v>EPA
EPA 822-R-21 -007
The Biological Condition Gradient (BCG)
for Puerto Rico and U.S. Virgin Islands Coral Reefs
TECHNICAL REPORT
September 15, 2021
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The BCG for Puerto Rico and USVI Coral Reefs
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The Biological Condition Gradient (BCG)
for Puerto Rico and U.S. Virgin Islands Coral Reefs
Contributing Authors
Pat Bradley
Tetra Tech; Key West, FL
Ben Jessup
Tetra Tech; Montpelier, VT
Deborah Santavy
US EPA, Office of Research and Development, Gulf Ecosystem Measurement and
Modeling Division; Gulf Breeze, FL
Ernesto Weil
Department of Marine Sciences, University of Puerto Rico; Mayagiiez, PR
Caroline S Rogers
USGS Wetland & Aquatic Research Center, Caribbean Field Station; St. John, USVI
Christina Horstmann
US EPA, Oak Ridge Institute for Science Education Fellow, Office of Research and
Development, Gulf Ecosystem Measurement and Modeling Division; Gulf Breeze, FL
Leah Oliver
US EPA, Office of Research and Development, Gulf Ecosystem Measurement and
Modeling Division; Gulf Breeze, FL
Contact Information
For more information, questions or comments about this document, please contact Susan
Jackson, U.S. Environmental Protection Agency, Office of Water/Office of Science and
Technology, 1200 Pennsylvania Avenue, 4304T, Washington DC, 20460 or by email at
iackson.susank@epa.gov
Citation
USEPA (U.S. Environmental Protection Agency). 2021. The Biological Condition
Gradient (BCG) for Puerto Rico and U.S. Virgin Islands Coral Reefs. EPA 822-R-
2-1007. U.S. Environmental Protection Agency, Office of Water/Office of Science
and Technology, Washington, D.C
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The BCG for Puerto Rico and USVI Coral Reefs
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Acknowledgments
We are grateful for the hard work, insights, commitment, and enthusiasm provided by the
experts, as listed in the table below. The work of sample review and model development was
fraught with a series of disruptive events that hampered communication and scheduling of
critical meetings, webinars, and discussions. This included evacuation from Magueyes Island due
to Hurricane Isaac in 2012, abruptly terminating the first workshop; the catastrophic impacts of
Hurricane Irma to Florida and the USVI, and Hurricane Maria to Puerto Rico in 2017; three
government shut-downs that caused all work on the BCG to cease (2013, 2018, 2019); the
devastating earthquake swarm in 2019-2020 that struck the southwestern part of Puerto Rico;
and the ongoing COVID-19 pandemic. The commitment and dedication of the experts has been
humbling and deeply appreciated.
BCG Coral Reef Experts
Affiliation
Expert
Assemblage Expertise
Richard Appeldoorn
Fish
University of Puerto Rico
Ernesto Weil
Paul Yoshioka
Benthic
Benthic
Alberto Sab at
Fish
University of Miami
Jerry Ault
Steve Smith
Fish
Fish
Smithsonian Institution
Melanie McField
David Ballantine
Benthic/Fish
Benthic
San Juan Bay Estuary Program
Jorge Bauza
Benthic
Lisamarie Carrubba
Fish
NO A A
Graciela Garcia Moliner
Fish
Randy Clark
Benthic
Brandi Todd
Benthic
Nova Southeastern University
Brian K. Walker
Benthic/Fish
Puerto Rico Department of
Craig Lilyestrom
Fish
Natural and Environmental
Ernesto Diaz
Benthic
Resources
Miguel Canals
Benthic
HJR Reefscaping
Michelle Scharer
Hector Ruiz
Fish
Benthic
University of the Virgin Islands
Tyler Smith
Benthic/Fish
University of North Carolina,
Wilmington
Alina Szmant
Benthic
US Geological Survey
Caroline Rogers
Benthic
National Park Service
Jeff Miller
Benthic
Marine Biological Laboratory
Loretta Roberson
Benthic
The Nature Conservancy
Aaron Hutchins
Benthic
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CSS-Inc., Fairfax, VA; Under
Chris Jeffrey
Benthic
Contract to NOAA
Simon Pittman
Fish
Vicente & Associates
Vance Vicente
Benthic
Protectores de Cuencas
Roberto Vi qui era
Benthic
David Cuevas
Benthic
Evelyn Huertas
Fish
US EPA
William Fisher
Benthic
Debbie Santavy
Benthic (facilitator)
Christina Horstmann (ORISE)
Benthic (facilitator)
In addition to expert deliberations and decisions, Ernest Weil and Caroline Rogers provided
expertise and analysis on specific topics that informed the model calibration and are included in
appendices L and T respectively.
We thank the Caribbean Coral Reef Institute for hosting the 1st and 4th workshops on Magueyes
Island; the El Yunque National Forest Headquarters for providing the conference facilities for
the 2nd workshop; and the Caribbean Landscape Cooperative (CLCC) and the International
Institute of Tropical Forestry (IITF) for providing the conference facilities for the 3rd workshop.
The BCG workshops were convened through the collaborative efforts of the U.S. Environmental
Protection Agency (EPA) Office of Research and Development (ORD), Office of Water (OW),
and Region 2.
Debbie Santavy and Christina Horstmann provided extensive technical support and expertise
fromproject start to finish. Leah Oliver, EPA ORD, provided expertise to define the generalized
stressor gradient. Their contribution exemplifies the type of partnership with the EPA OW and
the Regions that benefits state, tribal and territorial water programs. Thorough final technical
editing and reference reviews were provided by Debbie Santavy, Alex Almario (EPA ORD), and
Christina Horstmann with unfaltering technical support, guidance, and encouragement from
Sandy Raimondo (EPA ORD).
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Notice ami Disclaimer
The U.S. Environmental Protection Agency (EPA) through its Office of Water and Office of
Research and Development funded and collaborated on the project described here. The
discussion in this document is intended solely to provide information on advancements in the
field of biological assessments of coral reefs in the Caribbean and on use of biological
assessments to support state, territorial water quality management programs. This document is
not a regulation itself, nor does it change or substitute for those provisions or regulations. The
document does not substitute for the Clean Water Act, a National Pollutant Discharge
Elimination System permit, or EPA or state regulations applicable to permits; nor is this
document a permit or regulation itself. Thus, it does not impose legally binding requirements on
EPA, states, territories, tribes, or the regulated community. This document does not confer legal
rights or impose legal obligations on any member of the public.
Whereas EPA has made every effort to ensure the accuracy of the discussion in this document,
the obligations of the regulated community are determined by statutes, regulations, and other
legally binding requirements. In the event of a conflict between the discussion in this document
and any statute or regulation, this document will not be controlling.
Mention of any trade names, products, or services is not and should not be interpreted as
conveying official EPA approval, endorsement, or recommendation.
Photos were provided by the authors, in the public domain, or credited as they appear in the
document.
Cover Photo:
BCG Experts, Caribbean Coral Reef Institute, Magueyes Island, La Parguera, Puerto Rico March
12-14, 2019. Photo credit: Susan Jackson (U.S. EPA).
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Table of Contents
Acknowledgments ii
Notice and Disclaimer iv
Acronyms vii
List of Tables viii
List of Figures ix
Executive Summary xi
Introduction 1
Problem Statement 4
Description of the study area 7
Data used in the development of the Coral Reef BCG Models 12
Convening the Experts 23
Assignment of BCG Attributes to Fish and Stony Coral Species 23
Development of the Predictive BCG Decision Model 27
Results 29
Conceptual Model 29
Benthic BCG Model 32
Why benthic organisms? 32
Narrative Benthic Model 33
Reef Classification 35
Coral BCG Attributes 35
Narrative Descriptions of BCG Levels 36
Numeric Model - Calibration and Validation 39
Benthic Model Validation 52
Benthic Model Discussion 54
BCG Attribute VII: Organism Condition for Hard Corals 55
Ecological Traits for Hard Corals 56
Benthic Screening Assessment Tool (BSAT) 56
Fish BCG Model 58
Why fish? 58
Fish BCG Attributes 62
Assignment of BCG Levels to Sites and Preliminary Narrative 63
Numeric Model - Calibration and Validation 65
Fish Model Rules 71
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Fish Model Discussion
Summary and Recommendations for Future Research
References Cited
74
75
81
Appendices
A. Glossary
B. BCG Attributes
C. BCG Levels
D. CWA and BCG
E. BCG Workshops and Webinars
F. Gorgonian and sponge morphological shapes
G. Coral Metric Calculations
H. BCG Coral Reef Experts
I. Management Observers at Coral Reef BCG Workshops
J. BCG Team
K. Development of the Predictive BCG Decision Model
L. Characterization of BCG Condition Level 1 for coral reefs in Puerto Rico and the US
Virgin Islands
M. BCG Attribute Assignment (Benthic Organisms)
N. Benthic Metrics Used in Developing BCG Rules
O. BCG Attribute Assignments (Fish)
P. Fish Metrics Used in Developing BCG Rules
Q. Recommendations for Future Research
R. Generalized Stressor Gradient
S. Ecological Attributes for Caribbean Coral Species
T. Investigating BCG Attribute VII for Evaluating Stony Coral Condition and Disease
Impacts
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Acronyms
BCG - Biological Condition Gradient
CWA - Clean Water Act
DEMO - Demographic benthic sampling method
DPNR - Department of Planning and Natural Resources (USVI)
EPA - US Environmental Protection Agency
FKNMS - Florida Keys National Marine Sanctuary
GIS - Geographic Information System
GSA - Generalized Stressor Axis
LDI - Landscape Development Intensity Index
LPI - Linear Point Intercept benthic sampling method
MPA - Marine Protected Area
NCRMP - National Coral Reef Monitoring Program (NOAA)
NMFS - National Marine Fisheries Service (NOAA)
NOAA - National Oceanic and Atmospheric Administration
NPS - National Park Service
ORD - Office of Research and Development (EPA)
PR - Puerto Rico
QA/QC - Quality Assurance/Quality Control
SST - Sea Surface Temperature
ST - Sediment Threat
USCRTF - United States Coral Reef Task Force
USN - United States Navy
USVI - United States Virgin Islands
UVI - University of the Virgin Islands
WQS - Water Quality Standards
WRI - World Resources Institute
Glossary: See Appendix A
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List of Tables
Table 1. Potential applications of the BCG for Existing Coral Reef Management Programs 3
Table 2. Data Used in the Development of the Coral Reef BCG Benthic and Fish Models 13
Table 3. Caribbean scleractinian coral species listed as threatened under the endangered species
act 17
Table 4. Example fish data showing fish species and counts in length bins 19
Table 5. Hypothetical example of expert ratings and rationales for a single benthic reef sample
with summary rating of BCG Level 3 26
Table 6. Descriptions of four condition categories (very good to poor) based on expert
assessments of individual sites 30
Table 7. Benthic BCG Narrative Rules 37
Table 8. Numbers of sites used for development of the benthic BCG model, showing location,
depth, and sampling method 42
Table 9. BCG predictive model rules for the coral reef benthic assemblage (first generation),
showing the Level definition, narrative rules, quantitative rules, and rule combinations. 47
Table 10. Comparison of expert assignment of BCG Levels for benthic calibration of reef sites
compared to BCG Levels predicted by the model 51
Table 11. Comparison of expert ratings of BCG Levels for benthic validation of reef sites
compared to BCG Levels predicted by the model 53
Table 12. Benthic Screening Assessment Tool rules (first generation) 58
Table 13. Caribbean fish species listed as threatened under the U.S. Endangered Species Act... 63
Table 14. Narrative rules for fish BCG Levels in Puerto Rico coral reefs 65
Table 15. Comparison of expert ratings of BCG Levels for fish calibration reef sites compared to
BCG Levels predicted by the model 69
Table 16. Comparison of expert ratings of BCG Levels for fish validation reef sites compared to
BCG Levels predicted by the model 69
Table 17. BCG reef fish assemblage decision rules 72
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1 ist of Figures
Figure 1. The Biological Condition Gradient (BCG) 1
Figure 2. Patterns of frequency or abundance in relation to increasing stress associated with the
BCG Attributes assigned to fish and stony coral taxa 2
Figure 3. Conceptual Coral Reef BCG Model developed by experts in 2012 7
Figure 4. Target jurisdictions for EPA Coral Project include Florida (Florida Keys and Southeast
Florida reefs), Puerto Rico, and the U.S. Virgin Islands, including St. John, St. Thomas,
and St. Croix 8
Figure 5. General process for development of the BCG model 11
Figure 6. Location and Distribution of 2010 EPA Sampling Sites in Puerto Rico 14
Figure 7. Location and Distribution of 2011 EPA Sampling Stations (Fisher et al. 2019) 15
Figure 8. Two divers conducting the EPA DEMO survey 16
Figure 9. Examples of low rugosity (left) and high rugosity (right) reefs (source: Santavy et al.
2012) 18
Figure 10. Diagram of fish transect using two divers in a 4 m x 25 m belt transect (100 m^) 18
Figure 11. Fork length for different types of fish 19
Figure 12. Diagram of NCRMP surveys (NOAA 2015a) 20
Figure 13. Conceptual diagram of Reef Visual Census (RVC) diver within 7.5 m-radius survey
cylinder 22
Figure 14. Illustration of the sample review and rating process, showing the expert panel
reviewing the sample data 25
Figure 15. Photos from EPA coral reef sites reflect a range of coral reef conditions, from good to
intermediate quality, to severely degraded 29
Figure 16. Screenshot of benthic organism data sheet used in assessing EPA 2010 and 2011 data:
Taxa list 34
Figure 17. Screenshot of Excel worksheet: site and sample characteristics used in assessing EPA
2010 and 2011 data 34
Figure 18. Screenshot of the benthic organism data sheet used in assessing NOAA NCRMP data:
Taxa list 40
Figure 19. Example data from Excel worksheet: Station and sample characteristics used in
assessing NOAA NCRMP data 41
Figure 20. Distribution of metrics used in model rules for discriminating Benthic BCG Levels 3
and 4 44
Figure 21. Distribution of metrics used in model rules for discriminating Benthic BCG Levels 4
and 5 45
Figure 22. Distribution of metrics used in model rules for discriminating Benthic BCG Levels 5
and 6 46
Figure 23. Individual rating precision for calibration sites, measured as the difference between
the median BCG Level for a site and the expert's individual rating 52
Figure 24. Individual rating precision for validation sites, measured as the difference between the
median BCG Level for a site and the expert's individual rating 53
Figure 25. Screenshot of Fish data sheet (MS Excel): taxa list with site and sample characteristics
60
Figure 26. Diagrams of fish rules for Level 3, showing metric distributions for sites as rated by
the experts 66
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Figure 27. Distribution of metrics used in model rules for discriminating Fish BCG Levels 4 and
5 67
Figure 28. Distribution of metrics used in model rules for discriminating Fish BCG Levels 5 and
6 67
Figure 29. Distribution of fish panelists' BCG Level assignments expressed as difference from
the group median in 1/3 BCG Level steps 70
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Executive Summary
The Biological Condition Gradient (BCG), initially developed by freshwater scientists, has been
applied to the Caribbean coral reef ecosystem. The conceptual BCG describes how biological
attributes of aquatic ecosystems change along a gradient of increasing human disturbance. The
conceptual model has been calibrated for application to the near shore coral reefs of the U.S.
Virgin Islands (USVI) and Puerto Rico. The model can be used to support biological
assessments of reef condition, monitor for changes in condition, identify high quality reefs,
evaluate effectiveness of Best Management Practice (BMP), and support biological criteria
development.
Coral reef ecologists and fisheries scientists with specific knowledge of the Caribbean region
evaluated site-specific quantitative data from diver-based visual surveys on species abundance,
community assemblage structure, and benthic habitat composition to develop quantitative
decision rules. The experts then:
• developed a conceptual model
• assigned BCG attributes to individual species
• assigned BCG Levels to survey sites based on the sample composition, including taxa
characteristics such as trophic group, organism condition, and BCG attribute assignments
• developed preliminary narrative decision rules for semi-quantitative BCG models
• and developed, reconciled, revised, and tested quantitative decision rules for benthic
organisms and fish
The experts agreed that BCG Level 1 sites (as naturally occur) no longer exist in the Caribbean
region. Historic data were used to help define BCG Level 1 conditions in absence of empirical
data. BCG Level 1 is defined narratively and provides context for interpreting Levels 2 through
6.
In calibrating the BCG models, the experts used coral reef condition data from both EPA 2010
and 2011 surveys in Puerto Rico, and NOAA's National Coral Reef Monitoring Program
(NCRMP) 2013 -2015 surveys in Puerto Rico and the USVI.
The models were calibrated separately for benthic and fish assemblages. Each model includes a
cascade of rules for membership at each BCG Level, starting with conceptual rules for Level 2
and proceeding with testable rules for Levels 3 through 5. Samples that failed at all Levels
automatically were evaluated as Level 6.
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Rules were calibrated through a process that prompted experts to first conceptualize good, fair,
and poor reef conditions and to describe reefs in these broad condition categories. Experts
characterized fish and coral species attributes based on native range, endemism, and sensitivity
to pollution. Narrative decision rules were based upon experts' expectations of the fish and
benthic assemblages at each BCG Level. Experts reviewed data for taxa attributes and traits (e.g.,
fish: trophic group) present at each site. With support of the technical analysts, the narrative rules
were translated into numeric rules that distinguished between BCG Levels based on measurable
sample characteristics (metrics). The numeric rules were compiled for application as a BCG
expert decision model that could accurately and transparently replicate the decisions that the
experts expressed during sample reviews.
The predictive BCG model was accurate, though not perfect, in replicating assessment decisions
made by the experts. Predictions of BCG Levels from model application agreed with expert
consensus of BCG Levels for 92% and 82% of the fish sites (calibration ) and for 84% and 89%
of the benthic sites (calibration ). The model predictions for all sites (100%) were within one
BCG Level of the expert consensus. The experts also tested potential transferability of the
Puerto Rico fish model to a different jurisdiction (i.e., the Florida Keys and Dry Tortugas). A set
of 14 fish samples was reviewed by the experts, and the quantitative BCG model developed for
Puerto Rico and the USVI was applied. The model was 79% accurate in replicating the experts'
assessments for the Florida Keys calibration.
The experts identified areas for further research that could improve the rigor of the models.
These included refinement of data collection methods to increase both measurement specificity
and sampling efficiency; calibrating the model with surveys from relatively unimpaired areas
elsewhere in the Caribbean (and perhaps from years of long-term data such as are available from
the National Park Service for St John and St Croix); taxa trait and metric refinement;
classification by depth stratification; and development of a generalized stressor axis that would
include land-based pollution, fishing pressure and water temperature.
The fish and benthic BCG models can be combined for a robust interpretation since these diverse
assemblages can respond differently to stressors. While the BCG model was developed using
data from Puerto Rico and the USVI, the BCG general framework could potentially be applied to
other coral reef ecosystems. This was demonstrated for sites from the Florida Keys and Dry
Tortugas.
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Introduction
Since 2012 the US Environmental Protection Agency (EPA) and a group of scientific coral reef
experts have collaborated to develop a Biological Condition Gradient (BCG) model for the coral
reefs of Puerto Rico and the U.S. Virgin Islands (USVI). This report summarizes the process
used to derive a predictive model of the BCG for coral reef fish and benthic assemblages. This
report can be used by coral reef managers in Puerto Rico and the USVI to develop and
implement elements of a biological monitoring and assessment program.
Beginning in 2000, EPA collaborated with freshwater biologists and managers from across the
United States to develop and implement the BCG (Davies and Jackson 2006; EPA 2016). The
BCG is a conceptual framework (Figure 1) that describes how biological attributes of aquatic
ecosystems (i.e., biological condition) are expected to change along a gradient of increasing
anthropogenic stress (e.g., physical, chemical, and biological impacts).
c
z
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c
D
O
'~£
_c
c
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Increasing Levels of Stressors *
Figure 1. The Biological Condition Gradient (BCG).
Two Important BCG Concepts
Two important concepts are fundamental to the BCG framework: Attributes and Levels (see text
box). The attributes are standard descriptions of taxa characteristics that help with interpreting
community composition and function (Figure 2 and Appendix B) In the BCG model- building
context, attributes are coded using Roman numerals I - VI. Attributes II - V are generally related
to taxa endemism and pollution tolerance associated with a generalized stressor gradient.
Attribute I describes specialist, historically important, or endemic taxa. Attribute VI describes
non-native taxa. Attributes VII - X pertain to organism condition, system performance, and
physical-biotic interactions, and these have not typically been used in model development.
Natural structure & function of blotk community maintained
Minimal changes In structure A function
Evident changes In structure and
minimal changes In function
In structure &
changes In function
Major changes In structure &
moderate changes In function
Severe changes In structure & function
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The BCG for Puerto Rico and USVI Coral Reefs
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BCG Levels are standardized descriptions of
biological condition related to assemblage
structure, function, and sensitivity to stressors
(Figure 1 and Appendix C). BCG Level 1
describes an assemblage that occurs when
human disturbance is entirely or almost entirely
absent. This is an undisturbed condition as
naturally occurs. Level 1 conditions are rarely
observable in any aquatic environment,
especially given ubiquitous stressors
introduced by global phenomena such as
climate change and atmospheric deposition.
Level 6 conditions assemblages have severely
altered structure and function compared to natural expectations. Levels 2-5 have successively
decreasing resemblance to biological integrity. Levels 2-5 are most often observed during BCG
calibration exercises.
BCG Attributes
Attributes include properties of the assemblage (e.g.,
tolerance, rarity, native-ness) and organisms (e.g.,
condition, function). In the BCG model-building
exercise, BCG attributes I - VI are assigned to taxa
(see Figure 2 and Appendix B).
BCG Levels
BCG Levels describe levels, or tiers, of biological
response to increasing amounts of stressors. Six BCG
Levels are defined ranging from biological conditions
found at no or low amounts of stressors (Level 1) to
those found at high amounts of stressors (Level 6)
(Figure 1 and Appendix C).
II Highly Sensitive: Higher
relative abundance and
occurrence in minimally
disturbed sites, but can
occur In low numbers.
Might be specialists.
Ill Sensitive: Occur
throughout the stressor
gradient, but with higher
probability in sites with
l«ss disturbance.
&
c
o
Attribute II;
highly sensitive
Attribute IV:
ir.lni irodialo Inlnrant
Attribute III:
rrermediate sensitive
Attribute V:
highly tolerant
IV Intermediate Tolerant:
Occur throughout the
stressor gradient and with
equal probability
throughout, or with a
central peak.
->¦ Increasing Stress
V Highly Tolerant: Occur
throughout the stressor
gradient, but with higher
probability of occurrence
and greater abundance in
disturbed sites.
Figure 2. Patterns of frequency or abundance in relation to increasing stress associated with the BCG
Attributes assigned to fish and stony coral taxa. Attributes II V are based on taxa specialization,
endemic or native status and stressor tolerance. Attributes I (endemic, specialist species) and VI (non-
native species) are not shown in the Figure because they are not necessarily associated with the stressor
intensity shown on the x-axis.
The BCG is now a recognized tool in the water quality management toolbox. The BCG builds
upon and complements other tools (e.g., biological indices, models, and statistical approaches
and guidance) to provide a more refined and detailed measure of biological condition and will
help states and territories to:
• More precisely define and measure biological condition for specific waters
• Identify and protect high quality waters
• Evaluate potential for improvement in degraded waters and track improvements
• Develop biological criteria
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The BCG for Puerto Rico and USVI Coral Reefs
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• Clearly communicate the likely impact of water quality management decisions to the
public
• Promote similarity of assessments and endpoints across different geographic area (e.g.,
states, territories, etc.)
The BCG can support CWA programs such as 305(b) assessments and reports, 303(d) listing of
impaired waters, and TMDL program implementation. It can also be used by federal, state, and
territorial managers in support of other coral reef and fisheries management programs (Table 1).
Table I. Potential applications of the BCG for Existing Coral Reef Management Programs (modified
from Bradley et al. 2010). Continued, on next page.
Management Area
Description
Application of the BCG
Marine Protected Areas
(MP As)
Selecting MPA Sites
• To identify waterbodies that have outstanding
biological condition and require protection
Managing MP As
• To establish thresholds against which to measure
effectiveness of MP As
Effectively manage the waters
between MP As
• With establishment of designated uses, to protect
those uses (i.e., ecosystem connectivity)
Managing Fisheries
Eliminate open-access
fisheries in coral reef
ecosystems and establish
sustainable fisheries
regulations
• To establish levels (e.g., taxa richness, abundance)
expected to sustain reef fisheries
• Degradation can trigger changes in fishery
practices and regulations
Restricting the species being
selected (e.g., coral reef
herbivores, including
parrotfish)
• To establish expected or desired levels of
individual species (e.g., abundance, biomass)
• Degradation can trigger changes in fishery
practices and regulations
Managing Tourism
Mooring Buoys
• To identify locations with outstanding biological
condition that would benefit from the protection of
mooring buoys
Permits - diving, fishing,
boating
• With establishment of designated uses, to protect
those uses
Watershed Management
Developing and implementing
watershed management plans
• To support setting goals for watershed and
regional planning
• To prioritize watershed goals and
actions
• To establish thresholds against which to measure
effectiveness of permits or other management
actions
Coastal Zone
Management
Regulating Coastal
Development
• To support setting goals for watershed and
regional planning
• To prioritize watershed goals and actions
• To develop management plans
Habitat Connectivity
Maintain connectivity between
coral reefs and associated
habitats such as mangroves,
sea grass beds, and lagoons
• All nearshore environments are protected by the
Clean Water Act (CWA)
• Coral reefs, mangroves, sea grass beds, and
lagoons can be specifically protected when they are
identified in water quality standards
Damage Assessment and
Restoration
Restoring coral reefs or
seagrass meadows damaged by
boats and anchors
• To establish thresholds against which to measure
effectiveness of restoration efforts.
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Managing Endangered
Species (Endangered
Species Act)
Protecting rare, threatened, and
endangered species
• To establish expected or desired levels of
individual species (e.g., abundance, biomass).
• To establish thresholds against which to measure
effectiveness of legal protection.
National Environmental
Policy Act (NEPA) of
1969
Environmental Impact
Statements
• To identify where site-specific criteria
modifications may be needed to effectively protect
a waterbody.
• To assess the overall ecological effects of
regulatory actions.
Problem Statement
More than half of the U.S. population lives in coastal counties - areas that border oceans and
coasts, bays, estuaries, and coral reefs (NOAA 2014a). In the states of Florida and Hawai'i and
the Commonwealth of Puerto Rico, the USVI, Guam, American Samoa, and the Commonwealth
of the Northern Marianas (CNMI), nearly everyone lives within 100 km of the coast. In
subtropical and tropical states and territories, coral reefs are ecosystems of concern. Coral reefs
provide many important ecosystem services such as: protection of coastlines from ocean storms,
support of significant fisheries and biodiversity, resource of sand for beaches and coral rock for
construction, tourism and recreation for locals and visitors, and sources of novel pharmaceuticals
and medicines. They are integral to many island and coastal traditions, economies, and cultures.
Coral reef ecosystems are declining around the world (Wilkinson 2004, 2008; Bellwood et al.
2004; Pandolfi et al. 2005; Bruno and Selig 2007; Knowlton and Jackson 2008; Hughes et al.
2018). Climate change related impacts (elevated sea surface temperatures causing increased
bleaching, disease, and mortality; and more frequent and intensive tropical storms causing
physical damage to the reef structure) are affecting coral reefs globally (Hughes et al. 2003;
Hoegh-Guldberg et al. 2007, 2011, 2017; Carpenter et al. 2008; Knowlton and Jackson 2008).
Local anthropogenic stressors (e.g., polluted runoff from agriculture and unsustainable land-use
practices, intense fishing pressure, ship groundings, etc.) also contribute directly to reef decline
and can exacerbate climate change impacts (Rogers 1990; Edinger et al. 1998; Jackson et al.
2001; Precht et al. 2001; Fabricius 2005; Mora 2008; Bejarno and Appeldoorn 2013; Vega
Thurber et al. 2014; Ennis et al. 2016; Robinson et al. 2017; Moustaka et al. 2018/ While local
managers have little control over climate change, they may be able to substantially reduce local
anthropogenic stressors by developing and enforcing laws, regulations and policies for
waterbody activities, and watershed land use.
On June 11, 1998, President Clinton signed Executive Order 13089 for Coral Reef Protection
that directed all federal agencies to protect coral reef ecosystems to the extent feasible, and
instructed agencies to develop coordinated, science-based plans to restore damaged reefs as well
as mitigate current and future impacts on reefs, in the United States and globally. Executive
4
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Order 13089 also established the interagency U.S. Coral Reef Task Force (USCRTF) that works
to develop and implement comprehensive, multidisciplinary, and coordinated approaches to
preserve and protect U.S. coral reef ecosystems and encourage sound coral reef conservation
practices globally. The Task Force seeks to use existing U.S. agencies' programs, statutory
authorities, competencies, and capabilities to promote coral reef conservation consistent with
U.S. law and treaty obligations. The USCRTF includes leaders of 12 Federal agencies, seven
U.S. States, Territories, and Commonwealths (Florida, Hawaii, Puerto Rico, the USVI, American
Samoa, Guam, and the Northern Marianas) and three Freely Associated States (Federated States
of Micronesia, Republic of the Marshall Islands, and the Republic of Palau).
The U.S. Clean Water Act (CWA) (33 USC § 1251 et seq. 1972) established a long-term
objective to restore and maintain chemical, physical, and biological integrity of aquatic
resources. The CWA requires states, territories, and tribes (herein referred to as "jurisdictions")
to adopt water quality standards as provisions of jurisdictional law or regulation (Appendix D).
Water quality standards establish the water quality goals for all waters within their jurisdiction,
including waters of the territorial seas and provide a regulatory basis when the water bodies do
not meet their designated use(s). EPA works with state and territorial governments and other
federal agencies to implement CWA programs and to protect coral reefs. EPA is a member of the
USCRTF and partners with jurisdictions and other federal agencies to prevent land-based sources
of pollution, such as stormwater, sediment, or sewage from impacting coral reefs and to develop
water quality standards and criteria to protect their waterbodies.
In 2006, Aaron Hutchins, the Director of the USVI Department of Planning and Natural
Resources (DPNR) requested assistance from EPA in developing protective measures for coral
reef ecosystems, including information and guidance on the development of biological criteria
for territorial water quality standards. In response, EPA's Office of Research and Development
(ORD) began to develop coral reef biological indicators and assessment methods for coral reef
ecosystems (Fisher 2007; Fisher et al. 2007, 2008; Fore et al. 2006a, b), including a 2006 coral
reef survey in the USVI (Fisher et al. 2014) and testing indicators for responsiveness to
anthropogenic stress as metrics that can be used in BCG rule development (Fisher et al. 2008). In
September 2007, the EPA and USVI DPNR held a workshop in St. Croix, USVI to initiate a
process to design an integrated monitoring program capable of meeting multiple management
objectives (Bradley et al. 2014a).
Following the workshop, EPA ORD focused the Agency's coral reef research program on coral
reef ecosystems in Florida, Puerto Rico, and the USVI (Bradley et al. unpublished). EPA
conducted two probabilistic surveys of stony coral condition in the USVI: St. Croix in 2007, and
the islands of St. Thomas and St. John in 2009 (Fisher et al. 2014). The same approach was
applied in 2010 and 2011 on Puerto Rico reefs, including an expanded protocol that
simultaneously assessed stony coral, fish, sponge, and gorgonian condition (Santavy et al. 2012;
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Oliver et al. 2014; Fisher et al. 2019). Detailed descriptions of the methods and indicators are
provided in Santavy et al. 2012.
In 2013, NOAA implemented the first year of its National Coral Reef Monitoring Program
(NCRMP) in the USVI using a stratified random sampling design in shallow water coral reefs (0-
30m). NOAA released the initial NCRMP guidance for the Caribbean in 2014 (NOAA 2014b, c,
d), and regularly thereafter (NOAA 2015a, b, c, d; 2018a, b, c, d). NOAA and partners (UVI,
NPS, University of Miami, TNC and USVI DPNR) monitored coral assemblage structure,
benthic cover estimates for ecologically important cover types/groups (e.g., macroalgae, turf
algae, crustose coralline algae, corals, sponges, sand/sediment, etc.), rugosity, prevalence of
bleaching, and measures of fish assemblage structure (abundance, diversity, size, etc.), mobile
invertebrate counts (Caribbean spiny lobster (Panulirus argus), queen conch (Aliger gigas),
long-spined sea urchins (Diadema antillarum)), and presence/absence of threatened and
endangered species. In the Caribbean, there are seven scleractinian coral species and two fish
species listed as threatened and no species listed as endangered. NMFS has the authority to use
regulatory measures (e.g., impose limitations on activities such as collection) to protect corals
listed under the Endangered Species Act (ESA) or managed as essential fish habitat. NOAA has
issued recovery plans for the two ESA-listed Atlantic Acroporid species (NOAA 2015e) and has
issued recovery outlines for the five other ESA-listed coral species and four fish species (NOAA
2020a, b)
EPA ORD and Office of Water (OW) held a workshop August 21-22, 2012 at the Caribbean
Coral Reef Institute, Isla Magueyes, La Parguera, Puerto Rico on coral reef biological integrity
that brought together scientists with expertise in coral reef taxonomic groups to begin
development of a model that describes characteristics of the coral reef for each Level of the BCG
(Bradley et al. 2014). The BCG Level definitions are standardized, but must be described for
each dataset, thus calibrating the meaning of the BCG to the characteristics observed in the
dataset. The experts individually rated each site as either very good, good, fair, or poor and
documented their rationale. The group discussed the reef attributes that characterize biological
integrity (or the natural condition) for Puerto Rico's coral reefs. The experts assembled a
conceptual BCG based on stony corals, fishes, gorgonians, sponges, algae, large vertebrates (e.g.,
turtles), and mobile invertebrates for shallow-water linear reefs of southwestern Puerto Rico. The
experts identified a suite of measurable attributes for each assemblage. The conceptual BCG had
four distinct Levels of condition: very good - excellent, good, fair, and poor (Figure 3; Bradley
et al. 2014). These were simplified descriptions of the six standardized BCG Levels that were
ultimately used in model development.
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Stressor Gradient
Figure 3. Conceptual Coral Reef BCG Model developed by experts in 2012.
Over the course of eight years, a committed workgroup of diverse coral reef experts met to refine
the initial BCG calibrati on and to develop a predictive model of biological conditi on (Appendix
E). The model incorporates the experts' interpretations of reef conditions relative to six
standardized BCG Levels. (Figure 1 and Appendix C). Sites from Puerto Rico, the USVI, and
Florida were reviewed in a systematic process to develop the BCG model that operationalized
the decision rationale so that the biological conditi on of new sites can be predicted based on
bioassessment monitoring data.
BCG Model Development Outline
2012 Proof of Concept - Experts examined whole reef assemblages using EPA data and videos to categorize
sites into Very Good. Good, Fair, and Poor biological conditions
2014 Narrative Model Development - Experts refined the Proof of Concept to formalize assemblage
descriptions in terms of the BCG Levels. Experts split into groups to address fish separately from the benthic
assemblage. BCG Attributes were assigned to fish and stony corals.
2015 Fish and Benthic Model Refinements - The benthic experts continued evaluating biological conditions in
narrative terms, addressing reef classification. The fish experts drafted and validated a numeric model. The
coral reef benthic model was revised to include algal metrics and other benthic components.
2019 Model Refinements - Benthic experts calibrated the numeric model using NOAA NCRMP data.
Validation occurred during webinars. Fish experts tested the transferability of the BCG numeric model using
data from the Florida Keys.
Description of the study area
Coral reefs differ in type and habitat across depth and geographic zones. For this project we
focused on forereef coral ecosystems in Puerto Rico, the U.S. Virgin Islands (USVI) and Florida
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(Figure 4) because: (1) they encompass the largest reef area; 2) they serve the greatest number of
beneficiaries; (3) they are subject to Clean Water Act (CWA) jurisdiction, and (4) they were
under the greatest environmental threats when we began the research (Burke and Maidens 2004).
Figure 4. Target jurisdictions for EPA Coral Project include Florida (Florida Keys and Southeast
Florida reefs), Puerto Rico, and the U.S. Virgin Islands, including St. John. St. Thomas, and St. Croix.
Puerto Rico
Puerto Rico, the smallest of the Greater Antilles, is an archipelago composed of the main island;
the oceanic islands of Mona, Monito, and Desecheo; Caja de Muertos Island on the south coast;
Vieques Island; Culebra Island; and a series of smaller islets or cays known as the "Cordillera de
Fajardo". The Commonwealth of Puerto Rico has an area of 5,320 square miles (13,800 km2), of
which 3,420 square miles (8,900 km2) is land and 1,900 square miles (4,900 km2) is water, with
fringing coral reefs totaling 1,301 square miles (3,370 km2) off the east, south and west coasts
(Wilkinson 2004; Burke and Maidens 2004).
• The north and northwest coasts are subject to strong wave action during winter and
receive substantial sediment and nutrient loading from the discharge of the largest rivers
of Puerto Rico.
• The northeast coast, partially protected from wave action by a chain of emergent rock
reefs (Cordillera de Fajardo) aligned east-west between the main island and the island of
Culebra is upstream from the discharge of large rivers, resulting in waters with good
transparency. Fringing reefs are found off the northeast coast at Rio Grande, Luquillo,
Fajardo, Culebra, and Vieques.
• The east coast is characterized by extensive sand deposits with scattered rock formations
that have been colonized by corals.
• Culebra is located approximately 17 miles (27 km) east of the Puerto Rican mainland, 12
miles (19 km) west of St. Thomas and 9 miles (14 km) north of Vieques. Culebra is an
archipelago consisting of the large island and twenty-three smaller isl ands that lie off its
coast. From 1939 to 1975 Culebra was used as a live-fire gunnery range for the USN.
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Since 2011 the Department of Defense and its contractors have been conducting
munitions cleanup of unexploded ordnance on the main island and offshore. Culebra's
shoreline is marked by cliffs, sandy beaches, mangrove forests, and coral reefs.
• Vieques is located about ten miles (16 km) east of Puerto Rico with a land area of 52
square miles (130 km2). In 1941 the USN purchased or seized about two thirds of
Vieques, and after the war, the USN continued to use the island for military exercises and
as a firing range and testing ground for munitions. The former USN lands, now a
National Wildlife Refuge, occupy the entire eastern and western ends of Vieques, with
the former live weapons testing site at the extreme eastern tip. These areas are
unpopulated. The former civilian area occupies roughly the central third of the island.
There are no permanent rivers or streams. Around the coast lie sandy beaches
interspersed with lagoons, mangroves, salt flats, and coral reefs.
• The south coast of the main island of Puerto Rico has relatively low wave energy, a wide
insular shelf, discharge from small rivers, a series of embayments and submarine
canyons, seagrass beds and fringing mangroves, and small mangrove islets fringing the
coast.
• Off the central west coast lies Mayaguez Bay, one of the largest estuarine systems of the
island with coral reefs showing a marked trend of deterioration closer to the shore.
• North of Mayaguez is Rincon, where coral reef systems are established throughout the
relatively narrow shelf off Tres Palmas, including an elkhorn coral (Acroporapalmata)
biotope fringing the coastline that is probably the largest remaining stand in Puerto Rico.
A series of patch reefs are distributed throughout the Rincon mid-shelf, and there is a
"spur-and-groove" coral reef formation at the shelf-edge.
• Off the northeast coast of Aguadilla, several small marginal shallow coral reefs are
associated with rock outcrops. These are strongly affected by intermittent river discharge
(Culebrinas River) and wave action. East of Aguadilla, the influence of large river
plumes, a prominent feature of the coastline, constrains coral reef development, but hard
ground and rock reefs with live corals are present throughout.
• Mona, Monito, and Desecheo are oceanic islands that are exposed to strong wave action,
with coral reefs along their southern coasts. There are no rivers on any of the islands,
which are surrounded by waters of exceptional transparency (Cintron et al. 1975).
U.S. Virgin Islands
The U.S. Virgin Islands (USVI) are in the Leeward Islands of the Lesser Antilles to the east of
Puerto Rico and west and south of the British Virgin Islands. The USVI includes the primary
islands of St. Croix, St. John, and St. Thomas, as well as off-shore cays. The USVI totals roughly
347 km2 of land area, 1,564 km2 of water, and total reef area of 485 km2 to a depth of 30 m
(Kendall et al. 2001; Rogers et al. 2008).
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• St. Croix is the largest of the three USVI islands at 215 km2 is separated from St. Thomas
and St. John by 55 km across the 4500-m deep Virgin Islands Trough. This island has
coral growth along much of the insular shelf with a well-developed fringing reef on the
eastern end, and deep coral walls including a submarine canyon on the north shore. St.
Croix is the only island with a permanent source of freshwater. Buck Island Reef
National Monument (National Park Service) is located on the northern portion of East
End Marine Park in St. Croix. The Salt River Bay National Historical Park and
Ecological Preserve is located on the north-central coast of St. Croix.
• St. Thomas is the second largest at 83 km2 and St. John is the smallest of the three USVI
islands at 52 km2. St. John is largely incorporated into the Virgin Islands National Park
(National Park Service), which covers all but the western coast of the island. Reefs in St.
Thomas and St. John generally form fringing, patch, or spur and groove formations that
are distributed irregularly around the islands.
Florida
Florida is the southern most of the 48 contiguous states, located at the convergence of the
subtropical and temperate climate zones. Florida totals 65,757.70 sq. mi (170,312 km2) of land
area, with a 1,350 mi (2,170 km) coastline. The water boundary is three nautical miles (3.5 mi;
5.6 km) offshore in the Atlantic Ocean and nine nautical miles (10 mi; 17 km) offshore in the
Gulf of Mexico.
Coral reefs in Florida occur along most of the Atlantic coastline and are easily separated into two
different regions: Southeast Florida (north of Miami, including Martin, Palm Beach, Broward,
and Miami-Dade counties) and the Florida Keys (south of Miami, consisting of Monroe County),
which extend south and west into the Gulf of Mexico. Reefs at Dry Tortugas National Park
represent the southwestern tip of the chain.
• Florida Keys. The Florida Keys is the only emergent coral reef ecosystem found off the
continental United States. This marine habitat is under protection, with the extreme
northern end as the Biscayne National Park managed by the NPS and the remainder of
the reef tract managed by NOAA and the State of Florida as the Florida Keys National
Marine Sanctuary (FKNMS), and Dry Tortugas National Park (managed by the NPS).
• Southeast Florida. The coastal region of SE Florida is highly developed, containing 43%
of Florida's population of 21.8 million people (U.S. Census Bureau, 2019). Many SE
Florida reefs are located just 1.5 km from this urbanized shoreline. SE Florida reefs are
the northern extension of the Florida Keys that extend into a more temperate climate.
Significant but more limited hard corals exist, including some of the largest staghorn
coral patches throughout the Florida system. These communities diminish northward
along Florida's coast. The importance of the southeast Florida reefs was recently
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The BCG for Puerto Rico and USVI Coral Reefs
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recognized by the establishment of the Southeast Florida Coral Reef Ecosystem
Conservation Area in 2018. Management of these reefs is through a consortium of local
and regional agencies that form the Southeast Florida Coral Reef Initiative (SEFCRI)
Team.
Steps to develop the BCG model for the Caribbean reef fish and benthic assemblages followed a
series of steps described in technical guidance on the development of a BCG (EPA 2016).
Constraints include the availability and consensus of fish and benthic assemblage experts, and
the availability and applicability of sample data. The basic steps include, 1) the organization of
sample data into interpretable presentations, 2) the orientation of the experts to BCG concepts
and project objectives, 3) the assignment of BCG attributes to taxa, 4) an expert rating of
biological samples from field surveys into BCG Levels, 5) the translation of sample ratings into
narrative rules and responsive metric values into quantitative models, and 6) the validation of the
models with independent data (Figure 5). Technical analysts facilitated and supported the
experts. The analysts had thorough knowledge and experience with the BCG and were able to
remain neutral on taxa attribute and sample Level assignments after describing the standard
definitions and processes. Analysts also compiled, organized, and summarized data for review of
taxa, samples, metrics, and draft models.
Analysts compile data, calculate metrics,
prepare data worksheets, select sites
Analysts orient expert panel to concepts,
terms, data descriptions, methods, etc.
Experts associate characteristics with taxa
Expert panel discussion to rate samples in levels
of biological condition and declare rationale
Analyststranslatesample rationaleand ratings
into conceptual and numeric predictive models
Experts confirm that the model replicates
expert decisions by application to new samples
Figure 5. General process for development of the BCG model.
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Data used in the development of the Coral Reef BCG Models
Three different data sets were used to develop the coral reef BCG models, which were used for
different assemblages and steps of model development. A summary is provided in Table 2, and a
full description of the data sets is provided below. Water quality data were not collected during
these surveys. The field survey methods were observational and resulted in minimal impacts to
the ecosystem.
Survey data were subjected to thorough QA/QC to eliminate uncorrectable, unmatched, or
conflicting data, sites deemed to be in non-target habitat types, and to correct older taxonomic
names or synonyms. The data were then put into an Excel workbook for use by the experts. The
workbook included a series of linked worksheets:
• Notes, including descriptions of the other worksheets and metadata
• Status page, with a summary of sites and expert consensus BCG Level assignments
• A master table of taxonomic attributes and characteristics that provides species
information, including scientific and common names, classification, BCG attribute, and
assemblage-specific traits. For fish, these included trophic guild, whether large or small
for important targeted species, preferred habitat (Humann and DeLoach 2003), and
tolerance to sediment and fishing pressure. For the benthic assemblage, these included
attributes for hard corals.
• A data habitat worksheet that provides other information by sample (e.g., exercise ID,
collection date, collection method (EPA, NCRMP, RVC), region, latitude/longitude,
survey year, reef type, whether in an MP A, habitat (NOAA benthic maps), etc).
Data sheets from individual monitoring sites, including site and sample information,
including assemblage-specific metrics.
EPA 2010/2011 surveys
EPA conducted two underwater coral reef surveys in 2010 and 2011 along the south coast of
Puerto Rico to support the development of coral reef biocriteria and the BCG (Fisher et al. 2019).
