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A Probabilistic Community Analysis for Coral Reef Ecosystems in Puerto Rico

A Probabilistic Community Analysis for Coral Reef Ecosystems in Puerto Rico

Presented at the 10th Annual BayesiaLab Conference on Monday, October 24, 2022.

Abstract

Environmental assessments require endpoints representative of ecological communities. These can include summary indicators or indicators for different components of the community. However, summary indicators applied to a complex system can sometimes create mathematical challenges that result in metrics that are ambiguous or uninterpretable. Coral reefs are complex ecosystems, so patterns of ecological interactions were explored by probabilistic clustering of reef monitoring variables with Bayesian networks. In 2010 and 2011, the U.S. Environmental Protection Agency sampled coral reef communities along the coast of Puerto Rico with probabilistic surveys, and the data were examined in a clustering analysis with Bayesian networks. Most of the component variables (gorgonians, sponges, fish, and coral) were found to have stronger associations within than between taxa, but unsupervised structure learning with lowered complexity weights identified two cross-taxa relationships. Survey data were also used in data clustering analyses to identify site clusters for sponge, gorgonian, stony coral, and fish variables. These clusters were constructed using an expectation-maximization algorithm that created a factor node jointly characterizing the density, size, and diversity of individuals in each taxon. The clusters were interpreted in terms of their relationship with the monitoring variables used in their construction and the relationship of the fish clusters to the monitoring variables for other taxa, such as stony coral variables. Each of these factor nodes was then used to create a set of meta-factor clusters that further summarized the aggregate monitoring variables for the four taxa. Once identified, taxon-specific and meta-clusters can be applied on a regional or site-specific basis to better understand reef communities in terms of ecosystem services and risk assessment.

EPA Disclaimer: The views expressed in this presentation are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

Presentation Video

Presentation Slides

Authors

  • John F. Carriger
    U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Solutions and Emergency Response, Cincinnati, Ohio, USA

  • William S. Fisher
    U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Gulf Breeze, Florida, USA

About the Presenter

John Carriger is a research scientist at the U.S. Environmental Protection Agency’s Office of Research and Development in Cincinnati, Ohio. John has a marine science Ph.D. from the College of William and Mary. John’s research interests include applying risk assessment, decision analysis, and weight of evidence tools to environmental problems.

Previous Conference Presentations

assessing-coral-reef-condition-indicators-for-local-and-global-stressors-using-bayesian-networks

a-bayesian-network-analysis-of-the-federal-employee-viewpoint-survey-fevs-for-the-u.s.-epa


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