Prospecting the potential of ecosystem restoration: A proposed framework and a case study

Resumo

Projects focusing on the restoration of degraded ecosystems have to be financially appealing, spatially multiscaled, and ecologically efficient. Considering such premises, a model was elaborated to assess the locals in relation to the kind of management to be adopted (conservation or restoration) and, for locals indicated for restoration, the kind of restoration to be adopted (assisted or passive). Furthermore, we propose a set of ecologically-based alternatives at medium-and local-scaleto assist the restoration of areas considered unsuitable for passive restoration. Such techniques are: install artificial connectors among forest fragments near each other, or, for areas where forest fragments are far each other, install nucleation techniques, revitalization of concrete-lined urban rivers, and the control of erosion and invasive plant species. We tested the potential of our model through a case study carried out in Sorocaba, Sao Paulo State, Brazil. The study area is predominantly occupied by pasture lands, but urbanization also is an important land cover category. There are 661 forest fragments, being 25 of them larger than 50 ha. From the area considered non-habitat, i.e., modified due to human usage, 35.5% of the total study area and 45.5% of the study area classified as non-habitat is suitable for passive restoration, and the rest of the area needs is suitable only for assisted restoration techniques. We verified that the facility and low cost of installation are advantageous features of such techniques and the results obtained by mean of application of the assisted techniques indicate that the alternatives tend to accelerate the process of establishing connectivity of the landscape in locals devoid of connections.

Descrição

Palavras-chave

Assisted restoration, Ecological restoration, Environmental degradation, Landscape connectivity, Multi-scale model, Passive restoration

Como citar

Ecological Engineering. Amsterdam: Elsevier Science Bv, v. 108, p. 505-513, 2017.