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Authors:
Fernanda Tubenchlak, Camila Islas, Vinicius Pacheco, Maria Vitória Palhares, Nathalia Dreyer, Renato Crouzeilles, Bernardo Baeta Neves Strassburg, Carlos Alberto de Mattos Scaramuzza
Publication Date:
2021
Abstract/Summary:
To achieve large-scale global restoration commitments, it is necessary to restore areas at an unprecedented pace. To prepare local stakeholders for implementing restoration projects in target areas, it is important to conduct an assessment of the restoration value chain and estimate the expected impacts of such additional demand. We developed a comprehensive study of the restoration value chain in the region of the Central Fluminense Mosaic, located around metropolitan Rio de Janeiro, in the Brazilian Atlantic Forest hotspot. Our study combined multiple methods (e.g. literature review, interviews, workshop with local stakeholders and experts, spatial and economic analyses) divided in three phases: (i) diagnosis of the region and restoration activities; (ii) development of restoration models; and (iii) economic evaluation of the large-scale implementation of proposed models in the value chain. We estimated that, to comply with Brazilian environmental laws, the rural properties of the region need to restore 60 thousand hectares of forest. Thus, we proposed nine restoration models considering multiple socioecological aspects of the areas that should be restored, including different restoration methods and agroforestry options. Our financial analysis showed that agroforestry-based restoration models and the consideration of natural regeneration potentials can increase cost-effectiveness and leverage large-scale restoration. Implementing all the proposed models to achieve legal compliance could represent an inflow of U$ 1.5 billion in the local economy. Specifically, agroforestry-based restoration could offer more than 4.2 million tons of food and 2.4 million m³ of wood, adding U$ 904 million in products, contributing to increase food security.
Resource Type:
Conference Presentation, SER2021
Pre-approved for CECs under SER's CERP program
Source:
SER2021