The EPA data were used for the proof of concept to demonstrate a conceptual BCG model for
both fish and benthic assemblages. The EPA data were also used in development of narrative
BCG rules for the benthic assemblage and for calibration and validation of the numeric fish BCG
model. For completion of the numeric benthic model, the NOAA NCRMP data were used.
The EPA survey methodology was designed as an efficient, inexpensive, nondestructive method
that generates useful indicators for management programs. This was particularly important
because U.S. jurisdictions have limited resources for the monitoring and assessment needed to
support CWA requirements. The surveys targeted scleractinian coral, fish, sponge, and
gorgonian assemblages on linear coral reefs within 4.8 km of shore (including shores of small
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The BCG for Puerto Rico and USVI Coral Reefs
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islands) at depths < 12 m as characterized in NOAA's benthic habitat map (Kendall et al. 2001)
for several reasons: 1) the shallow, near-shore environment can be readily accessed by small
boats and is therefore efficient and safe for divers; 2) the near-shore environment maintains
proximity to potential human disturbance in adjacent watersheds (Fisher 2007; Fisher et al.
2014); and 3) the literature shows a distinct difference in shallow and deep reef fish assemblage
structure (Brokovich et al. 2008).
Table 2. Data Used in the Development of the Coral Reef BCG Benthic and Fish Models.
Data set
Brief Description
Application in BCG
Development
EPA 2010 and 2011
surveys along the south
coast of Puerto Rico
The surveys targeted scleractinian coral, fish,
sponge, and gorgonian assemblages on linear coral
reefs that occur on coral reef and hard bottom
substrate as defined in the 2001 NOAA benthic
habitat maps for southern Puerto Rico (Kendall et
al. 2001). Surveys were conducted within 1.5 km
from shore and to a maximum depth of 12m.
• Proof of Concept (narrative
descriptions of 4 Levels of
Coral Reef Condition) -
using visual media only
• Fish Model development -
entire process
• Benthic Model - narrative
rule development only
NOAA National Coral
Reef Monitoring
Protocols (NCRMP)
2013-2015 surveys of
Puerto Rico and the U.S.
Virgin Islands
NCRMP targeted sessile benthic and fish
assemblages in a stratified random sampling
design, where the sampling domain for each region
(e.g., Puerto Rico, the USVI) was partitioned by
habitat type and depth, sub-regional location (e.g.,
along-shelf position), and management zone.
Benthic Model - numeric
rules development and model
validation
Fish surveys in Florida
Keys and Dry Tortugas,
20142016
Reef Visual Census (RVC) for 14 sites from 2014-
16 surveys in Florida Keys and Dry Tortugas, at
depths shallower than 16 m.
To test the transferability of
the BCG fish model from
Puerto Rico and the USVI to
another region (Florida)
The 2010 survey was designed to document coral reef impacts from land-based sources of
sediment (i.e., terrigenous sediment) at 76 sites (Oliver et al. 2014, 2018; Bradley et al. 2014,
2020) (Figure 6). Risk of contamination by terrigenous sediment was based on the Reefs at Risk
Program analyses (Burke and Maidens 2004), by which threat declines as distance from the
threat increases. The benthic sediment threat (BST) is a compilation of watershed sources of
sediment and pollution that incorporates erosion rates (slope, land cover type, precipitation, and
soil type) and dispersion rates (hydrological dispersal in the coastal zone). The BST values were
obtained for reef habitats which demonstrated the relative erosion potential for watersheds,
adjusted for watershed size, and modeled to correspond with pour points (Oliver et al. 2018). The
values and G1S platform were obtained from the World Resources Institute (WRI) and NO A A
Summit to Sea model (WRI and NOAA 2006).
The 2011 survey sites were selected using a generalized random tessellation stratified approach
(Stevens and Olsen 2004) for the 2011 survey (Figure 7). One objective of the project was to
support development of a long-term monitoring program that could be used by Puerto Rico for
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2.021
CWA reporting purposes. A second objective was to assemble a dataset that could be used for
development of the BCG and ultimately, biocriteria (Fisher et al. 2019).
Ts
Gjayanilla
-'As!.
** „ ,
M
Sediment Threat
| 0 - 53585
53586-107171
| 107172- 160756
3 160757-214342
214343 • 267497
~ 2010 Survey Stations
20 Kilometers
Salinas
Jobos
.4
1)
>Ma.
Sediment Threat
|
0 - 53585
1 *1
53586-107171
1
107172-160756
¦1
160757 - 214342
214343 ¦ 267497
~
2010 Survey Stations
10
Ti7-
Figure 6. Location and Distribution of 2010 EPA Sampling Sites in Puerto Rico. Seventy-six targeted
coral survey sites (black triangles) at regular intervals across human disturbance gradients were
distributed across linear reefs within 1.5 km of shore (including cays) and between 2-12 m depth (Bradley
et al. 2020).
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The BCG for Puerto Rico and USVI Coral Reefs
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2019). Sixty randomly selected coral survey locations (black triangles) were
distributed across linear reefs within 1.5 km of shore (including cays in the target
substrate).
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EPA Coral Demographics Method.
The coral demographic (DEMO) method was used to observe and record hard coral condition .
This method provided metrics for calculation of coral surface area, counts of taxa, and coral
colony condition. A pair of divers swam along one 25m x 2m belt transect (Figure 8). One diver
recorded the species, colony size, percent live tissue, and any disease or bleaching on all stony
coral colonies found within 1 m of the tape (25m2 stony coral transect area); while the other
diver recorded the morphology (Appendix F) and size of all gorgonians and sponges found in
five 1-m2 quadrats along the other side of the tape at the 0, 5, 10, 15, and 20-m marks (a total
5m2 transect area at each site for sponge and gorgonian census). The percent area covered by the
zoanthid Palvlhoa caribaeorum was also recorded in the quadrats (Santavy et al. 2012; Fisher et
al. 2019).
< 25 m
3 J
<
1
3
Figure 8. Two divers conducting the EPA DEMO survey. One diver is surveying stony corals on the right
side of the transect and the other diver is surveying sponges and gorgonians on the left side of the
transect.
The three measurements/observations recorded for each coral colony (species, size, and percent
tissue area) allowed calculation of metrics reflecting aspects of assemblage composition,
physical status, and biological condition of the colonies (Fisher 2007; Santavy et al. 2012). The
sponge and gorgonian metrics provided estimates of the surface area contribution to reef habitat.
EPA Method to Identify Presence of Endangered/Threatened Species. Along the 25m transect,
divers also recorded the presence of species listed under the ESA (Table 3). Threatened coral
species incltided Acropora cervicornis andAcroporapalmata. In 2014, NOAA listed five
additional Caribbean coral species as threatened: Dendrogyrci cylindrus, Orbicella annularis,
Orbicellafaveolata, Orbicella franksi, andMycetophyllia ferox (50 CFRPart 223, 2014).
EPA Method to Record Mobile Invertebrates The density of Aliger gigas (queen conch),
Panulirus argus (spiny lobster), Scyllaridae (slipper lobster), and Diadema antillarum (long-
spined black sea urchins) observed along the transect were recorded. Underwater videos were
taken along the entire length of 25m transect and still photographs were taken to capture
representative elements of the environment that might not have been reflected in the transect
data. Only summaiy statistics of taxa richness were used for all other assemblages except
scleractinian corals (Santavy et al. 2012).
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Table 3. Caribbean scleractinian coral species listed as threatened under the endangered species act.
Scientific Name and
Common Name
Photograph
Scientific Name and
Common Name
Photograph
Mycetophyllia ferox
Rough cactus coral
Acropora
cervicornis
Staghorn coral
Orbicella faveolata
Mountainous star
coral
Dendrogyra
cylindrus
Pillar coral
Orbicella franksi
Boulder star coral
Acropora palm at a
Elkhom coral
Orbicella annularis
Lobed star coral
EPA Reef Rugosity Method. Reef rugosity (vertical relief and topographic complexity) was
surveyed to infer topographical complexity of the coral reef surface. A rugosity index was
applied as a reef-scale metric of reef contour or roughness (McCormick 1994; Alvarez-Filip el
at 2009) (Figure 9). For the 2010-2011 EPA surveys, rugosity was determined using a chain-
transect method that compares the length of a chain draped along the contour of stony corals and
non-coral substrate to the length of a taut line across the same linear distance. This generates a
unitless value that can be used for relative comparisons across sites and reefs (Santavy et al.
2012).
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Figure 9. Examples of low rugosity (left) and high rugosity (right) reefs (source: Santavv etal. 2012).
EPA Fish Survey Method. Reef fish were surveyed visually to document the species, numbers,
and sizes of all reef fishes along a single 25 m x 4 m underwater belt transect (100 m2) and
within the entire water column to the surface (Figure 10). Data were used to estimate abundance,
species richness, and biomass for the fish populations, and subsequently classified by taxonomy
and trophic guilds (Santavy et al. 2012).
————; 25 m
Diver s Direction
Figure 10. Diagram offish transect using two divers in a 4 m x 25 m belt transect (100 m^). All fish
encountered in the water column or on the reef are included in the visual assessment, (source: Santavy et
al. 2012).
Each fish was scored in 5cm size class increments up to 35cm using visual estimation of fork
length (Table 4). For individuals greater than 35 cm, an estimate of the actual fork length was
made. The fork length is measured from the snout (with closed mouth) to the fork at the base of
the tail or caudal fin (Figure 11).
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Table 4. Example fish data showing fish species and counts in length bins.
Species
Length (in centimeters)
<5
5-10
10-15
15-20
20-25
25-30
30-35
>35
Threespot Dam selfish
1
19
9
Yellowtail Snapper
2
1
Spani sh Hogfish
1
2
1 -60
Stoplight Parrotfish
3
2
Black Grouper
1 -72
Bar Jack
40
30
30
Figure 11. Fork length for different types offish. The fork length is measured from the tip of the snout
(with closed mouth) to the base of the caudal fin. (source: Santavy et al. 2012).
NOAA NCRMP surveys
Bioassessment data from NOAA's NCRMP Puerto Rico and the U.S. Virgin Islands surveys
collected in 2013 - 2015 were used for developing the numeric benthic rules. NCRMP data
quality is optimized by stratifying using combinations of depth (e.g., shallow, medium, deep),
reef zone (forereef, backreef, etc.), habitat type (e.g., spur and groove, colonized pavement), and
management zone (e.g., MP A, no-take area, etc.).
Although several NCRMP protocols were similar to those described for the EPA Puerto Rico
data, there are some significant differences (detailed below). For example, EPA did not estimate
the benthic coverage by other sessile benthic assemblages (algal taxa, exposed substrate,
sponges, gorgonians, etc.), NOAA did not include sponge and gorgonian measurements in the
DEMO surveys, NOAA used a microheterogeneity approach for reef rugosity, and NOAA
sampled to 100-foot depths. The experts recognized natural differences in benthic reef
assemblages inhabiting shallow and deep sites (Aguilar-Perera and Appeldoorn 2008; Smith et
al. 2010; Andradi-Brown et al. 2016; Baker et al. 2016; Kahng et al. 2010; Rocha et al. 2018).
The deepest sites in the data set were approximately 100 feet deep, which NOAA considers the
maximum practical depth for routine underwater monitoring. Within this depth range, the experts
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suggested that differences in reef structure occurred at approximately 40 feet deep, as a result of
gradual and general differences in light penetration and wave action. There was an effort to
concentrate on shallow reef sites (<40 ft). However, a fuller range of BCG condition levels was
found when including both shallow and deep sites for the benthic model. In addition, more
samples were collected from deeper sites. Therefore, the reviewed benthic samples were from all
depths (up to 100 ft). Differences in natural expectations and assessment results relative to depth
were assessed during and after the BCG rating and prediction processes.
Transect end: 25m
Benthic
rugosity
survey area
(fish diver)
24 m s 4 m
(surveyed in
2 m x 2 m
blocks)
Transect origin: Ora
Figure 12. Diagram ofNCRMP surveys (NOAA 2015a). Size of each respective survey area is also
indicated. Fish, LPI, and Coral Demographics were surveyed as the divers moved away from the transect
origin. Mobile invertebrates (e.g.. spiny lobster, queen conch, Diadema urchins) and topographic
complexity were surveyed as the divers returned to the transect origin.
NOAA NCRMPLine-Point Intercept (LPI) Method. NOAA employed the Line-Point Intercept
(LPI) method to estimate the percent benthic cover of ecologically important cover types
(macroalgae, turf algae, crustose coralline algae, corals, sponges, sand/sediment, etc.) (Figure
12). This method used points along a single 25m transect to quantify each of the benthic
organisms or substrate types present lying every 20cm under the tape, a total of 100 points
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documenting the substrates and biota. Because the intervals were 100th of the transect length,
each point constituted 1% of cover.
Along a 2m width of the 25m transect, divers conducted a survey for Key Species (ESA-listed
species and selected mobile invertebrates), as described above (Table 3). The densities of Aliger
gigas (queen conch), Panulirus argus (spiny lobster), Scyllaridae (slipper lobster), and Diadema
antillarum (sea urchins) were recorded (Santavy et al. 2012). No underwater videos were taken.
Underwater photographs were taken along the entire length of 25m transect (6-7 photos per
survey).
NOAA NCRMPMicroheterogeneity Measure. The NCR.MP 2013-2015 surveys used a
microheterogeneity measure to estimate reef rugosity. This measure was the calculated
difference between the lowest and highest vertical heights in quadrats along the transect,
averaged for all sampled quadrats at a site. Maximum hard bottom relief was measured at 24
locations along the 25m LPI transect, recorded as centimeters, and binned into six height classes
(<0.2m, 0.2-<0.5m, 0.5-<1.0m, 1.0-<1.5m, 1.5-<2.0m, >2m). Using the frequencies from each
transect, a single rugosity index was calculated. The frequency of each height class was used as
the midpoint of each height class (lowest to highest: 0.1, 0.35, 0.75, 1.25, 1.75, actual height if
>2m) multiplied by the number of observations in that height class. If the height was >2m, the
maximum vertical height was the multiplier. Finally, the sum of the products from all height
classes was divided by the total number of observations (24) to obtain the microheterogeneity
rugosity value (MRV) (NOAA 2014d). The maximum and minimum transect depths were noted
(Brandt et al. 2009).
NOAA NCRMP Coral Demographic Method. The DEMO surveys were conducted at a subset
of LPI sample sites (2013: 220 DEMO surveys/283 total surveys; 2014: 111/230; 2015:
139/239). Divers swam along a single 10m x lm belt transect, recording information on coral
species composition, size, abundance, and specific parameters of condition (% live vs. dead and
bleaching; presence/absence of disease) of non-juvenile scleractinian corals (> 4cm maximum
diameter), (Figure 12). From the species, size, and condition measures of the DEMO surveys,
coral surface area (CSA) and live coral surface area (LCSA) were calculated in two and three
dimensions (Appendix G).
Florida Reef Visual Census (RVC)
The 4th BCG workshop focused on potential transferability of the Puerto Rico fish model to a
different jurisdiction (Florida). Experts rated 14 sites in the Florida Keys and Dry Tortugas at
depths shallower than 16 m, which were co-sampled by both the fish and benthic teams
(Bohnsack and Bannerot, 1986). The sites were selected by the RVC leads across a stressor
gradient: water quality (low anthropogenic impact - Dry Tortugas, low-moderate impact -
Florida Keys forereef, and high impact - Hawk's Channel); and fishing pressure based upon
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management zones (low - Dry Tortugas National Park; medium - Florida Keys, Marine
Protected Areas; and high - Florida Keys outside of Marine Protected Areas).
The Florida Reef Visual Census (RVC) method has been used to survey reef fish populations
along the Florida reef tract in a variety of benthic habitat types, ecoregions, and management
areas (Brandt et al. 2009; Kilfoyle et al. 2017). This method collects information on the density
and size distributions of the fish assemblage (except for cryptic species), as well as information
on benthic habitat features.
The RVC uses a two-stage stratified random sampling design. The Florida Keys and Dry
Tortugas sampling domains are partitioned into 200 x 200 m grid cells (the primary units), which
are each assigned to a strata designation based on habitat type, geographic sub-region,
management type (open vs. closed to fishing), and depth. Primary units to be sampled are then
randomly selected from a list of all possible primary units for each stratum. Within each selected
primary unit, two smaller units (the second stage) are haphazardly selected. Each second-stage
unit consists of a pair of divers who each perform a Reef Visual Census (RVC) which is a 15 m
diameter stationary point count (Bohnsack and Bannerot 1986; Figure 13). A comparability
study between the stationary point count method and the transect method conducted in 1999-
2000 determined that the stationary point count method was most successful at estimating fish
species densities in Florida and has been employed annually in the Florida Keys ever since
(Colvocoresses and Acosta 2007).
Figure 13. Conceptual diagram of Reef Visual Census (RVC) diver within 7.5 m-radins survey cylinder
(from Rogers et al. 1994, based on Bohnsack and Bannerot 1986).
It is important to note that underwater visual census techniques (stationary point counts or belt
transects) have biases that affect the accuracy of density estimates, in particular crevice-dwelling,
cryptic, very secretive and nocturnal species (Bohnsack and Bannerot 1986; Ackerman and
Bellwood 2000; Stewart and Beukers 2000; Willis 2001 Bozec et al. 2011). Very intensive
sampling would be needed to detect these types of species (Bohnsack and Bannerot 1986).
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Convening the Experts
An important component of the BCG process is the establishment of a panel of experts familiar
with the taxonomy and ecology of coral reef aquatic biota. The experts' primary task is to make
biological assessments of environmental conditions and to relate them to the BCG model (EPA
2016). In general, experts have been highly concordant in their ratings of sites for several
different ecosystems, including marine benthic invertebrate communities in California bays
(Weisberg et al. 2008), marine coastal benthic communities from four widely separated
geographic regions (Teixeira et al. 2010), fish communities in a South African estuary (Harrison
and Whitfield 2004), and a river ecosystem in Australia (Davies et al. 2010). In development of
freshwater BCGs, experts have come to a strong consensus on the descriptions of individual
BCG Levels and very close agreement on the BCG Levels assigned to individual sites (EPA
2016; Gerritsen et al. 2017).
A panel of coral reef experts was assembled in 2012 (Bradley et al. 2014b; Santavy et al. 2016;
Bradley et al. 2020). Experts were chosen based on their scientific expertise in Caribbean coral
reef taxonomic groups (e.g., stony corals, fishes, sponges, gorgonians, algae, seagrasses and
mobile invertebrates), and overall coral reef ecology. Experts included research scientists from
federal and state organizations, academia, and non-governmental organizations (NGOs), as well
as water quality managers and natural resource managers from Puerto Rico and the USVI. A list
of the BCG experts is available in Bradley et al. 2016 and Appendix H. The expert panel had
few retirements and replacements over the course of the project. During the workshops, coral
reef managers observed the expert deliberations, while the BCG technical team facilitated the
process (Appendices I and J).
The BCG concepts and terminology were unfamiliar to most on the expert panel. The BCG had
not previously been applied in tropical reefs, and the data interpretation was complex. Due to this
fact, the orientation steps of the process were iterated until the understanding and calibration of
the BCG model was completed.
Assignment of BCG Attributes to Fish and Stony Coral Species
To complement data interpretation, the taxonomic components (fish and stony coral) were
associated with one of six BCG attribute categories that represented degree of sensitivity to
pollution (I-V) and non-native taxa (VI). During the BCG model development, expert panelists
consistently used these categories, and metrics based on these categories, to summarize shared
characteristics among taxa. Many expert panelists (in particular, the fish experts) found these
categories useful in addition to taxa lists in their analysis of site data.
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Rating Biological Sites at BCG Levels
In early workshops and web-assisted conferences, the basic ideas of reef assessment were
discussed without reliance on BCG terminology. This was done to facilitate expert sharing of
knowledge and understanding of how coral reef biota respond to stress without getting distracted
by new and unfamiliar terminology. Once a conceptual gradient of biotic response to stress was
defined by the expert panel, BCG terminology was introduced and was readily understood and
accepted.
Early meetings established a conceptual model that was later used to tailor the process and define
data requirements for assessing the biological condition of coral reefs. Using this approach, the
group formulated expectations for all condition Levels defined in the BCG framework by
employing reef taxa and biological characteristics to align with the structural and functional
descriptions for each BCG Level generic description. In the next rounds of BCG calibration, the
expert panel broke out into two different assemblage groups; benthic and fish assemblages. Each
assemblage had differences in sampling programs, sites, and methods, as well as in data
availability and treatments, as described above.
Experts were asked to assign BCG Levels to sites based on their interpretation of taxa lists,
assemblage metrics, and site information (Figure 14). The experts then provided their logic for
assigning BCG Levels to sites. This expert logic was critical to the development of the BCG
model with the aim of answering the questions - which information in the data set was
ecologically meaningful to the experts? And why? Each expert assessed the site data
individually, recorded their individual interpretation and rationale, and then, through a facilitated
process, shared their ratings and logic with the full panel. Through discussion and further
testing, the panel developed a consensus recommendation on a set of narrative decision rules.
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Compare to standard expectations
Assign a BCG level
Bio
Biological Integrity, As Naturally Occurs
Severely Altered
Provide decision rationale
Examine sample data
Figure 14. Illustration of the sample review and rating process, showing the expert panel reviewing the
sample data, comparing sample characteristics to standard expectations for BCG Levels, assigning a
BCG Level, and providing rationale for the BCG Level assignment.
The experts reviewed, discussed, and evaluated site characteristics and assemblage metrics for
indications of biological condition. The expert panel members decided first individually, then as
a group, which BCG Level best represented the biological conditions at a site. The experts then
expressed the decision criteria as narrative statements relating metrics to the standardized BCG
Level descriptions. The experts converted the sample BCG Level assignments (ratings) and
rationale into narrative rules.
Decision rationales expressed by panelists usually included a statement about the critical
components of the sample, such as overall taxa richness, organism density, taxa that indicated
stress or lack thereof, trophic structure, organism condition, biomass, and other measurable
metrics (Table 5). While experts were asked to provide an integer rating for the BCG Levels,
they were sometimes unwilling to do so, and intermediate Levels were assigned as '+'
(exhibiting characteristic of the next best conditions but not enough to rank the site in the better
Level), and W (exhibiting characteristics that suggest somewhat worse conditions but not
enough to rank the site in the corresponding worse (i.e. more highly degraded) Level). For
example, a site was rated "4+" because the site was a very good "4" but not as good as a "3". In
each case, the expert provided their logic for the "+" or rating. This decision logic was
extremely important information that indicated what shifts in the assemblage structure and
function signaled that a site was approaching another BCG Level. Articulating these change-
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points and uncertainties allowed incorporation of ecologically meaningful decision rules in the
BCG model.
Whether site reviews were conducted as a group during in-person meetings or web-assisted
conferences, experts would first individually rate the site. When working individually on
homework assignments, experts would write out their rationale. In both review settings, the
resulting ratings and rationales would be compiled and discussed by the group at the workshop
or a webinar. The median score was proposed as the site rating, and experts were asked to concur
in a final rating for the site. This resulted in a BCG Level assignment that was agreed upon by
consensus.
Table 5. Hypothetical example of expert ratings and rationales for a single benthic reef sample with
summary rating of BCG Level 3.
Expert
Rating
Rationale
Expert #1
3+
Good live cover, good sizes, no new mortality, good fish diversity. Slightly better
than a Level 3.
Expert #2
3-
Pro: cover, large colonies, no disease, or new mortality; Con: low sensitive taxa, high
old mortality. Not quite a Level 3.
Expert #3
3-
Mid depth surmising forereef terrace. Lots of small coral colonies and a few larger
colonies of Orbicella: not that much partial mortality. Coral cover in the model range
for Level 3. Algae cover not that high. Few sponges and gorgonians. More or less
expected for mid-depth terraces except coral cover should be higher.
Expert #4
4
Low density and only 1 attribute III taxon; a few large colonies but high mortality,
indicating good conditions gone bad
Expert #5
2-
Best site we have seen but does not meet Level 2 because of coral mortality.
Expert #6
3-
Moderate coral cover but mostly small colonies, moderate turf algae %
The review process would continue until adequate numbers of sites were rated for the model
development stage. Ideally, 20 sites per BCG Level would be evaluated so that characteristics of
each Level could be distinguished with some degree of robustness. However, this number of sites
was not always attained due to a lack of valid sites or sites covering all BCG Levels. For
example, there were no undisturbed or minimally disturbed sites available. The BCG Level 1
was defined narratively to provide context and the quantitative model was derived to identify
sites that range in condition from BCG Level 2 to Level 6.
Rule Development and Refinement
The technical analysts interpreted the narrative rules as numeric sample metrics based on
available data. Over 100 metrics for each assemblage were calculated to address the narrative
rules and variations. The metrics were presented to the expert panel, showing boxplots of metric
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distributions among sample BCG ratings. The experts selected metrics that represented the
narrative intent as candidates for the model. The visual evaluation of the distributions was
sufficient to illustrate general patterns of metric response that supported, partially supported, or
refuted expectations described in the narrative rules. The experts usually eliminated metrics that
did not distinguish between levels because they would not improve model results. However, with
expert consent these unresponsive metrics could be included because they truly represented the
narrative rules.
The analysts then drafted numeric rules and combinations of rules to produce a model with
measurable predictive accuracy, where the model predicted the same Level as assigned by the
experts. Each model includes a cascade of rules for membership at each BCG Level, starting
with conceptual rules for Level 2 and proceeding with testable rules for Levels 3 through 5.
Samples that failed at all Levels automatically were evaluated as Level 6. The analysts attempted
to use several responsive metrics selected by the experts, meaningful thresholds provided by the
experts or detected in the metric distributions, and logical combinations to maximize model
performance. The draft model was iteratively applied, presented, reviewed, and revised until the
expert panel agreed that the model replicated their decision processes and accurately predicted
each BCG Level they assigned through consensus.
Development of the Predictive BCG Decision Model
To allow for consistent assignments of sites to BCG Levels, it was necessary to formalize and
quantify the expert knowledge by codifying Level descriptions into a set of quantitative rules
(e.g., Droesen 1996). Rules are logical statements that the experts used to make their decisions
on BCG Levels. Once the rules have been quantified, it is expected that a knowledgeable person
can follow them to obtain the same BCG Level ratings as the group of experts, allowing the
decision criteria to be transparent for water quality managers and stakeholders. Rules can be
nonlinear or non-monotonic and are robust to missing information.
The process of rule quantification was guided by the narrative descriptions of sample
characteristics at each BCG Level, by any quantitative thresholds or observations expressed by
the experts, and by distributions of measurable site characteristics corresponding to the
descriptions (especially box-plots of metric distributions in sites at each rated Level). When the
metric patterns in the visually assessed boxplots matched the expert narrative statements, then
the metric was considered a good candidate for the model. If the metric patterns did not match
the narrative statements, then several explanations were possible. These explanations include
metrics responding to natural factors that were not recognized, inconsistent rating by individual
experts or the entire panel, or metrics that did not represent the narrative rule as originally
intended. There also could be confounding or compounding factors that were not recognized,
were not stated, or were not discernible in the data set. When these situations occurred, the
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expert panel was consulted and their evaluation and hypothesis for discrepancy recorded. An
expert panel recommendation was solicited for future work to address any discrepancies.
An example of a narrative rule that was not supported in the data regards rugosity. High rugosity
was expected by the expert panelists to indicate natural or close to natural reef biological
conditions. The experts stated this expectation as a narrative rule when reviewing both benthic
and fish site data. However, rugosity as measured by either of two methods did not discriminate
among the BCG Levels. Because of this unexpected lack of corroboration, the experts
recommended reconsideration of how rugosity is measured (as discussed in the Summary and
Recommendations for Future Research section). The rugosity measure was not used in the BCG
benthic model even though the narrative rule was expressed, and the data were available.
Numeric model rules were expressed as a range of possible values that were expected for
assemblage metrics at a certain BCG Level (EPA 2016; Bradley et al. 2020). The range of values
acknowledges that there is uncertainty around the quantitative thresholds for the metrics, as
expressed in the experts' narrative rationale. For example, a fish rule for Level 3 is: fish taxa >
15 (10 - 20) taxa. Whereas the nominal value for the rule is 15, if the sample has fewer than 10
taxa, it is not at all like a Level 3, and if it has 20 taxa, it is similar to a Level 3 with respect to
the number of taxa (see Appendix K for more detailed explanation of rule derivation). The rule
thresholds were derived after multiple samples were rated and rationale for those samples were
stated in relation to each metric. The numeric thresholds were first determined from the range of
observed metric values compared among the assigned levels and any stated numeric values
stated by the experts.
The uncertainty associated with the metric rule was apparent when sites with different metric
values were assigned to the same level and the same narrative rational was expressed even
though the metric values differed among samples. For example, an expert rationale for assigning
a sample to a Level might be 'high live coral coverage' for two samples assigned to the same
Level though the live coral coverage might be 20% in one sample and 30% in the other. The rule
thresholds (nominal central value and ranges) were drafted using the empirical evidence from the
metric distributions per assigned level. The ranges were centered on the nominal value to
accommodate a linear interpolation of membership for the level. After being drafted for each
responsive metric, each rule was presented to the expert panel, which decided to keep the rule,
reject it, or modify some part of it (metric calculation or thresholds).
To characterize the dynamic and multifaceted nature of a biotic assemblage, the BCG model is
comprised of a set of decision rules for each BCG Level that include an "and" for those rules that
are always expected to be met and an "or" for combination of rules that capture the shifts and
variability in an assemblage. The experts determined how the rules for each Level were to be
applied: (1) all rules must be met, (2) some number of rules for that Level must be met, or (3)
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some rules can override results of other rules (EPA 2016). After formulating the rules, rule
thresholds, and combination rules, the model was presented to the expert panel for approval or
adjustment.
Results
Conceptual Model
Development of the Coral Reef BCG Framework
In a facilitated workshop held in 2012 at the Caribbean Coral Reef Institute, Isla Magueyes, La
Parguera, Puerto Rico, the experts evaluated photos and videos for 12 sites collected during EPA
suiveys (2010 and 2011) from Puerto Rico coral reefs exhibiting a wide range of conditions. The
experts individually rated each site as to observed condition (good, fair, or poor) based on videos
and photos and documented their rationales for the assignments (Figure 15). At this stage in the
process, benthic and fish experts collaborated in a single panel.
Figure 15. Photos from EPA coral reef sites reflect a range of coral reef conditions, from good (left) to
intermediate quality (middle), to severely degraded (right).
The group discussed the reef attributes that characterize BCG Level 1: biological integrity (or the
natural condition) for Puerto Rico's coral reefs, that served as the baseline condition, because
CWA is grounded in the concept of natural, undisturbed conditions. Preliminary attributes were
identified that would characterize a reef with excellent condition (undisturbed by anthropogenic
stress) and that would serve as the reference condition for biological integrity. The concept of
reference condition for biological integrity anchors the highest quality Level of the BCG, to aid
in the interpretation of results when considering shifting baselines (Pauly 1995; Stoddard et al.
2006), and to help identify biotic changes resulting from historic pressures, as well as gradual
regional or global stresses such as climate change. Furthermore, a concise description of
reference condition in terms of biological integrity provides a basis for effective public
communication of changes over time.
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The experts agreed that there were no longer any reefs in Puerto Rico that met the BCG Level 1
definition corresponding to very good-excellent condition (Bradley et al. 2014b, 2020; EPA
2016). A BCG Level 1 condition was never observed and since underwater observations were
not possible until substantial human disturbance was ubiquitous in the Caribbean (Jackson et al.
1997), the experts were not able to develop quantifiable rules for BCG Level 1. Experts shared
videos and pictures of reefs from the MesoAmerican Reef that they believed exhibited full
biological integrity (McField and Kramer 2007).
Using only the 12 sites, the experts developed a narrative framework to assess the biological
condition for the forereef zone (i.e., the area along the seaward edge of the reef crest that slopes
into deeper water on the barrier or fringing reef type; Costa et al. 2013) of shallow-water linear
reefs of southwestern Puerto Rico based on physical structure of the reef, scleractinian corals and
their condition, fishes, gorgonians, sponges, large vertebrates, algae, seagrasses, and mobile
invertebrates. This approach resulted in attributes that were largely species-based (e.g., species
diversity, apex predators), with notable additions (e.g., physical structure, organism condition).
The experts identified four condition states: very good, good, fair, and poor; each with a
consistent well-defined narrative (Table 6). As expected, no sites were rated as very good;
however, the experts conceptualized the attributes for this Level, based on expert technical
expectations.
The workshop provided proof of concept that the BCG can be adapted for coral reef ecosystems.
The four condition levels represent BCG Levels. There were recognizable differences between
levels that the experts could collectively describe with narrative statements of biological integrity
that could be interpreted numerically, given appropriate survey data. EPA published a report
(Bradley et al. 2014b) that provides a detailed summary of the workshop.
Table 6. Descriptions of four condition categories (very good to poor) based on expert assessments of
individual sites (Bradley et al. 2014b). Continued on following pages.
Very Good
High rugosity or 3D structure; substantial reef built above bedrock; many irregular surfaces
provide habitat for fish; very clear water; no sediment, floes, or films
Physical
structure:
Good
Moderate to high rugosity; moderate reef built above bedrock; some irregular cover for fish
habitat; water slightly turbid; low sediment, floes, or films on substrate
Fair
Low rugosity: limited reef built above bedrock; erosion of reef structure obvious; water
turbid; more sediment accumulation, floes and films; Acropora usually gone or present as
rubble for recruitment substrate
Poor
Very low rugosity: no or little reef built above bedrock; no or low relief for fish habitat; very
turbid water; thick sediment film and thick floe covering bottom; no substrate for recruits
Corals:
Very Good
High species diversity including rare; large old colonies (Orbicella) with high tissue coverage;
balanced population structure (old and middle-sized colonies, recruits); Acropora thickets
present
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Good
Moderate coral diversity; large old colonies (Orbicella) with some tissue loss; varied
population structure (usually old colonies, few middle aged and some recruits); Acropora
thickets may be present; rare species absent
Fair
Reduced coral diversity; emergence of tolerant species, few, or no living, large old colonies
(Orbicella); Acropora thickets gone, large remnants mostly dead with long uncropped turf
algae
Poor
Absence of colonies, those present are small; only highly tolerant species with little or no live
tissue
Gorgonians:
Very Good
Gorgonians present but subdominant to corals
Good
Gorgonians more abundant than Levels 1-2
Fair
Gorgonians more abundant than Levels 1-3, replacing sensitive coral and sponge species
Poor
Small and sparse colonies; mostly small sea fans; often diseased
Sponges:
Very Good
Large autotrophic and highly sensitive sponges abundant
Good
Autotrophic species present but highly sensitive species missing
Fair
Mostly heterotrophic tolerant species and clionids
Poor
Heterotrophic sponges buried deep in sediment; highly tolerant species
Fish:
Very Good
Populations have balanced species abundances, sizes, and trophic interactions
Good
Decline of large apex predators (e.g., groupers, snappers) noticeable; small reef fishes more
abundant
Fair
Absence of small reef fishes (mostly Damselfish remain)
Poor
No large fishes; only a few tolerant species remain; lack of multiple trophic levels
Large
vertebrates:
Very Good
Large, long-lived species present and diverse (turtles, eels, sharks)
Good
Large, long-lived species locally extirpated (turtles, eels)
Fair
Large, long-lived species locally extirpated (turtles, eels)
Poor
Usually devoid of vertebrates other than fishes
Other
invertebrates:
Very Good
Diadema, lobster, small crustaceans, and polychaetes abundant; some large sensitive
anemone species present
Good
Diadema, lobster, small crustaceans, and polychaetes less abundant than Levels 1-2; large
sensitive anemone species absent
Fair
Diadema absent; Palythoa overgrowing corals; crustaceans, polychaetes and sensitive
anemones conspicuously absent
Poor
Few or no reef invertebrates; high abundance of sediment dwelling organisms such as mud-
dwelling polychaetes and holothurians
Algae:
Very Good
Crustose coralline algae abundant; turf algae present but cropped and grazed by Diadema
and herbivorous fish; low abundance of fleshy algae
Good
Crustose coralline algae present but less than Levels 1-2; turf algae present and longer, more
fleshy algae present than Levels 1-2
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Fair
Some coralline algae present but no crustose coralline algae; turf is uncropped, covered in
sediment; abundant fleshy algae (e.g., Dictyota) with high diversity
Poor
High cover of fleshy algae (Dictyota); complete absence of crustose coralline algae
Very Good
Low prevalence of disease and tumors; mostly live tissue on colonies
Organism
Condition:
Good
Disease and tumor presence slightly above background level; more colonies have irregular
tissue loss
Fair
Higher prevalence of diseased corals, sponges, gorgonians; evidence of high mortality;
usually less tissue than dead portions on colonies
Poor
High incidence of disease and low or no tissue coverage on small colonies of corals, sponges,
and gorgonians, if present
Benthic BCG Model
Why benthic organisms?
Reefs in Puerto Rico were historically dominated by the reef-building coral taxa Orbicella
annularis, Orbicella faveolata, Orbicella franksi, Agaricia agaricites, Montastraea cavernosa,
Porites astreoides and Colpophyllia natans and Acroporapalmata. Acroporapalmata and
Acropora cervicornis often formed dense, high-relief monospecific thickets; A. palmata in
shallow exposed forereef habitats and A. cervicornis on fore reefs and in shallow, protected
back-reefs (Morelock et al. 2001). Corals of the genus Orbicella are critical for the biodiversity
of fish and invertebrates (Beets and Friedlander 1998; Mumby et al. 2008). A. palmata and A.
cervicornis, listed as a threatened Caribbean species in 2006 under the National Marine Fisheries
Service (NMFS), also significantly contribute to reef growth, development, and also provide
essential habitat for fish (NOAA 2012).
Together with stony corals, octocorals, sponges, and gorgonians form the three-dimensional reef
habitat that supports a multitude of fish, crustaceans, mollusks, and other animals. Undisturbed
coral reef habitats possess a wide range of morphologies that provide habitable surface areas for
fish and other organisms (Alvarez-Filip et al. 2009; Lirman 2013). Crustose coralline algae are
also important because they bind coral skeletons and provide settling sites for coral larvae. Coral
reefs have also been shown to protect coastlines from erosion, flooding, and storm damage
(UNEP- WCMC 2006; WRI 2009; Principe et al. 2012; Ferrario et al. 2014; Yee et al. 2015).
Some organisms on the reef can kill and overgrow corals and crustose coralline algae, or prevent
coral larvae from settling (e.g., macroalgae, cyanobacteria and peyssonnelids). In thriving reefs,
these organisms are naturally present at low proportions of the reef community. Impacts to water
quality (e.g., increased nitrogen, phosphorous, iron) can enable these faster-growing organisms
32
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
to out-compete many other benthic species by overgrowth and reduction of larval settlement.
This can cause phase shifts to algal-dominated communities that are difficult to re-establish as
thriving reefs.
The benthic BCG focuses on the structural and functional importance of benthic organisms
including reef-building corals, algae, and other invertebrates, how they interact, and how they
indicate overall reef condition. Through the process of model development, all benthic organisms
were addressed as potential metrics of biological condition. However, as the model was refined
from narrative to numeric characteristics, coral species and metrics became prominent and other
benthic organisms were rarely used. We continue to describe all benthic organisms because the
narrative expectations were discussed by the experts, regardless of utility in the models.
Narrative Benthic Model
Data used in developing the narrative rules.
The narrative BCG rules were derived using data from the EPA 2010 and 2011 surveys. The reef
sites the experts assessed ranged from BCG Level 2 to BCG level 6 (fully degraded). A narrative
description of BCG Level 1 characteristics was developed and based on historical narrative
descriptions of reefs from the published literature; several included numeric estimates of percent
cover of various reef fauna (Appendix L, Weil 2020). Quantitative surveys of reef conditions
were uncommon and difficult before SCUBA technology was introduced in the 1960s, after
widespread human induced changes in reef structure were evident or suspected (Appendix L).
Many of the historical descriptions were relative to more recent declines in conditions resulting
from anthropogenic disturbances.
Data sheets for individual monitoring sites contained taxa lists, attribute-based metrics, coral
cover metrics, and metrics of other cover types. An example of the benthic information evaluated
by the expert panel for a single site is shown as screenshots of an Excel workbook (Figures 16
and 17). Metrics were calculated as in Appendix G.
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
ExerciselD
Samp0037
Assigned Level
Reasoning
Date
11/30/2011
Method
USEPA
ATTRIBUTE SUMMARY
BCG
Attribute
Number of Taxa
Colony
Density (#/m2)
% Cover (2D,
live)
% of Taxa
% of Colonies
% of total CSA
(2D)
I
0
0.00
0.0
0
0
0
II
1
0.04
0.1
13
2
1
III
1
0.04
0.1
13
2
1
IV
1
0.16
0.2
13
10
3
V
5
1.44
6.8
63
86
95
VI
o
0.00
0.0
0
0
0
X
0
0.00
0.0
0
0
0
Total
8
1.68
7.2
TAXA LIST
3D Av Total
3D Av Live
2D Av Live
BCG
Scie ntific Name
Colony
% Mortality
3D Total Surf
3D Live Surf
% Cover (2D,
Colony Surf
Colony Surf
Colony Surf
Attribute
De nsity (#/m2)
Area (cm2/m2)
Area (cm2/m2)
live)
Area
(cm2/colony)
Area (live
cm2/coIony)
Area (live
cm2/coIony)
TOTALS
1.68
1503.2
1153.7
7.2
IV
Agaricia hurmlis
0.16
0.0
16.5
16.5
0.2
103.1
103.1
137.4
II
Isophyllia sinuosa
0.04
0.0
19.2
19.2
0.1
481.1
481.1
176.7
III
Madracis decactis
0.04
35.0
37.7
24.5
0.1
942.5
612.6
204.2
Pontes astreoides
0.52
28.2
133.4
95.7
0.7
256.6
184.1
127.6
Pseudodiploria strigosa
0.16
16.0
227.4
190.9
1.1
1421.1
1193.2
674.2
Siderastrea radians
0.04
0.0
3.1
3.1
0.0
77.0
77.0
78.5
Siderastrea siderea
0.64
24.5
1049.8
792.1
5.0
1640.4
1237.7
779.4
Stephanocoenia intersepta
0.08
27.8
16.1
11.6
0.1
201.3
145.3
94.2
Figure 16. Screenshot of benthic organism data sheet (MS Excel) used in assessing EP/
data. This view shows the taxa list, including the assigned BCG attribute, scientific and
density, % mortality, and various calculated metrics.
2010 and 2011
common names,
STATION AND SAMPLE CHARACTERISTICS
StationID
PR11-28
Re gion
Guayanilla/Jobos
Latitude
17.9578
Longitude
-66.5899
ReefType
Linear Reef
Depth (Coral, ft)
19
Distance (shore, km)
0.78
Distance (shelf, km)
5.28
Distance (disturbance)
22.79
Sediment Threat
0.00
Rugosity Index (EPA)
1.208
Diadema (#/100 m2)
0
Coral Density (col/m2)
1.68
Height sd (cm)
6.24
Coral 2D Live Cover (%)
7.2%
3D live surface area (% of col area)
76.7%
CSA Total (3D, cmW)
1503.2
CSA Total Live (3D, cm2/m2)
1153.7
Sponge Density (#/m2)
3
Gorgonia Density (#/m2)
2.2
Sponge Morph Richness (5m2)
2
Gorgonia Morph Richness (5m2)
2
Fish, Richness (taxa/100m2)
15
Figure 17. Screenshot of Excel worksheet: site and sample characteristics used in assessing EPA 2010
and 2011 data, with sample metrics.
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
Reef Classification
The selection of habitat classification category for model development is essential for reliable,
accurate assessments and ultimately for reliable, robust monitoring and assessment.
Classification is critical for establishing the benchmark, or reference, for assessing condition of a
site. A robust classification approach enables discrimination between assemblage changes due to
natural variability and changes due to anthropogenic disturbance. To establish the foundation for
the BCG model, the expert panel selected a habitat classification framework as the basis for rule
development and to guide future monitoring. Coral reef environments have distinct horizontal
and vertical zones created by differences in depth, wave and current energy, temperature, and
light (Zitello et al. 2009). Important physical traits to consider while determining expected
species composition of a site include reef zones, geology, sea level change, and sediment
exposure (Hubbard 1997; Hubbard et al. 2009; Costa et al. 2009; 2013; Zitello et al. 2009). The
Coastal and Marine Ecological Classification Standard (CMECS) developed by the Marine and
Coastal Spatial Data Subcommittee Federal Geographic Data Committee (FGDC 2012), states:
"All coral reef environments contain distinct horizontal and vertical zones created by differences
in depth, morphology, wave and current energy, temperature, and light (Zitello et al. 2009)."
Goreau and Land (1974) developed a morphology-based reef classification for Discovery Bay,
Jamaica that is common for Caribbean reefs: shallow reef, fore reef, forereef slope, deep fore
reef, and the reef wall.
The panel's consensus was to use the NOAA Benthic Habitat Reef Classification Scheme (Costa
et al. 2009, 2013); a hierarchical structure that classifies benthic habitat into reef types,
geographic zones, and geomorphological structures. Only sites classified as fore reefs were used
in this model development, which closely aligned with the data sets. The forereef zone is defined
as the area along the seaward edge of the reef crest that slopes into deeper water on the barrier or
fringing reef type (Costa et al. 2013). Features associated with a non-emergent reef crest but still
having a seaward-facing slope that was significantly greater than the slope of the bank/shelf,
were also designated as fore reef. The fore reefs were further divided into two zones; one was
dominated by Orbicella species, and the other was hard bottom primarily colonized by
gorgonians (Williams et al. 2015). The former zone was emphasized in this study.
Coral BCG Attributes
The BCG Attribute categories provide a basis for summing up shared characteristics among taxa
and for some experts can facilitate examining the structure and function of sample composition
(EPA 2016). The benthic experts had lengthy discussions about the terminology used in the BCG
Attribute definitions (Appendix B). They agreed that abundance, dominance, frequency, vitality,
fidelity, and natural variations or cycles were useful traits for identifying indicator species. The
experts felt that the term "ubiquitous" (especially for Attribute IV) means a species is observed
35
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
on every dive at least once at each site. It is not ubiquitous if the surveyor must search for it. The
concept is that the species is widely distributed within a given habitat.
