A comparison between an existing ad hoc MPA and a prioritization model using the decision support tool Marxan

Detalhes bibliográficos
Ano de defesa: 2021
Autor(a) principal: Vieira, Natália Brandão
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal do Espírito Santo
BR
Mestrado em Biologia Animal
Centro de Ciências Humanas e Naturais
UFES
Programa de Pós-Graduação em Ciências Biológicas (Biologia Animal)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufes.br/handle/10/15462
Resumo: Marine Protected Areas (MPAs) have been a broadly used strategy to ensure ecosystem and biodiversity conservation. However, the adoption of ad hoc frameworks in the designing process of MPAs networks have been narrowing down their capacity of conservation by selecting non representative areas where exploitation is restrained and there is least need for protection. In this sense, advances in the Marine Spatial Planning field have led to development of specific decision support tools that help in the Systematic Conservation Planning (SCP) process, which have been demonstrated satisfactory outcomes for selecting priority areas for conservation. This study makes a comparison between an existing MPA, created in an ad hoc context, located in an economically and ecologically important region in South Eastern Brazil, and a prioritization model developed with the software Marxan as an SCP exercise in the same area, using benthic habitats as surrogates of biodiversity. The results showed that the current MPA fails in meeting conservation features’ targets of most of the habitats used as surrogates of biodiversity and does not include any portion of mesophotic reefs representation. Additionally, this perimeter is the region with higher conservation costs for fisheries, which may interfere with the effectiveness of the MPA. On the other hand, the best solution provided by the model is a selection of areas that in the same time meets the conservation features’ targets while aiming at planning units with the least possible conservation costs for fisheries. The results also include a map of the selection frequency of each planning unit, giving flexibility to possible conservation measures adopted. Despite restrictions that using habitats as surrogates for biodiversity and their respective arbitrary targets may bring, the results indicate important areas for more representative conservation measures for the marine region, besides providing a model organized to receive new data regarding ecological and economic matters. This way, it is possible to achieve an efficient SCP for the local biodiversity, with the proper discussions between stakeholders, so that they avoid conflicts in use, and at the same time maintain environmental sustainability.