A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms

• Published in: Ecological indicators Vol. 135; pp. 1 - 13
• Main Authors: Santavy, Deborah L, Jackson, Susan K, Jessup, Benjamin, Horstmann, Christina, Rogers, Caroline, Weil, Ernesto, Szmant, Alina, Miranda, David Cuevas, Walker, Brian K., Jeffrey, Christopher, Ballantine, David, Fisher, William S, Clark, Randy, Torres, Hector Ruiz, Todd, Brandi, Raimondo, Sandy
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.02.2022; Elsevier
• Subjects: Biocriteria; Biological Condition Gradient (BCG); Biological integrity; Coral reef condition; Coral reef protection, numeric model; Biological Condition Gradient (BCG); Coral reef protection, numeric model; Biocriteria; Coral reef condition; Biological integrity; numeric model; Coral reef protection
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2022.108576

•Biological Condition Gradient (BCG) conceptual model detects coral condition change.•Decision rules for numeric model detect condition change to human stressor gradient.•Tool supports bioassessment and biocriteria development for coral reef protection.•BCG decision rules use benthic assemblage metrics discern different reef conditions.•Numeric thresholds more defensible in disputed regulatory and management decisions. The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions, and the benefits that healthy coral reef ecosystems provide for many economies and societies. We developed a numeric (quantitative) BGC model for the coral reefs of Puerto Rico and the US Virgin Islands to transparently facilitate ecologically meaningful management decisions regarding these fragile resources. Here, reef conditions range from natural, undisturbed conditions to severely altered or degraded conditions. Numeric decision rules were developed by an expert panel for scleractinian corals and other benthic assemblages using multiple attributes to apply in shallow-water tropical fore reefs with depths <30 m. The numeric model employed decision rules based on metrics (e.g., % live coral cover, coral species richness, pollution-sensitive coral species, unproductive and sediment substrates, % cover by Orbicella spp.) used to assess coral reef condition. Model confirmation showed the numeric BCG model predicted the panel’s median site ratings for 84% of the sites used to calibrate the model and 89% of independent validation sites. The numeric BCG model is suitable for adaptive management applications and supports bioassessment and criteria development. It is a robust assessment tool that could be used to establish ecosystem condition that would aid resource managers in evaluating and communicating current or changing conditions, protect water and habitat quality in areas of high biological integrity, or develop restoration goals with stakeholders and other public beneficiaries.