Quantifying and mapping rates of ecologically-driven sediment production on coral reefs
Tropical coral reef ecosystems sustain not only high levels of biodiversity, but also provide numerous ecosystem goods and services that directly benefit society.
Some of these goods and services are well documented and can be quantified with increasing reliability (e.g., food resource provisioning, coastal protection).
However, far more poorly quantified are rates of carbonate sand production - a process strongly influenced by reef ecology because most reef sediment derives from the fauna and flora living on reefs e.g., as a by-product of parrotfish and urchin feeding, from skeletal organisms such as molluscs and foraminifera, and from carbonate-secreting algae such as Halimeda.
Data on the rates at which these producers generate sediment on reefs is generally sparse, and is especially poorly understood in relationto different types of reef settings that differ in their environmental conditions and reef community composition.
This is a major knowledge gap because the quantity and grade (size) of sedimentary material produced on reefs impacts upon reef growth and is essential for proximal beach and island building.
Project aims and methods
The aim of this project is to parameterise and then apply methodologies for quantifying sediment generation rates, with a specific focus on remote reef-reef islands systems in Western Australia (WA).
The project will build on recent approaches that have piloted methods for quantifying sediment generation based on ecological census approaches (Perry et al. 2015, 2017, 2019), and which have also started to explore the influence of disturbance events on ecologically-driven sand production (Perry et al. 2020).
The student will firstly establish a set of empirical datasets to quantify rates of biological sand production for a range of sediment producing reef species (parrotfish, sea urchins, Halimeda, foraminifera) across a range of both clear-water and turbid reefs of WA (the intention being that this will include sites in Exmouth Gulfand on Ningaloo Reef).
This phase of the project will include testing of AI-based tools to support auto-analysis of reef sediments for quantifying the abundance of common producers groups such as benthic foraminifera. Resultant datasets will then be used to quantify and map reef-level sand generation rates from census data across these sites.
Benthic ecology and environmental conditions (light, turbidity, temperature, wave energy) are known to differ markedly between these reef systems and thus so too, we hypothesise, will rates and sources of reef-derived sediment.
This project will thus add significantly to our currently limited understanding of, and capacity to quantify, rates of ecologically-driven reef sedimentgeneration - data that is needed to support enhanced coastal and reef island vulnerability modelling.