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

Abstract

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.

Keywords: Biocriteria; Biological Condition Gradient (BCG); Biological integrity; Coral reef condition; Coral reef protection; numeric model.

Fig. 1.

Conceptual model of the BCG relating biological condition on the y axis to level of exposure to stressors on the × axis (adapted from Davies and Jackson 2005).

Fig. 2.

Summary of metric values in numeric rules used for discriminating between benthic BCG levels 3 and 4. Metrics shown in each graph: a) % coral cover (LPI), b) # coral spp. (LPI), c) # non-tolerant coral spp. (LPI), d) % unproductive cover (LPI), and e) % live Orbicella (DEMO). The dashed line showed the rule thresholds and ranges shown in the color-shaded region. Membership values were calculated as 1.0 if the metric value is better than the blue range, 0.0 if worse than the red region, and partial membership between 0.0 and 1.0 if within the shaded region. Distributions included the median (central square), interquartile range (rectangular box), non-outlier ranges (whiskers), and outliers (circular marks).

Fig. 3.

Summary of metric values in numeric rules used for discriminating between benthic BCG levels 4 and 5. Metrics shown in each graph: a) % coral cover (LPI), b) % non-tolerant coral cover (LPI), c) live coral cover 3D (DEMO), d) density med-large colonies (DEMO), e) % live Orbicella (DEMO), f) % Orbicella cover (LPI), and g) % unproductive cover (LPI). The dashed line showed the rule thresholds and ranges shown in the color-shaded region. Membership values were calculated as 1.0 if the metric value was better than the blue range, 0.0 if worse than the red region, and partial membership between 0.0 and 1.0 if within the shaded region. Distributions included the median (central square), interquartile range (rectangular box), non-outlier ranges (whiskers), outliers (circular marks) and extremes (stars).

Fig. 4.

Summary of metric values in numeric rules used for discriminating between benthic BCG levels 5 and 6. Metrics shown in each graph: a) % coral cover (LPI), b) colony density (DEMO) and c) # non-tolerant coral spp. (DEMO). The dashed line showed the rule thresholds and ranges shown in the color-shaded region. Membership values were calculated as 1.0 if the metric value was better than the blue range, 0.0 if worse than the red region, and partial membership between 0.0 and 1.0 if within the shaded region. Distributions included the median (central square), interquartile range (rectangular box), non-outlier ranges (whiskers), and outliers (circular marks).

Fig. 5.

Precision of individual ratings for the BCG model calibration samples, measured as the difference between the sample’s median BCG level and the expert’s individual rating. Increments of ± 0.33 represent differences that included “+”, and “−” ratings.

Fig. 6.

Precision of individual ratings for the BCG model validation samples, measured as the difference between the sample’s median BCG level and the expert’s individual rating. Increments of ± 0.33 represent differences that included “+” and “−” ratings.

Fig. 7.

Comparison of expert assignments to BCG levels for benthic calibration of reef samples compared to BCG levels predicted by the model. Cells showed where there was agreement (shaded cells) and differences (unshaded cells).

Fig. 8.

Comparison of expert ratings to BCG levels for benthic validation reef samples compared to BCG levels predicted by the model. Cells showed where there was agreement (shaded cells) and differences (unshaded cells).

Fig. 9.

Box-and-whisker plots for additional benthic BCG metric values considered by the expert panel for developing quantitative rules for BCG levels. Rugosity data did not support the narrative rules and were not used in developing the model. Depth showed trends that were not related to either metric. Squares in boxes are medians, boxes are interquartile range (IQR), whiskers are to 1.5 × IQR, circles are outliers up to 3 IQR, and crosses show extreme values > 3 IQR.