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

Author:

Carturan Bruno Sylvain1ORCID,Pither Jason123ORCID,Maréchal Jean-Philippe4ORCID,Bradshaw Corey JA5ORCID,Parrott Lael123

Affiliation:

1. Department of Biology, University of British Columbia, Kelowna, Canada

2. Institute for Biodiversity, Resilience, and Ecosystem Services, University of British Columbia, Kelowna, Canada

3. Department of Earth, Environmental and Geographic Sciences, University of British Columbia, Kelowna, Canada

4. Nova Blue Environment, Schoelcher, France

5. Global Ecology, College of Science and Engineering, Flinders University, Adelaide, 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.

Funder

Canada Foundation for Innovation

Natural Sciences and Engineering Research Council of Canada

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference289 articles.

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