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Incorporating resilience and cost in ecological restoration strategies at landscape scale

Maurício Stefanes, Faculdade de Ciências Biológicas e Ambientais - FCBA/UFGD - Brazil; Programa de Pós-Graduação em Ecologia e Conservação, Campo Grande - MS/Brazil
Jose Manuel Ochoa-Quintero, Programa de Pós-Graduação em Ecologia e Conservação, Campo Grande - MS/Brazil; Corporación para Investigaciones Biológicas, Medellín, Colombia
Fabio de Oliveira Roque, Programa de Pós-Graduação em Ecologia e Conservação, Campo Grande - MS/Brazil; Centre for Tropical Environmental and Sustainability Science, College of Science and Engineering, James Cook University, Cairns, Australia
Larissa Sayuri Moreira Sugai, Instituto de Biociências, UNESP - Univ Estadual Paulista, Rio Claro, Departamento de Ecologia, Programa de Pós-Graduação em Ecologia & Biodiversidade, São Paulo, Brazil
Leandro Reverberi Tambosi, Departamento de Ecologia, Universidade de São Paulo, São Paulo, Brazil; Centro de Engenharia, Modelagem e Ciências Sociais Aplicadas, Universidade Federal do ABC, Santo André, Brazil; Ecology, Evolution and Environmental Biology, Columbia University, New York, USA
Reinaldo Lourival, Programa de Pós-Graduação em Ecologia e Conservação, Campo Grande - MS/Brazil; Nature and Culture International, Del Mar, California, USA
Susan Laurance, Centre for Tropical Environmental and Sustainability Science, College of Science and Engineering, James Cook University, Cairns, Australia

DOI: http://dx.doi.org/10.5751/ES-08922-210454

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Abstract

The restoration of deforested or degraded areas can contribute to biodiversity conservation and global resilience given the current and projected impacts of climate change. In recent years, a robust array of ecological restoration frameworks have been generated to address restoration challenges at large scales in different ecosystems around the world. Unfortunately, the costs associated with restoration at such scales greatly challenges the implementation of such frameworks. We used landscape ecology principles with multicriteria optimization of landscape resilience and agricultural productivity as a way to mitigate the trade-offs between production and restoration. We used the Cerrado biome in Mato Grosso do Sul State, Brazil, as a case study to apply our framework. We compared three scenarios: minimal legal compliance (MLC); selection by ecological resilience (SER); and selection by restoration cost (SRC). Our results show that increasing the restoration target from MLC (25%) to SER (30%) means moving from 968,316 to 1592 million hectares, which can represent a huge opportunity cost for agricultural lands. However, because costs and resilience are not homogeneously distributed throughout landscapes, we can select areas of intermediate ecological resilience and low cost, for the same restoration area target. This process can reduce potential conflicts and make restoration a more viable process. Our results also reveal some areas that can be particularly important for reconciling agriculture and landscape restoration. Those areas combined high and intermediate resilience and an above average profitability. This could mean that increasing restoration in this area could be very expensive, assuming that our proxy roughly represents the restoration implementation cost. However, there is another important message here, that some areas can be productive at the same time that they maintain levels of resilience above the legal compliance, which facilitates win-win scenarios in human-dominated landscapes.

Key words

decision-making tool; ecological resilience; fragmentation; opportunity cost; prioritization restoration; restoration costs; trade-off analysis

Copyright © 2016 by the author(s). Published here under license by The Resilience Alliance. This article  is under a Creative Commons Attribution-NonCommercial 4.0 International License.  You may share and adapt the work for noncommercial purposes provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.

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