The coral experts assigned BCG Attributes to 48 scleractinian and hydrozoan coral species found
in the Western Atlantic based on their known sensitivity and tolerance to human-induced
stressors or their origin in the Caribbean region. They identified elevated sea temperature
anomalies and land-based pollution (e.g., sediment, nutrients, and contaminants) as the most
critical stressors on Caribbean stony corals. Because studies documenting the tolerances of coral
species to different anthropogenic stressors are limited, assignments were based on expert
knowledge and panel consensus. The rationale for the decisions made on attribute assignments
was fully documented. The experts agreed stressors must be independently evaluated, because
there is no evidence to suggest a given species would have the same sensitivity to multiple
stressors. They assigned an attribute to each species for elevated temperature exposure (as
happens before a bleaching episode) and for sediment exposure as a surrogate for land-based
pollution (Appendix M). For the final attribute assignments to represent a general stressor
gradient and to be used in metrics and models, the attributes assigned for sediments were used.
The experts did not associate any species with Attribute I, only two species were associated with
Attribute II (Isophyllia rigida and Isophyllia sinuosa), and one species was associated with
Attribute VI (non-native taxa). Twenty-three coral species were not associated with attributes
because little is known of their sensitivity. Assignments to other species are as follows: Attribute
III - 9 species, Attribute IV - 22 species, Attribute V - 13 species.
Narrative Descriptions of BCG Levels
The benthic experts used 46 forereef sites from the 2010 to 2011 Puerto Rico surveys to calibrate
the narrative model for the BCG Levels derived from 358 individual expert ratings (an average
of 8 experts per sample). The experts developed narrative decision rules for each BCG Level
based on perceived patterns of decreasing total percent coral cover, accompanied by higher
percentages of tissue loss on individual coral colonies with increasing BCG Level (Table 7). As
the reef condition decreased with deteriorating environmental conditions, moving down the
gradient from BCG Levels 2, 3 or 4 to Levels 5 and 6, reef rugosity decreased, mortality of coral
colonies increased, and disease prevalence increased. Algal composition also changed as the
BCG Levels changed. In better conditions, crustose coralline algae were more abundant,
however with degradation turf and fleshy algae increased. Algal characteristics were determined
from videos and photos as no algal surveys were performed. As reefs degraded, the number of
rules or descriptors of condition decreased until BCG Level 6 was defined by virtual absence of
most taxa found in BCG Levels 1-5.
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
Table 7. Benthic BCG Narrative Rules. Continued on following pages.
BCG Level2 (minimally disturbed)
Stony corals
• >45% live cover of coral in fore reef habitat
• Minimal recent mortality in large reef-building genera (Orbicella,
Pseudodiploria, Colpophyllia, Acropora, Dendrogyra)
• Normal frequency distribution of colony sizes within each species size range to
include large, medium, and small colonies (> 4 cm) and presence of recruits (< 4
cm)
• Species composition and diversity: composed of sensitive, rare species
(Isophyllia, Isophyllastrea, Mycetophyllia, Eusmilia, Scolymia) present in
appropriate habitat type
• Very low or just background levels of disease, tissue and skeletal anomalies,
and bleaching
• Orbicella (fore reef), Acropora (back reef, reef crest) colonies dominant reef
structure within respective zones
Rugosity
• High rugosity resulting from large living coral colonies, producing spatial and
topographical complexity
Macroinvertebrates
• Diadema abundant
• Reef macroinvertebrates (e.g., Lobsters, crabs) common and abundant
• Low levels of invertebrate coral predators (Coralliophila spp, Hermodice spp)
Algae
• Minimal fleshy, filamentous, and cyanobacterial algae present
• Crustose coralline algae present, with some turf algae
Sponges
• Phototrophic sponges dominate
• Low frequency of Clionid boring sponges
Water Quality
• High clarity, low particulates
BCG Level 3
Stony corals
• >25% live cover of coral in forereef habitat
• Higher % of tissue loss with signs of recent mortality especially on large reef-
building genera (Orbicella, Pseudodiploria, Colpophyllia, Acropora,
Dendrogyra)
• Frequency distribution of colony sizes within each species size range starting to
become skewed to include fewer medium and small colonies (> 4 cm) and
lower number of recruits than expected (< 4 cm)
• Species composition and diversity: sensitive, rare species present in appropriate
habitat
37
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
•
Low to moderate levels of disease and bleaching
•
Orbicellct and Acroporct colonies still dominant (within respective reef
geomorphological zones)
•
Moderate to high rugosity or reef structure resulting from large living reef-
Rugosity
forming and dead coral colonies, producing spatial complexity (or
topographical heterogeneity)
Macroinvertebrates
•
•
Dictdema present
Reef macroinvertebrates (e.g., lobsters, crabs) present
Algae
•
•
Minimal presence of fleshy, filamentous, and cyanobacterial algae cover
Crustose coralline and turf algae present
Sponges
•
•
Phototrophic sponges present
Low cover and abundance of Clionid boring sponges
Water Quality
•
Moderate quality and medium water clarity
BCG Level 4
•
>15% live cover of coral in appropriate habitat
•
Moderate amount of recent mortality on reef-building genera (Orbicellct,
Pseudodiploria, Colpophyllict, Acroporct, Dendrogvrct)
•
Mix of colony sizes: large colonies may be absent, primarily medium and small
colonies; low number of recruits
Stony corals
•
Species composition and diversity: sensitive species may be absent (Agaricia,
Mycetophyllia, Colpophyllict, etc.), more tolerant spp present (Montastraea
cavernosa, Siderastrea siderea, Porites ctslreoides): at least some reef-building
corals present but not primarily dominant (Orbicellct)
•
Moderate to high levels of disease and potential bleaching on corals and sea
fans/branching gorgonians
Rugosity
•
Usually lower rugosity due to old, mostly dead coral structure
Macroinvertebrates
•
Palythoa may be present, but not dominant
Algae
•
Moderate to high amount of fleshy, filamentous, and cyanobacterial algae
cover
Sponges
•
Moderate cover and abundance of Clionid boring sponges
•
Quality could be poor with low clarity and high particulates
Water Quality
38
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
BCG Level 5
Stony corals
>1% live cover of coral in appropriate habitat but less than 15%
High mortality on most colonies, present primarily on small colonies
Rugosity
Low rugosity composed of mostly dead and eroded coral structure
Algae
Coral cover replaced by fleshy, filamentous, and cyanobacterial algae
Macroinvertebrates
Pctlythoa dominant
Sponges
Highest presence of Clionid boring sponges
Non-phototrophic sponges dominant
Water Quality
Probably persistently poor quality, low water clarity, high turbidity
Numeric Model - Calibration and Validation
Developing the numeric rules.
In developing the numeric rules, bioassessment data from NOAA NCRMP 2013 -2015 surveys
in Puerto Rico and the USVI were used. While the NCRMP field sampling protocols were
similar to those described above for the EPA Puerto Rico data, there are some important
differences. For example, EPA did not use the Line-Point Intercept method. Also, NOAA did not
include morphology and sizes of sponges and gorgonians as was done in the EPA DEMO
surveys, and used a microheterogeneity approach (MRV) for reef rugosity while sampling down
to 100-foot depths. The expert opinion was that the LPI data including the benthic coverage was
more important than the sponge and gorgonian 3D measurements, and because the NOAA
method was intended for continued application in monitoring programs, calibration of the
numeric model was based on the NOAA data.
The deepest sites in the data set were approximately 100 feet deep, which is the maximum
practical depth for scuba diver-based underwater monitoring (Brylske 2006). Within this depth
range, the experts suggested that differences in reef structure occurred at approximately 40 feet
deep, as a result of gradual differences in light penetration and wave action. However, when
experts attempted to develop depth-dependent rules, biological differences among the depth
strata were not distinguishable. Therefore, the sample sites used in model development were
from depths from the entire 100-foot depth range. Differences in natural expectations and
assessment results relative to depth were assessed during and after the BCG rating and prediction
processes. Data sheets for individual sites included site and sample information (including site
depth) with taxa lists, attribute-based metrics, coral cover metrics, and metrics of other cover
types (Figures 18 and 19).
39
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2.021
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data: This view shows the taxa list, including the assigned BCG attribute, scientific and common names,
density, % mortality, and various calculated metrics.
40
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
STATION AND SAMPLE CHARACTERISTICS LPI (% Cover)
Station ID
M78
SEAGRASS
0
Latitude
18.295581
BARE SUBSTRATE
5
Longitude
-64.750031
SPONGES
2
Distance (shore, kin)
Porifera spp
2
Distance (shelf, km)
Cliona spp
0
NOAA Habitat Type (Kendall)
MSROPENPTRFDEEP
SCLERACTINIAN CORALS
38
Habitat Type by Diver
OCTOCORALS
4
Depth (min-max) (feet)
86-95
Encrusting Gorgonians
3
Depth Strata
DEEP
Branched Gorgonians
1
Microheterogeneity
0.750
ZOOANTHIDS
0
% Substrate Types
96%Hard/4% Soft
Palvthoa spp
0
LPI (% Cover)
OTHER SPP
0
ALGAL GROUPS
51
Mobile Invertebrates
Cyanobacteria/Diatoms
3
Diadema antillarum
0
Cyanobacteria spp
3
Aliger gigas
0
Macro Fleshy
36
Pamilirus argus
8
Dictvota spp
7
ESA Taxa (Presence/Absence)
Lobophora spp
29
Acropora cen'icornis
0
Other Fleshy spp
0
Acropora palmata
0
Macro Calcareous
5
Agaricia lamarcki
0
Halimeda spp
0
Dendrogyra cylindrus
0
Peysonnellia
5
Dichocoenia stokesii
0
Other Calcareous spp
0
Mycetophyllia ferox
0
Crustose Coralline
3
Orbicella annularis
0
Ramicrusta
3
Orbicella faveolata
1
Turf Algae
4
Orbicella franksi
1
Turf Algae Free of Sediment
0
Fish
Turf Algae with Sediment
4
Fish, Richness
54
Fish, Diversity
1.482
Figure 19. Example data from Excel worksheet: Station and sample characteristics used in assessing
NOAA NCRMP data. This view shows information about the station and metrics calculated at the site
scale.
41
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
In webinars and the final workshop, experts reviewed 72 NCRMP sites, resulting in BCG Level
assignments for 57 sites. Initially 66 sites were considered but those that lacked both LPI and
DEMO data, or that were not valid forereef habitat (gorgonian plains or bedrock), were not used
in model development. The 57 sites were from Puerto Rico and the USVI and included deep and
shallow habitats (Table 8).
Table 8. Numbers of sites used for development of the benthic BCXJ model, showing location, depth, and.
sampling method.
BCG Level
3
4
5
St. Thomas/
St. John
16
10
2
Island
St. Croix
3
11
3
Puerto Rico
0
13
8
Shallow (<40')
2
12
11
Depth
Deep (>40')
17
22
2
LPI and DEMO
17
28
12
Method
LPI only
2
6
1
From these sites, the metrics were tested for discrimination between BCG Levels. Each metric
was plotted to show its values distributed among sites within BCG Levels rated by its experts.
The experts used the plots to confirm the narrative rules and to the analyst tested quantitative rule
thresholds (Figures 20-22). The analyst formulated model drafts by applying the rule thresholds
in combination at each Level. The experts reviewed and revised the drafts iteratively until the
predictive BCG model was finalized (Table 9).
When separation between Levels showed that the better Level had consistently better metric
values, the rule was developed so that there were few errors in identifying the better Level. In
these cases (like the rules for Level 2), all the rules were required and the rules were combined
with "AND" logic. In other cases, when the panel was clearly considering an either/or situation,
alternative rules were applied using "OR" logic. Panelists were not always aware they did this -
it became apparent when the draft numeric model yielded poorer BCG levels than the panel, i.e.,
the numeric model was too stringent. Upon discussion, the panel generally agreed to an "OR"
logic for combining the given rules (like the rules for Level 4).
42
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
Combination rules at Level 2 of the benthic BCG model are that all the rules are required,
meaning the "AND" logic is applied (Rule 1 and 2 and 3 and 4). The experts expected that all the
rule conditions must be attained for a site to be exhibit Level 2 conditions. This is derived
numerically by calculating the membership value for each rule then finding the minimum of
those four values. The minimum rule membership value is the site membership for Level 2.
At Level 3, five rules were included in the model. The experts expressed that the first four rules
were required. However, they also expressed that if the percent live Orbicella cover (DEMO)
was high, it was a more meaningful indication of Level 3 conditions than the other rules. In this
case, the minimum membership value of the four rules is compared to the membership value for
the fifth rule and the maximum of that comparison is the site membership in Level 3.
At Level 4, seven rules were used to describe biological conditions. However, because of diverse
Level 4 conditions, all of which were recognizable by the experts, all the rules were not expected
to indicate Level 4 at the same site. All the metrics used in the rules showed considerable overlap
with metric values of Level 5 sites. Therefore, if only three rules indicated Level 4, then the site
satisfied requirements for Level 4. Hardly any of the Level 5 sites could pass three of the seven
rules. To calculate the site membership in Level 4, The best three membership rules were
compared and the minimum of these was used as the site membership in Level 4.
At Level 5, three rules were defined, two of which needed to be satisfied. In other words, one
rule could be discounted; the one with the lowest membership value. Because the rules are
applied in order from Level 2 to Level 5, any site not meeting any of the Level 5 rules is
automatically predicted to be Level 6.
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
50
40
30
O 20
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Figure 20. Distribution of metrics used in model rules for discriminating Benthic BCG Levels 3 and 4,
showing the rule thresholds (dashed line) and ranges (color-shaded region). Membership values are
calculated as 1.0 if the metric value is better than the blue range, 0.0 if worse than the red region, and
interpolated between 0.0 and 1.0 if within the shaded region. Distributions include the median (central
square), interquartile range (rectangular box), non-outlier ranges (whiskers), and outliers (circular
marks).
44
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
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Figure 21. Distribution of metrics used in model rules for discriminating Benthic BCG Levels 4 and 5,
showing the rule thresholds (dashed line) and ranges (color-shaded region). Membership values are
calculated as 1.0 if the metric value is better than the blue range, 0.0 if worse than the red region, and
interpolated between 0.0 and 1.0 if within the shaded region. Distributions include the median (central
square), interquartile range (rectangular box), non-outlier ranges (whiskers), outliers (circular marks),
and extremes (stars).
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The BCG for Puerto Rico and USVI Coral Reefs
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16
14
Q. 12
10
Figure 22. Distribution of metrics used in model rules for discriminating Benthic BCG Levels 5 and 6,
showing the rule thresholds (dashed line) and ranges (color-shaded region). Membership values are
calculated as 1.0 if the metric value is better than the blue range, 0.0 if worse than the red region, and
interpolated between 0.0 and 1.0 if within the shaded region. Distributions include the median (central
square), interquartile range (rectangular box), non-outlier ranges (whiskers), outliers (circular marks),
and extremes (stars).
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Table 9. BCG predictive model rules for the coral reefbenthic assemblage (first generation), showing the
Level definition (details in Appendix C), narrative rules, quantitative rules, and rule combinations. In
application, sample metrics were tested first at Level 2. Level 3 rules were applied next, but only if Level
2 rules were not met with 100% membership. The rules were likewise applied at Levels 4 and 5 until site
membership was established. If rules were not met at Level 5. then the site was determined to be Level 6
by de fault. In the quantitative rules, the numeric range is shown so that partial membership can be
determined for each rule at each Level. Continued on following pages.
BCG Level 1
Definition: Natural or native condition—native structural,
functional, and taxonomic integrity is preserved; ecosystem
function is preserved within the range of natural variability
Narrative: Level 1 and 2 narratives were combined for the coral
reef exercise; no quantitative rules were developed for Level 1
BCG Level 2
Definition: Minimal changes in structure of the biotic community
and minimal changes in ecosystem function—virtually all native
taxa are maintained with some changes in biomass and/or
abundance; ecosystem functions are fully maintained within the
range of natural variability
Narrative: Coral species are highly diverse, including rare
species; large old colonies of reef-building species (e.g.,
Orbicello) with high live tissue cover; balanced population
structure (old and middle-aged colonies, recruits); Acroporids
present
BCG Metrics
Narrative Rules
Quantitative Rules
Percent Coral Cover (LPI)
Coral cover high
>40% (35 -45)a
Percent live coral cover
(DEMO)
Coral cover high
>30% (20 - 40)
Percent coral mortality
(DEMO)
Low percentage of tissue loss (2-D
and 3-D cover)
<10% (5-15) b
Percent live cover of large,
reef-building coral species
(DEMO)
Substantial coverage of reef-
building taxa
>30% (25 -35)c
Level 2 Combination: Minimum of 4 rules d
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BCG Level 3
Definition: Evident changes in structure of the biotic community
and minimal changes in ecosystem function—Some changes in
structure due to loss of some rare native taxa; shifts in relative
abundance of taxa but intermediate sensitive taxa are common and
abundant; ecosystem functions are fully maintained through
redundant attributes of the system
Narrative: Moderate coral diversity; large old colonies
(Orbicella) with some tissue loss; varied population structure
(usually old colonies, few middle-aged, and some recruitment);
Acropora thickets may be present; rare species absent
BCG Metrics
Narrative Rales
Quantitative Rales
Percent Coral Cover (LPI)
Moderate coral cover
>20% (15-25)
Total Coral Richness (LPI)
Moderate coral richness
> 4 species (3-5)
Non-tolerant Coral Richness
(LPI)
Non-tolerant BCG Attribute I, II,
III, IV taxa are present
> 2 species (1-3)e
Bare Substrate and Turf with
Sediment Cover (LPI)
Minimal presence of unproductive
and sedimented cover
< 30% (20-40)
Percent live Orbicella cover
(DEMO)
Orbicella colonies are important
>20% (15-25)
Level 3 Combination: Minimum of first 4 rules or the Orbicella rule f
BCG Level 4
Definition: Moderate changes in structure of the biotic
community and minimal changes in ecosystem function—
moderate changes in structure due to replacement of some
intermediate sensitive taxa by more tolerant taxa, but reproducing
populations of some sensitive taxa are maintained; overall
balanced distribution of all expected major groups; ecosystem
functions largely maintained through redundant attributes
Narrative: Reduced coral diversity compared to Level 3;
emergence of tolerant species; few or no large old colonies
(Orbicella), or mostly dead; Acropora thickets gone
BCG Metrics
Narrative Rales
Quantitative Rales
Percent Coral Cover (LPI)
Low to moderate total coral cover
>15% (10-20)
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Non-tolerant Coral Cover (LPI)
Low to moderate non-tolerant BCG
Attribute I, II, III, IV cover
>5% (0-10)e
Live Coral Cover (DEMO)
Low to moderate total coral cover
(based on surface area 3-D)
> 2000 cm2/m2 (1000-3000)
Percent live Orbicella cover
(DEMO)
Orbicella present, though sparse
>2.5% (0-5)
Percent Orbicella cover (LPI)
Orbicella present, though sparse
>2.5% (0-5)
Density of medium or large
colonies (DEMO)
Medium size colonies (max D >
20cm) present in the transect
> 7.5 colonies (5-10)
Bare Substrate and Turf with
Sediment Cover (LPI)
Moderate presence of unproductive
and sedimented cover
< 40% (30-50) g
Level 4 Combination: Minimum of the three highest membership values h
BCG Level 5
Definition: Major changes in structure of the biotic community
and moderate changes in ecosystem function—Sensitive taxa are
markedly diminished; conspicuously unbalanced distribution of
major groups from that expected; organism condition shows signs
of physiological stress; system function shows reduced
complexity and redundancy; increased build-up or export of
unused materials
Narrative: Severely reduced coral diversity, minimal presence of
colonies, tolerant species dominant
BCG Metrics
Narrative Rales
Quantitative Rales
Percent Coral Cover (LPI)
At least some living coral
> 5% (2-8)1
Density of Colonies (DEMO)
At least some living coral
> 1 colony/m2 (1 -2)
Non-tolerant Taxa Abundance
Attribute I, II, III, or IV taxa are
present
> 1 species (0-2)k
Level 5 Combination: Minimum of the two highest membership values 1
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The BCG for Puerto Rico and USVI Coral Reefs September 15, 2021
BCG Level 6
Definition: Severe changes in structure of the biotic community
and major loss of ecosystem function. Extreme changes in
structure; wholesale changes in taxonomic composition; extreme
alterations from normal densities and distributions; organism
condition is often poor; ecosystem functions are severely altered.
Narrative: Absence of colonies; those present are small; only
tolerant species; little or no tissue
Rules: No rules were established for Level 6. By default, failure
of Level 5 rules results in a Level 6 model prediction.
Table 9 notes
a. Though the rules for Level 2 were conceptual, the expert panel suggested that total coral cover
should be limited to functional/sensitive taxa. The specific rule might address BCG Attribute
assignment; specific sensitivities to bleaching, turbidity, and disease; large reef-building coral;
or observed large colony size. This comment prompted further refinements and descriptions of
coral traits and attributes (see Weil 2019).
b. Although this rule is still conceptual, the expert panel questioned whether they had adequately
described expectations for coral mortality in Level 2. It was suggested that perhaps the
expectation of <5-15% mortality was too strict. Also, the specification of old or new mortality
might be used to further refine the rule.
c. Large Reef-Building Corals (LRBC) include the genera Orbicellct, Acropora, Diploria,
Pseudodiploria, Colpophyllict, and Dendrogyra, and species ofMontastraea cavernosa, and
Siderastrea siderea. Orbicella and Acropora are the major reef building coral genera in the
Caribbean.
d. At the workshop, the experts expressed that the size structure of the coral assemblage might be
used to recognize functional Level 2 conditions. The specific size structure metrics (species,
size classes, and numeric thresholds) were not detailed during the meeting and no new
conceptual rule was developed. Rather, this expectation might be explored in continued research
efforts on size expectations per species, recruitment, and size diversity.
e. Attribute I taxa were included because, though they are not specifically non-tolerant, they are in
some way specialists, endemic, or long-living.
f. Live 2D cover of Orbicella does not need to be high for a reef to be Level 3 (if Orbicella cover
is <20%, the minimum of the other rules is the predicted membership of Level 4). However, if
Orbicella cover is >20%, then the Orbicella rule alone can override the minimum of the other
four rules.
g. The expert panel expressed that a rule regarding algae should be applied in Level 4. The rule on
bare substrate and turf algae with sediment was added compared to the previous model draft.
h. The expert panel suggested that three rules should be met instead of only two that were required
in the previous model draft. This rule on its own would result in additional model errors, but
when also adding the bare substrate and turf with sediment rule, no additional model errors
result. The Level 4 rule thresholds were established to identify possible Level 4 conditions,
rather than to screen out Level 5 conditions, so only a few indications are required.
i. Experts suggested raising the % LPI cover threshold to 5% instead of the previous threshold of
2%. Raising the LPI % cover threshold resulted in 5 errors at Level 5 (predicting Level 6
conditions for this rule).
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The BCG for Puerto Rico and USVI Coral Reefs
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j. Experts considered that maybe the threshold should be raised. However, no quantitative
threshold was proposed, and additional errors may be introduced when raising the threshold, so
no change was made.
k. Experts suggested adding a rule about sensitive taxa richness. This rule was added.
1. When the Number of Non-tolerant Tax rule is added and the best 2 of 3 rules are evaluated, there
are 2 more errors in comparison to the original rule set, which required evaluation of two out of
two rules.
Of the 57 evaluated sites that had both LPI and Demo survey data, the model (first generation)
predicted the same BCG Level as assigned by the experts for 48 sites (Table 10). The model
accuracy is therefore 84% (90% confidence interval: 74 - 92%). No prediction was more than
one Level different than the assignment. There were 9 predictions counted as correct that were
tied between Levels either in expert assignment or model prediction. For 4 sites, the prediction
was counted as an error although the difference from the assignment was very similar. For
example, an assigned Level 3- is very similar to a predicted Level 4+, but because they are in
different Levels, the prediction was counted as an error.
Table 10. Comparison of expert assignment of BCG Levels for benthic calibration of reef sites compared
to BCG Levels predicted by the model indicating where there was agreement (shaded cells) and
disagreement (unshaded cells).
BCG Model Predictions - Benthic Calibration
Rating
Total #
Rated
2
3-4
3
tie
4
4-5
tie
5-6
tie
6
s—»
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
160
140
120
w
0)
100
CO
DC
o 80
CD
"§ 60
Z
40
20
0
-2 -1.33 -0.67 0 0.67 1.33
-1.67 -1 -0.33 0.33 1 1.67
Rating Difference from Median
Figure 23. Individual rating precision for calibration sites, measured as the difference between the
median BCG Level for a site and the expert's individual rating. Increments are 1/3 to represent whole,
"+ and "- " ratings.
Benthic Model Validation
To validate the benthic model with an independent set of forereef sites, 18 valid reef sites were
reviewed by nine experts. All but two of the 18 ratings (median per site) matched the model
prediction (Table 11), resulting in 89% agreement (90% confidence interval: 69 - 98%). This
compares with an 84% agreement rate for the calibration sites and indicates successful validation
of the model. Ties in either the expert ratings or the model predictions were deemed correct for
adjacent Levels. As seen in the calibration data, the individual ratings were precisely centered
around the median rating for each site (Figure 24).
Of the two sites where the expert median rating did not match the model prediction, one was a
straight disagreement where the experts perceived conditions that were Level 5, and the model
predicted a Level 4 condition. The other disagreement between ratings and the prediction was for
a site that was rated as a Level 4 but was predicted as a Level 3 because there was more than
25% coverage of live Orbicella colonies. Though other rules at Level 3 failed, this rule was
applied using "or" logic that over-ruled the others. Despite these disagreements, the experts
considered the model to be adequately validated.
36%
1%%
1$%
12%
5°/o
8^0
3 . o# w .1^0
4%o
2%o
1^0
, , i .—y—i—e_i
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The BCG for Puerto Rico and USVI Coral Reefs
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Table 11. Comparison of expert ratings of BCG Levels for benthic validation of reef sites compared to
BCG Levels predicted by the model showing where there was agreement (shaded cells) and disagreement
(unshaded cells).
BCG Model Predictions
Benthic Validation
Rating
Total #
Rated
2
3
3-4 tie
4
4-5 tie
5
5-6 tie
6
2
0
0
0
0
0
0
0
0
0
s—»
C
CD
S
3
1
0
0
1
0
0
0
0
0
c
op
cr
3-4 tie
1
0
1
0
0
0
0
0
0
<
o
u
PQ
t:
(L)
a
w
4
8
0
1
0
6
1
0
0
0
4-5 tie
0
0
0
0
0
0
0
0
0
5
3
0
0
0
1
0
2
0
0
6
2
0
0
0
0
0
0
0
2
70
60
& 50
c
ro
a: 40
4—
0
o3 30
-Q
E
1 20
10
0
-1.67 -1.33 -1 -0.67 -0.33 0 0.33 0.67 1 1.33
Rating Difference from Median
Figure 24. Individual rating precision for validation sites, measured as the difference between the median
BCG Level for a site and the expert's individual rating. Increments are 1/3 to represent whole, "+ and
"- " ratings.
M-
M-
M-
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Benthie Model Discussion
The experts determined that the first generation benthie BCG model can be used to quantitively
interpret Caribbean reef conditions ranging from BCG Level 3 to BCG Level 6. The model was
based on expert derived numeric decisions rules. There were no Level 2 conditions observed in
the NCRMP calibration data used to develop the numeric rules. However, the experts proposed
conceptual Level 2 narrative rules based on a limited set of Level 2 EPA sites that the experts
observed while developing the narrative model and drawing upon their decades of field
experience and knowledge of historical descriptions. The conceptual rules for BCG Level 2 can
be used to identify sites that may be of higher quality than the BCG Level 3 rules. A practitioner
can make note of a site where the taxa appeared to match a narrative BCG Level 2 condition, and
they may consider whether those taxa might be candidate species for protection or conservation
based on a follow up assessment.
Level 3 quantitative rules include four LPI metrics and one DEMO metric. The rules in Level 3
are applied as an "either/or" rule. Either all four LPI metrics or the single DEMO metric can be
used to assign a site to BCG Level 3. The DEMO rule is defined as high Orbicella cover, which
was considered by the experts to be a dependable metric of relatively undisturbed reef
conditions. At Level 3, the expected characteristics are ample coral cover of various species,
most of which are sensitive or moderately tolerant to sediment stress, and non-coral cover that is
productive (low benthie coverage of bare substrate or sedimented algal turf).
To be assigned to Level 4, only three of the seven rules must pass for a site, because each metric
at Level 4 was more variable, and there were different combinations of metrics that indicated a
reef matched the description of BCG Level 4. The experts saw signs of fair conditions in the
midst of some poor indications. Moderate LPI cover and Orbicella cover were expected at Level
4, but not at values as high as expected at Level 3.
For sites to be assigned to Level 5 rather than 6, there must be at least some live coral cover, and
some coral cover comprised of moderately tolerant coral species. If a site did not meet BCG
level 5 rules, then it was assigned to BCG Level 6.
This numeric benthie BCG model was accurate in predicting the experts' median ratings for 84%
of the calibration data and 89% of the validation data. The model replicated the expert consensus
within one BCG Level for 100% of sites. This degree of accuracy was acceptable to the experts,
who considered a one Level difference to be minimal and infrequent. A table listing the metrics
used in the BCG Benthie Model rules and ecological/biological importance of each metric is
provided in Appendix N.
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BCG Attribute VII: Organism Condition for Hard Corals
The coral experts discussed hard coral health and biological condition as possible metrics that
might be used in model rules. Weil 2020 (Appendix R) and Rogers et al. 2020 (Appendix T)
contend that the species composition of coral reef ecosystems is of less importance than the
condition of the colonies and their responses documented by long-term monitoring (with the
exception of Acropora species (spp.) and Orbicella spp.). The condition and health of
framework-building corals are important because they are colonial, modular organisms that
create the architecture of the reef and can persist for decades in spite of partial mortality to
individual colonies. Alternatively, the metrics used in freshwater systems are often species
absence or presence and abundance of solitary organisms that live as independent units.
The presence and condition of Acropora spp. and Orbicella spp. are important to evaluate the
overall condition and status of a reef area. Both are the most important and prolific genera for
building the architecture of coral reef structures in the Caribbean and Western Atlantic. The
presence of "standing dead" A. palmata structure provides profound insights into the ecological
history of a reef site. A. palmata is typically confined to depths <10m. Orbicella spp. compose
structure in deeper reefs and under environmental conditions not conducive for Acroporid
growth and survival. Although the number of coral species (diversity, richness) is informative, it
is not as crucial as defining coral condition (Rogers et al. 2020).
Rogers et al. (2020) recommended that an indicator for coral health or condition be developed
and tested as a potential metric that could be included at all Levels of the numeric BCG model.
The specific recommendation for reef corals was disease prevalence for all tissue loss diseases
affecting the coral assemblage at each Level. The tentative guidelines proposed for
consideration and further discussion are: BCG Level 1 (0-1 percent); BCG Level 2 (> 1-5
percent); BCG Level 3 (>5-10 percent); BCG Level 4 (>10-20 percent); BCG Level 5 (>20-30
percent); and BCG Level 6 (>30 percent).
Specific measures for health indicators recommended by experts, and the Weil (2020) and
Rogers et al. (2020) reports included: incidence and prevalence of specific coral diseases and
bleaching, recording which species are affected, percent coral mortality that distinguishes
between recent and old colony mortality, vitality of colonies (percent of the colony that is tissue
growing over skeleton), and percent and status of diseased and healthy tissue. This process could
begin by examining several bioassessment protocols that estimate coral condition used in the
USVI Territorial Coral Reef Monitoring Program (TCRMP) (Smith et al. 2008, 2013) and the
Atlantic and Gulf Rapid Reef Assessment (AGRRA) (Calnan 2008). These metrics could
highlight vulnerable reefs that might be declining and be incorporated into the Benthic Screening
Assessment Tool (BSAT).
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Ecological Traits for Hard Corals
Weil (2020, Appendix R) reviewed the life history, biological, ecological, and geographical
characteristics of scleractinian and hydrocoral species recognized in the wider Caribbean that
could inform additional traits to consider in future generations of the benthic BCG numeric
model. He documented hard coral traits such as current taxonomic status, reproduction, growth,
mean colony size, common colony morphology, and both local and geographic distribution. The
review described extensive information about coral disease in the Western Atlantic, including the
species affected and their susceptibility to both disease and bleaching. Additionally, all hard
corals were evaluated to document individual species sensitivity and tolerance to the most
prominent anthropogenic threats as determined by the expert panel (sedimentation and elevated
sea temperature). The criteria used to define the species response included population
survivorship, fitness, and potential resilience.
Benthic Screening Assessment Tool (BSAT)
The metrics used in the numeric BCG model require both LPI and DEMO methods and consume
considerable resources and logistics to implement. These resources might not be available for
routine monitoring in Puerto Rico and the USVI by the territorial jurisdictions or resource
managers. For greater accessibility and less resource intensive bioassessments, abbreviated
protocols are recommended to achieve a screening-level assessment of biological conditions. The
abbreviated protocols could provide a coarser level evaluation to identify degraded or high-
quality reefs. Identifying critical sites could allow a triaging approach to focus efforts and
resources on those reefs in critical need of attention due to severe alteration or to further protect
those reefs in high quality condition.
The LPI protocol is generally suitable for a screening-level assessment. Nadon and Stirling
(2006) found the LPI was a cost-effective, highly accurate, and precise method for measuring
benthic cover. They recommended sampling 100 points on a 20m transect using 5-10 randomly
positioned replicates within a homogenous area. The LPI methods are simple and quick enough
to be used by the territorial monitoring agencies stretched for resources, because they require
inexpensive equipment, a single surveyor (with a dive buddy who can take the photographs), and
are relatively fast to complete underwater. The benthic screening assessment tool (BSAT) would
include elements of the calibrated BCG Benthic Model related to the LPI measurements as well
as additional non-LPI elements that could be easily observed and quickly recorded. The BSAT
was developed with the sampling limitations in mind.
Four LPI measures were scored in the BCG Benthic Model. Quantitative rule thresholds were
derived from existing rules, expert panel remarks, and iterative model testing. The BSAT applies
these LPI rules from the BCG Benthic Model. These include % LPI coral cover, % bare substrate
and turf algal cover with sediment (2 categories combined), and number of non-tolerant (BCG
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The BCG for Puerto Rico and USVI Coral Reefs
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Attributes IV and V) coral species. Percentage of Orbicella and Acropora cover were included
for assessment of the good and fair conditions.
Additional measures that were often discussed by the experts as critical indicators of condition
included % mortality and number of diseased colonies. These were only measured in the DEMO
methods and would need to be estimated if used for any screening-level assessments. Excessive
mortality, especially recent mortality, could be estimated by divers while surveying with the LPI
methods. An estimation protocol might include diver notations for each point of the linear
transect, similar to the methodologies used by the USVI Territorial Coral Reef Monitoring
Program (TCRMP) and Atlantic and Gulf Rapid Reef Assessment (AGRRA) (Calnan 2008;
Smith et al. 2008). Notations could include "no mortality", "partial mortality", and "substantial
mortality" as well as an indication of old or recent mortality. Diseased colonies could be noted
for the points of the linear transect and for the broader survey area. TCRMP categorizes disease
into recognized Caribbean scleractinian diseases and syndromes that included bleaching, black
band disease, dark spots disease, white plague, and yellow band (blotch) disease), and most
recently the Stony coral tissue loss disease (SCTLD).
These indicators could be used as metrics to highlight vulnerable reef conditions that might be
worsening. In developing the BSAT, the DEMO measures of percent mortality and number of
diseased colonies were tested. These rules were not incorporated into the screening tool because
they did not improve discrimination between BCG Levels and might not be consistently
estimated.
Additional considerations included presence of scleractinian ESA taxa, and fish diversity and
abundance. Presence of a high number of ESA taxa might indicate that the reef is not severely
degraded. Absence or paucity of fish might indicate that the reef is moderately or severely
degraded. These measures were not included in the BSAT but could add additional interpretive
information for a screening-level assessment.
For the draft screening-level evaluation, quantitative rules were established using distributions of
the metrics as guides for establishing thresholds (Table 12). The primary threshold for finding a
difference between "Good-Fair" conditions and "Poor-Very Poor" conditions was similar to the
threshold between BCG Levels 4 and 5 of the full first generation BCG benthic model. Using
this threshold, the screening model predicted the same condition as the experts for 83% of the
sites including all rated sites (calibration and validation). Additional thresholds were described
for estimation of differences between "Good" and "Fair" conditions (similar to Levels 3 and 4),
and between "Poor" and "Very Poor" conditions (similar to Levels 5 and 6). There was more
disagreement among the secondary threshold conditions and the overall correct agreement within
the four condition Levels was 70%.
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Table 12. Benthic Screening Assessment Tool rules (first generation). The primary thresholds are those
described at the Fair Level. A Very Poor assessment would result from sites that do not meet the Poor
thresholds.
Comparable BCG Level
Good
(Level 3 and
above)
Fair
(Level 4)
Poor
(Level 5 and
below)
LPI % coral cover
>20 (15-25)
>10(5-15)
>4 (0-8)
% Orbicella and Acropora cover
>6 (2-10)
>1 (0-2)
Non-tolerant taxa richness
>2 (1-3)
>1.5 (0-3)
>1 (0-2)
% bare substrate and turf algal cover
with sediment
<40 (30-50)
<50 (40-60)
<60 (50-70)
Fish BCG Model
Why fish?
Fish assemblages can be integral components of coral reef ecosystems and are indicators of reef
ecosystem condition. The benthic organisms (e.g., stony corals, gorgonians, and sponges) and
adjacent habitats (e.g., seagrass meadow and mangrove forests) provide critical nurseries,
foraging areas, habitat, and refugia for fish (Nagelkerken et al. 2000; Christensen et al. 2003;
Mumby et al. 2004, 2008; Adams et al. 2006; Cerveny 2006; Dahlgren et al. 2006; Aguilar-
Perera and Appeldoorn 2007; McField and Kramer 2007; Meynecke et al. 2008; Clark et al.
2009; Pittman et al. 2010). Reef fish abundance and diversity are associated with reef habitat
structure, complexity, and quality, and can therefore be indicators of reef condition (Gladfelter et
al. 1978; Carpenter et al. 1981; Bell and Galzin 1984; Sano et al. 1984; McClanahan 1994; Caley
and St. John 1996; Ormond et al. 1996; Lewis 1997a, b 1998; Williams 1991; Warren-Rhodes et
al. 2003; Lindberg et al. 2006; Bejarano-Rodriguez 2006; Wilson et al. 2006; Alvarez-Filip et al.
2009; Walker et al. 2009; Pittman et al. 2007a, b; Brandt et al. 2009).
Reef fish have diverse functional roles that are essential to coral reef integrity. For example,
herbivores control algae that may otherwise replace living corals (Hughes 1994; Burkepile and
Hay 2008). Large piscivores provide top-down control of the fishes that prey on herbivores
(Mumby et al. 2006; Stallings 2008, 2009), and help to control the abundance of coral feeders
and bioeroders (Bradley et al. 2020). Additionally, reef fish provide economic and cultural value
(e.g., food provisioning via subsistence and commercial fishing) and support tourism and
recreational activities (Pendleton 1995; Hawkins and Roberts 2004; Principe et al. 2012; Brander
and van Beukering 2013; Spalding et al. 2017). Given their diverse functional roles in the
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The BCG for Puerto Rico and USVI Coral Reefs
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ecosystem and their societal value, using reef fish as indicators of coral reef ecosystem condition
can help managers to set targets for protection and restoration of coral reefs (Bradley et al. 2020).
Fish Data
EPA 2010 and 2011 survey data for southern Puerto Rico were subjected to thorough QA/QC to
eliminate uncorrectable, unmatched, or conflicting data, sites deemed to be in non-target habitat
types, and to correct older taxonomic names or synonyms. The data were then put into an Excel
workbook for use by the experts. The workbook included a series of linked worksheets,
including:
• Notes with descriptions of the other worksheets and metadata
• A Status Page with a summary of sites and expert consensus BCG Level assignments
• A data taxa master worksheet that provides species information, including scientific and
common names, classification, BCG attribute, trophic guild, whether large or small for
important targeted species, preferred habitat (Humann and DeLoach 2003), tolerance to
sediment, fishing pressure
• A data habitat worksheet, that provides other information by site (e.g., exercise ID,
survey index, collection date, collection method (EPA, NCRMP, RVC), region,
latitude/longitude, survey year, whether in an MP A, habitat (NOAA benthic maps), etc.)
• Data sheets from individual monitoring sites, including site and sample information (see
Figure 25.)
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2.021
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Figure 25. Screenshot of Fish data sheet (MS Excel). This view shows the site and sample characteristics
on the right side, and the taxa list on the left side, including the assigned BCG attribute, common name,
scientific name, density, biomass, and family.
Considerable information was provided to the experts for each site. Basic information included
the site ID, collection date, region, and locational information (lat/long). Additional information
useful for rating the sites included:
• Depth. Roberts and Ormand (1987) stated that depth alone can be a good indicator of fish
species richness. Additionally, depth is a defining variable for reef type (Walker et al
2009).
• Distance from Shore. Distance from shore was a surrogate for sediment stress. It is
particularly important because certain fish species use near-shore habitats as nurseries
prior to moving out to adult reef habitats (Appeldoorn et al. 1997, 2003; Lindeman et al.
2000; Nagelkerken et. al 2015; Dahlgren and Eggleston 2000; Cocheret de la Moriniere
et al. 2002a, b; Christen sen et al. 2003; Aguilar-Perera 2004; Mumby et al. 2004, 2008;
Aguilar-Perera and Appeldoorn 2007; McField and Kramer 2007; Meynecke et al. 2008;
Sale et al. 2010, Scharer-Umpierre 2009).
60
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
• Distance from Shelf Edge. Shelf breaks are areas of unique habitats and physical
properties (Scherbina et al. 2008) that support distinctive fish assemblages (Kimmel
1985, Cerveny 2006, Pittman et al. 2010). Additionally, they are an important spawning
habitat for a variety of species (Thompson and Munro 1974; Johannes 1978; Colin et al.
1987; Shapiro et al. 1993; Sadovy et al. 1994a, b; Sala et. al 2001; Claro and Lindeman
2003; Nemeth et al. 2006; Ojeda-Serrano et al. 2007a, b; Heyman and Kjerfve 2008;
Scharer-Umpierre 2009; Scharer et al. 2014).
• Reef Type. Reef types were based upon the benthic classification (Kendall et al. 2001).
Classifications for Coral Reef and Hardbottom, were further delineated as either Coral
Reef and Colonized Hardbottom or Uncolonized Hardbottom Reef Rubble. Within the
Coral Reef and Colonized Hardbottom category, there were seven possible habitats:
Linear Reef, Spur and Groove, Individual Patch Reef, Aggregated Patch Reefs, Scattered
Coral/Rock in Unconsolidated Sediment Colonized Pavement, Colonized Bedrock and
Colonized Pavement with Sand Channels. Within the Uncolonized Hardbottom Reef
Rubble category there are three possible habitats: Uncolonized Pavement, Uncolonized
Bedrock and Uncolonized Pavement with Sand Channels.
• Rugosity. The rugosity index provides an estimate of reef topographic complexity. In the
EPA dataset, rugosity was measured using the chain-and-tape method (McCormick,
1994): a ratio of the length of a chain draped across the reef surface to the linear stretched
length (Hobsonl972; McCormick 1994; Rogers et al. 1994; Lang 2003; Santavy et al.
2012). A strong positive correlation between topographic complexity and reef fish
abundance, biomass, and/or species richness has been documented (Talbot 1965; Talbot
and Goldman 1972; Risk 1972; Luckhurst and Luckhurst 1978; McClanahan 1994;
McCormick 1994; Green 1996; Appeldoorn et al. 1997; Friedlander and Parrish 1998;
Friedlander et al. 2003; Gratwicke and Speight 2005a and 2005b; Kuffner et al. 2007;
Pittman et al. 2007a; Walker et al. 2009). Reef flattening, the reduction in the amount and
complexity of reef structure resulting from physical destruction and erosion of stony
corals, has resulted in the loss of species richness and abundance of reef fishes and
invertebrates (Gratwicke and Speight 2005b; Idjadi and Edmunds 2006; Wilson et al.
2007).
• Three-dimensional habitat. Whereas the rugosity index accounts for important vertical
dimensions, it does not fully reflect the three-dimensional availability of fish habitat.
Therefore, the data also included additional indicators of available habitat, such as 3D
colony surface area estimates for the three major sessile benthic populations, stony corals,
sponges, and gorgonians (Courtney et al. 2007; Santavy et al. 2012; Fisher et al. 2007,
2014). (See benthic chapter for more discussion of these metrics).
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The BCG for Puerto Rico and USVI Coral Reefs
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Fish Assemblage Calculated Metrics. Commonly used metrics about the fish assemblage were
calculated, including fish species richness, density, fish length mean and standard deviation, total
fish biomass, number of fish schools, percent of fish in various families, Acanthuridae, Scaridae,
Chaetodontidae, Haemulidae, Pomacentridae, Labridae, Lutjanidae and Carangidae and
Serranidae, and relative biomass of herbivores and piscivores (Caldow et al. 2009; Santavy et
al. 2012).
Fish Species Information. The list of fish species observed at the site was provided, including
density and biomass by species, and BCG attribute assignments. Summary information,
organized by BCG attribute, was provided including the number of taxa, density and biomass,
the percent of the taxa, density and biomass, and totals for number of taxa, density and biomass.
Note: Cryptic species are present at sites, but not easily detectible in fish surveys.
Fish BCG Attributes
As a first task, the fish experts identified the stressors most relevant to fish assemblage condition
as habitat degradation, sediment stress, and fishing pressure (Bradley et al. 2016). The experts
used the BCG attribute definitions (Appendix B), their expert knowledge and experience,
available literature, and frequency of a species occurring in the data set to assign 357 Caribbean
fish species to the taxonomic attributes (attributes I-V) based on their sensitivities to two
anthropogenic stressors (sediment and fishing).
