Melissa has a BS in environmental science and policy from University of Maryland, and a MS in marine science from California State University, Monterey Bay. Her MS thesis was entitled 'Effects of land-based sources of pollution on coral thermotolerance' and examined how pollution affects Acropora hyacinthus heat tolerance in American Samoa. She also examined how both pollution and heat stress affected the algal symbiont community, and coral host gene expression.

PhD in Environment, Science, and Management

2022 to 2025

Project Description

This project aims to classify variation in heat tolerance traits of a widespread tabular coral, Acropora hyacinthus, along the Great Barrier Reef (GBR) and identify potential drivers of that variation including environment, endosymbiont, and genetic variation. I also aim to identify genetic markers of coral heat tolerance and build genomic prediction models that can be used to select candidates for coral propagation programs.

Project Importance

This PhD project is important to monitor existing variation in heat tolerance across the GBR, which is useful to identify reefs or individuals which may be most resilient to climate warming. This work may inform conservation programs interested in reefs or areas with especially heat tolerant corals that require additional protections, or may inform more active restoration-focused work. Identifying environmental and genetic drivers or correlates of heat tolerance may be useful to coral propagation programs that aim to rapidly adapt corals to climate warming by breeding especially heat tolerant parents.

Project Methods

Heat tolerance traits are generated from non-invasive image-based metrics including imaging-PAM and hyperspectral data. Endosymbiont communities are quantified using ITS2 metabarcoding and environmental variables are computed from repositories such as eReefs, NOAA CoRTAD, and NASA MODIS. Machine learning algorithms are generated to identify important drivers of heat tolerance across the GBR. Coral genomes are sequenced using shallow whole genome sequencing and genomic markers are identified using a genome wide association study (GWAS). Genomic prediction using best linear unbiased prediction is performed to generate models that predict heat tolerance traits based on variation across thousands of sites on the genome.

Project Results

Preliminary results show a wide range of heat tolerance trait values both across and within reef sites. Variation in heat tolerance traits vary with environmental variables such as climatology. For example, absolute thermal thresholds are highest on warmer reefs while heat tolerance above local climatology is greatest on more temperate reefs.

Keywords

Algae,
Biostatistics,
Climate change,
Controlled Environment,
Coral reefs,
Corals,
Distribution,
Ecology,
Field based,
Genetics,
Human use,
Management tools,
Manipulative experiments,
Marine planning,
Modelling,
Molecular techniques,
Monitoring,
Natural disturbance,
Ocean warming,
Physiology,
Pollution,
Quantitative marine science,
Remote Sensing,
Temporal change