Renata de Toledo Capellão^*, Luiz Gustavo Oliveira, Diogo Rocha, Clarice Braúna Mendes, Viviane Dib, Mariana Iguatemy, Helena Alves

r.capellao@iis-rio.org

Instituto Internacional para Sustentabilidade – IIS, Rua João Borges, 215 – Gávea, 22451-100, Rio de Janeiro/ RJ, Brazil.

Large-scale ecological restoration is a cross-cutting pathway to deliver benefits for biodiversity, climate, and water security. Brazil’s updated National Plan for Native Vegetation Recovery (Planaveg 2025–2028) adopts spatial intelligence to guide restoration towards areas of highest impact, while halving associated costs. Here, we present the methodological framework and preliminary results of a nationwide prioritization that integrates ecological and socio-economic criteria, along with feasibility and cost factors, to rank all restoration-eligible areas across Brazilian biomes at 1 km resolution. Input data include multiple spatially explicit layers representing the relative contribution of restoration to biodiversity gains, climate change mitigation, water resources improvement, and socio-economic returns, in addition to the implementation and opportunity costs associated with restoration process. Prioritizations were conducted independently for each biome, with model parameters and benefit weights adjusted according to expert recommendations gathered in technical workshops. For each biome, two sets of scenarios are reported: (i) Maximum Benefits Scenario, pointing areas targeting optimal return for benefit criteria and (ii) Cost-effective Scenario, that identifies areas that present higher cost-benefit relationship. For each scenario, the framework delivers a restoration-priority ranking map by ordering all planning units until 100% of restorable areas are classified, yielding a biome-level priority gradient in 5%-point steps (20 classes). Additionally, optional spatial constraints by state and Otto level-2 basins were analyzed to ensure territorial representation. This cumulative ranking allows us to quantify stepwise gains as a function of total area restored and to assess the incremental ecological return of alternative strategies. Results deliver a transparent, reproducible decision surface that identifies where restoration can most efficiently improve biodiversity and ecosystems benefits while revealing trade-offs once implementation and opportunity costs are considered.

Keywords: linear programming; spatial prioritization, ecosystem restoration

References: MINISTÉRIO DO MEIO AMBIENTE E MUDANÇA DO CLIMA (MMA). DEPARTAMENTO DE FLORESTAS, SECRETARIA DE BIODIVERSIDADE, FLORESTAS E DIREITOS ANIMAIS (DFLO/SBIO). Plano Nacional de Recuperação da Vegetação Nativa (Planaveg) 2025-2028: Sumário Executivo – 1ª edição. Brasília: MMA, 2024. 8 p. 

 
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