Non-native species were identified as BCG Attribute VI, reflecting the detrimental effects of
nonnative taxa on native species (Davies and Jackson 2006; EPA 2016). Some taxa were
assigned an "x" because the fish experts were unfamiliar or had little supporting information in
the literature relative to stressor tolerance to assign them to a BCG attribute, or because the
survey methodology did not allow an accurate count of the species (e.g., cryptic species). The list
of species with their assigned attributes is provided in Appendix O. Four fish species are listed
under the ES A, Epinephelus striatus (Nassau Grouper) and Manta birostris
(Giant Manta Ray), Sphyrna lewini (Scalloped Hammerhead Shark - Central and Southwest
Atlantic Distinct Population Segment), and Carcharhinus longimanus (Oceanic Whitetip Shark)
(Table 13)
For fishing pressure, the fish experts considered whether each species was subject to fishing
pressure and the degree of that pressure, the category of fishing pressure (e.g., commercial,
recreational, or ornamental), and whether that species was regulated under federal or territorial
fishing laws (EPA 2016).
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2.021
Because there is limited literature on reef fish species' sensitivity to sediment stress, the experts
considered life-history characteristics (e.g., ontogenetic migrations between habitats) as well as
personal observations of a species in turbid waters, very clear waters, or both.
The experts assigned fish to Attributes I - VI with the following frequency:
• Attribute I: Historically Documented, Long-lived, or Regionally Endemic Taxa - 15 taxa
• Attribute II: Highly Sensitive Taxa - 54 taxa
• Attribute III: Intermediate Sensitive Taxa - 108 taxa
• Attribute IV: Intermediate Tolerant Taxa - 51 taxa
• Attribute V: Tolerant Taxa - 4 taxa
• Attribute VI: Non-native or Intentionally Introduced Taxa - 3 taxa
• X - Taxa not assigned to an attribute - 122 taxa.
Table 13. Caribbean fish species listed as threatened under the U.S. Endangered Species Act.
Scientific Name
Common Name
Photograph
Scientific Name
Common Name
Photograph
Epinephelus striatus
Nassau Grouper
m
Manta birostris
Giant Manta Ray
Sphyrna lew in i
(Scalloped
Hammerhead Shark
Carcharhinus
longimanus (Oceanic
Whitetip Shark)
¦ifl
1m*
.
Assignment of BCG Levels to Sites and Preliminary Narrative
Model Development
The second task for the fish experts was to assign BCG Levels to individual sites based on
natural site classification and species composition. A set of 38 sites was selected from the EPA
2010/2011 surveys that spanned the range and gradient of sediment stress that occurs in south-
western Puerto Rico. These were not necessarily the same sites as were used in the benthic
narrative model development. In a workshop setting, the panel facilitator projected the data for
each site onto a screen and presented the site data and summary metrics. The experts were asked
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
to consider a site then document their recommended BCG Level, the critical or most important
information they used to inform the decision, any confounding or conflicting information, and
how they resolved these conflicts (EPA 2016; Gerritsen et al. 2017). The facilitator then called
on each expert to present their rating and rationale, capturing the information in the projected
BCG workbook.
Once all experts had provided their individual ratings, the experts discussed the ratings and
rationales and revised their individual ratings if new information or insight caused them to
evaluate the site differently. The experts felt that the group discussions and ability to share
knowledge with each other was important. The median score was proposed as the site rating, and
experts were asked to concur in a final rating for the site. Rationale for the rating was then
documented.
The experts agreed that all sites had some degree of disturbance, including ubiquitous effects
from fishing pressure, reef degradation, and turbidity from terrigenous sediment. The experts did
not assign any sites to BCG Levels 1 or 2. All sites were rated as BCG Levels 3-6.
Next the fish experts provided narrative statements to describe what they expected to see for
each BCG Level starting from the highest quality condition observed in the data set. This
narrative became the basis for BCG rule development. The fish experts developed conceptual
rules for Level 2, as was done by the benthic experts.
The experts identified a set of metrics that they used to distinguish BCG Levels, including taxa
richness total biomass, sensitive taxa, density of damselfish, piscivores, and other fishes. Based
upon the analysis, a set of draft narrative fish rules was developed by the experts. These narrative
Level descriptions were qualitative (e.g., high diversity, reduced diversity). The narrative
decision rules exhibited a general pattern of decreasing richness and biomass, especially of
sensitive or specialist fish, as biological condition degrades (Table 14).
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The BCG for Puerto Rico and USVI Coral Reefs
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Table 14. Narrative rules for fish BCG Tevels in Puerto Rico coral reefs
Level
Narrative Rule
BCG
Level 1
Populations have balanced species abundance, sizes, biomass, and trophic interactions;
Large piscivores present (groupers, barracuda, and sharks)
BCG
Level 2
Populations have balanced species abundance, sizes, biomass, and trophic interactions;
Large piscivores present (groupers and snappers, but not sharks); schools of piscivores
present *
BCG
Level 3
Decline of large apex predators (e.g., groupers, snappers, etc.) noticeable, however still
present; small reef fish more abundant than Levels 1-2; large body parrotfish present; high
within-family diversity
BCG
Level 4
Near absence of large piscivores, however at least one piscivore present; small reef fish
abundant (mostly damselfish and wrasses); parrotfish present
BCG
Level 5
No large fish, few intolerant species, lack of multiple trophic levels; more than 4-5 fish
species
BCG
Level 6
Does not meet Level 5 rules
* The fish experts felt that it was important to separate sharks out from other large predators. The long history of
shark exploitation makes it difficult to accurately characterize the role of sharks on coral reefs, because fishing has
selectively removed larger, older individuals, causing mean sizes to decline (Anderson et al. 2008; Barley et al.
2020). However, sharks most certainly function as either transient apex predators or reef-associated mesopredators
(Frisch et al. 2016; Roff et al. 2016; Desbiens 2021), directly impacting the demography of many reef fish
(DeMartini et al. 2008; Stallings 2008).
Numeric Model - Calibration and Validation
The fish experts' narrative rules and reasoning, both quantitative and qualitative, were compared
to data summaries of the sites evaluated by the experts. For example, if the experts identified a
small to moderate number of sensitive taxa for BCG Level 3, then the number of sensitive taxa in
sites the panel assigned to BCG Level 3 were examined (e.g., sensitive taxa ranged from 4-8 in
all sites assigned to BCG Level 3). Box plots were developed for each of the experts' narrative
statements (Figures 26-28), which informed thresholds for the numeric rules. Opinions
repeatedly expressed by the experts that were not included in the draft narrative rules were used
to formulate additional rules. Some rules suggested by the panel (e.g., species per family in
Levels 3 and 4; damselfish and wrasses in Level 4; and piscivores in Level 4) either did not
discriminate between Levels or were redundant with other rules and therefore were not included
in the final rules.
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2.021
26
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Figure 26. Diagrams offish rules (Y axis) for Level 3, showing metric distributions for sites as rated by
the experts (BCGLevels; Xaxis) showing ride thresholds (dashed lines) and threshold ranges (shaded
box). Membership values are calculated as 1.0 if the metric value is better than the blue range, 0.0 if
worse than the red region, and interpolated between 0.0 and 1.0 if within the shaded region. Distributions
include the median (central square), intraquartile range (rectangular box), non-outlier ranges (whiskers),
and outliers (circular marks).
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
4 5
BCG Level
T
T
CM
£
-Q
E
-S
,o
4 5 o 3 4 5
BCG Level BCG Level
Figure 28. Distribution of metrics used in model rules for discriminating Fish BCG Levels 5 and 6,
showing the rule thresholds (dashed line) and ranges (color-shaded region). Membership values are
calculated as 1.0 if the metric value is better than the blue range, 0.0 if worse than the red region, and
interpolated between 0.0 and 1.0 if within the shaded region. Distributions include the median (central
square), intraquartile range (rectangular box), non-outlier ranges (whiskers), and outliers (circular
marks).
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The BCG for Puerto Rico and USVI Coral Reefs
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The fish experts had different expectations for fish assemblages in reef habitat than in other
colonized hard-bottom habitats. Colonized hard bottom is characterized as mixed communities of
algae, sponges, octocorals and stony corals. While hard bottom can support coral communities,
they generally lack the coral diversity, density, and reef development of patch and outer bank
reefs. Adjustments were made to the rules by the experts based on their knowledge and field
experience studying these two different coral habitats. Seven decision rules were developed for
BCG Level 3; any six of the seven rules must be met to assign BCG Level 3 in reef habitat,
while five must be met in colonized hard-bottom habitats.
The draft BCG decision model was applied to the 38 original sites and those results were
compared to the expert BCG Level ratings for the same sites. The quantitative model was 92%
accurate (90% confidence interval: 81 - 98%) in replicating the expert panel assessments within
one-half BCG Level for the calibration dataset (Table 15). When there was a discrepancy (3
sites), it was never more than one Level of difference, and occurred at the threshold between
BCG Levels 3 and 4. Figure 29 shows the distribution of individual panelist scores compared to
the group median for each site. Because of the expected variability in a natural system, the
experts did not consider a half-Level mismatch (a comparison including a tie level) with their
consensus to be a meaningfully different assessment, and a half-Level was similar to the spread
in ratings among experts. The experts assigned individual ratings that were within one third of
the group median BCG Level for 85% of individual assessments. That is a difference of a "+" or
rating, as described in the benthic Numeric Model.
The next step was to confirm (validate) the model with new (not previously rated) sites. The
experts reviewed 11 validation sites, applied the numeric fish rules to assign a BCG Level to
each site, and stated reasons if they disagreed with any given quantitative rule. No disagreements
with rules were stated and the experts completed the validation sites. Accordingly, the experts
did not adjust ratings or modify rules for small mismatches. There were, however, several issues
that arose that warrant further investigation (see Future Research Section). The quantitative
model was 82% accurate (90% confidence interval: 53 - 97%) for the validation dataset (Table
16). The experts' ratings for the validation sites were mostly close to the group median, with
78%) of individual ratings within one third of the BCG Level of the panel median (Figure 29).
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
Table 15. Comparison of expert ratings of BCG Levels for fish calibration reef sites compared to BCG
Levels predicted by the model showing where there was agreement (shaded cells) and disagreement
(unshaded cells).
BCG Model Predictions
- Fish Calibration
Rating
Total #
Rated
2
3
3-4 tie
4
4-5 tie
5
5-6 tie
6
2
0
0
0
0
0
0
0
0
0
s—»
G
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
Calibration
160
140
S 120
E
c
O)
"55 100
-Q
E
3
10
-1.00 -0.66 -0.33 0.00 0.33
Difference from the Median
Confirmation
0.66
1.00
1%%
1^0
-1.00
-0.66
0.66
1.00
-0.33 0.00 0.33
Difference from the Median
Figure 29. Distribution offish panelists' BCG Level assignments expressed as difference from the group
median in 1/3 BCG Level steps. Calibration (top) and confirmation (bottom) sites from the Puerto Rico
reef fish dataset.
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The BCG for Puerto Rico and USVI Coral Reefs
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Transferability to Another Region
As an exploratory test of model transferability to other coral reef fish communities, the fish
experts rated 14 sites collected using RVC methods in the Florida Keys and Dry Tortugas from
2014-16 at depths shallower than 16 m. A reference dataset was used to establish "recent best"
condition (e.g., low stressor levels, water quality and fishing impacts): RVC surveys conducted
in Dry Tortugas National Park, depths < 16m, during years 2011-2016 (surveys in 2011, 2012,
2014, 2016). This period encompasses recent surveys, conducted well after a period of intense
hurricanes (2004-2005) and implementation of large Marine Protected Areas (MP As; 2001 in
Tortugas Bank and Riley's Hump, 2007 in Dry Tortugas National Park). For the reference
dataset, the RVC leads computed richness, total fish density, large piscivore density for each site
(100 x 100 m grid cell, 2 sites, 2 divers each site). All three metrics showed increasing
median/mean values with increasing rugosity category. Richness showed the best discrimination
by rugosity. The RVC leads computed mean and standard deviation of each metric for each
habitat type (Low-, Mid-, High-Relief). These were used to 'standardize' the site-specific
metrics for the workshop dataset (2014-16 fish-coral sites).
The sites were selected by the RVC leads to reflect a stressor gradient for both fishing and land-
based pollution. Four zones were identified, with three sites selected from each zone;
one from the upper end of the standardized richness distribution, one from the middle, and one
from the lower end; 12 sites total. The Dry Tortugas was the best representation of an
undisturbed reference region with respect to WQ and fishing impacts, in the Florida Keys. Two
sites were selected from the upper end of the richness score distribution from the Dry Tortugas
sites to provide a starting point for the workshop exercise reflecting the high-end of fish
assemblage metrics forjudging sites from other areas a total of 14 sites were used for the
workshop.
The quantitative BCG model developed for Puerto Rico was 79% accurate in replicating the
expert panel assessments within one-half BCG Level for the Florida Keys calibration. The
biomass metric was the rule that was not met in the mismatched sites. The experts felt that
species attribute assignments might need to be revisited based on location, particularly because
fishing pressure varies significantly by jurisdiction.
Fish Model Rules
The BCG model has been successfully adapted to accommodate fish in coral reef ecosystems
while maintaining the model's conceptual integrity (Table 17). A regional panel of experts
assigned fish species inhabiting Puerto Rico's near-shore linear coral reefs to attributes of
sensitivity to human disturbance, natural prevalence, historic species importance in the
Caribbean, and native or non-native origin. The experts developed fish rules for six Levels of
coral reef condition, with a well-defined narrative for each Level.
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
Table 17. BCG reef fish assemblage decision rules. Numbers in parentheses are lower and upper bounds
for group membership. Puerto Rico rules are based on 4 m x 25 m belt transect data collected during
2010-2011 (Santavv etal. 2012). Florida rules are based on 15 m diameter cylinder RVCpoint count
data (Smith etal. 2011) collected during 2014-2016. Continued on following pages.
BCG metric
Narrative rules
Quantitative rules
BCG Level 2 (No survey sites were identified, rules are conceptual)
Total taxa
Richness is high - valid taxa only a
> 20 (15 - 25) taxa
Rare, endemic and
special species (Attribute
I species)
Present
> 1 taxon
Highly sensitive taxa
(Attribute II species)
Present
> 1 (0 - 2) taxon
Proportion of all
sensitive taxa (Attribute
I, II, and III species)
Sensitive taxa constitute a large
proportion of species richness
> 50% taxa (45 - 55)
Total biomass
High fish biomass - valid taxa only a
Puerto Rico: > 65 (50 - 80
g/m2) b
Florida: >65 (51 -79 g/m2)
Large groupers
Present (Epinephelus and
Mycteroperca)
> 1 (0 - 1) individual
Large predators 0
Present
> 1 (0 - 2) individual
Piscivore individuals
Abundant
> 20 individuals
BCG Level 3 (reef habitat - must meet 6 of 7 rules; hardbottom habitat - must meet 5 of 7 rules)
Total taxa
Richness moderate to high - valid
taxa onlya
>15 (10 - 20) taxa
Number of all sensitive
taxa (Attribute I, II, and
III species)
Sensitive taxa are a small to
moderate proportion of fish species
richness
> 6 (4 - 8) taxa
Total biomass (g/m2)
Total fish biomass is moderate to
high - valid taxa only a
Puerto Rico: > 35 (30 - 40
g/m2) b
Florida: >37 (32 - 42 g/m2)
Piscivores
Presence of snappers or other
piscivores
> 1 individual
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The BCG for Puerto Rico and USVI Coral Reefs
September 15, 2021
BCG metric
Narrative rules
Quantitative rules
Parrotfish
Presence of large parrotfish d
> 1 (0 - 2) individual
Damselfish
Damselfish individuals are not
dominant
< 25% individuals (20 - 30)
Groupers
Groupers present {Dermatolepis,
Epinephelus, Mycteroperca, and
Cephalopholis)
> 1 individual
Rule application:e
Reef Habitats: More stringent
requirements
Hard-bottom Habitats: Less stringent
requirements
Require 6 of 7 rules
Require 5 of 7 rules
BCG Level 4
Total taxa
Richness low to moderate - valid
taxa only a
> 9 (4 - 14) taxa
Number of all sensitive
taxa (Attribute I, II, and
III species)
Some sensitive taxa
>3(1-5) taxa
Total biomass (g/m2)
Low or higher - valid taxa only a
Puerto Rico: >11(7 — 15
g/m2) b
Florida: > 6.2 (4 - 8.4 g/m2)
BCG Level 5
Total taxa
Sparse - valid taxa only a
> 5 (2 - 8) taxa
Total biomass (g/m2)
Very low - valid taxa only a
Puerto Rico and Florida: > 2
(1-3 g/m2)
BCG Level 6
Does not meet Level 5 rules
a. Valid taxa are those that were expected to be consistently sampled. They did not include taxa with attribute
x-MNS (method not suitable) or with attribute x-NRF (not a reef fish).
b. Because of differences in sampling protocols, the calculation of biomass differs between Puerto Rico
(including the U.S. Virgin Islands) and Florida.
c. Large predators include groupers, sharks, snappers, jacks, tarpon, and barracuda.
d. Large parrotfish include all taxa in the Scaridae family.
e. For Level 3, rules can be discounted depending on the habitat type. For reef habitats, the highest 6 rule
results are considered, discounting the rule resulting in the lowest membership value. For hard-bottom
habitats, the lowest 2 membership values can be discounted.
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Fish Model Discussion
The fish BCG model can be used to quantitatively interpret Caribbean reef condition for
conditions ranging from BCG Level 3 to BCG Level 6. The model was based on expert-derived
numeric decisions rules. BCG Level 1 was not expected to occur in Puerto Rico or the USVI
because of the impacts of habitat destruction from intense land-based activities and fishing
pressure over the past 50 years. No Level 2 conditions were observed; however, conceptual
Level 2 rules were proposed based on experience and knowledge of historical descriptions.
Some rules were specific for a single Level but not for other Levels. For example, a rule that
discriminated for Level 3 did not discriminate for Level 4 (e.g., percentage of damselfish;
presences of piscivores, groupers and parrotfish) and therefore were not used except for Level 3
assignments. However, some rules were discriminatory along the full gradient and used to
discriminate BCG Levels 3, 4 and 5. For example, the total taxa and total biomass rules
discriminated for all Levels. Level 5 expectations were not very high. If there were at least some
fish species observed, then the site was not relegated to the final lowest Level 6.
The fish BCG model (as developed for Puerto Rico) had a high degree of fidelity to the expert
decisions: the model replicated the expert consensus within one BCG Level for 100% of sites
and replicated the expert consensus within a half BCG Level for 82% (validation) to 92%
(calibration) of the sites. This degree of predictive accuracy is as good as or better than that for
freshwater systems (Gerritsen 2017; Hausmann et al. 2016). Given the variability in sampling
fish assemblages, the experts considered a half-Level difference to be "splitting hairs".
An exploration of the model application to coral reef systems in other regions was tested using
data from 14 sites in the Florida Keys and Dry Tortugas. The model was 79% accurate in
replicating the expert panel assessments within one-half BCG Level for the Florida Keys
calibration. The biomass metric was the rule that was not met in the mismatched sites, and the
experts recommended further research to develop age/size class metrics for future updates to the
BCG fish model. The experts also recommended that species attribute assignments be revisited
based on location, particularly because fishing pressure varies significantly by jurisdiction.
The BCG fish model development, calibration, and validation were successful for Puerto Rico
and the USVI, and the narrative model can be readily transferred to Florida. Some species
assignments to BCG attributes may need to be revised due to differences in fishing regulations
and the numeric rules may need to be calibrated for Florida. The BCG process is fully
transferable to other regions. A Table listing the metrics used in the BCG fish model rules and
ecological/biological importance of each metric is provided in Appendix P.
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Evaluation of Sites using Both the Benthic and Fish Models
In a joint meeting, the experts applied the BCG rules for both assemblages at common sites. As
an example, at one site the benthic organisms met the benthic level 3 rules, but the fish only met
the fish Level 5 rules. The panel assessed the site as degraded but with high potential for
recovery of the fish population because important habitat andfoodfor fish were present. This
might require a fisheries management action, perhaps establishment of a Marine Protected Area
that would be closed to fishing.
Nummary and Recommendations for Future Research
The BCG model initially developed and applied in stream ecosystems was successfully adapted
to assess the condition of coral reef ecosystems while maintaining the model's conceptual
integrity. The experts used bioassessment data and personal knowledge to develop quantitative
decision rules to describe six Levels of coral reef ecosystem condition through an iterative
process. The BCG Levels are biologically recognizable, measurable stages in the condition of
coral reef ecosystems in response to increasing amounts of anthropogenic stress. The fish BCG
model had a high degree of fidelity to the expert decisions. The model replicated the expert
consensus within one BCG Level for 100% of sites and replicated the expert consensus within a
half BCG Level for 82% to 92% of the sites (validation and calibration, respectively). These
percentages of correct fish model predictions are associated with 90% confidence intervals of 53
- 97%) and 81 - 98%, The benthic BCG model also showed high concordance between ratings
and model predictions. The benthic model replicated the expert consensus within one BCG Level
for 100%) of sites and replicated the expert consensus within a half BCG Level for 84% to 89%
of the sites (validation and calibration, respectively). These percentages of correct benthic model
predictions are associated with 90% confidence interval: 74 - 92% and 69 - 98%, Because fish
and benthic assemblages respond differently to stressors, they can be combined for a robust
assessment of biological condition. Both models have a degree of predictive accuracy that is as
good as or better than the examples described for freshwater systems (Gerritsen 2017; Hausmann
etal. 2016).
The BCG framework documents experimentally established scientific knowledge and employs
rigorous testing of empirical observations (Davies and Jackson 2006). The BCG model can
support both regulatory and non-regulatory water quality and natural resource programs,
including development of biocriteria. Numeric biocriteria coupled with biologically based
aquatic life uses provide a direct measure of the aquatic resource that is being protected (e.g.,
coral reefs), complementing chemical and physical water quality criteria. To facilitate use by
territorial and state water quality and natural resource managers, the BCG rule application will
be automated, and clear instructions will be provided for each BCG rule. For example, the fish
rule of "at least one large-bodied parrotfish species present" requires clarification of what
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scientists mean by "large-bodied parrotfish". A precise definition has been documented for each
rule, and guidance material is being developed so the BCG models can be easily applied and
interpreted.
The general steps for the application of the coral reef fish and benthic BCG models are to collect
or select site data, calculate metrics, and apply BCG rules to assign a BCG Level to fish or
benthic assemblage data. Sample collection would use protocols for collecting the BCG
calibration data, including the limitations on site habitat type. Metric calculations would be
derived from sample data, taxa lists, traits, attribute designations (Appendices M and O), metric
calculation procedures (Appendix G), and descriptions in the model rules tables (Tables 9,12,
and 17). In future efforts, calculation procedures will be automated so that agencies will be able
to enter data in tabular format to generate BCG model predictions. The automated calculation
tool is planned for application using R-Shiny.
Although the BCG model was developed using data from Puerto Rico and the USVI, it is
important to note that the BCG is a general framework that can be applied to other coral reef
ecosystems, as demonstrated by using sites from the Florida Keys and Dry Tortugas to test the
transferability of the numeric BCG fish model. Other states and territories would need to adapt it
to their own coral reef habitat and biota and develop a numeric model specific to their
jurisdiction. Broader application in the Caribbean or the Pacific will require additional focused
study using many of the same analytical processes described in this report. After 2018, NCRMP
switched the fish method from belt transect to RVC in USVI and PR, which will affect the
comparability of fish data pre-2018 to fish data post-2018 in the Caribbean. The NCRMP fish
experts are working on calibrations between the belt transect method and the RVC method.
The issues the expert panel recommended for further investigation could lead to model
improvements and refinements. The issues are presented below with possible approaches for
resolution. More detailed discussion and details are provided in Appendix Q.
1. Recommendations from the full group (both benthic and fish experts)
Field Methodfor Measuring Rugosity/Surface Structural Complexity. Both the fish and benthic
expert panels agreed that the methods used to estimate coral reef coarse rugosity (Risk 1972;
Rogers et al. 1994. Measured in US EPA data) and 3D surface microheterogeneity rugosity value
(MRV) (Measured in NOAA NCRMP data) were inadequate. Neither provided a measure of
topography that represented and correlated to the features most important to the fish, coral, or
other sessile benthic organism (includes invertebrates and algae). The MRV estimated reef
rugosity, as the difference between the lowest and highest points in a quadrat along the transect,
averaged for all quadrats at a site (NOAA Coral Program 2014; NOAA NCRMP 2014 Puerto
Rico). Both measures attempt to reflect the importance of the height of coral colonies above the
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substrate, how much reef structure is present, and its provision of potential habitat for fish and
other invertebrates.
Despite the drawbacks with the metric, benthic experts agreed measures from a single transect or
bioassessment census survey were not adequate to accurately characterize the rugosity, or to
explain where and why reefs do or do not occur at a specified location. Identification of a robust
and valid approach to measure this feature is a research need (Dustan et al. 2013). The goal is to
capture a measure of rugosity that is useful to compare qualities important to both fish habitat
usage and benthic structural architecture built by the sessile calcareous hard corals.
Undisturbed Baseline Conditions. The BCG should be calibrated with surveys from relatively
less disturbed areas elsewhere in the Caribbean. Two potential approaches were identified: 1)
conduct a new coral reef survey at a long-established and presumably effective marine reserve to
define a less disturbed reference condition, and 2) explore coral reef monitoring program data
from AGRRA, which has been collecting coral reef data from sites throughout the Caribbean
since 1997 and NPS data collected in the USVI.
The Generalized Stressor Axis (GSA). Both expert panels discussed the development of a GSA
for coral reefs and other coastal and marine habitats that combines land-based sources of
pollution, fishing pressure, and global climate change-associated thermal anomalies. The GSA is
represented as the x-axis of the BCG conceptual diagram (Figure 1) and it informs the shape of
the stressor-response curve as well as allowing BCG Levels to be associated with disturbances.
The BCG model for both assemblages was developed based on expert knowledge and data on
taxa responses to stressors that are predominant in the coastal waters of Puerto Rico and U.S.V.I.
such as elevated sea temperature, suspended sediment, and fishing pressure. Both panels
recommended exploring the development of a GSA. EPA has begun work on this research effort
(Appendix R). In addition to supporting coastal and marine BCGs, the GSA will be useful for a
variety of management programs, including Clean Water Act enforcement, Coastal Zone
Management Programs, and Fisheries Management.
Habitat Classification. A research project to develop and update a standard classification system
and GIS dataset to describe and map coral reef ecosystems of Puerto Rico and the USVI for use
in biocriteria reporting is proposed. The project would include Lidar, predicted background
habitat conditions, or another approach to improve reef classification as well as reconnaissance
dives to ground-truth and refine the potential classifications and maps.
Transferring the BCG to Other Regions. The fish BCG is transferable to other regions. The next
step would be to apply the benthic BCG to NCRMP data from Florida, which has similar species
and reef conditions to Puerto Rico and the USVI. As evidence builds and model refinements
occur for the first generation of the coral reef BCG models, it supports efforts to develop the
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BCG for Hawaii and the Pacific territories, using the fundamental BCG approach and
foundational models developed for Puerto Rico and the USVI.
2. Recommendations from the Fish Experts
Reconsidering Biomass: Age/Class Metrics for the Fish BCG. The BCG fish experts consistently
expressed dissatisfaction with the fish biomass metrics and requested information about the size
class frequency distribution (not just enumeration) of the fish observed. Enumeration of juvenile
and adults (or size distribution based on maximum size for each species) for future rating
exercises would allow calculation of life-stage metrics for reef fish. Associating the life stages
with size ranges might allow better discrimination of BCG Levels and reveal areas of
ontogenetic connectivity.
Ecosystem Connectivity - Seascape Ecology. Coral reefs are part of a tropical marine seascape
that functionally links them with the adjacent shallow coastal habitats. Many reef fish respond to
this spatial mosaic by showing pronounced associations with specific habitat types. Three types
of future research were recommended by the fish experts: 1) high-resolution reef bottom
topography (LIDAR or other) and habitat maps (such as are available for La Parguera) to allow
for better estimation of connectivity, 2) application of landscape ecology methods to coastal and
coral reef ecosystems to identify metrics that can be used to quantify BCG Attribute X -
Ecosystem Connectivity, and 3) development of improved information on species and functional
traits for Caribbean reef fish.
Ecological Traits for Caribbean Fish Species. Detailed information is needed about the life
history, biological, ecological, and geographical characteristics of Caribbean fish species similar
to that provided in Weil (2019; Appendix S) for Caribbean coral species.
3. Recommendations from the Benthic Experts
Increased replication of LPI Surveys. The LPI methodology is considered an economical time
and cost-effective approach proven to be precise and highly accurate for measuring benthic cover
(Beenaerts and Berghe 2005; Nadon and Stirling 2006) The benthic panel recommended using
four to five 10m LPI transects and agreed a single 10m transect was insufficient to characterize
reef condition or adequately determine benthic cover. This recommendation was further
supported by literature research (Rogers et al. 2020 Appendix T; Weil 2020 Appendix R).
Studies examining statistically robust designs have recommended sampling 100 points on a 20m
transect using 5-10 randomly positioned replicates within a homogenous area (Nadon and
Stirling 2006). Additionally, the experts recommended expanding substrate categorized as "bare
substrate" to designate as hard bottom devoid of life, coarse sand, or fine sediment.
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Photos and Videos at Survey Sites. The benthic experts suggested that photographs and videos
should be methodically taken at all sites to provide interpretive visual data during expert reviews.
Visual media could allow interpretation for reconciling discrepancies perceived in the data to
refine BCG ratings or to confirm the outcome of BCG model application. The experts
recommended the use of existing videographic methodology in the literature to assess transects
and take photos of both common and unusual features at survey sites.
Transferability Goal or Assumption. The transferability of the benthic BCG numeric model
should be demonstrated for other areas. The fish model has been proven to be transferable to the
Florida Keys. The benthic experts could use the same sites of the NCRMP study in the Florida
Keys that were used in the fish model testing, which could be completed with additional
commitment and minor effort.
A basic premise of a BCG for any ecosystem is that it can be applied for any site within the
bounds of model calibration. Model transferability has been demonstrated for freshwater BCGs
by adapting the models to different regions where the ecological structure and function are
similar to the original model. The BCG can also be adapted to different regions where the
species presence and abundance are similar to sites surveyed in Puerto Rico, USVI, and south
Florida. In some cases, the species included in model metrics might be substituted with other
species performing those same roles in a different region. Several habitat types from the
Western Atlantic that contain major architectural structure from calcite coral skeletons are based
on A. palmata monocultures dominating reef crest environments. In other areas, A. cervicornis
monocultures dominate back reef lagoonal areas and Orbicella spp. dominate deeper forereef
areas (Weil 2020).
BCG Attribute I-V assignments for Hard Corals. Responses of coral populations and
assemblages to increasing stress do not appear to be incremental or necessarily follow a
predictable sequence of changes reflected by species turnover as documented in freshwater
streams (US EPA 2012; Rogers et al. 2020). With increasing anthropogenic disturbance, coral
species are unlikely to be replaced by more resilient species with the same functional roles, as
observed in higher quality freshwater systems where sensitive taxa are replaced in lower quality
streams by more tolerant taxa (Rogers et al. 2020; Weil 2020). The experts agreed more
sustained research is required to understand the responses of different coral species more fully to
the same stressors, and the response of the same coral species to different stressors.
Organism Condition. During several discussions among experts, coral condition was discussed
as a possible indicator that might be tested for use as a metric in model rules. This could result in
model rules pertaining to condition of organisms (colony mortality, bleaching, and disease) that
would improve interpretations of reef conditions. (Appendices R and T). Rogers et al. (2020)
suggested guidelines to begin discussions for ascertaining the health of reef corals. She proposed
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disease prevalence intervals for diseased corals affected by any tissue loss diseases as: BCG
Level 1 (0-1 percent); BCG Level 2 (> 1-5 percent); BCG Level 3 (>5-10 percent); BCG Level
4 (>10-20 percent); BCG Level 5 (>20-30 percent); and BCG Level 6 (>30 percent).
Size Structure Demographics of coral populations. Experts suggested the size and demographic
structure of the coral assemblage could be useful in determining overall condition of coral reefs.
Rogers et al. (2020, Appendix T) presented evidence for how unfavorable or degraded habitat is
reflected in specific patterns for unbalanced size structures of hard coral communities and
potential long-term environmental consequences (Appendix T). For example, coral populations
that are dominated by larger colonies at degraded sites might be attributed to lack of recruitment
and (or) low survival of small colonies (McClanahan et. al. 2008). This is an area for continued
research to better understand healthy size distributions and recruitment for each species, and to
set expectations for biological condition.
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Appendices
Appendix A. - Glossary
Appendix B - BCG Attributes
Appendix C - BCG Levels
Appendix D - Clean Water Act (CWA)
Appendix E - BCG Workshops and Webinars
Appendix F - Gorgonian and Sponge Morphological Shapes
Appendix G - Coral Metric Calculations
Appendix H - BCG Coral Reef Experts
Appendix I - Management Observers at Coral Reef BCG Workshops
Appendix J - BCG Team
Appendix K - Development of the_Predictive BCG Decision Model
Appendix L - Characterization of BCG Condition Level 1 for coral reefs in Puerto Rico and the
US Virgin Islands
Appendix M - Coral Species Attribute Assignments Made by Professional Judgment of Coral
Reef Experts
Appendix N - Benthic Metrics Used in Developing BCG Rules
Appendix O - Fish Species Attribute Assignments Made by Professional Judgment of Coral
Reef Experts
Appendix P - Fish Metrics Used in Developing BCG Rules
Appendix Q - Recommendations for Future Research
Appendix R - Metadata for Caribbean Coral Species
Appendix S - Generalized Stressor Gradient
Appendix T - Investigating BCG Attribute VII for Evaluating Stony Coral Condition and
Disease Impacts.
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Appendix A - Glossary
abundance: An ecological concept referring to the relative representation of a species in a
particular ecosystem.
anthropogenic: Originating from man, not naturally occurring.
assemblage: An association of interacting populations of organisms in a given waterbody.
arthropod: An invertebrate animal having an exoskeleton (external skeleton), a segmented
body, and jointed appendages (paired appendages).
attribute: Any measurable component of a biological system (Karr and Chu 1999). The BCG
describes how ten biological attributes of natural aquatic systems change in response to
increasing pollution and disturbance. The ten BCG attributes are in principle measurable,
although several are not commonly measured in monitoring programs. The BCG attributes are:
• Historically documented, sensitive, long-lived or regionally endemic taxa
• Sensitive and rare taxa
• Sensitive but ubiquitous taxa
• Taxa of intermediate tolerance
• Tolerant taxa
• Non-native taxa
• Organism condition
• Ecosystem functions
• Spatial and temporal extent of detrimental effects
• Ecosystem connectivity
bait species: Small fish caught for use as bait to attract larger predatory fish, particularly game
fish.
benthic: Living in or on the bottom of a body of water.
best attainable condition: A condition that is equivalent to the ecological condition of
(hypothetical) least disturbed sites where the best possible management practices are in use. This
condition can be determined using techniques such as historical reconstruction, best ecological
judgment and modeling, restoration experiments, or inference from data distributions.
Biological Condition Gradient (BCG): A scientific model that describes how biological
attributes of aquatic ecosystems (i.e., biological condition) might change along a gradient of
increasing anthropogenic stress.
biological criteria: Narrative expressions or numerical values that define an expected or desired
biological condition for a waterbody and can be used to evaluate the biological integrity of the
waterbody. When adopted by the U.S. jurisdictions, they become legally enforceable standards.
biological integrity: The capacity of supporting and maintaining a balanced, integrated, adaptive
community of organisms having a species composition, diversity, and functional organization
comparable to that of the natural habitat of the region.
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biological traits: A specific characteristic of an organism (e.g., life stage, body size, life history,
physiology and behavior) that reflect both inter-specific interactions and the connection between
species and their environment.
calcareous reef: Reefs formed as calcareous (calcium carbonate) skeletons are deposited and
bound by corals.
carbon dioxide (C02): A heavy odorless colorless gas formed during respiration and by the
decomposition of organic substances; absorbed from the air by plants in photosynthesis. It is also
a by-product of burning fossil fuels and biomass, as well as land-use changes and other industrial
processes. It is the principal anthropogenic greenhouse gas affecting the Earth's radiative
balance.
carnivore: Meaning 'meat eater' is an organism that derives its energy and nutrient requirements
from a diet consisting mainly or exclusively of animal tissue, whether through predation or
scavenging.
Clean Water Act (CWA): An act passed by the U.S. Congress to control water pollution (also
known as the Federal Water Pollution Control Act (33 U.S.C. 1251 et seq.) [As Amended
Through P.L. 107-303, November 27, 2002] (Bradley et al. 2010).
community: All the groups of organisms living together in the same area, usually interacting or
depending on each other for existence (Bradley et al. 2010).
condition: The relative ability of an aquatic resource to support and maintain a community of
organisms having a species composition, diversity, and functional organization comparable to
reference aquatic resources in the region.
connectivity: The demographic linking of local populations through dispersal of pelagic larvae
and movement of juveniles or adults (Jones et al. 2009). There are different types of connectivity
including: connectivity among populations in the same habitat in different locations; connectivity
among marine habitats (e.g., where species use different habitats at different stages in their life
history); and connectivity between the land and the sea.
coral bleaching: When corals are stressed by changes in conditions such as temperature, light,
or nutrients, they expel the symbiotic algae living in their tissues, causing them to turn
completely white.
coral reef: Any reefs or shoals composed primarily of corals and formed by coral growth.
decision rules: Logic statements that experts use to make their decisions.
diversity: in relation to species, the number of species and abundance of each species that live
in a particular location
echinoderm: Any of various marine invertebrates of the phylum Echinodermata, having a lattice
like internal skeleton composed of calcite and usually a hard, spiny outer covering. The body
plans of adult echinoderms show radial symmetry, typically in the pattern of a five-pointed star,
while the larvae show bilateral symmetry. Examples are starfish, sea urchin, or sea cucumber.
ecologically extinct: Populations are so greatly reduced relative to past levels that the species no
longer fulfills its former ecological/functional role
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ecosystem functions: Processes performed by ecosystems, including, among other things,
primary and secondary production, respiration, nutrient cycling, and decomposition (EPA 2005).
ecosystem services: Benefits that human populations receive from ecosystems.
Environmental Impact Statement (EIS): A document required of federal agencies by the
National Environmental Policy Act for major projects or legislative proposals significantly
affecting the environment. A tool for decision-making, it describes the positive and negative
effects of the undertaking and cites alternative actions (EPA 2010).
Essential Fish Habitat (EFH): Describes all waters and substrate necessary for fish for
spawning, breeding, feeding, or growth to maturity.
fore reef zone: The area along the seaward edge of the reef crest that slopes into deeper water on
the barrier or fringing reef type (Costa et al. 2013).
functional organization: Trophic interactions such as the relationships between the feeding
habits of organisms and/or flow of materials and energy.
global climate change: Refers to a suite of changes in the Earth's climate, including phenomena
such as global warming, severe storm frequency and intensity, and glacial melting. Increasingly,
scientists believe that global climate change is accelerating due to anthropogenic inputs of ^2
gorgonians: Corals having a horny or calcareous branching skeleton (e.g., Sea Fans).
habitat: A place where the physical and biological elements of ecosystems provide a suitable
environment including the food, cover, and space resources needed for plant and animal
livelihood (Bradley et al. 2010).
Habitat Areas of Particular Concern (HAPC): Discreet subsets of Essential Fish Habitat
(EFH) that are rare, particularly susceptible to human-induced degradation, especially
ecologically important, or located in an environmentally stressed area.
hardbottom: Shallow and deep-water habitats with solid floor that can provide an attachment
surface for sessile organisms such as corals.
herbivore: An animal that feeds on plants (EPA 2010).
historical condition: The ecological condition at some previous point in history. Conditions
reflective of the historic time period may no longer exist in actual ecosystems in an area.
human disturbance: Human activity that alters the natural state and can occur at or across many
spatial and temporal scales.
hydrology: The scientific study of the movement, distribution, and quality of water on Earth
indicator: A measured characteristic that indicates the condition of a biological, chemical or
physical system.
Integrated Taxonomic Information System (ITIS): An American partnership of federal
agencies designed to provide consistent and reliable information on the taxonomy of biological
species.
integrity: The extent to which all parts or elements of a system (e.g., an aquatic ecosystem) are
present and functioning.
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intermediate sensitive taxa: Taxa with restricted, geographically isolated distribution patterns
(occurring only in a locale as opposed to a region), often due to unique life history requirements.
May be long-lived, late maturing, low fecundity, limited mobility, or require mutualist relation
with other species. May be listed as threatened, endangered (under federal or local threatened
and endangered species laws) or species of special concern. Predictability of occurrence often
low, therefore, requires documented observation. Recorded occurrence may be highly dependent
on sample methods, site selection and level of effort (EPA 2005).
intermediate tolerance taxa: Taxa that comprise a substantial portion of natural communities,
which may increase in number in waters which have moderately increased organic resources and
reduced competition, but they are intolerant of excessive pollution loads or habitat alteration.
These may be r-strategists (early colonizers with rapid turnover times; boom/bust population
characteristics), eurythermal (having a broad thermal tolerance range), or have generalist or
facultative feeding strategies enabling them to utilize more diversified food types. They are
readily collected with conventional sample methods (EPA 2005).
keystone taxa: A species that has a disproportionately large effect on its environment relative to
its abundance (Paine 1995).
least disturbed condition: The best available existing conditions with regard to physical,
chemical, and biological characteristics or attributes of a waterbody within a class or region.
These waters have the least amount of human disturbance in comparison to others within the
waterbody class, region or basin. Least disturbed conditions can be readily found but may depart
significantly from natural, undisturbed conditions or minimally disturbed conditions. Least
disturbed condition may change significantly over time as human disturbances change (EPA
2005).
levels: In the context of this report, levels are the discrete ratings of biological condition along a
stressor-response curve (e.g., BCG Level 1 = excellent condition, BCG Level 6 = completely
degraded).
LIDAR (Light Detection and Ranging): A surveying technology that measures distance by
illuminating a target with a laser light.
linear reefs: Are linear coral formations that are oriented parallel to shore or the shelf edge.
They follow the contours of the shore/shelf edge. This category of reefs may apply to commonly
used terms such as fore reef, fringing reef, and shelf edge reef.
live coral cover: A measure of the proportion of reef surface covered by live stony corals.
macroinvertebrates: Animals without backbones of a size large enough to be seen by the
unaided eye and which can be retained by a U.S. Standard No. 30 sieve (28 meshes per inch,
0.595 mm openings) (Bradley et al. 2010).
mangroves: Salt-tolerant woody plants that grow in muddy swamps inundated by tides, offshore
cays, and along shallow coastlines. Mangrove plants form communities that help stabilize banks
and coastlines (Conservation International 2009).
marine protected areas: Any clearly-delineated, managed marine area that contributes to
protection of natural resources in some manner (Dudley 2008). Marine reserves are one type of
marine protected area where extraction of resources is prohibited (IUCN-WCPA 2008).
megafauna: Animals of large or very large size (e.g., whales, sharks, etc.).
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metadata: Structured information that describes, explains, locates, or otherwise makes it easier
to retrieve, use, or manage data.
metric: Measurable quantity of an attribute empirically shown to change in value along a
gradient of human influence. A dose-response context is documented and confirmed.
minimally disturbed condition: The physical, chemical, and biological conditions of a
waterbody with very limited or minimal human disturbance in comparison to others within the
waterbody class or region. Minimally disturbed conditions can change over time in response to
natural processes (EPA 2005).
model: A physical, mathematical, or logical representation of a system of entities, phenomena,
or processes; i.e., a simplified abstract view of the complex reality. For example, meteorologists
use models to predict the weather.
model calibration: The process of adjustment of the model parameters and forcing within the
margins of the uncertainties to obtain a model representation of the assemblage
model validation: The set of processes and activities intended to verify that the model is
performing as expected, in line with its design objectives and intended uses.
monitoring: A periodic or continuous measurement of the properties or conditions of something,
such as a waterbody.
mollusk: An invertebrate animal with a soft body which typically has a "head" and a "foot"
region. Often their bodies are covered by a hard exoskeleton (e.g., clams, scallops, oysters and
chitons).
monotonic: A function between ordered sets that preserves or reverses the given order, and must
be either entirely non-increasing, or entirely non-decreasing.
multimetric index: An index (expressed as a single numerical value) that integrates several
biological metrics to indicate the environmental status of a place.
native species: Species that originated in their location naturally and without the involvement of
human activity or intervention.
non-native species: Any species that is not naturally found in that ecosystem. Species
introduced or spread from one region to another outside their normal range are non-native or
non-indigenous, as are species introduced from other continents (EPA 2005).
nutrients: Chemicals needed by plants and animals for growth (e.g., nitrogen, phosphorus). In
water resources, if other physical and chemical conditions are optimal, excessive amounts of
nutrients can lead to degradation of water quality by promoting excessive growth, accumulation,
and subsequent decay of plants, especially algae. Some nutrients can be toxic to animals at high
concentrations.
ocean acidification: The decrease in the pH of the Earth's oceans caused by the uptake of
carbon dioxide (C02) from the atmosphere. When atmospheric carbon dioxide dissolves in
seawater produces carbonic acid, which subsequently lowers pH of surrounding seawater,
decreases the availability of carbonate (C02- 3) ions, and lowers the saturation state of the
major shell-forming carbonate minerals. Current research indicates the impact of ocean
acidification on marine organisms will largely be negative, and the impacts may differ from one
life stage to another.
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ornamental species: A generic term to describe aquatic animals kept in the aquarium hobby,
including fishes, invertebrates such as corals, crustaceans (e.g., crabs, hermit crabs, shrimps),
mollusks (e.g., snails, clams, scallops), and also live rock (e.g., rock encrusted with, and
containing within its orifices, a wide variety of marine organisms including algae and colorful
sessile invertebrates).
pelagic species: Inhabit the water column - being neither close to the bottom nor near the shore
- in contrast with reef fish, which are associated with coral reefs. Examples include sharks,
barracuda and jacks.
piscivore: A carnivorous animal which eats primarily fish.
pour point: The point on the surface at which water flows out of an area. It is the
lowest point along the boundary of a watershed.
