Fully-funded PhD: Molecular Applications for Malagasy Fish (MAppFish): Developing a rapid, cost-effective method for mapping distributions of freshwater fish in a global biodiversity hotspot

Madagascar is a globally important biodiversity hotspot, home to hundreds of endemic species.  At juxtaposition with this rich natural heritage is a growing human population and a poverty rate that is amongst the highest in the world, putting immense pressure on Madagascar’s natural resources. All but one freshwater Malagasy fish is endemic to the island. At the same time, fish is a vital source of dietary protein, and fish provision is supplemented by farming non-endemic species like highly invasive tilapia. Consequently, Malagasy freshwater fish face many threats from habitat degradation and loss, to overexploitation and competition from invasive species. 

The absence of routine/standardised monitoring in Madagascar’s freshwaters makes identifying and prioritising conservation action especially challenging. Conventional survey methods, such as direct observation or trapping, require a significant time and effort, can be damaging to habitats and target species, and can yield biased samples. This project aims to develop a low-cost, field-based, portable and easy-to-use lab-on-a-chip (LOC) device for environmental DNA monitoring of freshwater species, which would facilitate greater spatial and temporal sampling of freshwater fishes in Madagascar. This project has a direct conservation impact, providing data to support the sustainable management of fisheries for biodiversity and human communities. 

Project aims and objectives

The project will develop biotechnological tools to facilitate the conservation and sustainable management of Malagasy freshwater fishes, structured around the following objectives:

• Develop an LOC method for application on freshwater fishes in Madagascar.
• Use the LOC to map the freshwater fish distributions in Madagascar, including threatened, invasive and human food species.
• Create predictive models of target species distributions by combining species presence/absence with environmental data to predict wider-scale fish distribution and identify niches.
• Use data and models to identify: 
  • Additional species for Red Lists.
  • New protected sites.
  • Sites for reintroductions or other conservation action.