Forecasting the future of coral reefs using spatial indicators

Coral site on Easter Island Coral reefs on Easter Island (Photo: ECIM)

Natural ecosystems will change in the coming decades, as a result of the ever-increasing human footprint. While some ecosystems will respond smoothly,
others may exhibit abrupt regime shifts, which are large and sudden changes in ecosystem state. Of course, such shifts can have dire consequences for societies depending on natural ecosystems for their social or economical activities.

Understanding where and when those shifts occur in nature has puzzled scientists for decades - what are the ecological drivers? how can we know that an upcoming shift may occur in a given ecosystem? A possible approach to answer such questions is through ecological modelling, which allows us to come up with scenarios on how an ecosystem could respond to global changes.

Presentation of the project (2:06)

Ecological modelling also helps us understand the link between the patterns we measure in a given system, and the properties of the ecosystem as a whole. In many terrestrial ecosystems where abrupt shifts occur, spatial patterns are known to inform us on how robust a given system is to external perturbations. This has led to the creation of indicators of regime shifts, which measure a given aspect of the spatial structure, such as spatial autocorrelation, and are correlated to the ability of the ecosystem to withstand perturbations (its resilience).

Indecostab aims at translating previous work done on terrestrial ecosystems to the underwater world, and develop spatial indicators of ecosystem resilience for coral reefs. We will combine modelling work with empirical surveys to understand how the spatial structure of reefs informs us on their potential ability to exhibit regime shifts.

Project description on CORDIS

Software repository


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University of Utrecht


Pontificia Universidad Católica de Chile, ECIM

Selected project publications


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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 896159.

3D underwater mapping done during the course of this project