Coral reefs around the world are at risk from overexploitation and climate change, and coral reefs of the Red Sea are no exception. Science-based designation of marine protected areas (MPAs), within which human activities are restricted, has become a popular method for conserving biodiversity, restoring degraded habitats, and replenishing depleted populations. The aim of this project was to explore adaptable methods for designing locally-manageable MPAs for various conservation goals near Thuwal in the central Saudi Arabian Red Sea while allowing human activities to continue. First, the potential for using simple spatial habitat distribution metrics to aid in designing MPAs that are well-connected with larval supply was explored. Results showed that the degree of habitat patchiness may be positively correlated with realized dispersal distances, making it possible to space MPAs further apart in patchier habitats while still maintaining larval connectivity. However, this relationship requires further study and may be informative to MPA design only in the absence of spatially-explicit empirical dispersal data. Next, biological data was collected, and the spatial variation in biomass, trophic structure, biodiversity, and community assemblages on Thuwal reefs was analyzed in order to inform the process of prioritizing reefs for inclusion in MPA networks. Inshore and offshore reef community assemblages were found to be different and indicated relatively degraded inshore habitats. These trends were used to select species and benthic categories that would be important to conserve in a local MPA. The abundances of these “conservation features” were then modeled throughout the study area, and the decision support software “Marxan” was used to design MPA networks in Thuwal that included these features to achieve quantitative objectives. While achieving objectives relevant to fisheries concerns was relatively more challenging, results showed that it is possible to design a local MPA that achieves fisheries and biodiversity goals simultaneously. However, future work should focus on expanding the biological dataset and on acquiring socio-economic data in order to formulate a comprehensive local management plan.
| Identifer | oai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/583931 |
| Date | 12 1900 |
| Creators | Khalil, Maha T. |
| Contributors | Berumen, Michael L., Biological and Environmental Sciences and Engineering (BESE) Division, Irigoien, Xabier, Genton, Marc G., Beger, Maria |
| Source Sets | King Abdullah University of Science and Technology |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
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