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Related Experiment Video

Updated: Jul 18, 2025

Coral Reef Arks: An In Situ Mesocosm and Toolkit for Assembling Reef Communities

Coral Reef Arks: An In Situ Mesocosm and Toolkit for Assembling Reef Communities

Published on: January 6, 2023

Zigzag persistence for coral reef resilience using a stochastic spatial model.

R A McDonald¹, R Neuhausler², M Robinson³

¹Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK.

Journal of the Royal Society, Interface

|August 23, 2023

Summary

This summary is machine-generated.

This study introduces new methods to analyze complex coral reef data, revealing how local species interactions shape reef resilience and survival. Understanding these spatial patterns is key to protecting coral ecosystems.

Keywords:

coral reefs individual-based modelling stochastic bifurcation topological data analysis zigzag persistence

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Area of Science:

Ecology
Mathematical Biology
Data Science

Background:

Ecological systems exhibit complex spatial patterns driven by species interactions.
Characterizing spatio-temporal ecological data and understanding local-to-global dynamics remain significant challenges.

Purpose of the Study:

To extend a temporal model of coral reef dynamics to include spatial and stochastic elements.
To develop and apply novel descriptors for heterogeneous spatio-temporal data.
To utilize topological data analysis for characterizing reef resilience mechanisms.

Main Methods:

Developed a spatially extended mathematical model for coral reef dynamics.
Introduced novel descriptors for analyzing heterogeneous spatio-temporal data.
Applied persistent homology and zigzag persistence (topological data analysis techniques).

Main Results:

Local competition drives the formation of coral clusters.
Neighbourhood composition significantly influences coral site long-term survival.
Zigzag persistence identified spatial configurations crucial for coral resilience in diverse environments.

Conclusions:

The developed toolkit effectively characterizes spatio-temporal reef dynamics.
The methods distinguish reef dynamics across different locations using empirical data.
This approach is applicable to a wide range of ecological datasets.