Manta munchies
Dillys will be collecting plankton samples and environmental data around D’Arros island and St. Joseph atoll, where highly resident reef manta rays feed, to quantify the prey density threshold. She will process these samples in the lab and use the biomass data to estimate the prey density threshold; and using the environmental data, she will also identify potential drivers of prey density patterns. This will provide insights on reef manta ray feeding ecology globally.
Dillys Pouponeau
I was raised on Praslin Island, a place of outstanding beauty and biodiversity that birthed me into the nature lover I am today. My passion brought me to many other beautiful islands in the Seychelles, not only to explore but to understand the importance of protecting biodiversity.
Driven to do my part, I pursued a BSc in Environmental Science, specialising in Tropical Biodiversity Conservation, at the University of Seychelles. Since then, I have contributed to several domains in this field, ranging from research, conservation, education, media, and sustainability.
Still very ambitious after working in the field for a few years,...
Estimating the critical prey density threshold of reef manta rays and identifying the potential drivers of prey density patterns around D’Arros and St Joseph atoll in the Seychelles
The aim of this study is to investigate the fine-scale feeding patterns of reef manta rays around D’Arros and St. Joseph atoll
The reef manta ray (Mobula alfredi) is a large, iconic species with great importance for our oceans, balancing zooplankton populations, cycling nutrients, and fertilizing reefs. Despite this, reef mantas are subjected to overfishing, and other pervasive threats that. have contributed to significant declines in their numbers. Globally, they are listed as vulnerable on the IUCN red list of threatened species. In Seychelles, reef mantas have recently been suggested as a candidate for protection through the local Wildlife Protection Bill, with an aim to conserve them and prevent further decline of their populations in our oceans. To protect reef manta rays and maintain their ecological functions, it is essential to primarily understand their ecology through scientific research, to predict how human activities, climate change and habitat alteration may impact them; therefore, guiding future regulation and management.
Reef manta rays are highly selective in choosing when and where they feed, a behaviour influenced by their high metabolic rates, which requires them to consume large quantities of food. This means that reef mantas will only begin feeding once zooplankton densities reach a certain threshold known as the prey density threshold, which is currently unknown for this population here in the Amirantes group of islands in the Seychelles.
Reef manta rays are highly resident to D’Arros island and St. Joseph atoll. During the day, they forage over the reef close to shores, feeding on zooplankton concentrations driven by tides and other factors yet to be understood. Given that this area of study has been designated as a Marine Protected Area, science-based evidence will be required to inform regulations, that will help manage these areas effectively.
By better understanding the various drivers that define feeding thresholds, we can better understand reef manta ray feeding ecology and are thus better able to predict visitation rates and habitat requirements that will help to effectively conserve reef mantas and the habitats they rely on.
The aim of the study is to quantify the critical prey density threshold of reef manta rays around D’Arros and St Joseph atoll in the Seychelles, and to identify the drivers of prey density patterns. To do this, the study will address several specific objectives:
To conduct weekly boat surveys around D’Arros island and part of St. Joseph atoll
To collect plankton samples at different sites and record the respective manta ray behaviour
To record environmental data at the sites sampled
To process plankton samples in the lab and calculate plankton biomass
To use logistic regression model and estimate the prey density threshold
To analyse environmental data and identify drivers of prey density patterns