Marine Lechene - AIMS@JCU

Marine Lechene

marine.lechene@my.jcu.edu.au

Recipient of an AIMS@JCU Scholarship

PhD
ARC Centre of Excellence Coral Reef Studies

Marine Lechene

marine.lechene@my.jcu.edu.au

PhD
ARC Centre of Excellence Coral Reef Studies
Identifying key indicators to quantify ecological recovery and adaptation of coral reefs across space and time

Marine Lechene is from New-Caledonia and studied in France and Australia. She completed her Bachelor's in Biology and Ecology from The University of Montpellier (France) and Master's in Marine Science and Management from The University of Sydney (Australia).

Identifying key indicators to quantify ecological recovery and adaptation of coral reefs across space and time

2021 to 2025

Project Description

Intensification of disturbance frequency and strength due to climate change is pushing coral reef ecosystems outside their adaptive range. The effects of main disturbances (warming, storms, crown-of-thorn outbreaks) on coral reef composition and coral cover have been described, but the drivers of recovery and adaptation to disturbances are yet to be investigated. This project will use innovative and cost- efficient marine observing technologies and assessment methods over large spatial and temporal scales to investigate intra and inter-reefal variation of key indicators of reef recovery and adaptation. In turn, these results will develop predictive models and inform potential restoration initiatives to enhance management of coral reef ecosystems.

Project Importance

Coral reefs are under pressure from global climate change and local human activities. As we progress in the Anthropocene, disturbances (warming, storms, or coral predator outbreaks) will push coral reef ecosystems outside their adaptive range and force organisms to cope with environmental change to survive into the future.
Our current understanding of how environmental and spatial conditions facilitate natural reef recovery remains limited. With environmental change predicted to continue, it is critical to determine the key drivers of adaptation and uncovering potential trade-offs between resistance and speed of recovery from disturbance. Tracking and predicting coral reef ecosystem futures is important to increase the success and cost-effectiveness of management, conservation and restoration programs.

Project Methods

The study sites will be organised in reef clusters along the geographical extent of the Great Barrier Reef. Each cluster will comprise three reefs, and each reef will have three different sites to capture different habitats. Within one site, multiple plots will be mapped in 3D at mm resolution by photographing the reef substrate. Images will be processed with off-the-shelf software using structure-from-motion algorithms to build 3D and 2D reconstructions of the transects. 3D and 2D maps will be used to extract data on benthic diversity, community composition and seascape geomorphology. Plots will be geotagged to allow comparisons over time to obtain rates of change (e.g. coral growth rate). Biophysical data (temperature, light, pH and water flow) will be collected at every site using EcoRRAP oceanographic instruments. This newly acquired dataset will be complemented by existing photo transect data from the AIMS Long Term Monitoring Program and Marine Monitoring Program to understand temporal dynamics and disturbance history of the reef clusters over the last 30 years.
To understand and quantify recovery and adaptation, a literature review and meta- analysis will be undertaken and existing data will be used to select and compare key indicators of reef recovery and adaptation across depths/habitats/reefs/clusters. Key indicators of recovery and adaptation may include (1) coral species, (2) functional diversity, (3) coral cover in 2D and 3D, (4) coral survival and (5) growth of several taxa, the exact metrics will be determined at the end of chapter 1. Landscape metrics (depth, orientation, structural complexity, depth, patchiness, spatial location of coral colonies) will be extracted from existing long-term dataset and measured either in situ or from the 3D maps, while biophysical variables (water flow, wave exposure, light, etc.) will be extracted from existing long-term dataset and measured in situ and/or modelled.
Coral diversity and composition will be quantified from 2D maps (from new and existing data) by digitising and annotating corals at the species level. Coral cover will be calculated from both 2D and 3D maps once digitisation has been completed. Coral survival and growth will be estimated by measuring change over time in 2D and 3D respectively. Some colonies may be imaged individually to maximise the quality of the growth data.
Spatial variation of each of the key metrics will be examined through a multiple regression approach by using generalised additive mixed models (GAMMS) or similar, run in R using the mgcv package. This will help understanding the relative importance of different variables in explaining recovery.
If acute disturbances occur at the studied sites during the study period (i.e. bleaching, coral predators outbreak, strong cyclone), the impact of said disturbance across the seascape will also be investigated. For instance, it is hypothesised that higher levels of structural complexity promote coral survival by creating physical shelters. If a coral predator outbreak was to occur at one of the sites during this project, 3D maps will be used to investigate how structural complexity can moderate the impact of said outbreaks and thus promote community resilience and recovery.

Project Results

This project will improve forecasting the ability of future coral reef to cope with environmental change based on information on rates of recovery and adaptation of coral reef taxa (AIMS Science Outcome #6). It will thus enhance management of tropical coral reef ecosystems by informing on where and at what scale coral reef restoration interventions are needed (AIMS Science Outcome #4). This project will use innovative, efficient and cost-effective photogrammetry methods (AIMS Science Outcome #2) to collect data at large spatial and temporal scales relevant to the study scope. At the end of the project, we will (1) have identified relevant key indicators to quantify reef recovery and adaptation; we will better understand (2) the spatial and (3) temporal variation of these key indicators; (4) how these key indicators change after an acute disturbance and (5) how this response varies depending on reef complexity and environments. (6) This project will develop models to inform restoration programs.

Keywords

Benthic,
Biostatistics,
Climate change,
Coral reefs,
Corals,
Crown of Thorn Starfish,
Distribution,
Ecology,
Field based,
Interaction,
Management tools,
Mapping,
Marine planning,
Modelling,
Monitoring,
Ocean acidification,
Ocean warming,
Physiology,
Quantitative marine science,
Remote Sensing,
Taxonomy,
Temporal change