Combining agent-based, trait-based and demographic approaches to model coral-community dynamics

  1. Bruno Sylvain Carturan  Is a corresponding author
  2. Jason Pither  Is a corresponding author
  3. Jean-Philippe Maréchal
  4. Corey J. A. Bradshaw
  5. Lael Parrott  Is a corresponding author
  1. University of British Columbia, Okanagan Campus, Canada
  2. Nova Blue Environment, France
  3. Flinders University, Australia

Abstract

The complexity of coral-reef ecosystems makes it challenging to predict their dynamics and resilience under future disturbance regimes. Models for coral-reef dynamics do not adequately account for the high functional diversity exhibited by corals. Models that are ecologically and mechanistically detailed are therefore required to simulate the ecological processes driving coral reef dynamics. Here we describe a novel model that includes processes at different spatial scales, and the contribution of species’ functional diversity to benthic-community dynamics. We calibrated and validated the model to reproduce observed dynamics using empirical data from Caribbean reefs. The model exhibits realistic community dynamics, and individual population dynamics are ecologically plausible. A global sensitivity analysis revealed that the number of larvae produced locally, and interaction-induced reductions in growth rate are the parameters with the largest influence on community dynamics. The model provides a platform for virtual experiments to explore diversity-functioning relationships in coral reefs.

Data availability

All data generated and associated scripts have been deposited in OSF under the DOI 10.17605/OSF.IO/CTQ43.

The following previously published data sets were used

Article and author information

Author details

  1. Bruno Sylvain Carturan

    Biology, University of British Columbia, Okanagan Campus, Kelowna, Canada
    For correspondence
    bruno.carturan@alumni.ubc.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6811-1063
  2. Jason Pither

    Biology, Earth, Environmental and Geographic Sciences, University of British Columbia, Okanagan Campus, Kelowna, Canada
    For correspondence
    jason.pither@ubc.ca
    Competing interests
    The authors declare that no competing interests exist.
  3. Jean-Philippe Maréchal

    NA, Nova Blue Environment, Schoelcher, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Corey J. A. Bradshaw

    Global Ecology, College of Science and Engineering, Flinders University, Adelaide, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5328-7741
  5. Lael Parrott

    Biology, Earth, Environmental and Geographic Sciences, University of British Columbia, Okanagan Campus, Kelowna, Canada
    For correspondence
    lael.parrott@ubc.ca
    Competing interests
    The authors declare that no competing interests exist.

Funding

Canada Foundation for Innovation (Leaders Opportunity Fund,23065)

  • Jason Pither

Natural Sciences and Engineering Research Council of Canada (RGPIN,2019-05190)

  • Lael Parrott

Natural Sciences and Engineering Research Council of Canada (RGPIN,2014-04176)

  • Jason Pither

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Carturan et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,303
    views
  • 388
    downloads
  • 9
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Bruno Sylvain Carturan
  2. Jason Pither
  3. Jean-Philippe Maréchal
  4. Corey J. A. Bradshaw
  5. Lael Parrott
(2020)
Combining agent-based, trait-based and demographic approaches to model coral-community dynamics
eLife 9:e55993.
https://doi.org/10.7554/eLife.55993

Share this article

https://doi.org/10.7554/eLife.55993

Further reading

    1. Computational and Systems Biology
    2. Neuroscience
    Cesare V Parise, Marc O Ernst
    Research Article

    Audiovisual information reaches the brain via both sustained and transient input channels, representing signals’ intensity over time or changes thereof, respectively. To date, it is unclear to what extent transient and sustained input channels contribute to the combined percept obtained through multisensory integration. Based on the results of two novel psychophysical experiments, here we demonstrate the importance of the transient (instead of the sustained) channel for the integration of audiovisual signals. To account for the present results, we developed a biologically inspired, general-purpose model for multisensory integration, the multisensory correlation detectors, which combines correlated input from unimodal transient channels. Besides accounting for the results of our psychophysical experiments, this model could quantitatively replicate several recent findings in multisensory research, as tested against a large collection of published datasets. In particular, the model could simultaneously account for the perceived timing of audiovisual events, multisensory facilitation in detection tasks, causality judgments, and optimal integration. This study demonstrates that several phenomena in multisensory research that were previously considered unrelated, all stem from the integration of correlated input from unimodal transient channels.

    1. Computational and Systems Biology
    Franck Simon, Maria Colomba Comes ... Herve Isambert
    Tools and Resources

    Live-cell microscopy routinely provides massive amounts of time-lapse images of complex cellular systems under various physiological or therapeutic conditions. However, this wealth of data remains difficult to interpret in terms of causal effects. Here, we describe CausalXtract, a flexible computational pipeline that discovers causal and possibly time-lagged effects from morphodynamic features and cell–cell interactions in live-cell imaging data. CausalXtract methodology combines network-based and information-based frameworks, which is shown to discover causal effects overlooked by classical Granger and Schreiber causality approaches. We showcase the use of CausalXtract to uncover novel causal effects in a tumor-on-chip cellular ecosystem under therapeutically relevant conditions. In particular, we find that cancer-associated fibroblasts directly inhibit cancer cell apoptosis, independently from anticancer treatment. CausalXtract uncovers also multiple antagonistic effects at different time delays. Hence, CausalXtract provides a unique computational tool to interpret live-cell imaging data for a range of fundamental and translational research applications.