Marine Protected Areas (MPAs) play an important role in protecting and conserving the world’s coral reefs species and communities. Commonly monitoring only takes place at a few locations and models can assist with providing predictions for the entire coral reef system. Developing models to predict the spatial patterns of species at the reef scale, can provide valuable additional information to assist conservation managers further assessing the benefits from existing or future MPAs.
Using a habitat map of Ningaloo reef collected using HyMap airborne hyperspectral imagery, and a set of environmental predictors including sea surface temperature, salinity, chlorophyll, nutrients, dissolved oxygen concentration, and percentage of sediments, I will develop statistical models in R to assess how such variables might drive coral reef species richness and abundance patterns. Coral reef fish data was collected in 2013 by CSIRO across a range of sampling stations along the reef. Specifically, I will test if coral reef fish biodiversity is influenced by changes in environmental variables, and if abundance is directly correlated with specific habitats.
The predictions that will derive from my project will increase our understanding of the spatial distribution of coral reef species at the reef scale. Our results will provide conservation managers with information about the locations on the Ningaloo reef that have the greater number of species which could aid in ensuring marine protected areas are conserving areas of high diversity and significance.