RESUMO

Effectively implementing landscape-scale forest restoration on the ground is particularly challenging. Available decision-support tools particularly lack the ability to comprehensively incorporate biophysical, social and institutional dimensions in a spatially explicit manner from the pixel to the whole landscape. In order to contribute to fulfilling this gap, this paper has two major objectives. The first is to present a spatially explicit decision-support tool for mapping Forest Restoration Vocation (FRV) that includes socio-economic and institutional aspects in forest landscape restoration. The second is to discuss the ways in which the FRV has been applied in the Brazilian decision-making context. The FRV was used to prioritize areas for three different restoration modalities: assisted natural regeneration (passive restoration), forest plantation with native trees to conserve biodiversity and forest plantation for agroforestry systems (active restoration). The FRV is already being adopted as a planning tool to invest R$ 1.2 billion (approx. US$ 300 million) to restore 40,000 ha in the Rio Doce, Brazil-an area corresponding to 0.05% of the area of watershed. Due to the high level of degradation of the basin, there is a need to restore 1.6 Mha via forest plantations in riparian Areas of Permanent Preservation (APPs) while 30% of APPs can be effectively restored using natural regeneration. The FRV can be effective for gauging progress and monitoring forest restoration implementation metrics across the landscape and through time. There are however still problems in effectively assessing if the investment in forest restoration will generate impact in the long term and deliver the ecosystem services society depends on.