Quality Assurance (QA): The process of profiling the data to discover inconsistencies and other
anomalies in the data, as well as performing data cleansing activities (e.g. removing outliers,
missing data interpolation) to improve the data quality .
reference condition: The condition that approximates natural unimpacted conditions (biological,
chemical, physical, etc.) for a waterbody. Reference condition (biological integrity) is best
determined by collecting measurements at a number of sites in a similar waterbody class or
region under undisturbed or minimally disturbed conditions (by human activity), if they exist.
Reference condition is used as a benchmark to determine how much other water bodies depart
from this condition due to human disturbance (EPA 2005).
resilience: The ability of an ecosystem to maintain key functions and processes in the face of
(human or natural) stresses or pressures, either by resisting or adapting to change (Nystrom and
Folke 2001; TNC 2009).
rugosity: A measure of small-scale variations or amplitude in the height of a surface. In coral
biology, high rugosity is often an indication of the presence of coral, which creates a complex
surface as it grows. A rugose sea floor's tendency to generate turbulence is understood to
promote the growth of coral and coralline algae by delivering nutrient-rich water after the
organisms have depleted the nutrients from the envelope of water immediately surrounding their
tissues (Wikipedia 2009).
seagrasses: Flowering plants from one of four plant families (Posidoniaceae, Zosteraceae,
Hydrocharitaceae, or Cyomodoceaceae), all in the order Alismatales (in the class of
monocotyledons), which grow in marine, fully-saline environments (Wikipedia 2009).
secondary data sources: Data previously collected for a different intended use. Sources include:
publicly-available databases; published literature; reports and handbooks generated and
rd
submitted by 3 parties; state and local monitoring programs; unpublished research results;
output generated by existing models; previously-performed pilot studies; and photographs.
sediment: Particles and/or clumps of particles of sand, clay, silt, and plant or animal matter that
are suspended in, transported by, and eventually deposited by water or air.
highly sensitive taxa: Taxa that naturally occur in low numbers relative to total population
density but may make up large relative proportion of richness. May be ubiquitous in occurrence
or may be restricted to certain microhabitats, but because of low density, recorded occurrence is
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dependent on sample effort. Often stenothermic (having a narrow range of thermal tolerance) or
cold-water obligates, commonly k-strategists (populations maintained at a fairly constant level,
slower development, longer life-span), may have specialized food resource needs or feeding
strategies. Generally intolerant to significant alteration of the physical or chemical environment;
are often the first taxa observed to be lost from a community (EPA 2005).
sensitive taxa: Taxa that are intolerant to a given anthropogenic stress, often the first species
affected by the specific stressor to which they are "sensitive" and the last to recover following
restoration (EPA 2005).
sensitive or regionally endemic taxa: Taxa with restricted, geographically isolated distribution
patterns (occurring only in a locale as opposed to a region), often due to unique life history
requirements. May be long lived, late maturing, low fecundity, limited mobility, or require
mutualist relation with other species. May be listed as threatened, endangered or of special
concern species. Predictability of occurrence often low, therefore, requires documented
observation. Recorded occurrence may be highly dependent on sample methods, site selection
and level of effort (EPA 2005).
sessile: Permanently attached or established; not free to move about (e.g., sessile sponges and
corals)
shifting baseline: A term used to describe the way significant changes to a system are measured
against previous baselines, which themselves may represent significant changes from the original
state of the system (Wikipedia 2009).
Spawning Aggregation Zone (SPAG): A group of fish gathered for the purpose of
reproduction, with individual densities higher than those normally found during non-
reproductive periods (Domeier and Colin 1997).
species: A category of taxonomic classification, ranking below a genus or subgenus and
consisting of related organisms capable of interbreeding. Also refers to an organism belonging to
such a category.
species composition: All of the organisms within a specific ecosystem or area; usually
expressed as a percent contribution of individual species or species groups.
species richness: The number of different species represented in an ecological community,
landscape or region.
sponge: A multicellular organism that has a body full of pores and channels allowing water to
circulate through it; usually occur in sessile colonies.
stock assessments: Provide fisheries managers with information (biological and fisheries data)
to regulate a fish stock.
stony corals: A group of coral species known as hard coral that form the hard, calcium
carbonate skeleton (e.g., brain corals, fungus or mushroom corals, staghorn, elkhorn, table
corals).
stressors: Physical, chemical and biological factors that adversely affect aquatic organisms
(Bradley et al. 2010).
taxa: A grouping of organisms given a formal taxonomic name such as species, genus, family,
etc. (EPA 2005).
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taxa richness: The number of different species represented in an ecological community,
landscape or region.
taxa of intermediate tolerance: Taxa that comprise a substantial portion of natural
communities, which may increase in number in waters which have moderately increased
organic resources and reduced competition, but they are intolerant of excessive pollution
loads or habitat alteration. These may be r-strategists (early colonizers with rapid turn-over
times; boom/bust population characteristics), eurythermal (having a broad thermal tolerance
range), or have generalist or facultative feeding strategies enabling them to utilize more
diversified food types. They are readily collected with conventional sample methods (EPA
2005).
taxonomic: Referring to the science of hierarchically classifying animals by categories (phylum
(pi. phyla), class, order, family, genus (pi. genera), species and subspecies) that share common
features and are thought to have a common evolutionary descent.
tolerant taxa: Taxa that comprise a low proportion of natural communities. Tolerant taxa often
are tolerant of a broader range of environmental conditions and are thus resistant to a variety of
pollution or habitat-induced stress. They may increase in number (sometimes greatly) in the
absence of competition. They are commonly r-strategists (early colonizers with rapid turnover
times; boom/bust population characteristics), able to colonize when stress conditions occur. Last
survivors (EPA 2005).
topography: The physical features of a surface area including relative elevations and the
position of natural and man-made (anthropogenic) features.
total biomass: The mass of living biological organisms in a given area or ecosystem at a given
time; either species biomass, which is the mass of one or more species, or community biomass,
which is the mass of all species in the community.
trophic: Describing the relationships between the feeding habits of organisms in a food chain.
turbidity: The amount of solid particles that are suspended in water and that cause light rays
shining through the water to scatter. Thus, turbidity makes the water cloudy or even opaque in
extreme cases. High levels of turbidity are harmful to aquatic life.
water quality: A term for the combined biological, chemical, and physical characteristics of
water with respect to its suitability for a beneficial use.
water quality criteria: Elements of State water quality standards, expressed as constituent
concentrations, levels, or narrative statements, representing a quality of water that supports a
particular use. When criteria are met, water quality will generally protect the designated use (40
CFR 131).
water quality standards: Provisions of State or Federal law which consist of a designated use
or uses for the waters of the United States, water quality criteria for such waters based upon such
uses. Water quality standards are to protect public health or welfare, enhance the quality of the
water and serve the purposes of the Act (40 CFR 131).
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Appendix B
Attribute
I. Historically
documented, long-
lived, or regionally
endemic taxa
II. Highly
sensitive taxa
BCG Attributes
Description
Taxa known to have been supported according to historical, museum or
archeological records, or taxa with restricted distribution (occurring only
in a locale as opposed to a region), often due to unique life history
requirements. They may be long-lived and late maturing and have low
fecundity, limited mobility, multiple habitat requirements as with
diadromous species, or require a mutualistic relationship with other
species. They may be among listed Endangered or Threatened (E/T) or
special concern species. Predictability of occurrence is often low, and
therefore requires documented observation. The taxa that are assigned to
this category require expert knowledge of life history and regional
occurrence of the taxa to appropriately interpret the significance of their
presence or absence. Long-lived species are especially important as they
provide evidence of multi-annual persistence of habitat condition.
Caribbean Coral Reef Fish Examples: Carcharhinusperezii (Caribbean
Reef Shark), Mycteroperca bonaci (Black Grouper), and Scarus
coelestinus (Midnight Parrotfish)
Taxa that are highly sensitive to pollution or anthropogenic disturbance.
Tend to occur in low numbers relative to total population density, but
they might make up a large relative proportion of richness. In high
quality sites, they might be ubiquitous in occurrence or might be
restricted to certain micro-habitats. They often have slow growth - long-
lived (K-strategists) vs. short-lived—fast growth (r-strategists). In coral
reef ecosystems, large-bodied, slow-growing, late-maturing fishes (K-
strategists) are generally more sensitive to fishing pressure and
environmental stress than faster-growing, shorter-lived species (Beverton
and Holt 1957; Man et al. 1995; Jennings et al. 1998; Coleman et al.
2000; Goodwin et al. 2006; Ault et al. 2008). The distinguishing
characteristic for this attribute category was found to be sensitivity and
not relative rarity, although some of these taxa might be uncommon in
the data set (e.g., very small percent of sample occurrence or sample
density), therefore, these are the first to disappear with disturbance or
pollution.
Caribbean Coral Reef Fish Examples: Aluterus scriptus (Scrawled
Filefish), Clepticusparrae (Creole Wrasse) Haemulon chrysargyreum
(Smallmouth Grunt) and Pareques acuminatus (Highhat)
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Attribute
III. Intermediate
sensitive taxa
IV. Intermediate
tolerant taxa
V. Tolerant taxa
Description
Taxa that are abundant in relatively undisturbed conditions but are
sensitive to anthropogenic disturbance/pollution. They have a broader
range of tolerance than Attribute II taxa and can be found in reduced
density and richness in moderately disturbed or polluted stations. These
taxa often comprise a substantial portion of natural communities.
Caribbean Coral Reef Fish Examples: Chaetodon capistratus (Foureye
Butterfly fish), Haemulon flavolineatum (French Grunt), Lutjanus
mahogoni (Mahogany Snapper) and Pomacanthus paru (French
Angelfish)
Taxa that commonly comprise a substantial portion of the fish
assemblage in undisturbed habitats, as well as in moderately disturbed or
polluted habitats. They exhibit physiological or life-history
characteristics that enable them to thrive under a broad range of thermal,
flow, or oxygen conditions. Many have generalist or facultative feeding
strategies enabling utilization of diverse food types. These species have
little or no detectable response to moderate stress, and they are often
equally abundant in both reference and moderately stressed sites. Some
intermediate tolerant taxa may show an "intermediate disturbance"
response, where densities and frequency of occurrence are relatively high
at intermediate levels of stress, but they are intolerant of excessive
pollution loads or habitat alteration.
Caribbean Coral Reef Fish Examples: Abudefduf saxatilis (Sergeant
Major), Carangoides ruber (Bar Jack), Ocyurus chrysurus (Yellowtail
Snapper) and Sparisoma aurofrenatum (Redband Parrotfish)
Tolerant taxa are those that typically comprise a low proportion of
natural communities. These taxa are more tolerant of a greater degree of
disturbance and stress than other organisms and are, thus, resistant to a
variety of pollution or habitat induced stress. They may increase in
number (sometimes greatly) under severely altered or stressed
conditions. They may possess adaptations in response to organic
pollution, hypoxia, or toxic substances. These are the last survivors in
severely disturbed systems and can prevail in great numbers due to lack
of competition or predation by less tolerant organisms, and they are key
community components of level 5 and 6 conditions.
Caribbean Coral Reef Fish Examples: Gerres cinereus (Yellowfin
Mojarra), Sphoeroides testudineus (Checkered Puffer) and Synodus
foetens (Inshore Lizardfish)
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Attribute
Description
VI. Non-native or
intentionally
introduced species
VII. Organism
condition
VIII. Ecosystem
function
IX. Spatial and
temporal extent of
detrimental effects
Any species not native to the ecosystem. Species introduced or spread
from one region to another outside their normal ranges are non-native,
non-indigenous, or alien species. This attribute represents both an effect
of human activities and a stressor in the form of biological pollution. The
BCG identifies the presence of native taxa expected under undisturbed or
minimally disturbed conditions as an essential characteristic of BCG
level 1 and 2 conditions. The BCG only allows for the occurrence of
non-native taxa in these levels if those taxa do not displace native taxa
and do not have a detrimental effect on native structure and function.
Condition levels 3 and 4 depict increasing occurrence of non-native taxa.
Extensive replacement of native taxa by tolerant or invasive, non-native
taxa can occur in levels 5 and 6.
Caribbean Coral Reef Fish Examples: Callogobius clitellus (Saddled
Goby) andPterois volitans (Red Lionfish)
Anomalies of the organisms; indicators of individual health (e.g.,
deformities, lesions, tumors).
Note: This attribute is being applied in the coral reef benthic group as
measures of disease, bleaching, and mortality. The fish surveys were not
designed to observe such anomalies.
Ecosystem function refers to processes required for the performance of a
biological system expected under naturally occurring conditions (e.g.,
primary and secondary production, respiration, nutrient cycling, and
decomposition). Assessing ecosystem function includes consideration of
the aggregate performance of dynamic interactions within an ecosystem,
such as the interactions among taxa (e.g., food web dynamics) and
energy and nutrient processing rates (e.g., energy and nutrient dynamics)
(Cairns 1977). Additionally, ecosystem function includes aspects of all
levels of biological organization (e.g., individual, population, and
community condition). Altered interactions between individual
organisms and their abiotic and biotic environments might generate
changes in growth rates, reproductive success, movement, or mortality.
These altered interactions are ultimately expressed at ecosystem-levels of
organization (e.g., shifts from heterotrophy to autotrophy, onset of
eutrophic conditions) and as changes in ecosystem process rates (e.g.,
photosynthesis, respiration, production, decomposition).
The spatial and temporal extent of stressor effects includes the near-field
to far-field range of observable effects of the stressors on a water body.
Such information can be conveyed by biological assessments provided
the spatial density of sampling sites is sufficient to convey changes along
a pollution continuum (U.S. EPA 2013). Use of a continuum provides a
method for determining the severity (i.e., departure from the desired
state) and extent (i.e., distance over which adverse effects are observed)
of an impairment from one or more sources.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Attribute
Description
X. Ecosystem
connectivity
Access or linkage (in space/time) to materials, locations and conditions
required for maintenance of interacting populations of aquatic life. It is
the opposite of fragmentation and is necessary for persistence of
metapopulations and natural flows of energy and nutrients across
ecosystem boundaries. Ecosystem connectivity can be indirectly
expressed by certain species that depend on the connectivity, or lack of
connectivity, within an aquatic ecosystem to fully complete their life
cycles and thus maintain their populations.
There are two commonly recognized categories of connectivity based
upon the typical life history (i.e., two-phase life cycle) of most reef
associated fishes: (1) pre-settlement connectivity through larval dispersal
and (2) post-settlement connectivity (Aguilar-Perera 2004).
Transport of larval reef fish around Puerto Rico, the United States Virgin
Islands, and the uninhabited island of Navassa, which comprise the
Caribbean portion of the US-EEZ, is poorly understood, and is not
reflected in current fish monitoring programs.
Post-settlement connectivity involves 1) juveniles that settle in nursery
areas and progressively migrate using intermediate habitats as they grow
(e.g., mangroves, lagoons and seagrass beds) until reaching deeper adult
habitats; or 2) other kinds of migrations, such as those related with
feeding and spawning. The BCG Fish experts recommended additional
research to better understand the connectivity between sampling
locations and non-coral reef habitats and the necessity of such habitats
for each fish species. The knowledge gained from such research would
support the future development of useful metrics.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix C - BCG Levels
The six Levels of the BCG are described as follows (modified from EPA 2016).
Level 1, Natural or native condition—Native structural, functional, and taxonomic integrity is
preserved; ecosystem function is preserved within the range of natural variability. Level 1
represents biological conditions as they existed (or still exist) in the absence of measurable
effects of stressors and provides the basis for comparison to the next five Levels. The Level 1
biological assemblages that occur in a given biogeophysical setting are the result of adaptive
evolutionary processes and biogeography. For this reason, the expected Level 1 assemblage of a
coral reef from the Caribbean will be very different from that of a coral reef in the Pacific. The
maintenance of native species populations and the expected natural diversity of species are
essential for Levels 1 and 2. Non-native taxa (Attribute VI) might be present in Level 1 if they
cause no displacement of native taxa, although the practical uncertainties of this provision are
acknowledged (see section 2.2). Attributes I and II (i.e., historically documented and sensitive
taxa) can be used to help assess the status of native taxa when classifying a site or assessing its
condition.
Level 2, Minimal changes in structure of the biotic community and minimal changes in
ecosystem function—Most native taxa are maintained with some changes in biomass and/or
abundance; ecosystem functions are fully maintained within the range of natural variability.
Level 2 represents the earliest changes in densities, species composition, and biomass that occur
as a result of slight elevation in stressors (e.g., increased temperature regime or nutrient
pollution). There might be some reduction of a small fraction of highly sensitive or specialized
taxa (Attribute II) or loss of some endemic or rare taxa as a result. The occurrence of non-native
taxa should not measurably alter the natural structure and function and should not replace any
native taxa. Level 2 can be characterized as the first change in condition from natural, and it is
most often manifested in nutrient-polluted waters as slightly increased richness and density of
either intermediate sensitive and intermediate tolerant taxa (Attributes III and IV) or both.
Level 3, Evident changes in structure of the biotic community and minimal changes in
ecosystem function—Evident changes in structure due to loss of some highly sensitive native
taxa; shifts in relative abundance of taxa, but sensitive-ubiquitous taxa are common and
relatively abundant; ecosystem functions are fully maintained through redundant Attributes of
the system. Level 3 represents readily observable changes that, for example, can occur in
response to organic pollution or increased temperature. The "evident" change in structure for
Level 3 is interpreted to be perceptible and detectable decreases in highly sensitive taxa
(Attribute II) and increases in sensitive-ubiquitous taxa or intermediate organisms (Attributes III
and IV).
Level 4, Moderate changes in structure of the biotic community with minimal changes in
ecosystem function—Moderate changes in structure due to replacement of some intermediate
sensitive taxa by more tolerant taxa, but reproducing populations of some sensitive taxa are
maintained; overall balanced distribution of all expected major groups; ecosystem functions
largely maintained through redundant traits. Moderate changes of structure occur as stressor
effects increase in Level 4. A substantial reduction of the two sensitive Attribute groups
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
(Attributes II and III) and replacement by more tolerant taxa (Attributes IV and V) might be
observed. A key consideration is that some Attribute III sensitive taxa are maintained at a
reduced Level, but they are still an important functional part of the system (i.e., function is
maintained). While total abundance (density) of organisms might increase, no single taxa or
functional group should be overly dominant.
Level 5, Major changes in structure of the biotic community and moderate changes in
ecosystem function—Sensitive taxa are markedly diminished or missing; conspicuously
unbalanced distribution of major groups from those expected; organism condition shows signs of
physiological stress; ecosystem function shows reduced complexity and redundancy; increased
build-up or export of unused materials. Changes in ecosystem function (as indicated by marked
changes in food-web structure and guilds) are critical in distinguishing between Levels 4 and 5.
This could include the loss of functionally important sensitive taxa and keystone taxa (Attribute
I, II, and III taxa), such that they are no longer important players in the system, though a few
individuals may be present. Keystone taxa control species composition and trophic interactions,
and are often, but not always, top predators. As an example, removal of keystone taxa by
overfishing has greatly altered the structure and function of many coastal ocean ecosystems
(Jackson et al. 2001). Additionally, tolerant non-native taxa (Attribute VI) may dominate some
assemblages, and changes in organism condition (Attribute VII) may include significantly
increased mortality, depressed fecundity, and/or increased frequency of lesions, tumors, and
deformities.
Level 6, Severe changes in structure of the biotic community and major loss of ecosystem
function—Extreme changes in structure; wholesale changes in taxonomic composition; extreme
alterations from normal densities and distributions; organism condition is often poor; ecosystem
functions are severely altered. Level 6 systems are taxonomically depauperate (i.e., low diversity
and/or reduced number of organisms) compared to the other Levels. For example, extremely
high or low densities of organisms caused by temperature anamolies, overfishing, and/or severe
habitat alteration may characterize Level 6 systems. Non-native taxa may predominate.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix D - Clean Water Act (CWA)
The US Clean Water Act (CWA) (33 USC § 1251 et seq. 1972) established a long-term objective
to restore and maintain chemical, physical and biological integrity of aquatic resources. The
CWA requires states, territories and tribes (herein referred to as "jurisdictions") to adopt water
quality standards as provisions of jurisdictional law or regulation. Water quality standards
establish the water quality goals for all waters within their jurisdiction, including waters of the
territorial seas, and provide a regulatory basis when the water bodies do not meet their
designated use(s). Components of Water Quality Standards are shown in Figure Dl.
Figure Dl. Components of Water Quality Standards.
Designated Uses/Aquatic Life Uses. Jurisdictions define the water quality goals of their water
bodies by designating the use or uses to be made of each waterbody. Typical designated uses
include aquatic life use; recreation; fishing; public drinking water supply; and agricultural,
industrial, navigational and other purposes. Aquatic life use (ALU) classes describe the expected
biological condition of a jurisdiction's waters. ALUs can cover a continuum of biological
conditions, with some waters being closer to an ideal of natural, undisturbed (biological
integrity) condition (EPA 2002).
Antidegradation Policy. Each jurisdiction must have an antidegradation policy and a plan to
implement that policy. The antidegradation policy is particularly important for outstanding
national resource waters (ONRW).
Criteria. Jurisdictions must also set criteria necessary to protect the uses and protect water
quality through antidegradation provisions. Water quality criteria are expressed as constituent
concentrations, levels or narrative statements, representing a level of water quality that supports
a particular use. Jurisdictions now routinely use biological information to directly assess the
biological condition of their aquatic resources, track changes in the condition, and develop
biological criteria (EPA 2002).
Designated
Uses
Criteria
(Narrative or
Numeric)
Aquatic Life Use (ALU):
A designed use in which
the water body provides
suitable habitat for survival
and reproduction of
desirable fish, shellfish, and
other aquatic organisms
(EPA 2009).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Biological criteria (biocriteria) are benchmark, guideline or threshold values that describe the
expected (or desired) condition for aquatic life in waters with a designated aquatic life use.
Narrative biocriteria are statements that describe a desirable biological condition, such as "a
balanced, healthy population of native aquatic life." Jurisdictions can define narrative biological
criteria early in program development.
To support the narrative criteria, a jurisdiction needs standardized protocols for data collection,
analysis and interpretation, that have been vetted through a rigorous scientific process. These
protocols provide the legal and programmatic basis for numeric criteria (EPA 1990; Karr 1991).
Numeric biocriteria identify specific thresholds expected to support a designated aquatic life
use. For example, assuming protection of coral reef ecosystem "as naturally occurs" is a
designated use, numeric biocriteria might include a minimum percentage of coral cover, a
minimum number of coral species in a defined region, or a maximum number of nonindigenous
fish—at whatever levels are deemed necessary to support the designated use (EPA 2002). When
biological condition does not meet a biological criteria that has been formally adopted into a
state's or territory's WQS through a formal rulemaking process and approved by USEPA, the
waterbody is considered impaired and automatically triggers a regulatory decision.
The Biological Condition Gradient (BCG). Beginning in the late 1990s, EPA collaborated with
freshwater biologists and managers from across the United States to develop and implement the
Biological Condition Gradient (BCG) (Davies and Jackson 2006; EPA 2016). The BCG is a
conceptual framework (Fig. D2) that describes how biological attributes of aquatic ecosystems
(i.e., biological condition) is expected to change along a gradient of increasing anthropogenic
stress (e.g., physical, chemical and biological impacts). The BCG is now a recognized tool in the
water quality management toolbox.
Natural structure & function of biotic community maintained
Minimal changes in structure & function
Evident changes in structure and
C ^6^ minimal changes in function
2
O
"o
S
Moderate changes in structure &
u Lminimal changes in function
3d
Increasing Levels of Stressors
Figure D2. The Biological Condition Gradient (BCG).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix E - BCG Workshops and Webinars
First Workshop (2012) - Proof of Concept. The workshop was held at the Caribbean Coral
Reef Institute in La Parguera, Puerto Rico, on August 21-22, 2012.
The experts evaluated photos and videos for 12 stations collected during EPA coral reef
surveys (2010 and 2011) from Puerto Rico coral reefs exhibiting a wide range of
conditions. The experts individually rated each station as to observed condition (good,
fair or poor) and documented their rationale for the assignment. The group discussed the
reef attributes that characterize biological integrity (or the natural condition) for Puerto
Rico's coral reefs, which will serve as the baseline condition, since the CWA is grounded
in the concept of natural, undisturbed conditions. The experts developed a conceptual
Coral Reef BCG with four Levels of Condition.
Webinars following the first workshop.
2012 Workshop Summary and Overview. Since some experts could not attend the first
workshop, we provided a PowerPoint presentation of the workshop process, including 3
videos representing best, fair and worst stations embedded into the presentation. Showed
them the completed conceptual model.
Generalized Stressor Gradient (23 Jan 2014). EPA and the expert panel discussed the
concept of a generalized stressor axis (GSA) and focused on three stressors that should be
considered for coral reefs: (1) land-based sources of pollution, (2) fishing pressure, and
(3) global climate change-associated thermal anomalies.
Updates, Data, Species Sensitivity (20 Feb 2014). Presented a review of EPA and
NOAA survey methods, discussion of differences and possible biases associated with
each.
Shared the EPA efforts to capture a wide range of species-specific data and reference
citations into a single spreadsheet.
Workshop 2 (2014). The 2nd BCG workshop was held at El Yunque National Forest
Headquarters, Puerto Rico, on April 8-10, 2014. Broke into two groups: benthic organisms and
fish.
Fish. The fish breakout group assigned 128 species (fish observed during EPA's 2010
and 2011 surveys in Puerto Rico) to BCG attributes. The stressor categories that the
experts considered most relevant to fish were land-based sedimentation and fishing
pressure. For fishing pressure, the experts considered whether the species was subject to
fishing pressure, the category of fishing (recreational, aquarium or commercial) and
whether the species was regulated.
The fish experts assigned 38 samples (EPA 2010 and 2011 data) to BCG levels. Panel
members identified several indicators and metrics that they used to distinguish BCG
levels, including taxa richness; total biomass; sensitive taxa; density of damselfish,
piscivores, and other fishes.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Benthic Organisms. The benthic experts assigned 46 scleractinian and hydrozoan hard
coral species found in the Western Atlantic to attributes I-V that defined different levels
of sensitivity and tolerance to specific human-induced stressors. The experts agreed that
thermal anomalies and land-based stressors were the most critical threats to corals, and all
agreed that the stressors must be independently evaluated, because there is no evidence to
suggest the same species would have the same sensitivity to multiple stressors.
EPA Effort following the 2nd Workshop. Following the 2nd workshop, EPA and Tetra Tech
developed quantitative rules for the fish model using the experts' narrative statements and the
box plots to assign numbers to the narrative rules. Some rules suggested by the panel (e.g.,
species per family in Levels 3 and 4; damselfish and wrasses in Level 4, and piscivores in level
4) were either ineffective or redundant and were not used. Rules are expressed as inequalities
(e.g., Level 3 sites have more than 14 species and less than 25% damselfish density), and in this
formulation the rules must be "true" for a site to retain membership in the given level. For
example, observations that there are fewer species and more damselfish in Level 4 sites than in
Level 3, contributes to the rules for Level 3, but not to Level 4 rules.
Webinars following second workshop:
Reef classification (Benthic Group) (26 Feb 2015). Presentation on reef habitat
classification derived from the NOAA Biogeography Caribbean classification scheme.
Evaluated 4 samples and discussed how these related to the habitat classification.
Assigned sites to BCG Levels (Benthic Group) (29 April 2015). Evaluated four
samples and assigned BCG levels. Discussed how these samples related to the fore reef
zone agreed upon for reef classification.
Reviewed quantitative rules (Fish Group) (7 May 2015). Presentation on fish experts'
progress. Reviewed draft quantitative rules. Looked at 4 NOAA stations chosen to be
comparable to the EPA sites - decided the surveys were not comparable.
Assigned sites to BCG Levels (Fish Group) (May 25, 2015).
Assigned sites to BCG Levels (Benthic Group) (26 June 2015). Presentation on
progress of fish group and preliminary fish rules. Evaluated more stations. 4 metrics
provided for each species observed at the station: density (m2), 3D colony surface area
(cm2/m2), 2D colony surface area (cm2/m2), % mortality
Assigned sites to BCG Levels (Benthic Group) (16 July 2015).
Workshop 3 (2015) third workshop held at the International Institute of Tropical Forestry
(IITF), in San Juan, Puerto Rico, on October 13 - 15, 2015.
Fish. The objective for the fish group was to improve the agreement between the expert
ratings and the scores predicted by the preliminary quantitative fish model. The group
reviewed 11 confirmation sites and applied the fish rules that had been established in
Workshop 2 to assign a BCG level to each site. The experts requested, and EPA
provided, the size structure distributions for all stations and for each species. Using the
confirmation sites the model correctly predicted 9 (82% correct).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
There was also a presentation about BCG Attribute X - Connectivity, followed by a
facilitated discussion. The presentation covered basic landscape ecology concepts
including structure, function and landscape metrics. The experts felt that high-resolution
reef bottom topography (LIDAR or other) was critically needed to so that features related
to connectivity would be recognizable and quantifiable. High-resolution topography
would also indicate elements of rugosity as well as connectivity, allowing
characterization of broad-scale relief and a possible basis for classification of reefs. This
project would require coordination among multiple agencies.
Webinars following the 3rd Workshop.
Fish species assignment to BCG attributes (Fish Group only). The experts assigned
the remaining 229 species to BCG Attributes I-VI based upon sensitivity to
anthropogenic stress, historic species importance in the Caribbean, and whether native or
exotic. The information was captured in a spreadsheet, including the assigned attribute,
the species name, common name (English), guild, # observed during EPA and NOAA PR
surveys, rationale for attribute assignment, and unresolved comments.
Update on Fish break-out group (all experts). Updated and presented all boxplots and
histograms to include verification samples. Identified remaining issues, such as habitat
effects and possible classification issues, effects of distance from shore and connectivity,
effects of fishing pressure, interpreting fish size structure is important, biomass could be
expressed differently, and water quality information would help.
Update on Benthic break-out group (all experts). The experts expressed that there
was a lack of metrics like 2D % coral cover, health condition metrics of
corals/octocorals, a need for metrics on benthic community cover addressing algae,
octocorals, zoanthids, sponges subgroups, sediment/substrate and "standing dead" coral.
There was also a need for recruitment measures and water quality (clarity, temperature,
DO). The rugosity measurement needed refinement to determine what used to be there,
what could live there, what is the apparent bioerosion rate. Rugosity could indicate what
kind of reef it was, rather than how degraded it is (geological history). The experts were
dependent on videos but recognized that poor quality videos might affect ratings.
Update on Coral Reef Biocriteria in USVI and Puerto Rico (all experts) (April
2017). Discussed site selection criteria, e.g., don't sample and compare different habitat
types. Define sampling to focus on the fore-reef, shallow and deep, as the best reef class
for consistent assessment. Also considered how to evaluate organism condition and
disease. Decided that additional data needed included % 2D coral cover (more intuitive
than 3D cm2 surface area), health of colonies, and algal coverage (CCA, fleshy, turf,
filamentous, cyanobacteria). It was suggested to use NOAA NCRMP data. Examples
were presented on LPI and DEMO data from NCRMP. Again, there was an emphasis on
sampling protocols and increased replication of shorter transects (10m).
Reef Benthic BCG: Rule Development (Sept 29, 2017). Results from sample ratings of
39 NCRMP samples rated in 2017. Box plots by assigned BCG Level were presented as a
step in establishing numeric rules. Rules were drafted and presented for expert
discussion.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Benthic and fish updates (April, 2018) Agenda items included: Welcome and webinar
purpose, BCG Concepts (very brief review), Level definitions,, Level narrative rules,
Level quantitative rules, Project progress report, Metric patterns with BCG levels, Draft
BCG models, New sample ratings and homework.
Expert ratings of benthic stations (Benthic Group) (18 June 2018). Agenda items
included: Welcome and webinar purpose, Review samples with consistent or variable
ratings, Level descriptions (Definition, Narrative, Semi-quantitative rules, Model rules),
and St Croix homework assignment. Reviewed 3 stations rated by experts as homework.
Discussion of rules that could be tested with box plots.
Workshop 4 (2019) fourth and final workshop held at the Caribbean Coral Reef Institute in La
Parguera, Puerto Rico, on March 12 - 14, 2019, preceded by a Fish Expert Meeting on March
11th.
Webinars following the 4th Workshop.
Benthic model update and review of samples (February 2019). Agenda items
included: Sampling Methods Review (LPI and DEMO), Sample Review for Re-
calibration (Samples rated by the experts at each end of the BC Gradient, Samples with
expert agreement and with high variability), Model Description, Model Mismatches.
Benthic model validation results (July 2020). Agenda items included: Validation
Summary Table (Very Good Agreement!), Reminder slides (Model rules, Levels and
Attributes commonality, Level qualifiers), Model Issues, Sample review slides, and
Screening Model.
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The BCG for Puerto Rico and IJSVI Coral Reefs - Appendices
Appendix F - Gorgonian and Sponge Morphological Shapes
With simulated models and in situ examples (Santavy et al. 2012). The gorgonian morphologies are
shown in the left table and the sponges in the right.
Gorgonian Morphology
Sea Fans
(Gorgonia
ventalina,
Leptogorgia)
(Gorgonia
flabellum)
Sea Rods
branch and
branch let
diameters
15 - <30mm
Sea Whips
branch &
branch let
diameter >5-
<15mm
Planar
Three-
dimensional
Unbranched
(digitate form,
Briareum)
Branched
(Plexaura)
Bushy
(Eunicea
fusca)
Planar
(Eunicea
tourneforti)
Branched
(Pterogorgia)
Bushy
(Pterogorgia
guadalupensi)
Sea Plumes
smallest branch &
branchlet diameter
usually £5mm
(Muriceopsis fiavida,
Pseudopterogorgia)
Encrusting Gorgonians
[Briareum, Erythopodium)
Simulated
Model
f
in situ
Example
Sponge Morphology
(spp. example)
Barrel
{Xestospongia muta,
Verongula reiswigi)
Vase
(Callyspongia plidfera,
Callyspongia vaginalis)
Globe
(Iricinia strobilina,
Sphedospongia vesparium)
Tube
(Aplysina archeri, Aplysina
fistularis)
Mound
(Oligoceras hemorrhages,
Iricinia feltt)
Rod
(Aplysina cauliformis,
Niphates erecta)
Bushy
(Aplysina fulva)
Branched Ropey
(lotrochota birotvlata)
Encrusting
(Amphimedon compressa,
Chrondrilla caribensis)
Boring
(all Oionids)
Simulated
Model
in situ
Example
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix G - Coral Metric Calculations
Metrics were calculated to represent taxa richness, relative richness, taxa density, and percent cover
of coral and other benthic organisms observed within the sampled transects. Metrics were also
calculated with limitations by taxonomy or taxa traits, e.g. the BCG attributes, fish trophic group, or
coral mortality. For the LPI data, each point was 1% of coverage. Taxa richness and percent
coverage was calculated by summation of the point data for the whole transect.
The coral demographic metrics (adapted from Santavy et al. 2012; Bradley et al. 2014b) were
Colony Surface Area (CSA), Live tissue area on Colony Surface Area (LCSA), based on both 2-
dimensional and 3-dimensional calculations. The CSA 3D was the total surface area (cm2) of a
single colony, which includes both living tissue covering the skeleton and dead portions on the three-
dimensional skeletal surface, such that:
CSA = 7tr2M (1)
where, r = [h_cm+ (d_cm/2)] /2 (2)
The variables used to calculate r were: h_cm=maximum colony height (cm), d_cm=maximum
colony diameter (cm), and M = morphological conversion factor. In general, morphological types
and relative values included flat (M=l), hemisphere (M=2), overlapping plates and lobes (M=3), and
branched (M=4) colonies. The LCSA 3D was the total surface area (cm2) of a single colony
including only the living tissue that covered the skeletal surface and was calculated as:
LCSA= CSA (%LT/100) (3)
Where %LT was the estimated percent of colony surface area that contained live tissue. In 2
dimensions, surface area was an estimated value of the total planar colony surface area (cm2) as
though it were viewed only from directly above the colony. The total colony area (CSA 2D) and the
area of living tissue (LCSA 2D) were estimated as:
CSA_2D = 7i [2r (cm)/2]2 (4)
LCSA 2D = 7i [2r (cm)/2]2 * (%LT/100) (5)
Metrics were calculated based on surface area and prevalence of colonies based on species BCG
attributes and ecological traits. Metrics were formulated to replicate the narrative rules expressed by
the expert panel. For a metric example, LCSA2D of large, reef building coral was calculated by
limiting the surface area calculations to those species that are typically massive enough to add
structure to the reef. In this example, the large reef building coral include Acropora cervicornis,
Acroporapalmata, Acroporaprolifera, Colpophyllia natans, Diploria labyrinthiformis, Dendrogyra
cylindrus, Montastraea cavernosa, Orbicella annularis, Orbicella faveolata, Orbicella franksi,
Pseudodiploria clivosa, Pseudodiploria strigosa and Siderastrea siderea.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix H - BCG Coral Reef Experts
Richard Appeldoorn
University of Puerto Rico
Department of Marine Sciences
Mayaguez, PR, 00681 9013
787-899-2048x251
Richard.appeldoorn@upr.edu
Jerry Ault
University of Miami (RSMAS/MBF)
4600 Rickenbacker Causeway
Miami, FL 33149
305-421-4884
iault@rsmas.miami.edu
David Ballantine
Department of Botany, NMNH
Smithsonian Institution
10th St. & Constitution Ave. NW
Washington, DC, 20560
ballantined@si.edu
Jorge Bauza
San Juan Bay Estuary Program
32 Cascada, Munoz Rivera
Guaynabo, PR, 00969
787-638-9979
ibauza@estuario.org
Miguel Canals (Menqui)
Puerto Rico DNER, retired
787-821-5706
menqui@hotmail. com
Lisamarie Carrubba
NOAA Fisheries, Office of Protected Resources
1315 East-West Highway
Silver Spring, MD 20910
301-427-8493
Lisamarie.carrubba@noaa.gov
Randy Clark
NOAA NCOS, Marine Spatial Ecology Div.
1021 Balch Blvd, Suite 1003
Stennis Space Center, MS 39529
228-688-3732
Randy.clark@noaa. gov
David Cuevas
US EPA, Region 2
Caribbean Environmental Protection Div.
48 CARR 165km 1.2
City View Plaza II, Suite 7000
Guaynabo, PR, 00968-8073
787-977-5856
Cuevas.david@epa.gov
Ernesto Diaz
Puerto Rico DNER, CZMP
PO Box 366147
San Juan, PR 00936
787-999-2200 x2729
ediaz@drna.pr.gov
William Fisher
US EPA, ORD, GED
1 Sabine Island Dr.
Gulf Breeze, FL 32563
850-934-9394
Fisher.william@epa.gov
Edwin A. Hernandez-Delgado
University of Puerto Rico
Center Applied Tropical Ecology and
Conservation
PO Box 23360
San Juan, PR 00931-3360
787-764-0000 x2009
Coral giac@vahoo.com
edwin. hernandez 13 @upr. edu
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The BCG for Puerto Rico and USVI Coral Reefs
Evelyn Huertas
US EPA, Region 2
Caribbean Environmental Protection Div.
City View Plaza II - Suite 7000
Guaynabo, PR, 00968-8069
787-977-5852
Huertas.evelyn@epa.gov
Aaron Hutchins
Island Life Adventures
William Roebuck Industrial Park,
Frederiksted 00850
St. Croix, USVI
aaronhutchins@vahoo.com
Chris Jeffrey
CSS-Dynamac, NOAA
10301 Democracy Lane, Suite 300
Fairfax, Virginia 22030
703-691-4612
Chris.Jeffrev@noaa.gov
Craig Lilyestrom
Retired, formerly PR DNER
161 Cesar Gonzalez St. Box 69
San Juan, PR 00918
Craig 02@icloud.com
Melanie McField
Smithsonian Trust
Healthy Reefs for Healthy People Initiative
1648 NE 47th St
Ft Lauderdale FL 33334
954-990-8842
mcfield@healthyreefs.org
Graciela Garcia Moliner
Caribbean Fishery Management Council
270 Munoz Rivera Ave. Suite 401
San Juan, PR, 00918-1913
787-766-5926
Graciela. garcia-moliner@noaa. gov
Appendices
Jeff Miller
Virgin Islands National Park
1300 Cruz Bay Creek,
St. John, VI, 00830
340-693-8950 x227
William J Miller@nps. gov
Simon Pittman
Seascape Analytics LTD.
13 Haddington Road
Plymouth
PL2 1RP
United Kingdom
si pittman@gmail. com
Antares Ramos Alvarez
Integra Foundation
El Caribe 53 Calle Palmeras
San Juan PR 00901-0000
antares.ramos.alvarez@gmail.com
Loretta Roberson
Associate Scientist, The Bell Center
Marine Biological Laboratory
7 MBL Street
Woods Hole, MA 02543 USA
508-289-7097
lroberson@mbl. edu
Caroline S Rogers
USGS Wetland & Aquatic Research Center
Caribbean Field Station
1300 Cruz Bay Creek
St. John, USVI 00830
340 693 8950x221
Caroline rogers@usgs.gov
Hector Ruiz
HJR Reefscaping
P.O. Box 1126
Hormigueros, P.R. 00660
787-691-7410
hectorruizt@me.com
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Alberto Sab at
University of Puerto Rico
Department of Biology
PO Box 23360
Rio Piedras, PR 00931-3360
787-764-0000 x2113
amsabat@gmail.com
Michelle Scharer
Caribbean Fishery Management Council
SW Region/HJR Reefscaping
P.O. Box 1442
Boqueron, PR 00622
Mi chell e. S charer@upr. edu
Steve Smith
University of Miami, RSMAS (CIMAS)
4600 Rickenbacker Causeway
Miami, FL 33149
305-421-4783
steve. smith@rsmas. mi ami. edu
Tyler Smith
University of the Virgin Islands
#2 John Brewer's Bay
St. Thomas, VI, 00802-9990
340-693-1394
tsmith@uvi.edu
Alina Szmant
Adjunct Professor, Center for Marine Science
University of North Carolina, Wilmington
5600 Marvin K. Moss Ln
Wilmington NC 28409 USA
910-962-2362
szmanta@uncw. edu
Brandi Todd
Scientific Support Coordinator, NOAA
500 Poydras, Suite 1213
New Orleans, LA 70130
(504) 589-4416
brandi ,todd@noaa. gov
Vance Vicente
Vicente & Associates Inc.
Garden Hills Pz 1353 19
Guaynabo, PR, 00966
787-781-6503
vance@prtc.net
Brian K. Walker
National Coral Reef Institute
Nova Southeastern University
8000 N. Ocean Drive
Dania Beach, FL 33004
954-262-3675
walkerb@nova. edu
Ernesto Weil
Department of Marine Sciences
University of Puerto Rico, Mayagiiez
PO Box 9000
Mayagiiez, Puerto Rico 00681
787-899-2048 x241/272
ernesto.weil@upr.edu; reefpal@gmail.com
Paul Yoshioka
613 NE Emerson St
Port St. Lucie, FL 34983
772-777 2834
paul.voshioka@upr.edu
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix I - Management Observers at Coral Reef BCG Workshops
Juan J. Cruz Motta
Director of the Caribbean Coral Reef Institute
Department of Marine Sciences
University of Puerto Rico, Mayagiiez
PO Box 9000
Mayagiiez, Puerto Rico 00681
Tel. (787) 899-2048 ext. 228;
i uan. cruz 13 @upr. edu
Damaris Delgado
Puerto Rico DNER
Urb. El Cerezal 1642 Calle Nieper
San Juan PR 00926
787-999-2200x2615
ddel gado@drna. gobi erno ,pr
Annette Feliberty Ruiz
EQB, Point Source Permits Div., WQ
Puerto Rico Environmental Quality Board
P.O. Box 11488
San Juan, PR 00910
787-767-8181
annettefeliberty@ica.pr.gov
Miguel Figuerola
PhD Student of Ernesto Weil, Quant Ecology
Contractor PR DRNA WQ
Department of Marine Sciences
University of Puerto Rico, Mayagiiez
PO Box 9000
Mayagiiez, Puerto Rico 00681
mgfiguerola@drna.pr.org
Leslie Henderson
VI Depart. Planning and Natural Resources
8100 Lindberg Bay, Suite 61
St. Thomas, USVI 00802
340-626-0402
leslie.henderson@dpnr.vi. gov
Kasey Jacobs
Caribbean Landscape Conservation Coop.
