Published August 29, 2023 | Version v1
Dataset Open

Data from: Emergent spatial patterns can indicate upcoming regime shifts in a realistic model of coral community

  • 1. Utrecht University
  • 2. Pontifical Catholic University of Chile

Description

Increased stress on coastal ecosystems, such as coral reefs, seagrasses, kelp forests and other habitats can make them shift towards degraded, often algae-dominated or barren communities. This has already occurred in many places around the world, calling for new approaches to identify where such regime shifts may be triggered. Theoretical work predicts that the spatial structure of habitat-forming species should exhibit changes prior to regime shifts, such as an increase in spatial autocorrelation. However, extending this theory to marine systems requires theoretical models connecting field-supported ecological mechanisms to data and spatial patterns at relevant scales. To do so, we built a spatially-explicit model of sub-tropical coral communities based on experiments and long-term datasets from Rapa Nui (Easter Island, Chile), to test whether spatial indicators could signal upcoming regime shifts in coral communities. Spatial indicators anticipated degradation of coral communities following increases in frequency of bleaching events or coral mortality. However, they were generally unable to signal shifts that followed herbivore loss, a widespread and well-researched source of degradation, likely because herbivory, despite being critical for the maintenance of corals, had comparatively little effect on their self-organization. Informative trends were found both under equilibrium and non-equilibrium conditions, but were determined by the type of direct neighbor interactions between corals, which remain relatively poorly documented. These inconsistencies show that while this approach is promising, its application to marine systems will require detailed information about the type of stressor, and filling current gaps in our knowledge of interactions at play in coral communities.

Notes

This dataset contains a set of tables which are in tab-separated format (in "./data_export/"). Alternatively, the same tables can be read from R data file (saved in R 4.2.0), in the folder "./data".

The code included with this package is divided into the model code which is used to run the simulations supporting the paper's conclusions (in "model_code"), along with a few R/Rmarkdown scripts which are used to dissect the results and produce the figures (in "./analyses").

Funding provided by: Horizon 2020
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100007601
Award Number: MSCA N°896159 (INDECOSTAB)

Funding provided by: Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100010751
Award Number: 1181719

Funding provided by: Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100010751
Award Number: 1200636

Funding provided by: Agencia Nacional de Investigación y Desarrollo
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100020884
Award Number: PIA/ BASAL FB0002 (CAPES)

Funding provided by: Millennium Science Initiative Program*
Crossref Funder Registry ID:
Award Number: NCN19_056 (SECOS)

Funding provided by: Agencia Nacional de Investigación y Desarrollo
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100020884
Award Number: FB210021 (COPAS COASTAL)

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