Despite the increases in the intensity and frequency of disturbances on coral reefs in the Red Sea over the past decade, patterns of variability in fish communities are still poorly understood. This study aims to contribute to a better understanding of how fish communities vary along multiple spatial scales (10-100’ of kilometers) and to provide a baseline for future comparisons, fundamental to assess responses to climate change and other disturbances. Coral reefs along the Saudi Arabian Red Sea coast were surveyed from 2017 to 2019. The reefs ranged from 28° N to 18 °N and were categorized according their geographical location and grouped within three regions, namely north (24-28.5°N; 12 reefs), central (20.4-22.3°N; 11 reefs), and south (18.5-21.2°N; 30 reefs). The quantification of spatial patterns was conducted based on both taxonomic- and trait-based approaches. Considering the dependence of fish communities on the benthic habitat the relationship between different attributes of the fish assemblages and coral cover was also investigated. A consistent pattern of separation between assemblages of the northern and central region from the ones in the south was observed in nearshore reefs but was not evident for offshore reefs. The southern region supported higher densities, biomass, and species richness than the other two regions. The analysis showed that transect and reef scales contributed to the greatest variation in fish communities, suggesting higher levels of variability within small spatial scales. Several parameters of the fish community (total species, total density, total biomass, total functional entities, functional richness, functional redundancy) were positively correlated to coral cover, particularly in the northern region. Responses were not consistent across the Red Sea basin, suggesting that management plans should be regionally based. This study can be helpful to design management strategies as it provides a current baseline from both taxonomic and trait perspectives for Red Sea reefs that can be used to evaluate future changes due to natural and human-based disturbances.
|Date made available
|KAUST Research Repository