Jardin IITF, Botanico Sur
1201 Calle Ceiba, Rio Piedras, PR 00926
787-764-7137
kasevriacobs@caribbeanlcc.org
Benjamin Keularts
Environmental Program Manager, WPC7WQM
Division of Environmental Protection, USVI
45 Mars Hill, Frederiksted, VI 00840
340-773-1082x2274
beni amin.keularts@dpnr. vi. gov
Jeiger Medina Muniz
Protectores de Cuencas
Paisage de Escorial
80 Blvd Media Luna 105
Carolina, PR 00987
787-506-5197
i eiger.medina@gmail. com
Angel R Melendez-Aguilar
Manager- Water Quality Area
Puerto Rico Environmental Quality Board
P.O. Box 11488
San Juan, PR 00910
787-767-8181 x. 3000, 3001
angelmelendez@ica.pr.gov
Tania M. Metz
Puerto Rico Coral Reef Program Coordinator
Calle Sagrado Corazon 467
Cond. Imperial Suites 401C
San Juan, PR 00915
787-999-2200 x 2406
tmetz@drna.pr.gov
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Brent A. Murray
Caribbean Landscape Conservation Coop
Jardin Botanico Sur, USFWS
1201 Calle Ceiba
Rio Piedras, PR 00926
787-764-7738
brent murray@fws.gov
Vanessa Rogers
Environmental Specialist III
Division of Environmental Protection, USVI
340-774-3320x5190
vanessa.rogers@dpnr.vi.gov
Lisbeth San Miguel
Puerto Rico Environmental Quality Board
PO Box 11488
San Juan, PR 00918
787-392-2484
lisbethsanmiguel@ica.gobierno.pr
Roberto Vi qui era
Protectores de Cuencas,
Guanica Coordinator
Box 673
Yauco, Puerto Rico 00698
787-457-8803
rviqueira@hotmail. com
Stacy Williams
Institute Socio-Ecological Research, Inc (ISER)
P.O. Box 3151, Lajas, PR 00667-3151
stcmwilliams@gmail.com; iser@isercaribe.org
Izabela Wojtenko
EPA Region 2 Clean Water Division
290 Broadway New York,
NY 10007-1866
212-637-3814
W oi tenko. Izab ela@epa. gov
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix J - BCG Team
Pat Bradley
Tetra Tech
1810 Harris Ave.
Key West, FL 33040
443-326-4884
Patbradley@comcast.net
Alexandra Gallindo
US Fish and Wildlife Service
Caribbean Ecological Services Field Office
P.O. Box 491
Boqueron, PR 00622
787/851 7297
alexandra galindo@fws.gov
Jeroen Gerritsen
Retired, formerly Tetra Tech
200 Summit blvd
Springfield, OR 97477
410 303-1547
iingyee.ieroen@gmail.com
Christina Horstmann
ORISE Participant, EPA, ORD, GED
1 Sabine Island Dr.
Gulf Breeze, FL 32563
850-934-9247
Horstmann.christina@epa.gov
Susan K.Jackson
Ariel Rios Building; Mail Code: 4304T
1200 Pennsylvania Avenue, N.W.
Washington, DC 20460
202-566-1112
iackson.susank@epa.gov
Ben Jessup
Tetra Tech
73 Main Street #38
Montpelier, VT 05602
802-229-1059
beniamin.iessup@tetratech.com
Leah Oliver
US EPA, ORD, Gulf Ecol. Div.
1 Sabine Island Dr.
Gulf Breeze, FL 32561
850-934-2470
01iver.leah@epa.gov
Deborah Santavy
US EPA, ORD, Gulf Ecol. Div.
1 Sabine Island Dr.
Gulf Breeze, FL 32561
850-934-9358
santavv.debbie@epa.gov
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Appendix K- Development of the Predictive BCG Decision Model
Rule thresholds
The statistical distribution of the metric values in sites assessed by the panel, including modes
and quantiles, were used to establish decision thresholds for assigning sites to each BCG level.
Mathematical fuzzy logic that mimicked human reasoning was used to develop an inference
model to replicate the fish experts' decision process (EPA 2016). Fuzzy logic is "a precise logic
of imprecision and approximate reasoning" (Zadeh 2008) that has been directly applied
worldwide in environmental assessments where imprecise and incomplete information is used to
make decisions on the quality and sustainability of systems (Castella and Speight 1996; Ibelings
et al. 2003; Ionnidou et al. 2003; EPA 2016; Gerritsen et al. 2017). The development of BCG
inference models is explained specifically in Gerritsen et al. (2017), and a general tutorial on
fuzzy logic can be found in Klir (2004).
Model rules were expressed as: metric >x (a- b), where the metric must be at least the rule
threshold (x) and is given partial membership within the range of the minimum rule threshold (a)
and the maximum rule threshold (b). Membership in the given level for each rule was
interpolated between a (0, not a member) and b (1, certainly a member). This fuzzy range around
the threshold accounts for the intrinsic uncertainty about exact quantitative cutoffs. With this rule
construction, the quantitative decision model yielded numeric memberships between 0 and 1 for
each BCG level for each rule. For the BCG Level 3 fish total taxa rule (Figure 1), at the
midpoint of the range (15), the membership factor is 0.5. The total taxa should be a minimum of
10 to indicate any characteristics of Level 3, and full membership is recognized at values above
20. Hence, membership of the site in BCG Level 3 was 0 (zero) when the metric total taxa was
less than or equal to 10, 50% when there were exactly 15 taxa, and 1 (100%) when the value
equaled or exceeded 20.
Metric Value (Number of fish taxa)
Figure K30. Rule diagram illustrating membership in Level 3 based on the rule: Fish taxa >15 (10 - 20).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
When combining multiple rules for any level, the combination strategy used logical operators to
describe whether all rules must be met (using the "and" function) or whether only one of a set of
rules must be met (using the "or" function). For example, if 4 rules are all required to be met to
designate a sample at a level, the combination strategy would be "rule 1 and rule 2 and rule 3 and
rule 4". The resulting membership for the BCG level would be the minimum membership of all 4
rules. If combined with the "or" function (rule 1 or rule 2 or rule 3 or rule 4), membership for the
level would be the maximum membership of the 4 rules.
Because each rule is interpolated between the minimum and maximum of the threshold range, it
is possible to have partial membership for a sample at a level after combining rules. When
applying rules in combination and in a cascade from Level 2 through Level 6, partial
membership at one level implies that the remainder of the membership is at the next level. This
allows for ties between levels, as well as dominant membership in a single level and smaller
memberships in an adjacent level. A 0.30 membership factor indicates partial membership in the
level being scrutinized and 0.70 membership in the next worst level.
How the model rules are applied
In applying the model rules, the rules for BCG Level 2 (or Level 1 if rules exist) are tested first.
If the rules are met, then the model indicates that the sample should be assigned to that Level. If
the model indicates non-membership or partial membership, then rules for the next Level are
tested. This cascade of rule application continues until membership is decided. Partial
membership at any Level implies that the sample has characteristics of that Level and the next in
sequence. If no rules are met at Level 5, then the sample is assigned to Level 6 without
application of any more rules.
Does the
sample meet
ALL BCG level 2
criteria?
NO
»Total coral cover (LPI) > 40% (35 - 45)
» Percent live coral cover (DEMO) > 30% (20 - 40)
» Percent coral mortality (DEMO) <10% (5-15)
• Percent live cover of large, reef building coral > 30% (25 - 35) YES
Assign to
BCG LEVEL 2
Does the sample
meet ALL 1st 4
Rules OR Orbicella
Rule?
NO
• Total coral cover (LPI) > 20% (15 - 25)
> Total coral richness (species #) (LPI) > 4 species (3-5)
» LPI Attribute II, III + IV > 2 species (1-3)
» Live cover of Orbicella (DEMO) > 20% (15 - 25)
• Bare substrate and Turf with sediment <30% (20-40)
> % live Orbicella cover (DEMO) > 20% (15-25)
YES
Assign to
BCG LEVEL 3
Does the
sample meet
3 or more of
BCG level 4
Criteria?
NO
• Total coral cover (LPI) > 15% (10 - 20)
• Non-tolerant coral cover (LPI) > 5% (0 -10)
• 3-D Live coral cover (DEMO) >2000 cm2 /m2 (10000-3000)
• % live Orbicella cover (DEMO) > 2.5% (0-5)
• % live Orbicella cover (LPI) > 2.5% (0-5)
• Density of medium or large colonies (DEMO) >7.5 colonies (5-10)
• Bare Substrate and Turf with Sediment (LPI) < 40% (30-50)
YES
Assign to
BCG LEVEL 4
And so on.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
FigureKS 1. The BCG Rule Application. BCG rules are applied like a cascade. This example is from the Benthic
Rules.
Model Perforamce
Performance of the BCG model was described in terms of agreement between model results and
the median of expert ratings per site. We assessed the number of sites where the model
prediction exactly matched the experts' median opinion ("exact match") and the number of sites
where the model predicted a BCG Level that differed from the median expert opinion
("mismatch" sites). For the mismatched sites, differences between the expert ratings and the
model predictions were examined to determine whether there was a bias to model predictions or
whether the magnitude of the difference was meaningful.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix L - Characterization of BCG Condition Level 1 for coral reefs in
Puerto Rico and the US Virgin Islands
Ernesto Weil
Deptartment of Marine Sciences
University of Puerto Rico
Technical Report completed under USEPA Contract 68HERC20D0019
Introduction
Detecting major changes in natural ecosystems requires well-designed and statistically robust
monitoring programs to determine biological composition and structure over short- and long-
terms to detect trends. Studies that are well-designed, have consistent and standard methods
(quality control). Long-term monitoring programs using permanent transects/quadrats are scarce
and/or incomplete (few localities or short-term) in the Caribbean. Surveys assessing the same
areas using permanent transects over time are the only way to discriminate temporal changes
(variability) in community structure and other population descriptors. The spatial variability
generated by random/haphazardly placement of transects every time the surveys are done in the
same locality are too great to detect these temporal and spatial trends (Miller and Rogers 2016).
Humans are altering coral communities in ways that are unprecedented from the historical record
(Pandolfi and Jackson 2006; van Woesik et al. 2012), as historically dominant coral species
decline, and weedy, opportunistic and more resistant species increase in abundance and cover
over time (Knowlton 2001; McClanahan et al. 2007; Green et al. 2008; Alvarez-Filip et al. 2011;
Garcia-Sais et al. 2017). Climate change, overexploitation of resources, pollution, and disease
have resulted in global declines of live coral cover, diversity and structural complexity of coral
reefs that has been regarded as the world's most complex and biodiverse marine ecosystem
(Gardner et al. 2003; Pandolfi et al. 2003; Alvarez-Filip et al. 2009).
However, community shifts in coral species can often be overlooked as they may be subtle
because coral species identification is challenging, and substantial community changes may
occur on decadal, centennial, or millennial timescales (Pandolfi and Jackson 2006; van Woesik
et al. 2012). Changes may be undetectable as the baseline for what is considered a 'normal'
community composition today is often unknown and may be different from what was considered
'normal' five, 20 or 100 years ago. Shifts in species composition and changes in live coral cover
can occur at different rates depending on the intensity and duration of disturbances, original
composition and structure of the coral community, and its location. The widespread mortality of
massive reef-building coral species in the US Virgin Islands (USVI) and Puerto Rico (PR) during
2005-2007 did not occur in many other Caribbean localities. The increased thermal anomaly that
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
caused coral bleaching was confined to those regions (Wilkinson and Souter 2008). Five years
later, a similar event occurred in the southern Caribbean off the coast of Venezuela, with no
massive coral mortalities reported elsewhere in the Caribbean (Jackson et al. 2014). Coral
community shifts can be rapid, occurring over a single year or several years, as changes observed
in the mid 1980's after mass mortalities of the acroporids (an important foundational species at
that time) and the keystone species of sea urchin, Diadema antillarum (Gladfelter 1982; Lessios
et al. 1984; Knowlton et al. 1990; Pauly 1995; Aronson and Precht 2001b; Jackson et al. 2014).
More importantly, a general lack of temporal (short- and long-term) information on the
presence/status of individual coral species makes it difficult to identify species responses to
environmental change and/or anthropogenic stress, and whether these responses can be
predictable (Darling et al. 2012).
In the last 40 years three major events have produced substantial coral mortalities with different
degrees of coral community changes around the Caribbean. All three were associated with mild
to strong elevated thermal anomalies linked to global climate change. These include the disease-
induced massive mortalities of the branching acroporids and the sea urchin Diadema in the early
1980's, and the disease- and bleaching-induced mass mortalities of the massive reef-building,
foundational coral species (i.e., Orbicella species complex; Pseudodiploria spp., Diploria sp.,
Siderastrea spp., Colpophyllia spp. etc.) in the early 2000's in the northern Caribbean and in
2010 in the southern Caribbean (Weil et al. 2009a; Rogers et al. 2008; Weil and Rogers 2011;
Bastidas et al. 2012). These events were compounded by hurricanes and a wide range of local
and regional impacts related to explosive human population growth, overfishing, coastal
development, sedimentation, pollution, and invasive species (Weil et al. 2003, 2009a; Rogers et
al. 2009; Weil and Rogers 2011; Jackson et al. 2014).
The mass mortality of the acroporids in the early 1980's was the first massive mortality of corals
recorded for the region and marked a major turn for Caribbean reefs. The collapse of the
acroporids resulted in massive losses of live coral, structural complexity, biodiversity,
functionality, and ecological services (Lessios et al. 1984; Lessios 2016; Bythell et al. 1993;
Wilkinson 2005; Aronson and Precht 2001b; Weil et al. 2002; Gardner et al. 2003; Jackson et al.
2014). There was a significant loss of live coral and an increase in algal cover that have not
recovered after nearly 40 years. Gardner et al. (2003) and Jackson et al. (2014) summarized
(metadata analyzes) all monitoring data available for the Caribbean and showed that live coral
cover declined from an average 50% in the 1970's to 10-15% by 2002, which represented
between 70 and 80% of live tissue loss. This dramatic loss was followed by two major thermal
warming anomalies (>12 Degree Heating Weeks-NOAA Coral Reef Watch) that induced
widespread and severe coral bleaching and disease outbreaks in 2005 and 2010 in the
northeastern and south Caribbean respectively. NOAA's Extended Reconstructed SST product
showed that average ocean temperatures during the July-October period for the Caribbean in
2005 exceeded temperatures seen at any time during the prior 150 years (Eakin et al. 2010).
Puerto Rico and the USVI reported average total losses of 53% and 60% of live coral cover
respectively (Miller et al. 2003, 2006, 2009; Weil et al. 2009a). The significant declines of some
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
reef-building species in PR and USVI, combined with similar declines on the Florida Reef Tract,
prompted the listing of several foundational species, such as the acroporids, the Orbicella species
complex, and the pillar coral Dendrogyra cylindrus, as threatened under the United States
Endangered Species Act (71 FR 26852-26861; 79 FR 53851).
While global ocean warming intensifies and thermal anomalies become more frequent, intensive
and extensive bleaching and disease outbreaks will continue to occur (Hughes et al. 2018).
During their long evolutionary history, coral reefs have recovered, expanded and persisted when
relatively good and constant environmental conditions were present. Currently, coral recovery is
imperiled by the high number of distinct disturbances and multiple stressors acting concurrently
and/or in synergy that cause coral mortality. There has been a lack of high-quality environmental
conditions that would allow even partially recovery. The pattern and mode of reproduction,
fertilization success, larval dispersal, recruitment, and juvenile survivorship determine
population and coral community fitness for these foundational taxa and other important
organisms (Szmant 1986; Edmunds 2005; Van Oppen et al. 2002; Vermeij et al. 2003; Vermeij
2006; Harrison 2011). Each process is critical to maintaining healthy coral population dynamics
and the regeneration of healthy coral reef communities (Harrison and Wallace 1990; Vermeij
2005; Weil et al. 2009b; Harrison 2011). Recurrent recruitment failure, lower fecundities, and
low reproductive output for scleractinian corals have been attributed as major factors explaining
why impacted reefs are not recovering from recent mass mortalities (Hughes and Connell 1999;
Hughes and Tanner 2000).
Puerto Rico and the USVI
As in many other Caribbean islands, coral reef ecosystems in the USVI and Puerto Rico
include a mosaic of different habitats, structures and communities (i.e., coral, octocoral,
hydrocoral, crustose coralline algae reefs, seagrasses, soft bottom communities, and mangrove
forests). They all vary in structural complexity, biomass, productivity, and biodiversity; but
they have strong dependencies on the flow of resources and energy. These biologically rich
communities provide important ecosystem services such as shoreline protection and support
valuable socio-economic activities (e.g., fishing and tourism).
In both USVI and Puerto Rico island complexes, coral reefs are mostly found as fringing, bank,
patch, and spur and groove formations distributed near-shore, along the insular platforms and at
the shelf-edge of the island platform down to 60-70 m (Almy and Carrion-Torres 1963; Goenaga
and Cintron 1979; Ogden 1980; Beets et al. 1986; Garcia-Sais et al. 2003, 2005, 2008; Rogers et
al. 2008; Ballantine et al. 2008). However, Randall (1961) referenced the presence of a barrier
reef while making recommendations to recognize Buck Island in St. Croix as a National
Monument and stated that "The barrier reef is undoubtedly the most magnificent coral reef in the
possession of the United States and deserving ofprotection from the depredations of man. The
broad beach at the west end and placid, clear lagoon have excellent recreational potentiality.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Colonies of pelican andfrigate birds and sea turtles are in need of protection "Fringing and
bank coral reefs are the most common. These are located throughout most of the northeast, east,
south and southwestern coastlines associated with erosional consolidated rocky features of the
shelf. In most instances, coral is not the main constituent of the basic reef structure, but its
development has significantly contributed to topographic relief, influencing the sedimentation of
adjacent areas and providing habitat for a taxonomically diverse community that is consistent
with a coral reef system (Garcia-Sais et al. 2003, 2005). The geology of these two groups of
islands is different and has been well described (Adey et al. 1977; Hubbard et al. 1997, 2008;
Acevedo and Morelock 1988; Mann 2005). Modern shelf-edge reefs formed in Puerto Rico and
the USVI some 8,000 years ago (Adey 1978) (Table 1).
The USVI in the northeastern Caribbean, consist of St. Croix (207 km2), St. Thomas (83 km2),
St. John (52 km2) and numerous smaller islands (Dammann and Nellis 1992). An extensive
platform underlies St. Thomas and St. John and connects these islands to Puerto Rico and the
British Virgin Islands. St. Croix, St. Thomas, and St. John have 113, 85 and 80 km of shoreline,
respectively. The most developed reefs in general, are found off the eastern, windward ends of
the islands. Estimates of the spatial extent of coral reef ecosystems from Landsat satellite
imagery for the USVI indicate that coral reef ecosystems cover approximately 344 km2 (down to
18 m depth) or 2,126 km2 (down to 183 m depth) (Rohmann et al. 2005) (Table 1). Puerto Rico,
the easternmost island (18°15' N and 66°30' W) of the Greater Antilles, is about 50 km wide and
180 km long on its east/west axis and has a coastline of 1,384 km including the adjacent islands
of Vieques, Culebra, Desecheo, and Mona. Recent mapping by NOAA of the coastal ecosystems
and associated habitats of Puerto Rico indicate that coral reefs and hard bottom habitats comprise
about 757 km2 (15.1%), seagrass meadows 625 km2 (12.8%), macro algal dominated hard bottom
97 km2 (1.9%) and mangrove fringes and forests covered 73 km2 (1.9%).
Table El. Geographic/Disturbance Information. The impacting hurricane category includes all
hurricanes and tropical storms to impact Puerto Rico and the USVI since 1780 (deadliest
hurricane on record (San Calixto) caused over 27,000 deaths along the Lesser Antilles and
Dominican Republic). Thermal anomalies include those with a temperature accumulation of
more than 6 degree-heating weeks (Eakin et al. 2010) (6 consecutive weeks with water
temperatures 1°C above the historical average for seasons: 2005, 2010, and 2019) that produced
extensive bleaching.
Parameter USVI Puerto Rico
Coastal length
Land area
Maritime area
Population
Reef areas
Impacting Hurricanes
Thermal anomalies
Extensive bleaching
Deadly disease outbreaks
Type of disease
378 km
370 km2
5,894 km2
101,328
134 km2
36 (From 1780 until 2018)
6 (1987, 1998, 1999, 2005, 2010, 2019)
6 (1987, 1998, 1999, 2005, 2010, 2019)
6
WBD, WPD, CYBD, ASP, D. antillarum,
1,087 km
9,000 km2
204,942 km2
3,940,410
471 km2
58 (From 1780 until 2018)
5 (1969, 1998, 2003, 2005, 2010)
5 (1998, 2003, 2005, 2010, 2019)
8
BBD, WBD, WPD, CYBD, ASP,
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
SCTLD D. antillarum, GWD, SCTLD
WBD= white band disease; WPD= white plague disease; CYBD= Caribbean yellow band disease; ASP= aspergillosis; D.
antillarum= mass mortalities of the urchins; GWD= Gorgonia waste disease; SCTLD= Stony coral tissue loss disease.
There is very limited quantitative information for coral reef communities in USVI and PR before
1890. It was not until 1898, with the Fish Hawk expedition that the first organized scientific
study targeting Puerto Rico's coral reefs occurred, including the first in situ reef descriptions.
Reefs off the Mayagiiez area on the west coast were reported to consist primarily of Acropora
palmata and A. cervicornis mixed with brain corals (Pseudodiploria strigosa), and patches of
octocorals (Pseudopterogorgia acerosa and Gorgonia ventalina), the hydrocoral, Millepora
alcicornis, and in the interstices of the reef were starfishes, crustaceans, and the black sea urchin
I), antillarum. Elkhorn coral (A. palmata) was reported to grow close to the surface to 1-3 m
deep with large stands in several areas exposed at low tide (Evermann 1900). This report clearly
describes structurally complex, highly diverse, and healthy reefs dominated by acroporids in
areas where today, all that remains are dead skeletons, rubble, sediment, and algae-covered
consolidated limestone.
Have other healthy coral reef areas suffered the same fate after the development of coastal towns,
ports, and petro-chemical processing industries that caused overfishing and deforestation? Reefs
in Puerto Rico have shown a marked loss of living coral during the past three decades.
According to Morelock et al. (2001), "Rapid rates of human population growth and density in
Puerto Rico, have led to increased deforestation for agriculture and increased discharge of
sewage and industrial waste". According to the State of Coral Reef Ecosystems report (Turgeon
et al. 2002), anthropogenic stressors affecting reefs off urbanized areas in Puerto Rico originated
from human activities initiated during the 1950s - for example massive clearing of mangrove
forests, runoff from large scale agricultural developments, and construction of thermo-electrical
plants on the north and south coasts - to ship groundings, especially those occurring during the
1980's and 1990's. Some of the consequences associated with increased human modifications
include high terrigenous sediment influx, increased nutrient levels, overfishing, and extensive
habitat modification.
In Puerto Rico coral reefs fringe many small islands or cays along the south coast. In some
instances, coral growth has been primarily responsible for the formation of these small cays and
other emergent islands, such as the mangrove and coral cays off La Parguera Natural Reserve
(LPNR), considered to be the best coral reef development in Puerto Rico (Garcia-Sais and
Sabater 2004; Ballantine et al. 2008). Some fringing reefs are also found off the northeast coast,
mostly on the leeward section of the islands off Fajardo (in the Cordillera de Fajardo Natural
Reserve), Culebra, and Vieques. Most of the north shores are exposed to the Atlantic, with
narrow consolidated limestone fringes on top of a short platform that drops rapidly to mesophotic
depths and into the Puerto Rico Trench. All major rivers of Puerto Rico discharge along the
north coast, contributing large amounts of sediments, and lowering visibility and salinity
(Ballantine et al. 2008). In Puerto Rico, reefs with the highest live coral cover are generally
found: at the leeward side of the island (Desecheo, Mona); at offshore islands on the eastern,
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
windward side (Vieques, Culebra, Cayo Diablo); and associated with the mainland shelf-edge in
the south (Derrumbadero), southwest (La Boya Vieja and Weimberg) and west coast
(Tourmaline). Boulder star coral, the Orbicella annularis species complex, is generally the
dominant coral species by substrate cover on reefs with relatively high coral cover. Montastraea
cavernosa, Siderastrea siderea and Porites astreoides constitute the main coral populations of
degraded reefs communities (Ballantine et al. 2008; Garcia-Sais et al. 2008).
Most fringing, windward, exposed reefs around Puerto Rico and the USVI were formed by
extensive stands and thickets of A. palmata and A. cervicornis. Diadema antillarum, one of the
most important herbivores in the region's coral reefs, was very abundant in the USVI and Puerto
Rico until 1983 (Ogden et al. 1973; Levitan 1988; Weil et al. 2002, 2005; Tuohy et al. 2020).
This reef scape changed significantly after the acroporid and the Diadema mortalities in the early
1980's, which resulted in increased turf- and macro-algae as coral populations endured major
losses in live tissues, structural complexity, and biodiversity, with cascading consequences
affecting their functionality and most likely, other important ecological services (Gladfelter
1982; Goenaga and Boulon 1992; Bruckner and Bruckner 1997a, b; Williams et al. 1999; Weil et
al. 2002; Weil and Rogers 2011). Reefs continued to decline slowly, following mild bleaching
events associated with mild thermal anomalies in 1987, 1990, 1998, 1999, and 2003. Up to 90%
of coral species were affected, but no significant coral mortality was observed (Weil et al. 2002,
2009a; NPS 2019; Resource Brief. National Park Service.
https://irma.nps.gov/Datastore/Reference/Profile/2271606.)
Local disease outbreaks (black band disease (BBD), white plague disease (WPD), aspergillosis
(ASP), dark spots disease (DSD), and Caribbean yellow band disease (CYBD)) seem to be
associated with these thermal anomalies since they occurred during the summer and through the
fall following the bleaching events. The deadly CYBD was observed for the first time in 1998
and every following year with prevalence values varying seasonally but steadily increasing on
reefs of Southwest Puerto Rico, Desecheo and Mona Islands (Bruckner and Bruckner 2006;
Harvell et al. 2009; Weil et la. 2009a, b; Bruckner and Hill 2009). Other impacts from
hurricanes, sedimentation, algal overgrowth, overfishing, snail predation, and extensive decline
in water quality, contributed to local mortalities and deterioration of these important
communities (Rogers et al. 1988, 2009; Rogers 1990; Bruckner and Bruckner 2003; Ballantine et
al. 2008; Weil et al. 2009a). In 2005-2006, the north-eastern Caribbean was exposed to the
longest high thermal anomaly (14 degree-heating weeks) that induced the most intensive
bleaching event in recorded history (McClanahan et al. 2009; 2018; Eakin et al, 2010), triggering
new, widespread outbreaks of WPD in both Puerto Rico and the USVI, increasing virulence and
prevalence of CYBD, and outbreaks of other diseases affecting octocorals and crustose coralline
algae.
Up to 80% bleaching prevalence was observed in several reefs Puerto Rico during 2005 and
2010, with more than 90 cnidarian species affected. Five species of hydrocorals (100% of the
species pool), 60 species of scleractinians (90% of the species pool), and 30 octocoral species
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
(20% of the species pool) bleached along with other cnidarians and sponges (Garcia-Sais et al.,
2006; McClanahan et al. 2009, 2018; Prada et al. 2010). Individual species and community-level
disease prevalence, incidence, virulence, and mortality varied significantly both spatially and
temporarily in the different localities. Coral community level disease prevalence reached 32% in
the Spring-Summer of 2006 in Southwest Puerto Rico, with some foundational species showing
up to 50% of their colonies with disease signs (Weil et al. 2009a). Overall, between 53% and
60%) tissue loss was estimated at the coral community level over a few of years in Puerto Rico
and the USVI, most of this caused by disease rather than bleaching outbreaks (Miller et al. 2009;
Rogers et al. 2009; Weil et al. 2009a).
Declines in live coral cover in the USVI from the late 1970's to early 2011 indicates significant
losses ranging from 4% to 60%> of the original live cover over time (Smith et al. 2001, 2010;
Miller et al. 2006, 2009; Edmunds and Elahi 2007; Rogers et al. 2008, 2009; Jackson et al.
2014). Table 5 in Jackson et al. (2014) shows mean coral cover to be 23.1% in St. Croix, 34.1%>
in St. John and 32.5% in St. Thomas from 1970 to 1983; followed by 20.7%, 26.1% and 4.6%
respectively from 1984 to 1998; and 9%, 11.8% and 13.9% respectively from 1999 to 2011. This
represents proportional live cover losses of 62%, 65%, and 57% respectively from 1970 to 2011
(Tsounis and Edmunds 2017), mostly attributed to the AcroporalDiadema die-offs in the early
1980's, and the massive coral species mortalities between 2003 and 2007 (Miller et al. 2006,
2009). Live coral cover stabilized after 2011 and even increased in some well monitored
localities, but it has not recovered to pre-1980's levels (Goenaga and Boulon 1992; Edmunds
2002; Weil et al. 2002; Gardner et al. 2003; Rogers et al. 2009; Jackson et al 2014; South
Florida/Caribbean Network Coral Reef Monitoring 2019
https://irma.nps.gov/Datastore/Reference/Profile/2271606).
For Puerto Rico, the net loss of 70% of live coral referenced in the literature between 1970 and
1984 was only available from Vieques. This high mortality reflected the disappearance of
acroporids. This was probably the fate of most shallow and intermediate (1 to 10 m deep) reef
communities around Puerto Rico and adjacent islands during that time, when acroporids were
dominant and the primary builders of the complex shallow reef framework. Even the Mayagiiez
bay reefs, close to the mouth of the Yaguez River, had well developed acroporid communities in
the late 1800's (Evermann 1900). Similar declines occurred at other localities around the
Caribbean (Jamaica, Curacao, Caymans, etc.) with the major proportional decline in live coral
cover occurring from 1970 to 1984 as a consequence of WBD epizootic around the Caribbean
causing the regional disappearance of acroporids (Gardner 2003; Jackson et al 2014).
Overfishing of herbivorous fish and the Diadema antillarum mortality compounded these effects
by allowing algae to colonize and compete for space, and in many places overgrowing and
killing corals (Knowlton et al. 1990).
Even though a loss of 13% coral cover was reported for Vieques between 1994 and 2011, most
reefs in Fajardo (Culebra), and the south, south-west coast, and Desecheo and Mona islands
probably had significantly higher losses of live coral cover between 1994 and 2011. Culebra and
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
LPNR loss between 60% and 53% respectively, mostly related to disease and the 2005-2006
increased temperature-induced bleaching and subsequent new epizootic events that caused
widespread coral and octocoral mortalities (Hernandez-Delgado et al. 2006, 2010; Weil et al.
2009a; Prada et al. 2010; Jackson et al 2014). There has not been significant recovery on reefs
since 2007, so current live coral cover is ranging between 4% and 32 % for the USVI and Puerto
Rico respectively (Weil et al. 2009a; Miller et al. 2009; Jackson et al. 2014; Smith et al. 2015;
Garcia-Saiset al. 2017; South Florida/Caribbean Network Coral Reef Monitoring in US Virgin
Islands National Park 2019 https://irma.nps.gov/Datastore/Reference /Profile/2271606; Figuerola
et al. 2020). It is also important to keep in mind that variability in live coral cover (percentage),
composition and structure of coral reefs, as well as their response to different stressors could be
significant even at small spatial scales (hundreds of meters).
Several coral reef assessments in both the USVI and Puerto Rico over the years have provided a
broad overview of the continuous overall decline in coral cover (with short periods showing
increases in coral cover), current community characteristics, and the status of change of coral
reef ecosystems, which lead to recommendations for implementation and enforcement of existing
and new regulations to protect these communities (Catanzaro et al. 2002; Garcia-Saiset al. 2004,
2005, 2006; 2008; Miller et al. 2006; Rogers et al. 2008, 2009; Rogers and Miller 2016;
Rothenberger et al. 2008; Tsounis and Edmunds 2017; South Florida/Caribbean Network. 2019.
Coral Reef Monitoring in US Virgin Islands National Park, Buck Island and Salt River 2019
https://irma.nps.gov/Datastore/Reference /Profile/2271606).
Conceptual considerations to characterize BCG Condition Level 1 for fore reef habitats in
Puerto Rico and the USVI.
The standard definition for BCG condition Level 1 framework states "Biological conditions as
they existed (or still exist) in the absence of measurable effects of stressors and provides the
basis for comparison to the next five levels" (EPA 2016). This definition can be complemented
with concepts of biodiversity and ecosystem function which provides a conceptual basis to
model a healthy, stable, functional community. The two most important biological components
are the structure (the overall biodiversity) and the functionality defined by the flux of energy and
resources throughout the community (nutrient recycling, recruitment, productivity, herbivory,
reef accretion, growth of corals and other key organisms, etc.,) that could be reflected as the
resistance to change (stability of the structure, composition, and functionality over time), and the
capacity to recover after a disturbance (resilience).
The BCG Level 1 characterization for biological condition will benefit from inclusion of
properties for reef conditions and traits scientists believed were present in the northern and
northeastern Caribbean reefs before the major disturbances discussed above significantly
changed the region's coral reef landscape to the present. A fully functional and intact BCG Level
1 reef should not just be considered as a structure, but also include components to show it is a
functioning ecosystem with all processes intact. The duration of current local or regional,
favorable environmental conditions for "reef development" are probably too short to allow for
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
the recovery of most coral reef foundational taxa because of the intrinsic life-history
characteristics of these long-lived, slow growing organisms. Significant disturbances such as
bleaching, diseases, storms and pollution are occurring more frequently and with higher
intensity, continuously disrupting and eliminating any positive advances in the ecological
successional process, thus disguising that baseline that keeps eluding us.
Back in the late 1970's for example, many fore reefs probably did not have any significant
acroporid populations and were not affected by the WBD epizootic in the early 1980's. However,
they were most probably impacted by the emergence of the many new diseases affecting the
most foundational, massive species. Black band disease affected most boulder and massive
species since the early 1970's (Antonious 1973; Rutzler et al 1983), and it was followed by other
localized outbreaks (WPD, CYBD, bleaching) until the significant outbreaks of the early-mid
2000'. The combination of highly prevalent diseases together with intense bleaching events
produced significant mortalities across the region, including Puerto Rico and the USVI. Coral
reef structural complexity collapsed, decreasing biodiversity, productivity, trophic networks,
ecological redundancy, reproductive output, and ecosystem functionality; vital reef processes
that were impacted over many years in the future.
High coral cover of a single, dominant species is usually only characteristic of extreme habitats,
like A. palmata dominating shallow exposed frontal reef areas, P. porites monopolizing
extensive back reef areas, or A cervicornis in protected lagoon reef environments. Recovery of
these kinds of habitats might occur faster depending on availability and survival of recruits for
fast growing, weedy species. These species can easily monopolize extensive areas of reef
substrate with favorable environmental conditions that exist for shorter times compared to those
that need stable environmental conditions lasting for long periods, optimal for highly diverse
communities with slow-growing, massive species.
Species diversity can vary substantially from reef to reef, or even habitat-to-habitat within the
same reef. Although not recorded in the literature, local observations of the demise and decline
of highly abundant taxa such as Acropora spp., Millepora spp., and less common species such
Scolymia cubensis, Millepora squarrosa, Isophyllia spp., and D. cylindrus in the last 20-30
years, support assumptions that perhaps hundreds or thousands of other invertebrate species and
microorganisms associated with coral reefs became locally or regionally extinct. Overall, the loss
of biodiversity was significant, affecting the community functionality (fluxes of energy and
resources; microorganisms providing essential nutrients recycling), with a cascade of detrimental
ecological consequences that ensued thereafter. Due to the variety of concurrent and synergistic
detrimental factors (disturbances) still in progress, neither of these important community
components seem to have recovered to pre-1980's conditions. Moreover, since the foundational
and most important species of coral reefs are modular, slow growing, long-lived taxa, recovery if
any, could take a long time even under the best of conditions.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix M - Coral Species Attribute Assignments Made by Professional
Judgment of Coral Reef Experts
Sediment tolerance was used as a surrogate for landscape stressors and elevated heat tolerance as
a proxy for climate change stressors. The expected density at single site (distribution within a
BCG
Attribute
BCG
BCG
Scientific Name
Common English Name
Sediment
Heat
Attribute
Attribute
Acropora cervicornis
Staghorn coral
3
3
3
Acropora palmata
Elkhorn coral
4
4
3
Acropora prolifera
Fused staghorn
4
4
3
Agaricia agaricites
Lettuce coral
4
4
2
Agaricia fragilis
Fragile saucer coral
NA
Agaricia grahamae
Dimpled sheet coral
NA
Agaricia humilis
Low relief lettuce coral
4
4
2
Agaricia lamarcki
Whitestar sheet coral
3
3
2
Agaricia spp
NA
Agaricia tenuifolia
NA
Cladocora arbuscula
Tube coral
4
4
4
Colpophyllia natans
Boulder brain coral
3
3
3
Dendrogyra cylindricus
Pillar coral
3
3 4
3
Dichocoenia stokesii
Elliptical star coral
4
4
3
Diploria labyrinthiformis
Grooved brain coral
3
3
3
Diploria spp
NA
Eusmilia fastigiata
Smooth flower coral
3
3
3
Favia fragum
Golf ball coral
5
5
4
Helioseris cucullata
3
3
3
Isophyllastrea rigida
Rough star coral
2
2?
2?
Isophyllia sinuosa
Sinuous cactus coral
2
2?
2?
Madracis auretenra
Yellow pencil coral
4
4
3
Madracis decactis
Ten ray star coral
3
24
4
Madracis formosa
Eight-ray star coral
NA
Madracis pharensis
NA
Madracis senaria
Six-ray star coral
NA
Madracis spp
NA
Manicina areolata
Rose coral
5
5
5
Meandrina danae
Butterprint rose coral
NA
Meandrina jacksoni
White valley maze coral
4
4
3
Meandrina meandrites
Maze coral
4
4
3
Meandrina spp
NA
Millepora alcicornis
Branching fire hydrocoral
5
5
2
M-l
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
BCG
Attribute
BCG
BCG
Scientific Name
Common English Name
Sediment
Heat
Attribute
Attribute
Millepora complanata
Blade fire hydrocoral
3
3
2
Millepora spp
NA
Millepora squarrosa
Box fire hydrocoral
NA
2
Montastraea cavernosa
Great star coral
5
5
4 5
Mussa angulosa
Atlantic mushroom coral
4
4
2
Mycetophyllia aliciae
Knobby cactus coral
4
4
3
Mycetophyllia daniana
Low ridge cactus coral
NA
Mycetophyllia ferox
Rough cactus coral
4
4
23
Mycetophyllia lamarckiana
Ridged cactus coral
NA
Mycetophyllia reesi
NA
Mycetophyllia spp
Cactus coral
NA
Oculina diffusa
Diffuse ivory coral
5
5
4
Orbicella annularis
Lobed star coral
4
4
2
Orbicella annularis complex
4
Orbicella faveolata
Mountainous star coral
4
4
2
Orbicella franksi
Boulder star coral
4
4
2
Orbicella spp
4
Porites astreoides
Mustard hill coral
5
5
5
Porites branneri
Blue crust coral; porous coral
NA
Porites colonensis
Honeycomb plate coral
NA
Porites divaricata
Thin finger coral
5
5
4
Porites furcata
Branching finger coral
4
4
45
Porites porites
Clubtip finger coral
4
4
4
Porites spp
4
Pseudodiploria clivosa
Knobby brain coral
5
5
4
Pseudodiploria strigosa
Symmetrical brain coral
5
5
4
Scleractinia spp
Stony coral
NA
Scolymia cubensis
Solitary disk corals
4
4
4
Scolymia lacera
Solitary disk corals
4
4
4
Scolymia spp
NA
Siderastrea radians
Lesser starlet coral
5
5
5
Siderastrea siderea
Massive starlet coral
5
5
4
Siderastrea spp
NA
Solenastrea bournoni
Smooth star coral
5
5
4
Solenastrea spp
NA
Stephanocoenia intersepta
Blushing star coral
5
5
4
Tubastraea coccinea
Orange cup coral
6
M-2
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix N - Bent hie Metrics Used in Developing BCG Rules
Metric
Description
Ecological Rationale
Percent Coral Cover
(LPI)
Percent cover is
calculated by
dividing the number
of points on the LPI
survey where stony
coral was recorded
by the number of
total points along
the transect
The percentage of the seafloor occupied by living
scleractinian corals. Coral cover is related to habitat
complexity and is a predictor of fish and invertebrate
diversity and abundance (Risk 1972; Luckhurst and
Luckhurst 1978; Gladfelter et al. 1980; Bell and Galzin
1984; Friedlander et al. 2003; Jones et al. 2004; Gratwicke
and Speight 2005; Idjadi and Edmunds 2006; Alvarez-Filip
et al. 2009; Dustan, Doherty and Pardede 2013).
Percent live coral
cover (DEMO)
From the DEMO
survey; calculated in
2 dimensions based
on colony diameter,
height, and mortality
measures
Stony corals are marine invertebrates that live in colonies of
many identical individual soft-bodied polyps. At the base of
each polyp is a hard, protective limestone skeleton called a
calicle, which connect to other calicles, forming a coral
colony that acts as a single organism. Coral colonies are
unique in that they can experience partial tissue death and
still remain alive. Live coral cover is the primary indicator of
the health of coral reefs. Studies have shown a positive
relationship between live coral cover and fish diversity or
abundance, including abundance of obligate coral-dwelling
species and corallivorous fishes (Bell and Galzin 1984; Sano
et al. 1984; Bouchon-Navaro and Bouchon 1989; Chabenet
et al. 1995; Jones et al. 1997; Syms and Jones 2000; Kokita
and Nakazono 2001; Spalding and Jarvis 2002; Pratchett et
al. 2006).
Percent live cover of
large, reef-building
coral (DEMO)
From the DEMO
survey
Large Reef-Building Corals (LRBC) include Orbicella,
Acropora, Diploria, Pseudodiploria, Colpophyllia,
Dendrogyra, Monteastrea cavernosa, and Siderastrea
siderea. Orbicella and Acropora are the major reef building
coral genera in the Caribbean.
% live Orbicella cover
(DEMO and LPI)
% cover as
calculated from the
DEMO or LPI
surveys
High Orbicella cover was considered a dependable indicator
of relatively undisturbed reef conditions (Goreau 1959;
Cruz-Pinon et al 2003; Kramer 2003; Oliver et al. 2018).
3-D Live Coral Cover
(DEMO)
From the DEMO
survey
Calculated in 3 dimensions based on colony diameter,
height, morphology, and mortality measures. Rational is as
described for Percent Live Coral Cover (DEMO)
N-l
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Metric
Description
Ecological Rationale
Total Coral Richness
(LPI)
From the LPI survey
Species richness is the number of different species
represented in an ecological community, landscape or
region. Species richness is simply a count of species, and it
does not take into account the abundances of the species or
their relative abundance distributions. Coral species richness
is correlated with fish species richness. Some coral reef fish
are dependent on live coral, juveniles of many fish species
prefer to settle near live coral and some fish species exhibit
preferences for specific coral species or morphologies
(Beukers and Jones 1997; Munday 2001; Holbrook et al.
2002a, b; Jones et al. 2004; Pratchett et al. 2008;
Komyakova et al. 2013).
Non-tolerant Coral
Richness (DEMO and
LPI)
# taxa (both DEMO
and LPI)
Number of coral species that have demonstrated or are
thought to be sensitive to anthropogenic stressors (BCG
Attributes I, II and III).
Density of Colonies
(DEMO)
From the DEMO
survey
Density is the number of individuals observed per unit area;
in the case of coral surveys the unit area is m2 of seafloor.
Coral density characterizes the proximity of colonies to
one another—a factor that affects disease transmission,
sexual reproduction and recruitment (Fisher 2007).
Density of medium or
large colonies
(DEMO)
From the DEMO
survey
Coral colony size is an important indicator of growth,
reproduction, population dynamics and community
interactions (Fisher et al. 2007). It takes a long time to grow
a large coral colony. Measured as the number of number of
colonies with a diameter > 20cm within the transect. Larger
colonies indicate stability of coral growing conditions over
time (Fisher et al 2008).
