFQ)
US Partner: Thomas Rudel, Rutgers University
Project Dates: May 2012 - April 2015
Project team members Carolina Sampedro and Alexandra Guevara during fieldwork (Photo courtesy of Carlos Mena).
In tropical forest frontiers, agricultural policies that encourage cultivation increase greenhouse gas emissions, while at the same time forest policies that encourage an expansion in forest cover reduce greenhouse gas emissions but can create risks for food security. Can these contrasting goals be reconciled? This project aims to inform the current debate by proving links between payments for ecosystems services (i.e., Reducing emissions from deforestation and forest degradation or "REDD+") and the production of foodstuffs using emergent silvopastoral landscapes (pasture land with increasing forestation) in the Ecuadorian Amazon. The emergence of these new forested landscapes is viewed by these researchers as both an opportunity for REDD+ due the characteristics of these landscapes as a carbon sink and as a natural experiment to explore the relationship between the expansions of forested landscapes and the production of food.
This project has several interconnected objectives: (1) identifying the extent and drivers of silvopastoral landscapes; (2) identifying food consumption and production patterns and understanding how they are affected by the emergence of silvopastoral landscapes; and (3) developing an emissions profile of peri-urban and urban farmers with an eye towards providing them an equitable distribution from the benefits of REDD+ while providing food security to urban areas. This project will be developed in two main areas of the Ecuadorian Amazon--Coca and Macas--that share key characteristics, including high population growth, high urban expansion, and the emergence of silvopastoral landscapes. However, these two areas are different in several respects. Coca is the center of oil exploration and extraction in Ecuador, and this industry is an important driver of agricultural expansion or land abandonment. Macas, on the other hand, is undergoing agricultural change due to mechanisms of rural-to-urban and international outmigration from agricultural areas. The use of these two areas will provide the opportunity to study processes common to the entire Amazon, where urban growth and the emergence of silvopastoral landscapes occur but due to different factors. To achieve their objectives, the researchers on this project will use a number of methods and techniques, including remote sensing, household surveys, and complex systems modeling. The project should contribute to increasing understanding of the relationship between food production and consumption and should generate a package of recommendations on reduced-emissions agricultural policies for Ecuador and the Amazon in general.
Summary of Recent Activities
The project team continued their research in the summer of 2013, using remote sensing methods to explore land use and land cover patterns in the Northern Ecuadorian Amazon as the main independent variable for statistical models and for carbon emission profiles. The work has been divided in two spatial scales: (a) vegetation indices and (b) high resolution image analysis. On the vegetation side, several indices have been used to characterize the condition of the vegetation and to discriminate different discrete land cover changes, including deforestation. In this project Dr. Mena and his associates are analyzing subtle changes in the forest cover and in agriculture to characterize spatially continuous processes such as forest degradation and forest regeneration. Vegetation indices are likely to be useful, yet so far they are not very well explored. This effort will likely yield a publication in the comparison between the Normalized Difference Vegetation Index (NDVI) and the Fractional Coverage (FC) for subtle changes in forest and agricultural surfaces. The high resolution image analysis aspects of the project are based on the multispectral analysis of spatial high resolution imagery. The images come from the satellite WorldView and have a pixel size of 0.5 – 2 meters. Novel image processing methods are being used, including Object Oriented Image Analysis (OBIA), to classify forested areas in the Amazon. These images can provide very detailed data about forest change, including selective logging and cultivation of coffee, that are very hard to discriminate with traditional remote sensing products (i.e., Landsat). In addition to their research efforts this past quarter, Dr. Mena and his team conducted an outreach activity for a group of indigenous students from the Ethnic Diversity Program at the Universidad San Francisco de Quito who are participating in USFQ’s Social Survey Certificate program. During the training event, the 22 students completed a module on demography of indigenous people in the Ecuadorian Amazon, during which they were exposed to the latest developments regarding the topic. During the fall and winter, Dr. Mena and his group will be organizing a similar training class on geographic information systems for USFQ indigenous students in the Climate Change Certificate program. They will also continue with their remote sensing analysis of land use and land cover change and will design and implement a household survey.
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