A Framework to Optimize Biodiversity Restoration Efforts Based on Habitat Amount and Landscape Connectivity

Authors

  • Leandro R. Tambosi,

    Corresponding author
    1. Departamento de Ecologia, Instituto de Biociências, Universidade de São Paulo, Rua do Matão, nº 321 travessa 14, CEP 05508-090, São Paulo, SP, Brazil
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  • Alexandre C. Martensen,

    1. Departamento de Ecologia, Instituto de Biociências, Universidade de São Paulo, Rua do Matão, nº 321 travessa 14, CEP 05508-090, São Paulo, SP, Brazil
    2. Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON M5S 3G5, Canada
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  • Milton C. Ribeiro,

    1. Departamento de Ecologia, Universidade Estadual Paulista, Av. 24-A, 1515, Bela Vista, CEP 13506-900, Rio Claro, SP, Brazil
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  • Jean P. Metzger

    1. Departamento de Ecologia, Instituto de Biociências, Universidade de São Paulo, Rua do Matão, nº 321 travessa 14, CEP 05508-090, São Paulo, SP, Brazil
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Abstract

The effectiveness of ecological restoration actions toward biodiversity conservation depends on both local and landscape constraints. Extensive information on local constraints is already available, but few studies consider the landscape context when planning restoration actions. We propose a multiscale framework based on the landscape attributes of habitat amount and connectivity to infer landscape resilience and to set priority areas for restoration. Landscapes with intermediate habitat amount and where connectivity remains sufficiently high to favor recolonization were considered to be intermediately resilient, with high possibilities of restoration effectiveness and thus were designated as priority areas for restoration actions. The proposed method consists of three steps: (1) quantifying habitat amount and connectivity; (2) using landscape ecology theory to identify intermediate resilience landscapes based on habitat amount, percolation theory, and landscape connectivity; and (3) ranking landscapes according to their importance as corridors or bottlenecks for biological flows on a broader scale, based on a graph theory approach. We present a case study for the Brazilian Atlantic Forest (approximately 150 million hectares) in order to demonstrate the proposed method. For the Atlantic Forest, landscapes that present high restoration effectiveness represent only 10% of the region, but contain approximately 15 million hectares that could be targeted for restoration actions (an area similar to today's remaining forest extent). The proposed method represents a practical way to both plan restoration actions and optimize biodiversity conservation efforts by focusing on landscapes that would result in greater conservation benefits.

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