Percent coral mortality
(DEMO)
From the DEMO
survey
Mortality indicates poor individual and community condition
(Lirman et al. 2014)
Bare Substrate and
Turf with Sediment
(LPI)
From the LPI survey
Reef habitat that is not supporting healthy live organisms
indicates that the reef is either patchy or unable to sustain a
growing benthic assemblage.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix O - Fish Species Attribute Assignments Made by Professional
Judgment of Coral Reef Experts
Notes: (1) Assigned attributes are based upon sensitivity to fishing pressure and sediment stress and apply to the
entire US Caribbean unless otherwise noted in Column (2) Florida Assigned Attribute; 3) Abbreviations for the
trophic guilds are: H= herbivore, P = piscivores, I =invertivore, and Z = zooplanktonivore
Assigned FL Assigned Species Name
Attribute (1) Attribute (2)
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
Attribute I: Historically documented, sensitive, long-lived, or regionally endemic taxa
I Acanthostracion polygonius
Honeycomb cowfish
I
I Acanthostracion quadricomis
Scrawled cowfish
I
I Carcharhinus limbatus
Blacktip shark
P
LP
I Carcharhinus perezii
Caribbean reef shark
P
LP
I Epinephelus itajara
Atlantic Goliath Grouper
P
LP
I Epinephelus morio
Red grouper
I
I Epinephelus striatus
Nassau grouper
P
LP
I Mvcteroperca bonaci
Black grouper
P
LP
I Mvcteroperca interstitialis
Yellowmouth grouper
P
SP
I Mvcteroperca tigris
Tiger grouper
P
LP
I Mvcteroperca venenosa
Yellowfin grouper
P
LP
I Scarus coelestinus
Midnight parrotfish
H
I Scarus coeruleus
Blue parrotfish
H
I Scarus guacamaia
Rainbow parrotfish
H
I Sphyrna mokarran
Great Hammerhead
Shark
P
LP
Attribute II: Highly sensitive taxa (fishing pressure and sediment stress)
II Aetobatus narinari
Spotted eagle ray
I
II Aluterus scriptus
Scrawled filefish
I
II Amblvcirrhitus pinos
Redspotted hawkfish
Z
II Anisotremus Surinam en sis
Black margate
I
II Astrapogon stellatus
Conchfish
I
II Aulostomus maculatus
Trumpetfish
P
SP
II Cantherhines macrocerus
II Cantherhines pullus
America whitespotted
filefish
Orangespotted filefish
I
H
II Caranx crvsos
Blue runner
P
SP
II Caranx hippos
Crevalle jack
P
LP
II Cephalophilus furcifer
Atlantic creolefish
Z
0-1
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
II
Chaenopsis limbaughi
Yellowface pikeblenny
I
II
Chaetodipterus faber
Atlantic spadefish
I
II
Chromis cyanea
Blue chromis
Z
II
Chromis multilineata
Brown chromis
z
II
Clepticus parrae
Creole wrasse
z
II
Dactvlopterus volitans
Flying gurnard
I
II
Dasvatis americana
Southern stingray
I
II
Elacatimis genie
Cleaner goby
H
II
Elacatinus multifasciatus
Greenbanded goby
I
II
Elacatimis oceanops
Neon goby
I
II
Elacatimis prochilos
Broadstripe goby
I
II
Elacatimis saucrum
Leopard goby
I
II
Enchelycore nigricans
Viper moray
P
SP
II
Fistularia tabacaria
Bluespotted cornetfish
P
SP
II
Galeocerdo cuvier
Tiger shark
P
LP
II
Ginglymostoma cirratum
Nurse shark
P
LP
II
Gramma loreto
Fairy basslet
I
II
Haemulon chrysargyreum
Smallmouth grunt
I
II
Halichoeres radiatus
Puddingwife
I
II
Heteropriacanthus cruentatus
Glasseye snapper
Z
II
Holacanthus ciliaris
Queen angelfish
I
II
Holacanthus tricolor
Rock beauty
I
II
Hypoplectrus gemma
Blue hamlet
II
Hypoplectrus hybrid
Hybrid hamlet
II
Lachnolaimus maximus
Hogfish
I
II
Lactophrys triqueter
Smooth trunkfish
I
II
Lactophrys bicaudalis
Spotted trunkfish
I
II
Lactophrys trigonus
Trunkfish
I
II
Lutjanus analis
Mutton snapper
I
II
Lutjanus cyanopterus
Cubera snapper
P
LP
II
Lutjanus jocu
Dog snapper
P
LP
II
Melichthys niger
Black durgon
H
II
Negaprion brevirostris
Lemon Shark
P
LP
II
Pareques acuminatus
Highhat
I
II
Priacanthus arenatus
Bigeye
I
0-2
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned FL Assigned
Attribute (1) Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
II
Priolepis hipoliti
Rusty goby
I
II
II
Prognathodes aculeatus
Scomberomorus regalis
Longsnout butterflyfish
Cero
I
P
SP
II
Seriola dumerili
Greater ambeijack
P
LP
II
Seriola rivoliana
Almaco jack
P
LP
II
Serranus tigrinus
Harlequin bass
I
II
Thalassemia bifasciatum
Bluehead
I
II
Trachinotus falcatus
Permit
I
II
Trachinotus goodei
Palometa
P
SP
II
Xanthichthvs ringens
Sargassum triggerfish
Z
Attribute HI: Intermediate sensitive taxa (fishing pressure and sediment stress)
III
Abudefduf taurus
Night sergeant
H
III X
Acanthemblemaria aspera
Roughhead blenny
I
III
Acanthemblemaria maria
Secretary blenny
I
III
Acanthemblemaria spinosa
Spinyhead blenny
I
III
Acanthurus chirurgus
Doctorfish
H
III
Acanthurus coeruleus
Blue tang
H
III
Acanthurus tractus
Ocean surgeonfish
H
III
Apogon aurolineatus
Bridle cardinalfish
Z
III
Apogon binotatus
Barred cardinalfish
Z
III
Apogon lachneri
Whitestar cardinalfish
Z
III
Apogon quadrisquamatus
Sawcheek cardinalfish
Z
III
Astrapogon puncticulatus
Blackfin cardinalfish
I
III
Balistes vetula
Queen triggerfish
I
III
Bodianus pulchellus
Spotfin hogfish
I
III
Bodianus rufus
Spanish hogfish
I
III
Canthidermis sufflamen
Ocean triggerfish
I
III
Caranx latus
Horse-Eye jack
P
SP
III
Caranx lugubris
Blackjack
P
LP
III
Centropomus undecimalis
Common snook
P
SP
III
Centropyge aurantonotus
Flameback angelfish
H
III
Cephalopholis cruentata
Graysby
P
SP
III
Cephalopholis fulva
Coney
P
SP
III
Chaetodon capistratus
Foureye butterflyfish
I
III
Chaetodon ocellatus
Spotfin butterflyfish
I
0-3
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
III
Chaetodon striatus
Banded butterflyfish
I
III
Chilomvcterus antennatus
Bridled burrfish
I
III
Chromis insolata
Sunshinefish
Z
III
X
Coryphopterus dicrus
Colon goby
I
III
X
Coryphopterus eidolon
Pallid goby
I
III
Coryphopterus lipernes
Peppermint goby
I
III
Cosmocampus elucens
Shortfin pipefish
I
III
Diodon holocanthus
Balloonfish
I
III
Echidna catenata
Chain moray
I
III
Elacatinus chancei
Shortstripe goby
I
III
Elacatinus louisae
Spotlight goby
I
III
Emmelichthvops atlanticus
Bonne tmouth
SP
III
Epinephelus adscensionis
Rock hind
I
III
Epinephelus guttatus
Red hind
SP
III
Equetus lanceolatus
Jackknife fish
I
III
Equetus punctatus
Spotted dram
I
III
Gymnothorax miliaris
Goldentail moray
SP
III
Gymnothorax vicinus
Purplemouth moray
SP
III
Haemulon album
Margate (White)
I
III
Haemulon carbonarium
Caesar grant
I
III
Haemulon flavolineatum
French grunt
I
III
Haemulon macrostomum
Spanish grant
I
III
Haemulon parra
Sailors choice
I
III
Halichoeres garnoti
Yellowhead wrasse
I
III
Halichoeres maculipinna
Clown wrasse
I
III
Halichoeres pictus
Rainbow wrasse
I
III
Hippocampus reidi
Longsnout seahorse
I
III
Holocentrus adscensionis
Squirrelfish
I
III
Holocentrus rufus
Longspine squirrelfish
I
III
Hypoplectrus aberrans
Yellowbelly hamlet
I
III
Hypoplectrus chlorurus
Yellowtail hamlet
I
III
Hypoplectrus guttavarius
Shy hamlet
I
III
Hypoplectrus indigo
Indigo hamlet
I
III
Hypoplectrus nigricans
Black hamlet
P
SP
III
Hypoplectrus puella
Barred hamlet
I
0-4
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
III
Hypoplectrus randallorum
Tan hamlet
I
III
Hypoplectrus unicolor
Butler hamlet
P
SP
III
Kvphosus sectator
Chub (Bermuda/Yellow)
H
III
Labrisomus nuchipinnis
Hairy blenny
I
III
Liopropoma rubre
Peppermint basslet
I
III
Lutjanus buccanella
Blackfin snapper
P
SP
III
Lutjanus mahogoni
Mahogany snapper
P
SP
III
Lutjanus svnagris
Lane snapper
P
SP
III
Malacanthus plumieri
Sand tilefish
I
III
X
Malacoctenus aurolineatus
Goldline blenny
I
III
X
Malacoctenus macropus
Rosy blenny
I
III
Malacoctenus versicolor
Barfin blenny
I
III
Megalops atlanticus
Tarpon
P
LP
III
Microspathodon chrvsurus
Yellowtail damselfish
H
III
Monacanthus ciliatus
Fringed filefish
H
III
Monacanthus tuckeri
Slender filefish
Z
III
Mulloidichthvs martinicus
Yellow goatfish
I
III
Myrichthvs breviceps
Sharptail eel
I
III
Myrichthvs ocellatus
Goldspotted eel
I
III
Myripristis jacobus
Blackbar soldierfish
I
III
Neonifon marianus
Longjaw squirrelfish
I
III
Odontoscion dentex
Reef croaker
Z
III
Ophichthus ophis
Spotted snake eel
P
SP
III
Opistognathus aurifrons
Yellowheadjawfish
Z
III
Opistognathus macrognathus
Banded jawfish
I
III
Opistognathus whitehursti
Dusky jawfish
I
III
X
Parablennius marmoreus
Seaweed blenny
z
III
Pempheris schomb urgkii
Glassy sweeper
I
III
Pomacanthus arcuatus
Gray angelfish
I
III
Pomacanthus paru
French angelfish
I
III
Pseudupeneus maculatus
Spotted goatfish
I
III
Rvpticus saponaceus
Greater soapfish
III
Sargocentron bullisi
Deepwater squirrelfish
I
III
Sargocentron coruscum
Reef squirrelfish
I
III
Scarus iseri
Striped parrotfish
H
0-5
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
III
Scarus taeniopterus
Princess parrotfish
H
III
Scarus vetula
Queen parrotfish
H
III
Scomberomorus cavalla
King mackerel
III
Scomberomorus maculatus
Spanish mackerel
III
Scorpaena plumieri
Spotted scorpionfish
I
III
Selar crumenophthahnus
Bigeye scad
P
SP
III
Serranus tabacarius
Tobaccofish
P
SP
III
Sparisoma atomarium
Greenblotch parrotfish
H
III
Sparisoma chrysopterum
Redtail parrotfish
H
III
Sparisoma rubripinne
Yellowtail parrotfish
H
III
Sparisoma viride
Stoplight parrotfish
H
III
Sphoeroides spengleri
Bandtail puffer
I
III
Sphyraena barracuda
Great barracuda
P
LP
III
Sphyraena picudilla
Southern sennet
P
SP
III
Stegastes partitus
Bicolor damselfish
H
Attribute IV: Intermediate tolerant taxa (fishing pressure
and sediment stress)
IV
Abudefduf saxatilis
Sergeant major
I
IV
Alphestes afer
Mutton hamlet
I
IV
Anisotremus virginicus
Porkfish
I
IV
Apogon maculatus
Flamefish
Z
IV
Apogon pseudomaculatus
Twospot cardinalfish
Z
IV
Apogon townsendi
Belted cardinalfish
Z
IV
Archosargus rhomboidalis
Sea bream
H
IV
Both us lunatus
Peacock flounder
P
SP
IV
Bothus ocellatus
Eyed flounder
P
SP
IV
Calamus bajonado
Jolthead porgy
I
IV
Calamus calamus
Saucereye porgy
I
IV
Calamus nodosus
Knobbed porgy
I
IV
Calamus penna
Sheepshead porgy
I
IV
Calamus pennatula
Pluma
I
IV
Calamus proridens
Littlehead porgy
IV
Calamus LINK
Porgy
I
IV
Canthigaster rostrata
Sharpnose puffer
I
IV
Carangoides bartholomaei
Yellow Jack
P
LP
IV
Carangoides ruber
Bar jack
P
SP
0-6
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
IV
Chloroscombrus chrvsurus
Atlantic bumper
Z
IV
Conger triporiceps
Manytooth conger
P
SP
IV
X
Coryphopterus glaucofraenum
Bridled goby
I
IV
IV
X
Coryphopterus
person atus/hyalin us
Cryptotomus roseus
Masked/Glass goby
Bluelip parrotfish
I
H
IV
X
Ctenogobius saepepallens
Dash goby
I
IV
Diodon hystrix
Porcupine fish
I
IV
IV
Eucinostomus argenteus
Eucinostomus jonesii
Spotfin mojarra/Silver
mojarra
Slender mojarra
I
IV
Eucinostomus melanopterus
Flagfin mojarra
I
IV
X
Gnatholepis thompsoni
Goldspot goby
H
IV
Gynmothorax funebris
Green moray
P
SP
IV
Gvmnothorax moringa
Spotted moray
P
SP
IV
Haemulon aurolineatum
Tomtate
I
IV
Haemulon plumierii
White grunt
I
IV
Haemulon sciurus
Bluestriped grunt
I
IV
Halichoeres bivittatus
Slippery dick
I
IV
Inermia vittata
Boga
Z
IV
Lutjanus apodus
Schoolmaster
P
SP
IV
Lutjanus griseus
Gray snapper
P
SP
IV
Ocvurus chrvsurus
Yellowtail snapper
Z
IV
X
Ophioblennius macclurei
Redlip blenny
H
IV
Paradiplogrammus bairdi
Lancer dragonet
I
IV
Sargocentron vexillarium
Dusky squirrelfish
I
IV
Serranus baldwini
Lantern bass
I
IV
Serranus flaviventris
Twinspot bass
P
SP
IV
Serranus tortugarum
Chalk bass
Z
IV
Sparisoma aurofrenatum
Redband parrotfish
H
IV
Sparisoma radians
Bucktooth parrotfish
H
IV
Stegastes adustus
Dusky damselfish
H
IV
Stegastes diencaeus
Longfin damselfish
H
IV
Stegastes leucostictus
Beaugregory
H
IV
Stegastes planifrons
Threespot damselfish
I
IV
Stegastes variabilis
Cocoa damselfish
H
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
IV
Xvrichtvs splendens
Green razorfish
Z
Attribute V: Tolerant taxa (fishing pressure and sediment stress)
V
Diplodus argenteus
Silver porgy
H
V
Gerres cinereus
Yellowfin mojarra
I
V
Alugil cephalus
Striped mullet
Z
V
Sphoeroides testudineus
Checkered puffer
I
V
Synodus foetens
Inshore lizardfish
P
SP
Attribute VI: Non-native or intentionally introduced species 1
VI
Callogobius clitellus
Saddled goby
I
VI
Pterois volitans
Red lionfish
P
NA
Attribute x: No attribute assignment (insufficient data); x-MNS - survey method not sufficient to observe actual count;
x-UNK - surveyor did not identify down to species; x- NRF - not a reef fish; x-NPR - species not found in Puerto Rico
x-MNS
Ablennes hi arts
Flat needlefish
P
SP
x-MNS
Acanthemblemaria LINK
Tube Blenny
I
x-NRF
Acanthocvbium solandri
Wahoo
x-UNK
Acanthurus LINK
Surgeonfish
H
x-MNS
Acentronura dendritica
Pipehorse
I
x-NRF
Albula vulpes
Bonefish
I
x-NRF
Alectis ciliaris
African pompano
P
SP
x-UNK
Apogon LINK
Cardinalfish
Z
X
Archosargus probatocephalus
Sheepshead
I
x-MNS
Atherinomorus stipes
Hardhead silverside
Z
X
Balistes capriscus
Gray triggerfish
I
x-MNS
Bathygobious soporator
Frillfin goby
I
x-UNK
Belonidae LINK
Needlefish
P
SP
x-MNS
Bollmannia boqueronensis
White-eye goby
I
x-UNK
Bothus LINK
Flounder
P
SP
X
Canthigaster jamestyleri
Goldface toby
I
x-UNK
Canthigaster LINK
Puffer
I
X
Carcharhinus leucas
Bull shark
x-UNK
Caranx LINK
Jack
P
SP
X
Centropristis striata
Black sea bass
P
SP
X
Centropyge argi
Cherubfish
H
x-MNS
Chaenopsis ocellata
Bluethroat pikeblenny
I
x-MNS
Chaenopsis LINK
Pike blenny
I
X
Chaetodon sedentarius
Reef butterflyfish
I
0-8
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
X
Chromis enchrysura
Yellowtail reeffish
I
X
Chromis scotti
Purple reeffish
Z
X
Clupeidae LINK
Herrings
z
x-UNK
Coryphopterus LINK
Goby
I
x-MNS
X
Coryphopterus
punctipectophorus
Ctenogobius stigmaticus
Spotted Goby
Marked goby
I
x-MNS
Decapterus macarellus
Mackerel scad
z
x-MNS
Decapterus punctatus
Round scad
x-UNK
Decapterus LINK
Scad
z
X
Dermatolepis inermis
Marbled grouper
p
SP
X
Diplectrum bivittatum
Dwarf sand perch
I
X
Diplectrum formosum
Sand perch
p
SP
X
Diplodus holbrooki
Spottail pinfish
H
x-MNS
Doratonotus megalepis
Dwarf wrasse
I
X
Echeneis naucrates
Sharksucker
Z
X
Echeneis neucratoides
Whitefin sharksucker
Z
x-MNS
Elacatinus dilepis
Orangesided goby
I
x-MNS
Elacatimis evelynae
Sharknose goby
I
x-MNS
Elacatinus horsti
Yellowline goby
x-MNS
Elacatinus macrodon
Tiger goby
x-MNS
Elacatinus LINK
Goby
I
x-MNS
Elacatinus xanthiprora
Yellowprow goby
x-MNS
Elagatis bipinnulata
Rainbow runner
P
SP
x-MNS
Emblemaria pandionis
Sailfin blenny
z
x-MNS
Emblemaria sp
Tube blenny
z
x-MNS
Emblemariopsis LINK
Blenny
I
x-UNK
Engraulidae LINK
Anchovies
z
x-UNK
Enneanectes LINK
Triplefin
H
x-MNS
Eucinostomus gula
Silver jenny
I
x-UNK
Eucinostomus LINK
Mojarra
I
x-NRF
Euthynnus alletteratus
Little tuny
P
SP
x-MNS
Gobiidae LINK
Goby
I
x-MNS
Gobiosoma gros\>enori
Rockcut goby
I
x-UNK
Gymnothorax LINK
Moray eel
P
SP
X
Haemulon melanurum
Cottonwick
I
0-9
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
Attribute (1)
FL Assigned
Attribute (2)
Species Name
Common Name
Guild
(Caldow
2009)
Large (LP) or
Small
Piscivore (SP)
x-UNK
Haemulon LINK
Grant
I
X
Haemulon striatum
Striped grant
Z
X
Halichoeres burekae
Mardi gras wrasse
I
X
Halichoeres caudalis
Painted wrasse
I
X
Halichoeres cvanocephalus
Yellowcheek wrasse
I
X
Halichoeres poeyi
Blackear wrasse
I
x-UNK
Halichoeres LINK
Wrasse
I
x-MNS
Harengula jaguana
Scaled sardine
x-MNS
Hemiemblemaria simulas
Wrasse blenny
x-MNS
Hemiramphus brasiliensis
Ballyhoo
X
Heteroconger halis
Brown garden eel
z
X
Heteroconger longissimus
Brown garden eel
z
x- MNS
Hippocampus LINK
Pipefish
I
x-MNS
Holacanthus bermudensis
Blue angelfish
I
x-MNS
Holocanthus Townsendi
Townsend angelfish
x-UNK
Holacanthus LINK
Angelfish
I
x-MNS
Hypleurochilus bermudensis
Barred blenny
I
x-UNK
Hypoplectrus LINK
Hamlet
I
x-UNK
Jenkinsia LINK
Herring
z
x-MNS
Labrisomus filamentosus
Quillfin blenny
I
X
Lagodon rhomboides
Pinfish
I
X
Lonchopisthus micrognathus
Swordtail jawfish
z
X
Lophogobius cyprinoides
Crested goby
I
x-NPR
Lutjanus campechanus
Red snapper
p
SP
x-UNK
Lutjanus LINK
Snapper
p
SP
x-MNS
Malacoctenus boehlkei
Diamond blenny
I
x-MNS
Malacoctenus gilli
Dusky blenny
I
x-MNS
Malacoctenus triangulatus
Saddled blenny
I
x-MNS
Malacoctenus LINK
Scaly blenny
I
X
Manta birostris
Giant manta
z
x-MNS
Microgobius carri
Seminole goby
z
X
Microgobius signatus
Microgobius signatus
z
x-UNK
Microgobius LINK
Goby UNK
H
x-UNK
MuUidae LINK
Goatfishes
I
x-UNK
Muraenidae LINK
Moray eel
P
SP
O-IO
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
FL Assigned Species Name
Common Name
Guild
Large (LP) or
Attribute (1)
Attribute (2)
(Caldow
Small
2009)
Piscivore (SP)
x-NPR
Mvcteroperca microlepis
Gag
P
SP
x-NPR
Mycteroperca phenax
Scamp
P
SP
x-UNK
Mvcteroperca LINK
Grouper UNK
P
SP
x-UNK
Mvrichthvs LINK
Snake eel
I
x-MNS
Nes longus
Orangespotted goby
I
X
Nicholsina usta
Emerald parrotfish
H
X
Ogcocephalus nasutus
Shortnose batfish
I
x-UNK
Ophichthidae LINK
Snake eel UNK
P
SP
x-UNK
Opistognathus LINK
Jawfish
Z
X-MNS
Oxyurichthys stigmalophius
Spotfin goby
I
X
Pareques umbrosus
Cubbyu
I
x-MNS
Platybelone argains
Keeltail needlefish
P
SP
x-UNK
Pomacanthus LINK
Angelfish
I
x-NPR
Ptereleotris colli lira
Blue dartfish
X
Ptereleotris helenae
Hovering dartfish
z
X
Remora remora
Common remora
z
X
Rypticus bistrispimis
Freckled soapfish
p
SP
X
Rypticus maculatus
Whitespotted soapfish
p
SP
X
Scartella cristata
Molly miller
H
x-UNK
Scarus LINK
Parrotfish
H
x-UNK
Scorpaena LINK
Scorpionfish UNK
I
X
Scorpaenodes caribbaeus
Reef scorpionfish
X
Serraniculus pumilio
Pygmy sea bass
I
X
Serranus subligarius
Belted sandfish
I
x-UNK
Serranus LINK
Seabass UNK
P
SP
x-UNK
Sparisoma LINK
Parrotfish
H
X
Sphyraena borealis
Northern sennet
P
SP
X
Stephanolepis hispidus
Planehead filefish
H
X
Stephanolepsis setifer
Pygmy filefish
H
x-UNK
Stromateidae LINK
Butterfish
P
SP
x-UNK
Svacium LINK
Sand flounder
I
x-MNS
Svgnathus dawsoni
Pipefish
I
X
Synodus intermedins
Sand diver
P
SP
X
Synodus saurus
Bluestriped lizardfish
P
SP
x-MNS
Tigrigobius dilepis
Orangesided goby
I
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Assigned
FL Assigned
Species Name
Common Name
Guild
Large (LP) or
Attribute (1)
Attribute (2)
(Caldow
Small
2009)
Piscivore (SP)
X
Trachinocephalus myops
Snakefish
Z
x-UNK
Triglidae LINK
Searobin Family UNK
I
X
Tylosurus crocodilus
Houndfish
P
SP
x-NPR
Urobatis jamaicensis
Yellow stingray
X
Xvrichtvs martinicensis
Rosy razorfish
I
X
Xvrichtvs novacula
Pearly razorfish
I
x-UNK
Xvrichtvs UNK
Razorfish
I
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix P - Fish Metrics Used in Developing BCG Rules
Metric
Description
Ecological Rationale
Total taxa - Species
richness
# of fish species at
the site
Reef fish communities on healthy coral reefs are
characterized by high species richness and diversity (Ault
and Johnson 1998 ), often correlated with habitat structural
complexity and heterogeneity (MacArthur 1972; Risk 1972;
Talbot and Goldman 1972; Luckhurst and Luckhurst 1978;
Gladfelter et al. 1980; Carpenter et al. 1981; Hixon and
Beets 1989; Shepherd et al. 1992; Grigg 1994; Galzin et al.
1994; Friedlander and Parrish 1998), and the proportion of
live coral (Carpenter et al. 1981; Sano et al. 1984, 1987; Bell
and Galzin 1984, 1988; Jones et al. 2004; Komyakova et al.
2013).
Biomass (species or
station)
Total weight of all
individuals
Biomass can refer to species biomass, which is the mass of
one or more species, or to station biomass, which is the mass
of all species observed at the station. High fish biomass,
resulting from high density and large fish size, is typical in
coral reef ecosystems in excellent condition (Russ 1985;
Sandin et al. 2008; Dugan and Davis 1993). Biomass is
calculated as the weight of all fish at a station using the
power function: W = a x Lb, where W is the weight (grams),
L is the length (cm), and a and b are parameters estimated by
linear regression of logarithmically transformed length-
weight data. The parameters a and b are shown in the BCG
Data Taxa Master spreadsheet, along with the weight-length
conversion factor. Most of the length-weight relationships
were determined from southern Florida specimens
(Bohnsack and Harper 1988, with exceptions as noted from
Bohnsack and Harper 1988, Bullock et al. 1992, Claro and
Garcia-Arteaga 1994, and Letourneur et al. 1998). For the
fish BCG, biomass was calculated for each species in a
station, and for the entire station (all fish biomass
combined).
Species Abundance
Total # individuals
per species
The abundance of different species can provide insight into
how the reef fish community functions (Nagelkerken et al.
2001). In the case of the BCG, changes in abundance can be
used to infer changes in habitats and/or intensity of threats,
such as fishing pressure (Alvarez-Filip et al. 2013).
Caribbean reef-fish assemblages have been experiencing
profound changes in community composition since 1980,
probably largely due to habitat degradation; with.
generalists replacing habitat-specialists over a 30-year
period, indicative of anthropogenic disturbance (Alvarez-
Filip etal. 2013).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Metric
Description
Ecological Rationale
Abundance of Fish by
BCG Attribute
Total # individuals
The BCG Attributes respond to stressors in distinctly
different ways, so they are predictive, quantitative measures
along the full range of stress levels. "For example, highly
sensitive taxa might disappear from a community in early, or
low, levels of stress. Tolerant taxa might become more
dominant as stress increases, not only because they might
thrive, but also because there are fewer sensitive species and
the proportion of tolerant taxa in the entire community
increases. Intermediate tolerant taxa might not provide a
significant signal under most conditions if they are present
under a wide range of stress. However, the absence of this
group of taxa in highly stressed conditions can help
document highly disturbed conditions, and their
reappearance may indicate initial response to management
actions for restoration" (EPA 2016).
Family: Groupers
# of individuals
Groupers are recognized as sentinel or keystone piscivore
taxa that, when present, indicate a complete trophic structure
on the reef. Groupers are common and are expected to be
observable on high quality reefs using the sampling methods
employed for the FL/PR/USVI surveys. Other large
predators might not be as common and might not always be
observed. The BCG experts categorized groupers as large
and small according to genera. Groupers are taxa in the
recently re-organized Epinephelidae family (Ma and Craig
2018). Large groupers include all species in the Epinephelus
and Mycteroperca genera (Rock hind, Red hind, Atlantic
goliath grouper, Red grouper, Nassau grouper, Black
grouper, Yellowmouth grouper, Gag, Scamp, Tiger grouper,
and Yellowfin grouper). Other (smaller) groupers might be
observed in areas that have been overfished for the large
groupers. They include taxa in the Cephalopholis and
Dermatolepis genera (Graysby, Coney, Atlantic creolefish,
and Marbled grouper). Large, predatory groupers are present
in healthy reef fish communities (Beets and Friedlander
1992, 1998; Beets 1997; Olsen and LaPlace 1979)
Family: Parrotfish
# of large-body
parrotfish
Parrotfish are herbivores that trim algal turf around hard
coral colonies. They might also eat the live coral tissue near
algal mats. They are generally considered beneficial and
indicators of intact reef systems. The Parrotfish metrics were
calculated to include all taxa with Parrotfish in the common
name. This included all species in the Scarus and Sparisoma
genera as well as Cryptotomus roseus (Bluelip parrotfish)
and Nicholsina usta (Emerald parrotfish). Large body
parrotfish are common in reefs with good condition and are
important in the control of macroalgae due to their large size
(Randall 1963).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Metric
Description
Ecological Rationale
Family: Damselfish
% of total taxa
Damselfishes are highly territorial herbivores, aggressively
excluding other herbivore groups such as surgeonfishes,
tangs and parrotfishes from their feeding territories (Emery
1973; Robertson et al. 1976; Sammarco and Williams 1982.
Many damselfishes cultivate algal gardens on coral heads
(Irvine 1980; Lassuy 1980; Hixon and Brostoff 1983; Horn
1989), which can contribute to phase shifts in coral reef
communities. Damselfish are expected to be on the reef in
moderate numbers. If they are highly dominant in terms of
numbers of individuals, then the sample is considered out of
balance, indicating poor biological conditions. Damselfish
were counted as all taxa in the Pomacentridae family. In the
project dataset, this included 14 taxa in the following 4
genera: Abudefduf Chromis, Microspathodon, and Stegastes.
Trophic Group:
Piscivores (predators)
# of individuals
Coral reef ecosystems are shaped by apex predators and their
presence indicates a relatively intact system. Loss of apex
predators alters the patterns of predation and herb ivory,
leading to shifted benthic dynamics (Pauly et al. 1998;
Pinnegar et al. 2000; Borer et al. 2005; Heithaus et al. 2007;
Estes et al. 2011); top carnivores have specialized niches
that when depleted can lead to a cascade of species
extinctions (Pauly et al. 1998; Jennings and Polunin 1997;
Christensen and Pauly 1997; Friedlander and DeMartini
2002; Steneck et al. 2004; Stallings 2008, 2009) and make
them more vulnerable to natural and anthropogenic
disturbances (Hughes 1994; Jackson et al. 2001; Hughes
1994; Gardner et al. 2003). Predators can exert a strong top-
down control on the entire coral reef ecosystem and are
importance in maintaining ecosystem function (Friedlander
et al. 2013).
Note: Red lionfish are predators but are not considered
advantageous because they are invasive and might displace
or prey upon native species. Therefore, lionfish are not
included in metrics related to piscivores/predators.
Large-Bodied Fish
(Large groupers,
Large predators)
# of large-bodied
groupers
# of large-bodied
piscivores
Coral reef ecosystems are shaped by apex predators and their
presence indicates a relatively intact system. Loss of apex
predators alters the patterns of predation and herbivory,
leading to shifted benthic dynamics; top carnivores have
specialized niches that when depleted can lead to a cascade
of species extinctions and make them more vulnerable to
natural and anthropogenic disturbances.
Large predators are less common than small predators,
perhaps because they are targets for fisheries or because they
require a complete array of prey species. In better biological
conditions, large predators are expected. In fair conditions, at
least small predators are expected.
P-3
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Metric
Description
Ecological Rationale
Sensitive Taxa (BCG
Attributes I, II and III
# of taxa
A high percentage of sensitive species (Attributes I, II and
III) indicates a system with minimal stress pressure.
Moderate pollution can produce changes in taxa so that
diversity remains similar to natural but species composition
shifts (e.g., numbers of sensitive forms decrease while
numbers of tolerant species increase (Odum 1985; Rapport
and Whitford 1999; EPA 2016).
Rare, endemic, special
species
# of taxa
Attribute I species are historically documented, long-lived,
or regionally endemic taxa; They may be listed as
Endangered or Threatened (E/T) or special concern species.
Long-lived species are especially important as they provide
evidence of multi-annual persistence of habitat condition or
of minimal fishing pressure. For example, several shark
species historically found on Caribbean coral reefs are now
functionally extinct (Bonfil 1996; Ward-Paige et al. 2010).
Highly sensitive taxa
(BCG Attribute II
species)
# of taxa
Highly sensitive taxa typically occur in low numbers relative
to total population density, but they might make up a large
relative proportion of richness. In high quality sites, they
might be ubiquitous in occurrence or might be restricted to
certain micro-habitats. Their populations are maintained at a
fairly constant level, with slower development and a longer
life-span. They might have specialized food resource needs,
feeding strategies, or life history requirements, and they are
generally intolerant to significant alteration of the physical or
chemical environment. They are often the first taxa lost from
a community following moderate disturbance or pollution.
1 a and (3 are coefficients obtained from FishBase (Froese and Pauly 2002) for calculating biomass (see Santavy et al.
2012). Biomass for species with no published length-weight relationships can be calculated using terms for the
closest congener based on morphology.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Appendix Q- Recommendations for Future Research
Several issues that arose during discussions require further investigated. The issues are discussed
below with possible approaches for resolution.
4. Recommendations from the full group (both benthic and fish experts)
1A. The Generalized Stressor Axis (GSA)
Anthropogenic activities can cause disturbances that exceed the range of natural variability,
exerting pressure on the coral reef ecosystem by altering fundamental environmental processes,
generating stressors that alter the state of the environment, and adversely impacting biotic
condition (Niemi and McDonald 2004). Stress-response relationships are complex and not one-
to-one. Stressors may affect more than one aspect of biological condition, and changes in
biological condition may be the result of multiple stressors acting simultaneously. Many
stressors co-occur in time and space. Coral reef organisms are increasingly being subjected to the
cumulative impacts of multiple stressors. Stressors affect biological assemblages and ecosystem
processes both directly and indirectly, including altering metabolic pathways, energy availability,
and behavior of the organisms (Karr et al. 1986; Adams 1990; Poff et al. 1997). Stressors may
affect more than one aspect of biological condition and a particular change in biological
condition can also be the result of multiple stressors acting simultaneously.
Since multiple stressors are usually present, the x-axis represents their cumulative
spatial/temporal co-occurrence in a generalized stressor axis (GSA), much as the y-axis
generalizes biological condition (Figure Q-l). The BCG curve represents the in-situ response of
the resident biotic community to the sum of stresses to which that community is exposed.
Low High
Figure 01. The Biological Condition Gradient Conceptual Model. The Y-axis is the biological condition,
the x-axis is the generalized stressor gradient, and the BCG curve show the response of the biota to
increasing levels of stressors.
EPA and the coral reef experts discussed the concept of a generalized stressor axis (GSA) and
focused on three stressors that should be considered for coral reefs: (1) land-based sources of
Q-l
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
pollution (sediment), (2) fishing pressure, and (3) global climate change-associated thermal
anomalies.
Elevated Sea Surface Temperature (SST). Most coral reefs occur in tropical latitudes between
22 °S and 22 °N, experience relatively limited seasonal changes in water temperatures (4-5 °C)
and average maximum temperatures of -30 °C (Kleypas et al. 1999). Corals bleach in response
to stress, including sudden changes to light, temperature, and salinity, the presence of toxins and
microbial infections (Hoegh-Guldberg et al. 2011). The first small-scale coral bleaching episode
was reported at the Great Barrier Reef in March 1929 (Yonge and Nichols 1931), when sea
surface temperature (SST) had reached 35°C. However, it is only since 1979 that large-scale
bleaching events that affect most, if not all, of the reef- building corals across entire reefs,
regions, and countries have occurred as a result of warm water coral reefs being exposed to
rising SSTs (Glynn 1979, 1988a, 1991; Goreau et al. 1992; Hoegh-Guldberg and Smith 1989;
Glynn 1993, 2012; Hoegh-Guldberg 1999, 2011; Glynn et al. 2001; Hoegh-Guldberg et al. 2007,
2014; Baker et al. 2008; Eakin et al. 2010; Strong et al. 2011; Gattuso et al. 2014). Elevated
SSTs are correlated with mass bleaching events (Goreau et al. 1992; Glynn 1988b, 1991; Hoegh-
Guldberg 1999; McClanahan et al. 2007; Meissner et al. 2012). Sea surface temperatures have
been rising as a result of anthropogenically induced global climate change.
Bleaching adversely impacts growth and reproduction of corals, and their vulnerability to a range
of diseases (Harvell et al. 1999, 2007; Bruno and Selig, 2007; Baker et al., 2008). A reduction in
reef-building corals also adversely impacts the fish species that live on the reef - fish species
reliant on live coral cover for food and shelter (some 62% of reef fish species) decreased in
abundance within 3 years of disturbance events that reduced coral cover by 10% or more
(Wilson et al. 2006; Glynn 2012).
Sediment Threat (ST). Sedimentation from development along tropical shorelines and runoff
from agricultural land use is widely considered to have adversely impacted coral reef
ecosystems. Risk and Edinger (2011) documented the adverse impacts to stony corals from
increased sediment stress including: decreases in coral growth rates (Bak 1978; Dodge and Brass
1984: Dodge and Vaisnys 1977; Cortes and Risk 1985; Tomascik and Sander 1985. Acevedo and
Morelock 1988; Rogers 1990); partial or total mortality (Bak 1978, 1983; Bak and Steward-Van
Es 1980; Brown et al. 1990; Nugues and Roberts 2003), changes in coral population structure
(Cortes and Risk 1984, 1985; Acevedo and Morelock 1988); Rogers 1990; Maragos 1974);
changes in coral morphology (Bak and Elgershuizen, 1976). Logan (1988); and reduced species
richness and diversity (Cortes and Risk 1985; Acevedo and Morelock 1988; Rogers 1983; Dryer
and Logan 1978; Obura et al. 2000; Sheppard et al. 2000; Gabrie et al. 2000; Hodgson and Dixon
1988; Chou 1997; Dikou and van Woesik 2006; Chansang et al. 1981).
Sedimentation has been documented to adversely impact fish communities, particularly through
impaired feeding, poor water quality, and changes to benthic habitat (Rogers 1990; Bejarano-
Rodrigues 2006; Bejarano and Appeldoorn 2013; Wenger et al. 2015; Neves et al. 2016; Brown
et al. 2017). Reduced light intensity due to turbidity affects the visual cues that many fish species
rely upon, changing social and mating behavior (Jarvenpaa and Lindstrom 2004), and affecting
predator avoidance and foraging success (Leahy et al. 201 1), resulting in reduced fish abundance
and diversity (Amesbury 1981; Mai lei a et al. 2007) and modified trophic structures (Harmelin-
Vivien 1992). Species richness of key functional groups has been shown to significantly decline
as turbidity increases (Moustaka et al. 2018).
Q-2
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Fishing Pressure. Reef fish species have been subjected to intense fishing pressure (Munro
1983; Hughes 1994; Koslow et al. 1988; Williams and Polunin 2001; Jackson et al. 2001;
Pandolfi et al. 2003; Newman et al. 2006; Ault et al. 2005). Large groupers and snappers,
hogfishes, and the large parrotfishes are now rare, with a resultant loss of herbivory and
predation (Pittman et al. 2010; Appeldoorn 2011; Ault et al. 2005, 2013). The reduction of these
species has resulted in "trophic level dysfunction" (Steneck et al. 2004), with food chains now
dominated by small fishes and invertebrates (Hay 1984, 1991; Knowlton et al. 1990; Appeldoorn
and Meyers 1993; Jackson 1997). The reductions in the abundance and sizes of herbivores (e.g.,
parrotfishes, surgeonfishes, and sea urchins) has resulted in some locations with increased
abundance of macroalgae that compete with stony corals (Randal 1961; Lewis 1986; Lirman
2001; Hughes et al. 2007; Jackson et al. 2014).
The Puerto Rico reef fishery declined steadily beginning in the 1930s and then accelerated
rapidly in the late 1950s with massive fishing pressure (Appeldoorn personal communication). In
contrast, reduction in fishing pressure and resultant increases in fish populations has been shown
in the Tortugas Ecological Reserve in Florida, including density, and abundance within
management zones for a suite of exploited and non-target species (Ault et al. 2006, 2013).
EPA began research to develop a GSA, however, the GSA was not completed during the
development of the BCG. A summary of GSA research completed thus far is included as
Appendix K.
This is a priority project, not only for coral reefs, but for all coastal marine and estuarine
ecosystems. Coastal marine and estuarine stressor gradients cannot be as clearly defined as those
in streams. Streams have a distinct catchment and actual flow where the distance from a source
to a given sampling site can be measured. Coastal marine and estuarine ecosystems are non-
linear systems, and land-based stressors from multiple watersheds may impact a given reef as
they become dispersed by wave action, wind and oceanic currents. Coastal and marine
ecosystems are additionally stressed by fishing pressure and rising water temperatures.
Refinements in stressor modeling are needed to inform a comprehensive stressor gradient for the
BCG require data with appropriate scale to the reef communities of interest.
IB. Undisturbed Baseline Conditions
Healthy waterbodies exhibit biological integrity, representing a natural or undisturbed state (EPA
2002, 2011). This undisturbed state is known as reference condition for biological integrity
(Stoddard et al. 2006). The concept of reference condition arose from the objective of the Clean
Water Act Section 101: "to restore and maintain the chemical, physical and biological integrity
of the nation's waters". Biological integrity is defined as "the community of organisms having a
species composition, diversity and functional organization comparable to those of natural
habitats within a region" (Karr 1991). Reference condition for biological integrity is the baseline
for the BCG (Davies and Jackson 2006). Because the BCG is grounded in natural condition, it
provides an anchoring point in time and can help us to avoid problems associated with "shifting
baselines", particularly those associated with large-scale stressors such as changes in climatic
conditions or intense fishing pressure (Pauly 1995; Knowlton and Jackson 2008). It also can help
practitioners and the public recognize that current conditions do not necessarily represent natural
conditions (Davies and Jackson 2006).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
One challenge in developing the coral reef BCG was the difficulty in determining reference
condition for biological integrity (BCG Level 1). Coral reef monitoring information is
historically limited. By the 1950s fish populations were already decimated (Goreau 1959;
Jackson 1997; Greenstein et al. 1998; Jackson and Sala 2001; Jackson et al. 2001; Pandolfi et al.
2003). Several major events have affected the benthic community including a white-band disease
(WBD) epizootic event in the late 1970s and early 1980s that reduced the Acroporid corals by up
to 95% throughout their range (Gladfelter 1982; Weil 2003, 2009; Weil and Rogers 2011); the
catastrophic die-off of Diadema antillarum in 1983-1984, which reduced the population by
~90% (Bak et al. 1983; Lessios et al. 1984; Lessios 1988a and b, 2005); major bleaching events
in 1990, 1998, 2005, and 2010 resulting in significant losses of cnidarian species (Garcia-Saiset
al. 2006, 2008; Wilkinson 2005; Aronson and Precht 2001a; Weil et al. 2002, 2009; Gardner et
al. 2003; Jackson et al. 2014).
As a result of these events, there were no available reference stations in Puerto Rico or USVI.
BCG Level 1 was not expected to occur in PR or USVI and was not described conceptually or
with BCG model rules. Reference condition for biological integrity is most likely unobservable
in the Caribbean reefs that have been degraded through years of overfishing, climate change, and
land-based pollutant inputs. As described in the report introduction, current biological integrity
in Caribbean coral reefs is generally degraded in relation to past conditions. Conditions observed
in the 1950's through scuba diving and underwater photography might represent conditions that
were minimally disturbed. However, those observations were not common, usually were not
systematically recorded, or were not observable by members of the expert panel. Observations
and recording that are familiar to most members of the expert panel are mostly from the late 20th
and early 21st centuries. While the expert panel might not have direct familiarity with
undisturbed or minimally disturbed Caribbean reefs, they are able to conceptualize an
undisturbed reef based on historical descriptions, early publications on taxa distributions and reef
characteristics, and the trajectory of disturbance over time and across the region.
Most of the consensus ratings for the sites in the benthic dataset were 3, 4, or 5. Level 2 samples
were only recognized in calibration of the narrative model and Level 6 samples were uncommon.
There were conceptual rules developed for Level 2 and quantitative rules calibrated for Levels 5
and 6. Validation ratings were at Levels 3 through 6, leaving the Level 2 rules un-validated.
There was no attempt to outline benthic BCG model rules for Level 1 because this condition
could not be confidently quantified. Level 1 conditions were conceptualized through review of
historical records and by back-casting from current trends in reef degradation (Weil 2020,
Appendix L). Weil describes considerable recent disturbances of both natural/climatic and
anthropogenic origin. Historical and recent studies describe how historically dominant coral
species decline, and weedy, opportunistic and more persistent species increase in abundance and
cover over time due to Climate change, overexploitation, pollution and disease (Knowlton 2001;
McClanahan et al. 2007; Green et al. 2008; Alvarez-Filip et al. 2011; Garcia-Sais et al. 2017).
This was documented in recent years in the Caribbean where live coral cover declined from more
than 50% on average in the 1970's to just 10-15%> by 2002 (Gardner et al. 2003, Jackson et al.
2014). The description of possible Level 1 conditions is informative regarding a biological
baseline that is virtually impossible to observe in the Caribbean at the present time.
The fish consensus ratings were also mainly Levels 3 or 4 for both the calibration and validation
sites. There were no ratings at Level 2, so while quantitative rules were developed, they were
Q-4
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
not calibrated or confirmed. There were no validation ratings at Levels 5 or 6, so those rules
were not validated.
BCG Level
Fish Calibration
Sites
Fish Validation Sites
Benthic Calibration
Sites
Benthic Validation
Sites
1
0
0
0
0
2
0
0
0
0
3
10
11
19
1
4
11
3
34
8
5
5
0
13
4
6
1
0
0
4
Calibrating the model with surveys from relatively unimpaired areas elsewhere in the Caribbean
may be useful in further testing the reference condition attributes; however, differences in survey
protocols may present a complication. Regional reference conditions are based on measurements
from populations of least disturbed sites within a relatively homogeneous region using abiotic
characteristics such as human population density and distribution, road density, and the
proportion of mining, logging, agriculture, urbanization, grazing, or other land uses (e.g., Least
Disturbed Condition (LDC) (Stoddard et al. 2006). Additionally, for coral reef ecosystems,
current and historical fishing pressure is also a factor to consider. Two approaches are suggested
for consideration as future research:
1. Conduct a new coral reef survey at a long-established marine reserve to establish minimally
disturbed reference condition. It was suggested by the experts that Gardens of the Queen
National Park, Cuba, would be an appropriate location to establish coral reef ecosystem
minimally disturbed condition. Gardens of the Queen National Park, about 850 square miles
of islands and reefs, is one of the most unspoiled environments in the Caribbean. A coral reef
survey would be required, using methods comparable to the NCRMP methodology: every
station would include a Line-point Intercept (LPI) Survey, coral demographic survey,
topographic complexity survey, reef visual census (RVC) fish survey, and water quality
survey.
2. Mine coral reef monitoring program data from the Atlantic and Gulf Rapid Reef Assessment
(AGRRA) which has been collecting coral reef data throughout the Caribbean since 1997.
Early in their program, AGRRA conducted baseline assessments of remote reefs in locations
such as Cuba, the Bahamas, Panama and Los Roques National Park, Venezuela. AGRRA has
collaborated with teams of scientific professionals and partners to collectively conduct over
3,000 surveys. The AGRRA methodology is very similar to the NCRMP and produces
comparable data. AGRRA data is publicly available through their data portal.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Figure Q2: Map of AGRR A Survey Locations in the Greater Caribbean. The Greater Caribbean extends from the
Bahamas, Florida and Gulf of Mexico in the north through the Caribbean Sea to the south along the NE coast of
South America; including the Greater and Lesser Antilles to the East and Central America to the west. Caribbean
coral reefs have 65 stony coral species that provide homes to a diverse array of plants and animals, including nearly
700 reef fish species.
1C. Habitat Classification,
In designing a coral reef biocriteria program, it is important to be able to distinguish a signal of
anthropogenic stress to the biological assemblages from noise caused by natural spatial and
temporal variation (Jameson et al. 2001; EPA 2016). Establishment of reference condition is
dependent upon a classification system that groups natural coral reef systems by physical and
biological community characteristics to ensure that biotic responses are attributed to stressor
intensity after accounting for differences in natural expectations (Jameson et al. 2001; Edinger
and Risk 1999). The challenge is to determine the minimum number of classifications that
represent the range of relevant biological variation in a region that can be used to detect and
describe the biological effects of human activity in that location (Karr and Chu 1999; Jameson et
al. 2001).
