Geographical distribution of red and green Noctiluca scintillans

The dinoflagellate Noctiluca scintillans is one of the most important and abundant red tide organisms and it is distributed world-wide. It occurs in two forms. Red Noctiluca is heterotrophic and fills the role of one of the microzooplankton grazers in the foodweb. In contrast, green Noctiluca contains a photosynthetic symbiont Pedinomonas noctilucae (a prasinophyte), but it also feeds on other plankton when the food supply is abundant. In this review, we document the global distribution of these two forms and include the first maps of their global distribution. Red Noctiluca occurs widely in the temperate to sub-tropical coastal regions of the world. It occurs over a wide temperature range of about 10°C to 25°C and at higher salinities (generally not in estuaries). It is particularly abundant in high productivity areas such as upwelling or eutrophic areas where diatoms dominate since they are its preferred food source. Green Noctiluca is much more restricted to a temperature range of 25°C–30°C and mainly occurs in tropical waters of Southeast Asia, Bay of Bengal (east coast of India), in the eastern, western and northern Arabian Sea, the Red Sea, and recently it has become very abundant in the Gulf of Oman. Red and green Noctiluca do overlap in their distribution in the eastern, northern and western Arabian Sea with a seasonal shift from green Noctiluca in the cooler winter convective mixing, higher productivity season, to red Noctiluca in the more oligotrophic warmer summer season.

Macrofauna along the Sudanese Red Sea coast: potential effect of mangrove clearance on community and trophic structure

Mangroves along the Sudanese Red Sea coast are under constant anthropogenic pressure. To better understand the influence of mangrove clearance on the intertidal benthic community, we investigated the composition, biodiversity and standing stock of the macrofauna communities at high-, mid- and low-water levels in three contrasting habitats: a bare sand flat, a cleared mangrove and an intact mangrove. In addition, a community-wide metric approach based on taxon-specific carbon and nitrogen isotope values was used to compare the trophic structure between the three habitats. The habitats differed significantly in terms of macrofaunal standing stock, community composition and trophic structure. The high- and mid-water levels of the intact mangroves showed a distinct macrofaunal community characterized by elevated densities and biomass, largely governed by higher decapod and gastropod abundances. Diversity was similar for cleared and intact mangroves, but much lower for the bare sand flat. Community-wide metrics indicated highest trophic diversity and community niche breadth in the intact mangroves. Differences between the cleared and intact mangroves can be partly attributed to differences in sediment characteristics resulting from mangrove clearance. These results suggest a significant impact of mangrove clearance on the macrofaunal community and trophic structure. This study calls for further investigations and management actions to protect and restore these habitats, and ensure the survival of this ecologically valuable coastal ecosystem.

Exploring the Red Sea seasonal ecosystem functioning using a three-dimensional biophysical model

The Red Sea exhibits complex hydrodynamic and biogeochemical dynamics, which vary both in time and space. These dynamics have been explored through the development and application of a 3-D ecosystem model. The simulation system comprises two off-line coupled submodels: the MIT General Circulation Model (MITgcm) and the European Regional Seas Ecosystem Model (ERSEM), both adapted for the Red Sea. The results from an annual simulation under climatological forcing are presented. Simulation results are in good agreement with satellite and in situ data illustrating the role of the physical processes in determining the evolution and variability of the Red Sea ecosystem. The model was able to reproduce the main features of the Red Sea ecosystem functioning, including the exchange with the Gulf of Aden, which is a major driving mechanism for the whole Red Sea ecosystem and the winter overturning taking place in the north. Some model limitations, mainly related to the dynamics of the extended reef system located in the southern part of the Red Sea, which is not currently represented in the model, still need to be addressed.

Regional ocean-colour chlorophyll algorithms for the Red Sea

The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing.