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. 2020 Oct:159:111387.
doi: 10.1016/j.marpolbul.2020.111387. Epub 2020 Aug 19.

Development of a reef fish biological condition gradient model with quantitative decision rules for the protection and restoration of coral reef ecosystems

Patricia Bradley  1 , Ben Jessup  1 , Simon J Pittman  2 , Christopher F G Jeffrey  3 , Jerald S Ault  4 , Lisamarie Carrubba  5 , Craig Lilyestrom  6 , Richard S Appeldoorn  7 , Michelle T Schärer  7 , Brian K Walker  8 , Melanie McField  9 , Deborah L Santavy  10 , Tyler B Smith  11 , Graciela García-Moliner  12 , Steven G Smith  4 , Evelyn Huertas  13 , Jeroen Gerritsen  1 , Leah M Oliver  14 , Christina Horstmann  15 , Susan K Jackson  16
Affiliations

Development of a reef fish biological condition gradient model with quantitative decision rules for the protection and restoration of coral reef ecosystems

Patricia Bradley et al. Mar Pollut Bull. 2020 Oct.

Abstract

Coral reef ecosystems are declining due to multiple interacting stressors. A bioassessment framework focused on stressor-response associations was developed to help organize and communicate complex ecological information to support coral reef conservation. This study applied the Biological Condition Gradient (BCG), initially developed for freshwater ecosystems, to fish assemblages of U.S. Caribbean coral reef ecosystems. The reef fish BCG describes how biological conditions changed incrementally along a gradient of increasing anthropogenic stress. Coupled with physical and chemical water quality data, the BGC forms a scientifically defensible basis to prioritize, protect and restore water bodies containing coral reefs. Through an iterative process, scientists from across the U.S. Caribbean used fishery-independent survey data and expert knowledge to develop quantitative decision rules to describe six levels of coral reef ecosystem condition. The resultant reef fish BCG provides an effective tool for identifying healthy and degraded coral reef ecosystems and has potential for global application.

Keywords: Biocriteria; Biological attributes; Sustainability; Thresholds.

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Conflict of interest statement

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1.
Fig. 1.
Conceptual model of the biological condition gradient (Davies and Jackson, 2006).
Fig. 2.
Fig. 2.
Location and distribution of 2010 EPA sampling stations. Seventy-six targeted coral survey locations (red circles) at regular intervals across human disturbance gradients (low, medium and high sediment threat levels) were distributed across linear reefs within 1.5 km of shore (including cays) and between 2 and 12 m depth.
Fig. 3.
Fig. 3.
Location and distribution of 2011 EPA sampling stations (Fisher et al., 2019). Sixty randomly selected coral survey locations (red circles) were distributed across linear reefs within 1.5 km of shore (including cays in the target substrate) and between 2 and 12 m depth. Coral reef and colonized hardbottom substrate shown in gray shading.
Fig. 4.
Fig. 4.
Distribution of fish panelists’ BCG level assignments expressed as difference from the group median in 1/3 BCG level steps. Calibration (top) and confirmation (bottom) stations from the Puerto Rico reef fish dataset.
Fig. 5.
Fig. 5.
Non-metric multidimensional scaling (nMDS) plot of the fish density composition at the 38 sites that were used in development of the BCG model clustered by Bray-Curtis similarity (Stress = 0.19)I. a) Vector plot overlay shows the direction of linear increase of environmental variable concentrations, and the multiple correlation of each (transformed) variable on the 2D ordination points. The significant gradient vectors are bolded. b-d) Bubble plots overlay the same nMDS plot but with circles of increasing size representing the environmental variable at those sites.
See this image and copyright information in PMC

References

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