COMPARISON BETWEEN AN EXISTING ADHOC MARINE PROTECTED AREA (MPA) AND A MARXAN PRIORITIZATION MODEL
Name: Natalia Brandão Vieira
Type: MSc dissertation
Publication date: 01/10/2021
Advisor:
Name |
Role |
|---|---|
| Agnaldo Silva Martins | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| Agnaldo Silva Martins | Advisor * |
| Brandon P. Anthony | External Alternate * |
| Hudson Tercio Pinheiro | External Examiner * |
| João Batista Teixeira | Co advisor * |
| Tamara Steger | External Examiner * |
Summary: Marine Protected Areas 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, the use of Marine Spatial Planning with the support of Systematic Conservation Planning and the use of decision support tools such as Marxan have been demonstrated satisfactory outcomes for selecting priority areas for conservation. This study makes a comparison between an existing MPA in an economically and ecologically important region in South Eastern Brazil and a prioritization model developed with Marxan as a conservation exercise in the same area. 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 an area 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 most selected spots when considering priority for conservation with the least possible socioeconomic cost, giving flexibility to the model. This way, it is possible for decision makers to lead discussions with stakeholders, incorporate new data regarding ecological and economic matters to the model, so that they avoid conflicts, and at the same time maintain environmental sustainability.