Coral reef environments have distinct horizontal and vertical zones created by differences in
depth, wave and current energy, temperature, and light (Stoddart 1972; Zitello et al. 2009). A
zone, as defined by Wells (1954) is "an area where local ecological differences are reflected in
the species associated and signalized by one or more dominant species". Because of this
zonation, coral reefs cannot be considered homogeneous: sampling and corresponding analyses
must take the zones into consideration. Important physical traits to consider while determining
expected benthic species composition of a location include reef zones, geology, sea level change,
sediment exposure, and decadal temperature anomalies (Stoddart 1972; Hubbard 1997; Hubbard
et al. 2009; Costa et al. 2009; 2013; Zitello et al. 2009). The factors used for classifying reef
types that affect biological expectations should include environmental variables that are not
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greatly influenced by human activity. For example, reef zones defined by depth and currents are
not likely to change with human activity. Sediment exposure might be caused by natural sources
of sediment or by excessive erosion from terrestrial human activities. If sediment from human
activities, then sediment exposure would not be an appropriate classification variable.
Habitat classification is important when monitoring and assessing any biological assemblage,
including fish communities. In coral reef ecosystems, there is a strong positive correlation of
habitat complexity with fish species richness (Luckhurst and Luckhurst 1978; Carpenter et al.
1981; Roberts and Ormond 1987; McClanahan 1994; McCormick 1994; Green 1996;
Friedlander and Parrish 1998; Sale 1991; Friedlander et al. 2003; Gratwicke and Speight 2005a,
b; Kuffner et al. 2007; Pittman et al. 2007; Aguilar-Perera and Appeldoorn 2008; Walker et al.
2009; Smith et al. 2011).
To establish the foundation for the benthic BCG model, the benthic expert panel selected a
habitat classification framework as the basis for rule development and to guide future
monitoring. The panel's consensus was to limit the model to the fore reef zone] defined as the
area along the seaward edge of the reef crest that slopes into deeper water on the barrier or
fringing reef type (Costa et al. 2013). Features associated with a non-emergent reef crest but still
having a seaward-facing slope that was significantly greater than the slope of the bank/shelf,
were also designated as fore reef. The fore reefs were further divided into two zones; one was
dominated by Orbicella species, and the other was colonized hard bottom with gorgonian plains
(Williams et al. 2015). The former zone was used in this study. This approach should provide a
template for application to other well-defined coral reef habitats (e.g., deep fore reef/escarpment
with coral reef coverage) for future evaluations.
Based on the combined comments of the benthic and fish expert panels, a research project to
develop a standard classification system and GIS dataset to describe and map coral reef
ecosystems of Puerto Rico and USVI for use in biocriteria reporting is proposed. The project
would begin by using the maps (Kendall et al. 2001) to identify the location of coral reefs and
the habitat classification of those reefs. Lidar or another approach would be used on the reefs to
improve reef classification. Finally, divers would conduct reconnaissance dives to ground-truth
and refine the Lidar classifications and maps.
The refined reef classifications would be used in selecting representative transect locations when
designing the coral reef monitoring program for BCG application. During reconnaissance,
habitat strata can be identified from maps. If an assessment is then intended for application of the
benthic BCG model, fore-reef or hardbottom habitat can be targeted for locating sites and
confirmed on location at the surface and again underwater. If sites are selected in a probabilistic
design, the general reef location can be completely randomized for all locations within the strata,
but placement of the transect can be more purposeful; selecting specific transects at the location
that are the intended habitat and representative of the broader location on the reef. This could
allow avoidance of large sandy patches when the intention is to assess coral reef conditions.
To avoid unproductive sampling trips to locations that are determined to be inappropriate for
assessment, there might be justification for establishing fixed transect sites that would be
revisited annually or on another repeated schedule. Permanent transects would allow trend
analysis in locations that are determined to represent an important reef type, location, or stressor
condition. Comparisons over time in the same location with comparisons only in that location
would avoid arguments of unrepresentative assessments due to habitat classification, transect
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location, depth, or other differences among sites. While permanent transects allow trend analysis
within fixed stations, the sampling effort might displace one-time samples from multiple
locations. The sampling program and purpose might have reason for only one or both types of
sampling designs.
The proposed fine-scale mapping and assessment program can then be paired with the national
and territorial scale NCRMP monitoring program to provide a nested, multi-scale assessment
approach (Hawkins et al. 2000; Hughes and Peck 2003; NOAA 2014).
ID. Transferring the BCG to Other Jurisdictions
While the BCG model was developed using data from Puerto Rico, it is important to note that the
BCG is a general framework that could potentially be applied to other coral reef ecosystems. To
test the potential transferability of the Puerto Rico model to a different jurisdiction, the experts
rated 14 stations collected in the Florida Keys and Dry Tortugas at depths shallower than 16 m,
which were co-sampled by both the fish and benthic teams (RVC 2014-2016). The stations were
selected by the RVC leads across a stressor gradient: water quality (low anthropogenic impact -
Dry Tortugas, low-moderate impact - Florida Keys forereef, and high impact - Hawk's
Channel); and fishing pressure based upon management zones (low - Dry Tortugas National
Park, medium - Florida Keys, Marine Protected Areas, high - Florida Keys outside of Marine
Protected Areas). BCG attributes were not revised, with one exception - species not observed in
Florida were assigned an "x".
The quantitative Fish BCG model developed for Puerto Rico was 79% accurate in replicating the
expert panel assessments within one-half BCG Level for the Florida Keys calibration. For mis-
matched sites, the rule that was not met was the biomass rule. The experts felt that species
attribute assignment might need to be revisited due to variations in fishing pressure at different
jurisdictions. A full BCG calibration in Florida for both fish and benthic organisms is
recommended. However, a less intense project would entail using the same 12 stations that were
used for the fish BCG to test the Benthic BCG in Florida. Additionally, the BCG could be
developed for Hawaii and the Pacific territories. This is a much larger project and would require
multiple years and considerable effort to complete.
In general, the BCG conceptual framework is applicable to other coral reef ecosystems, as
demonstrated by the proof-of-concept work done using sites from Florida Keys and Dry
Tortugas. In order to use the BCG, other states and territories would need develop a numeric
model scheme specific to their jurisdiction's coral reefs, using local monitoring data. The
methods used to develop the BCG in Puerto Rico are likely applicable to other coral reef
ecosystems (e.g., the process to elicit expert judgment). In some cases, the qualitative rules may
be applicable (e.g., other Caribbean jurisdictions), but will require vetting by regional experts,
using regional datasets to test and refine the rules. In all cases the quantitative rules are
jurisdiction-specific.
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5. Recommendatior Fish Experts.
2A. Reconsidering Biomass: Age/Class Metrics for the Fish BCG
The data used for the Coral Reef Fish BCG documented composition, abundance, and size
structure. This information was summarized into a set of indicators for each fish species -
number of individuals of the species and biomass for that species. The BCG fish experts
consistently expressed dissatisfaction with the fish biomass metrics and requested information
about the size distribution (not just enumeration) of the fish observed.
Observations of juvenile and adult fish at a reef site might indicate that a full life cycle is
supported at the site, inferring connectivity at the site for certain species. With observation of a
single life stage, assessors are uncertain about the ability of the reef to support recruitment of
juveniles or sustenance of adults.
During the field sampling, size was recorded in 5 cm intervals for all fish species, but association
of juvenile and adult stages has not yet been completed for this data set. A listing of juvenile and
adult size ranges for fish species might be available in the literature or might be created by the
experts based on professional judgment. Enumeration of juvenile and adults (or size distribution)
for future rating exercises would allow calculation of life-stage metrics for reef fish. Associating
the life stages with size ranges might allow better discrimination of BCG Levels and
connectivity. Various metrics can be generated from the size data, including:
• the total biomass for the station, in size bins
• station-wide ratio of biomass juveniles to adults
• species-specific ratio of biomass juveniles to adults
• species-specific mean length
• station-wide mean biomass
• station-wide median biomass
• species-specific mean biomass
• species-specific median biomass
• trophic group ratio of juveniles to adults (e.g., herbivores, piscivores, invertivores, etc.)
• trophic group median length
• trophic group mean length
• sample size class structure for all taxa
These metrics could then be tested to determine potential suitability for inclusion in the Fish
BCG model; and could be subsequently developed into rules to improve the model's
discriminatory capability.
Field Method for Measuring Structural Complexity.
Structural complexity is the physical three-dimensional structure of an ecosystem. For coral reef
ecosystems, the structure is mainly provided by the physical shape and complexity of stony
corals, octocorals, gorgonians, and sponges. Structural complexity can also be provided by
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geological features and underlying structures formed by dead organisms (Kleypas et al. 2001;
Graham and Nash 2013). The importance of structural complexity for reef fish abundance,
biomass and/or species richness has been well documented (Talbot 1965; Talbot and Goldman
1972; Risk 1972; Luckhurst andLuckhurst 1978; McClanahan 1994; McCormick 1994; Green
1996; Appeldoorn et al. 1997; Friedlander and Parrish 1998; Holbrook et al. 2002; Friedlander et
al. 2003; Gratwicke and Speight 2005a, b; Kuffner et al. 2007; Purkis and Kohler 2008).
To estimate structural complexity, the EPA survey methodology measured linear rugosity using
the chain-and-tape method, where the ratio between the length of a chain draped across the reef
surface to the linear stretched length is calculated (Hobson 1972; Risk 1972; Talbot and
Goldman 1972; McCormick 1994; Santavy et al. 2012). This ratio provided the rugosity index,
accounting for important vertical dimensions.
The fish experts recommended revising the field method for measuring structural complexity
because it does not fully reflect the three-dimensional availability of fish habitat. Several
approaches have been developed that merit consideration. These methods should be evaluated to
determine which would most appropriately give a measure of topographic complexity at the
survey scale (i.e., site-scale as surveyed along a transect).
Methods to Evaluate
The NOAA NCRMP survey methodology is designed to capture basic information on three
separate elements along a 25 x 4m transect: 1) slope (e.g., the minimum and maximum depth the
transect); 2) vertical relief (e.g., the amplitude of substratum relief, recorded as the maximum
vertical relief in the transect; and 3) surface area topography (e.g., an estimate of the relative
proportion of different relief categories for the transect, using six different categories ranging
from <0.2m to >2m.
Dustan et al. (2013) describe another approach, the Digital Reef Rugosity (DRR) technique,
where a diver swims along a transect lone using a self-contained water level gauge as close as
possible to the reef contour without bumping the bottom to characterize rugosity with non-
invasive millimeter scale measurements of coral reef surface height at decimeter intervals along
meter scale transects. The measurements require very little post-processing and can be easily
imported into a spreadsheet for statistical analyses and modeling.
Storlazzi et al. (2016) describes a method that uses Structure for Motion (SfM) photogrammetry
with geospatial software tools for characterizing 3D attributes of coral colonies. The method uses
video that has been collected a part of the coral reef survey (e.g., Fisher et al. 2007) to produce
high-resolution bathymetric models and rugosity of the seafloor. This method requires no
additional field cost and lower hardware, software, and salary time than traditional remote
sensing methods.
Walker et al. (2009) utilized a high-resolution Light Detection and Ranging (lidar) bathymetric
survey to collect topographic measurements (i.e., surface rugosity, elevation, and volume) for the
approximately 110 km2 area in which all fish surveys were conducted. Lidar-measured
topographic complexity may be a useful metric for predictive models of reef fish distribution.
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2B. Ecosystem Connectivity - Seascape Ecology
Coral reefs are part of a tropical marine seascape that functionally links them with the adjacent
shallow coastal habitats (e.g., tidal pools, saltmarshes, estuaries and bays, mangrove forests and
seagrass meadows), pelagic habitats (e.g., shelf breaks) and unvegetated bottom (e.g., sand, hard
bottom, and rock) (Meynecke et al. 2008; Mumby et al. 2008; Mumby and Hastings 2008;
Hastings 2008; McCook et al. 2009; Miller and Lugo 2009; Scharer-Umpierre 2009; Sheaves
2009; Steneck et al. 2009; McMahon et al. 2012; Bostrom et al. 2011; Atkins et al. 2015; Pittman
2017; Lord et al. 2020).
Many reef fish respond to this spatial mosaic by showing pronounced associations with specific
habitat types (Dahlgren and Eggleston 2000; Sale 1991; Cerveny 2006). Some reef organisms
have life histories that depend on specific juvenile habitats that differ from those used by adults
(Beck et al. 2001; Christensen et al. 2003; Aguilar-Perera 2004; Cerveny 2006; Aguilar-Perera
and Appeldoorn 2007, 2008; McField and Kramer 2007; Cerveny et al. 2011; Atkins et al. 2015).
For example, many juvenile fish prefer shallow water habitats such as mangroves and seagrasses,
whereas the adult forms are found in adjacent coral reefs (Gratwicke and Speight 2005; Adams
et al. 2006; Dahlgren et al. 2006). Rainbow parrotfish, grunts, barracudas and several snapper
species depend on mangrove forests and seagrass beds for nursery habitat (Dorenbosch et al.
2006, 2007; Mumby et al. 2004; Machemer et al. 2012). Coral reefs provide essential habitat for
many species of adult fish (Jones et al. 2004; Feary et al. 2007; Grober-Dunsmore et al. 2007)
Spawning aggregation zones and currents (larval transport are essential characteristics for
reproduction (Mumby and Steneck 2008; Scharer et al. 2010).
The tropical marine mosaic also supports "charismatic megafauna" such as large animal species
with widespread popular appeal (e.g., manatees and dugongs, sea turtles, rays, sharks and
dolphins) (Heithaus 2007; Principe et al. 2012). Some of these species (e.g., manatees and sea
turtles) use a variety of habitats during different life stages (Lefebvre et al. 1999; McField and
Kramer 2007; LaCommere et al. 2008).
Ecosystem connectivity (Attribute X) is therefore an important attribute to include in a coral reef
conceptual model. Attribute X has typically been defined as access or linkage (in space/time) to
materials, locations, and conditions required for maintenance of interacting populations of
aquatic life; the opposite of fragmentation; necessary for metapopulation maintenance and
natural flows of energy and nutrients across ecosystem boundaries. Possible examples: spatial
proximity of coral reefs with mangroves, sea grass beds, and lagoons; flow of potential recruits
from upstream and upcurrent sources (larval dispersal).
Three types of future research were recommended by the fish experts: 1) high-resolution reef
bottom topography (LIDAR or other) and habitat maps to allow for better estimation of
connectivity, 2) application of landscape ecology methods to coastal and coral reef ecosystems to
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identify metrics that can be used to quantify BCG Attribute X - Ecosystem Connectivity and 3)
development of improved information on species and functional traits for Caribbean fish.
Ecosystem connectivity is a critical ecosystem attribute:
• Reproduction (spawning aggregation zones, larval dispersal);
• Critical foraging areas, nurseries and refugia;
• Physical and chemical buffering;
• Energy and material flows;
• Migratory corridors for transient species.
High Resolution Bottom Topography. One recommendation was that high-resolution reef
bottom topography (LIDAR or other) and habitat maps are expected to allow for better
estimation of connectivity (Prada et al. 2008; Lirman et al. 2010; Gintert et al. 2012). With high-
resolution topography and habitat maps, features related to connectivity could be recognizable
and quantifiable. High-resolution topography would also indicate elements of rugosity as well as
potential for ontogenetic connectivity of fish species, allowing characterization of broad-scale
relief and a possible basis for classification of reefs. NOAA, USGS, or ACOE might
have/provide/generate the high-resolution data. This is considered a high priority and would
require coordination among multiple agencies.
Application of Landscape Ecology Methods (Seascape Ecology). Landscape Ecology studies
the spatial distribution of organisms, patterns and processes (Dramstad et al. 1996; Farina and
Napoletano 2010), by focusing on three characteristics of the landscape (Forman and Godron
1986; Turner and Garner 1991; Forman 1995a, b; Turner et al. 2001): structure, function and
change. Aspects of landscape ecology that are applicable to the seascape include patch dynamics,
scaling, connectivity, fragmentation, corridors (Wiens et al, 1985; Urban et al. 1987; Forman and
Godron 1986; Wiens and Milne 1989; Saunders et al. 1991; Wiens 1992; Wiens 1999, Wiens
and Moss 2005; Pittman et al. 2011). In a facilitated discussion, the fish experts agreed that
coastal and marine ecosystems are arrayed in space in response to gradients of topography,
depth, water temperature, salinity, energy (wave regime, tide, etc.), rugosity and substrate type.
Research has begun to adapt the biotope mosaic approach developed for estuaries (Cicchetti and
Greening 2011; Fulford et al. 2011; Shumchenia et al. 2016) to the tropical marine seascape. A
biotope is an area that is relatively uniform in physical structure and that can be identified by a
dominant biota (Davies et al. 2004; Connor et al. 1997; Pittman et al. 2007a, b; Costello 2009;
FGDC 2012;). The research will develop metrics of change for coastal and marine biotopes.
Development of improved information on species and functional traits. Important species traits
might show patterns might influence their potential role as indicators in the BCG model. Reef
fish data can be associated with the NOAA benthic habitat maps to help determine the expected
assemblages in different habitats throughout a mapped space (Pittman et al. 2007a, b). For
example, the main factors used to determine reef fish assemblages in biogeographic regions on
the Southeast Florida reef tract were reef vs. hardbottom substrates, depth, relief, and geographic
space (Fisco 2016). Important species traits might show patterns only found at inshore or only at
offshore survey sites, exhibiting a distribution restricted by water depth, or geographically
widespread across depth, which might influence their potential role as indicators in the BCG
model. For example, the absence of a fish species from a nearshore site may not be indicative of
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the condition of the coral reef ecosystem if that species' range does not occur in nearshore reefs.
Similarly, the frequent occurrence of a species in waters known to be impaired due to the influx
of land-based pollutants may mean the species is more pollution-tolerant than a species found
only in waters that do not contain influxes of land-based pollutants, assuming benthic variables
are similar in both locations. The combination of the depth distribution, distance to shore, and the
frequency of occurrence provide an indication of relative abundance for each fish species and a
simplified geographical habitat width for each species. Improved information on species and
functional traits for Caribbean fish could aid in improving and interpreting results when applying
the BCG fish model to other Caribbean locations. Development of a matrix for reef fish species
traits, similar to the matrix for benthic species Weil (2019; Appendix R) is recommended.
2C. Metadata for Caribbean Fish Species
During development of the BCG, Dr. Ernesto Weil was contracted to develop detailed
information about Caribbean coral species (Weil et al. 2019; Appendix R). However, a similar
effort was not undertaken for fish species. Detailed information is needed about the life history,
biological, ecological and geographical characteristics of Caribbean fish species for future
versions of the Fish BCG model.
Life History Traits
Longevity.
In coral reef ecosystems, large-bodied, slow-growing, late-maturing fishes (K-strategists) are
generally more sensitive to exploitation than faster-growing, shorter-lived species (r-strategists)
(Beverton and Holt 1957; Man et al. 1995; Jennings et al. 1998; Coleman et al. 2000; Goodwin
et al. 2006; Ault et al. 1998, 2008). Consideration of K/r strategies informs coral reef fish
population responses to environmental stress, which is largely determined by life-history traits
with K-strategists being more susceptible to fishing pressure than r-strategists (Musick et al.
2000; Ault et al. 2005, 2008, 2014). The BCG Attribute definitions (Davies and Jackson 2006)
include considerations of these life history traits: Attributes I and II include long-lived, late
maturing, low fecundity species; while Attributes IV and V include early colonizers with rapid
turn-over times and "boom/bust" population characteristics. However, species-specific life
history data was not included in this BCG evaluation and was therefore not considered in the
assignment of species to coral reef BCG attributes.
Habitat requirements (larvae, juvenile, adult).
Many coral reef fishes migrate into different habitats throughout their life stages - Ontogenetic
migrations (i.e. progressive displacement of a given fish life stage from a given habitat to
another). Identifying essential habitats and preserving functional linkages among these habitats is
an important component of ecosystem integrity. Numerous studies have documented individual
Caribbean species" habitat requirements by life-stage (Dennis 1992; Eggleston 1995; Rooker
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1995; Appeldoorn et al. 1997, 2003; Lindeman 1997; Lindeman and Snyder 1999; Nagelkerken
et al. 2000; Recksiek et al. 2001; Cocheret de la Moriniere et al. 2002; Christensen et al. 2003;
Halpern 2004; Mumby et al. 2004; Dorenbosch et al. 2004, 2006; Lindeman and De Maria 2005;
Aguilar-Perera et al. 2006; Gratwicke et al. 2006; Vervveij et al. 2006; Aguilar-Perera and
Appeldoorn 2007, 2008; Jones et al. 2010; Scharer-lJmpierre 2008). The body of scientific
knowledge on ontogenetic migration should be organized by individual species and life stage to
better inform the BCG Fish Model.
Depth Preference.
While the composition and ecology of reef fish communities have been well characterized for the
upper 30 meters, coral ecosystems can extend to depths of 100 m or more, with large gradients
occurring in key physical parameters that are expected to have a significant impact on overall
fish diversity and community composition. Recent studies of mesophotic reefs have shown that
many shallow reef fish are also found in deeper waters (Colin 1974, 1976; Brokovich et al. 2010;
Garcia-Sais2010; Kahng et al. 2010; Bejarano et al. 2014), while others are only observed at
shallow depths. Large commercially important species threatened by overfishing can also be
found in mesophotic reefs (Garcia-Sais et al. 2004; Feitoza et al. 2005; Bejarano et al. 2014;
Laverick et al. 2016). Documentation of this information by individual species could inform
additional BCG rules.
Reproductive strategies (spawning aggregations).
Many Caribbean coral reef fish species form large group aggregations to reproduce (Smith 1972;
Munro et al. 1973; Johannes 1978; Olsen et al. 1978; Colin 1974; Carter and Perrine 1994;
Sadovy et al. 1994a, b; Aguilar-Perera and Aguilar-Davila 1996; Koenig et al. 1996; Domeier
and Colin 1997; Sadovy and Ecklund 1999; Lindeman et al. 2000; Garcia-Cagide et al. 2001;
Sala et al. 2001; Claro and Lindeman 2003; Clay don 2004; Whaylen et al. 2004; Burton et al.
2005; Graham and Castellanos 2005; Heyman and Kjerfve 2008). There are two types of
spawning aggregations ("resident" and "transient"), defined by using three criteria; the frequency
of aggregations, the longevity of aggregations, and the distance traveled by fish to the
aggregation. Resident aggregations are common to most rabbitfish, wrasses and angelfish. In
resident aggregation, spawning is brief (often 1-2 hours), occurs frequently (often daily) and
involves migration over short distances to the spawning site. Transient aggregations are used by
most groupers, snappers, and jacks. When transient spawning aggregation sites are known and
fished during the aggregation, then that species' population may be depleted due to unsuccessful
reproduction. There is considerable literature available on spawning aggregations throughout the
Caribbean that should be captured for use with the BCG Fish Model.
Shoaling and Schooling Behavior.
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Many fish species stay together for social reasons (shoaling) and may con si st of different species
that hang out together. If the group is swimming in the same direction in a coordinated manner,
they are schooling. Schooling provides benefits such as defense against predators (through better
predator detection and by diluting the chance of individual capture), enhanced foraging success,
and higher reproductive success. Schooling behavior is an attribute that should be included in
the metadata. We recommend using the three categories were used in Claudet et al. 2010: 1)
non-schooling (fish that are nearly always solitary), 2) facultative schooler (fish that can be seen
in school aggregations), and 3) obligate schooler (fish that are always in schools).
Diet Specialization.
The feeding guilds for the Caribbean reef fish have been included in the Fish BCG assessment.
However, fish feeding preferences may be either specialized or generalized. Generalists may
forage on a variety of food items, while specialists are limited in their diet. Dietary
specialization may increase a species' vulnerability to resource depletion.
Fishes that feed from live corals (corallivores) are a component of healthy coral reef ecosystems,
demonstrating distinct prey preferences and generally consuming corals from the genera
Acropora, Pocillopora and Porites (Cole et al. 2008). There are two categories of corallivores:
obligate (defined as having a diet which is at least 80% coral) and facultative (defined as
organisms that regularly consume coral without it comprising a large percentage of their diet)
(Cole et al. 2008). Because obligate corallivores are dependent upon live coral for their diet,
when there is increasing coral mortality, obligate corallivores decline proportionately (Pratchett
et al. 2006). Identifying the corallivore species and assigning them to one of the two categories
may provide information that could be incorporated into a future BCG rule.
6. Recommendations from the Beothie Experts.
3A. Photos and Videos at Survey Sites
During the sample review and BCG calibration process, the experts expressed that the data
sheets alone were difficult to interpret without photographs. In some of the reviewed samples,
the data sheets suggested that the site was either a highly degraded reef or a location that was not
expected to naturally support a reef. Photos would help in confirming that the site is potential
reef habitat.
Additional interpretive data could be gleaned from photographs, especially during expert
reviews. The experts suggested that photographs and/or videos should be routinely and
systematically taken at all sites, in the direction of the four compass points and along the
sampled transects. Photos would allow interpretation for reconciling discrepancies perceived in
the data, which could be used to refine BCG ratings or to confirm the outcome of BCG model
application. If the photos and videos were to be used for quantitative rules in future BCG models,
substantial post-processing would be required to translate the images into quantitative measures.
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The expert recommendation is that the survey methodology adopted for Puerto Rico and USVI
include a diver who makes a videographic record along the transects and takes photos of
interesting and unusual features at each survey site. The diver will swim at a uniform speed,
pointing the camera down and keeping the lens approximately 0.4 m above the substrate at all
times. A guide wand or dropper weight attached to the camera housing should be used to help the
diver maintain the camera a constant distance above the reef (Smith et al. 2015).
3B. LP I Surveys
Substrate categories in the LPI surveys should be refined, especially for the designation of "bare
substrate". The experts were uncertain whether this was an indication of a hard surface devoid of
life (not even algal turf) or it was always sand. If sand, the sand could be further characterized as
clean and coarse or fine sediment (indicative of terrigenous sedimentation). Sand might occur in
the troughs of a spur and groove system without indicating unproductive or degraded reef
habitat. Because sand might not be displacing potential coral microsites, the experts suggested
that coral cover could be calculated as a percentage of non-sand substrate. Recommendations for
future surveys are to designate hard surface devoid of life, clean and coarse sand, or fine
sediment.
The experts noted some differences in apparent reef characteristics between DEMO and LPI
methods at the same site. The methods represent different levels of effort and measure different
aspects of the benthic assemblage. On average, the LPI method yields higher coral cover values
than the demographic method (Tetra Tech 2020). After assessing several samples and comparing
to some photographs, the experts were in general agreement that a single 10m LPI transect was
not enough to characterize a reef condition. They suggested a longer transect or more transects at
the same site. Nadon and Stirling (2006) demonstrated that sampling 100 points on a 20 m chain
transect using 5-10 randomly positioned replicates is a low cost, highly accurate, and precise
method for estimating either low or high coral cover. The BCG benthic experts recommended
using 4-5 10m transects.
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Appendix R - Metadata for Caribbean Coral Species
Report submitted from: Dr. Ernesto Weil
Dept. of Marine Sciences
University of Puerto Rico
Technical Report completed under USEPA Contract EP-C14-022
The following tables present up-to-date information on life history, biological, ecological and
geographical characteristics for all scleractinian coral species recognized in the wider Caribbean.
The information was distilled by reviewing most of the available references, discussions with
colleagues, and from my personal experience of diving and conducting research in the region for
over 40 years. This is still an on-going work because we are still missing critical information
(reproduction, distribution, life history, tolerance limits, threat susceptibilities, etc.) for many
taxa from around the region. Hopefully, it will be completed over time, maybe by future
generations, when this information finally becomes available. Even the alpha-taxonomy of at
least 18 "ectomorphs" (20% of species listed) of which, 12 could end up being separated as true
species) is still un-resolved.
The color codes in the table define important information about the particular species in relation
to its threatened or endangered status according to the IUCN Red List, taxonomic status (if it is
fully resolved and accepted, still unresolved, or if it is an invalid name), if it is an exotic,
invasive species, an hydrocoral, and whether the species has a wide depth distribution, including
to the mesophotic habitats below 40 m.
The first tables provide information on the current taxonomic status; Family, Sub-family, genus,
the current and former (synonyms) species names used, the common names in English and
Spanish, and the commonly used species acronym for all shallow water and upper-mesophotic
(0-50m), mostly zooxanthellated coral and hydrocoral species in the wider Caribbean The only
non-zooxanthellated genus included is the conspicuous and common Tubastraea
(Dendrophylliidae), because of its abundance, accretion and wide geographic distribution, and
the identification of the recent exotic-invasive T. micrantus, that is rapidly spreading. Shallow,
non-zooxanthellated species in otherwise zooxanthellated genera are also included (i.e. Madracis
pharensis). Small, cryptic, non-zooxanthellated species in the family Caryophyllidae are not
included. Then, the known depth range which can vary across localities and regions.
Other tables include information (with categorization and/or rankings) for the most important life
history and biological/ecological traits (reproduction, growth, mean size, common colony
morphology, and finally the assessed susceptibility to three common threats (sedimentation,
disease, and bleaching), that ultimately define the species survivorship, fitness and potential
resilience. BCG attribute levels that are equivalent to the rankings (* to **** = low to high) used
are presented for bleaching, diseases and sedimentation susceptibility. Finally, complementary
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information about the traits, local and geographic distribution, etc. is presented for the different
species of scleractinian corals and hydrocorals. The table goes beyond the requested information
for the BCG project but, I though this information would be useful in helping to put into context
the traits that characterize the potential reef-building, survivorship, and resilience of the different
taxa for this and future coral reefs EPA program that will likely assess the conditions and
characterize the resistance/resilience and potential recovery of coral reef communities to the
ongoing and future threats around the Caribbean.
Additional tables present up-to-date information of the number of common diseases affecting the
different species of corals in the Caribbean, and the assessed/estimated susceptibility of each
species to each one of those reported diseases. Because environmental stressors, host immune
responses and pathogen (s) virulence can vary over time, the particular susceptibility ranking for
each case is not fixed over time, or for any particular locality, and could change accordingly.
Furthermore, surviving individuals to disease outbreaks in particular species and localities are
assumed to be resistant to that particular disease, and their genetic combinations are expected to
be passed on to future generations, potentially reducing the susceptibility to that particular
disease, and maybe others. Similarly, pathogen's virulence can increase (mutation) affecting
otherwise resistant or different hosts. These "negative" dynamics might not happen if
environmental stressors are significantly reduced.
Bleaching susceptibility and signs are also variable and could change over time in the same coral
species. They depend on the intensity and duration of thermal anomalies, other local
environmental factors, the symbiont composition (resistant strains??), densities and intra- and
inter-colony distribution, depth, light conditions, etc. that could be very significantly spatially
and over time.
Relevant information and ranking criteria
Corals are modular, sessile invertebrates with a long evolutionary history (>400 MY) and
complicated life histories and life cycles (Jackson and Hughes 1985). Modular, colonial
organisms are unusual because the "organism-colony" is comprised of many, genetically
identical, replicated, interdependent modules (polyps, zooids, etc.), each with its own birth and
death rates, complicating analyses of life-history patterns and population dynamics (Baird et al.
2009). Colonies are in reality communities of many different organisms (cnidarian polyp,
bacteria, algae, fungi, other protists, etc.,) living together in mutualistic and/or symbiotic
relationships, and they are called holobionts. These evolutionary advantageous relationships
could turn detrimental to the main "host" if conditions change and become stressful for one or
several of the members of the community. Scleractinian reef-building corals are foundation
species because they built the structural and energetic base of coral reefs, providing the complex
three-dimensional primary framework that becomes essential fish habitat and habitat for
thousands of other invertebrate species (Harrison and Booth 2007). Modularity is the primary
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cause of this.
Modularity provides several biological/ecological adaptive, emerging properties including; high
genetic variability, survivorship and fitness. Modular organisms are potentially "immortal" since
senescence only applies to the individual polyps, and polyps are continually (asexual
reproduction) producing new polyps, so as the colony growths there is continuous "rejuvenation"
provide by the new small modules (polyps) colony. Polyp size is limited by the capacity to move
nutrients and energy within and determined by the surface/volume ratio relationship that limits
maximum size in non-modular organisms. But there is no limit to how many polyps can be
added to the colony and therefore, modular organisms potentially have no limits to how big they
can get. Furthermore, the bigger the better, more polyps will increase feeding and photosynthesis
area, competitive ability, survivorship, and ultimately, fecundity. Size is therefore, usually
regulated by external stressors, diseases, predation, competition and other causes of partial
mortality. Colonies can suffer 99% mortality but, if a couple of polyps survive, they start
producing new polyps and eventually, the colony (genet) grows back and starts reproducing
sexually again. Some coral colonies in modern coral reefs may have genotypes that are
thousands of years old, carrying the information that allowed those colonies to survive
environmental and biological disturbances over time. This genetic information keeps being
passed on to new generations either by cross-breeding with much younger genotypes (across-
generations), or with other, old genotypes. In either case, genetic variability continues to
increase.
The total number of extant scleractinian "species" is not known, so estimating global coral
species richness is complicated by a number of issues (Harrison 2011). High morphological
variability within species is an issue for the still ongoing, imperfect (incomplete) taxonomic
resolution of many taxa, and cryptic and/or sibling species. Limited exploration of deeper
mesophotic coral communities, deep-sea environments, as well as some shallow tropical reef
regions (far away and isolated reefs where new species are likely to be found, and furthermore,
the discovery of hybridization among some morphologically different corals (morphospecies) are
challenges for some corals still preventing the complete taxonomic resolution for the group (e.g.,
Oliver et al. 1992; Willis et al., 1997; Szmant et al. 1997; van Oppen et al. 2002; Vollmer and
Palumbi 2002). The application of the traditional biological species concept based on
reproductive isolation between different species has not been tested for all species. Assuming
that the current primarily morphologically based taxonomy provides an appropriate indication of
global coral species richness, there are at least 900 extant zooxanthellated scleractinian species
(Wallace 1999; Veron 2000). Of these, 827 zooxanthellate hermatypic coral species have been
assessed for their conservation status (Carpenter et al. 2008). In addition, there are at least 706
non-zooxanthellate scleractinians known, including 187 colonial and 519 solitary coral species
mostly distributed between 200-1,000 m (Cairns 2007).
Paradoxically, the Caribbean has the older scleractinian genera, yet it shows a significantly
depauperated coral diversity, with significant lower genera and species compared to the Indo-
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Pacific. There are more or less 70 recognized zooxanthellated, mostly reef-building coral
species, with still 12-18 "ecomorphs" (=20% of the total number of listed species) that need
taxonomic verification. Over 150 non-zooxanthelated species have been identified (Cairns 2007).
Life History Traits
Life-history strategies in corals are complex and difficult to characterize because of modularity.
Life history describe consistent, and context-independent characteristics of organisms. The
classic two-strategy life-history framework of r-K models (Pianka 1970), is considered
oversimplified, and/or mostly referring the "extremes " since many species usually show
intermediate traits along the r-K continuum of 'fast' (r) to 'slow' (K) life histories (Stearns
1977). Three-strategy frameworks resolve some difficulties of r-K selection by adding a third
'beyond K' group of stress-adapted species that can persist in unfavorable habitats (i.e., via
adversity selection, Greenslade 1983). For example, Grime's C-S-R triangle describes three life-
history strategies in plants (modular organism), in which species are hypothesized to evolve
strategies that promote competitive (C), stress-tolerant (S) or ruderal (R) life histories (Grime
1977; Grime and Pierce 2012). Trait-based approaches can provide general and predictable rules
for community ecology, as well as a more mechanistic understanding of community assembly
and disassembly, habitat filtering and species coexistence, particularly in the context of global
climate change and overall community biodiversity loss (McGill et al. 2006). Species traits also
provide important information about life-history strategies, which can broadly define how
organisms interact with one another and their environment (Darling et al. 2012). These authors
evaluated if life-history strategies can be directly inferred from species biological traits.
A few studies have considered how some coral traits may relate to life-history strategies. For
example, small corals with brooding reproduction, fast growth rates and high population turnover
are expected to be 'weedy' (Knowlton 2001), while large, slow-growing colonies of massive
corals are expected to be "more tolerant" to chronically stressful or variable environments
(Jackson and Hughes 1985; Soong 1993; Rachello-Dolmen and Cleary 2007). Similarly,
variation in colony morphology and reproductive mode are thought to suggest three primary life
histories (competitors, stress-tolerant and ruderals (Edinger and Risk 2000; Murdoch 2007).
Observations of increasing abundances of 'weedy' species (Green et al. 2008) and the
persistence of massive species on disturbed Caribbean (Alvarez-Filip et al. 2011) and Indo-
Pacific reefs (McClanahan et al. 2007; Rachello-Dolmen and Cleary 2007), suggest that life-
history traits can predict which corals are 'winners' or 'losers' in the face of environmental
change (Loya et al. 2001; van Woesik et al. 2012) which is an important consideration in many
different projects. For example, branching and plating acroporid corals are dominant species that
are very sensitive to stress and disturbance (i.e., 'losers'), while massive species and 'weedy'
species are more likely to be 'winners' and persist in unfavorable and/or frequently disturbed
environments (Loya et al. 2001; McClanahan et al. 2007). However, the underlying species
characteristics that may predict these responses are difficult to evaluate without a comprehensive
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understanding of coral biological traits and associated life-history strategies.
Darling et al (2012) compiled a global database of species traits for reef-building corals and
classified taxa into life-history strategies that can be used to evaluate ongoing community shifts
on coral reefs. They used eleven species traits for which there is information in the literature:
colony growth form, solitary colony formation, reproductive mode andfecundity, maximum
colony size, corallite diameter, depth range, generation time, growth rate, skeletal density and
symbiotic zooxanthellae (Symbiodinium) associations, and focused on traits that were expected
to affect coral population dynamics, and for which quantitative data were available at a global
scale. Still, it is not easy to rank all species since some have common traits across the different
categories.
The Darling et al (2012) system aided by other literature was used to rank the "life history traits"
for the different species in the table. Four categories were used: (1) Weedy Species (W)= Small
branching and sub-massive colonies of mostly brooding spp. Small corallites, low fecundity but
high survivorship and high variability in LH traits; (2) Competitors (C)= Large, branching,
plating, and fast growing in shallow habitats. Broadcasters. High mortalities and susceptible to
bleaching and fragmentation; (3) Stress Tolerant (S): Slow growing, dome-shaped, massive,
sub-massive, and platy growth forms, Broadcaster with high fecundity and low survivorship, and
(4) Generalist (G)= mixed C, S, and W strategies. Massive, sub-massive dome shapes, crustose
or plates, slow growth, and brooders or broadcasters.
Reproduction
Modularity can potentially lead to a diverse array of sexual systems (Weiblen et al. 2000).
However, unlike flowering plants (Barrett 1998), and some unitary/individual animals, there are
essentially only two sexual systems in scleractinians. Colonies are either predominately out-
crossing, simultaneous hermaphrodites, with each polyp producing both male and female
gametes, or colonies have polyps that produce only one kind of gamete, one sex throughout their
life (gonochoric or dioecious). Of the more than 1,500 recognized coral species, aspects of
sexual reproduction have now been recorded in at least 444 species, the vast majority being
shallow-water zooxanthellate and hermaphroditic species (Harrison 2011). Either of these two
sexual patterns can show two different developmental modes; (1) those that liberate their
gametes into the water column for external fertilization and embryogenesis (broadcast
spawners), and (2) those that liberate well developed larvae into the water column after internal
fertilization and embryogenesis (brooders or planulators) (Baird et al. 2009, Richmond and
Hunter 1990, Harrison 2011).
Several taxa however show "mixed sexual patterns", with both gonochoric and hermaphrodite
polyps, and/or "mixed developmental modes", with spawning and brooding polyps (Chornesky
and Peters 1987; Soong 1991; Harrison 2011). Some of these findings however might have
resulted from incomplete, or biased experimental designs of the research. Over the last 30 years,
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research on coral reproduction has advanced substantially, expanding into many reef regions that
were not previously well studied, including equatorial and tropical regions of high coral
biodiversity (Richmond 1997; Guest et al. 2005; Harrison and Booth 2007; Baird et al. 2009a).
This has resulted in substantial new information and verifications and has almost doubled the
number of coral species for which sexual reproductive data is now available for at least 444
species (Harrison 2011). The current global data generally confirm, correct and/or extend many
of the trends and patterns highlighted in earlier studies, nevertheless some recent advances in our
understanding of coral sexual reproduction summarized in Harrison (2011), left it clear that
reproduction research still suffers from limitations imposed by the experimental design, methods,
and the limited time allocated. Most gametogenetic studies are limited to 12-14 months, use a
few colonies over reduced spatial scales, and sample only a few polyps of the colony. Recent
research for example found that some gonochoric fungid species in Japan show bi-directional sex
changes, with large individual polyps changing from male to female and vice versa year after
year (Loya and Sakai 2008). My own research in Puerto Rico show that Montastraea cavernosa
and Dendrogyra cylindrus are sequential gonochoric, changing sex over time.
Milleporid hydrocorals are overall gonochoric broadcast spawners that reproduce sexually by
producing free-living gonochoric medusoids which release the gametes in the water column for
external fertilization and embryogenesis of the planula larvae.
The table includes the most recent reproductive information for sexual pattern (G= gonochoric,
H= Hermaphrodite, MP= mixed pattern), and mode of development (B= brooder, S= spawner,
MM= mixed mode) known for Caribbean corals. There are at least 19 gonochoric species (14 of
which spawn gametes into the water column, and 5 brood their well-developed larvae), and 38
hermaphrodites (14 broadcasters and 24 brooders). The rest of the species have been reported
with mixed patterns and/or mode of development, or there is no information about their sexual
reproduction. All hermaphroditic-spawning and gonochoric-spawning species have one
gametogenetic cycle a year with 1-3 spawning events, mostly during late Summer early Fall,
with a few species spawning during the Spring. Most hermaphrodite-brooding species usually
have one or several oogenesis cycles with differential oocyte maturation over time, and a few
spermatogenesis cycles, and show more than 3 brooding events, up to 10. This strategy
compensates for the low number of larvae they can produce in each brooding event due to
limited space in the gastro-coelenteron. The exception as off today, is the golf-ball coral Favia
fragum, which has up to 10 gametogenetic cycles and broods year-around (Szmant 1986). There
is still limited or no information for many Caribbean. Species, and some studies are limited in
their design and sampling approach, spatial and temporal scales.
Growth morphologies, growth rates and "mean colony size"
Modular organisms, and specially corals, are highly plastic morphologically, changing growth
direction and form in response to changes in environmental and/or biological pressures along
their spatial/geographical distribution. The same species may show different colony
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morphologies along the depth gradient, from shallow, well-illuminated habitats where it could
grow as a massive, dome-like colony, to bi-dimensional crusts, wide plates or skirt-like plates in
low light, deeper habitats. This plasticity allows the colonies to enhance capture of low light
quality and quantity and maximize photosynthetic rates. Exposure to waves and currents can
produce different morphologies than in quiet lagoonal habitats within the same species.
Morphological plasticity has been one of the main issues in some taxonomic unresolved taxa.
The table presents the most common growth forms categorized as: BO = boulder, MA =
massive, SM = sub-massive, CR = crustose, PL = thick plates, BL = thin blades /foliose, CO =
Columns and SP= single polyps. A single species may have two or more of these categories.
There are only two species which growth forms are basically columnar, Dendrogyra cylindrus
and Orbicella annularis. However, Meandrina meandrites, O.franksi and M cavernosa may be
found growing vertically like a pinnacle.
Information on growth rates (cm/year) for at least 40 species was summarized from the relevant
literature. There is limited or no information for the rest of the species. How fast a species grows
was ranked as: (1) Very fast = species with max growth rates above 10 cm/year, (2) Fast =
Species with max growth rates between 2 and 10 cm/year, (3) Slow = species with maximum
growth rates between 0.5 and 2 cm/year, and (4) Very Slow = species with maximum growth
rates below 0.5 cm/year.
Theoretically, modular organisms do not have biological-structural restrictions to how big they
can grow. The continuous iteration of modules that adds new, "young" polyps to the colony
constantly is adaptive because it increases survivorship and fecundity. Shape constraints and lack
of intra-colony space for new calices could reduce growth and vertical expansion (Barnes 1970),
but colonies could change direction and shape to overcome these limitations. Most species have
slow-to-very-slow growth rates (0.1-2.0 cm/year) so, it will take hundreds to thousands of years
for massive colonies for example, to reach significant sizes. The opposite is true for branching,
fast-growing species like Acropora cervicornis and A. palmata, which can monopolize large reef
areas in a few decades. Before the 1980's, and for the previous 3000 years, acroporids were the
most important Caribbean reef-building species, providing tridimensional structural relief and a
diversity of habitats and refuges, while monopolizing most shallow, exposed reef habitats down
to 10-15m, and well flushed lagoonal areas in the Caribbean region (Gladfelter 1982, Aronson
and Precht 2001 a,b; Weil 2003). These are weedy species that come and go frequently and that
almost disappeared form Caribbean reefs after the WBD disease outbreak in the early 1980's
(Gladfelter 1982; Aronson and Precht 2001a).
If corals can grow "forever", why don't we see many gigantic massive or columnar colonies out
there?, The answer is probably determined by a combination of factors such as; the low growth
rates, the frequent partial mortality in colonies due to environmental stressors, competition,
predation, disease, bleaching, and human direct and indirect impacts. Mean colony sizes were
ranked mostly using published information and many decades of field observations of colonies
of the different species in reefs across the wider-Caribbean. The ranking is based on the longest
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diameter as: (1) Very small = 1 - 10 cm in diameter, (2) Small =10-30 cm in diameter, (3)
Medium = 30 - 80 cm in diameter, (4) Large = 80 - 200 cm in diameter, and (5) = Very Large
= > 200 cm in diameter.
Sediment susceptibility
There is some information related to the effect of sediment and tolerance to sedimentation for a
few species in the Caribbean (Hubbard et al 1972, Hubbard 1973; Dodge et al.1974; Loya 1976;
Hudson and Robbin 1980; Lasker 1980; Rogers 1983, 1990). Different coral species have
evolved different mechanisms (i.e. tissue swallowing, cilia, mucus, skeletal structure, water
spewing, etc.) to clean themselves of sediments (Stafford-Smith and Ormond, 1992), with some
species being highly efficient and others not. However, besides the cleaning mechanisms, the
sediment cleaning efficiency depends also on environmental factors such as water movement and
clarity, sediment type and size (silt, clay, sand, calcium carbonate, etc.), colony shape and
orientation, and how much energy is allocated to the process. In extreme sedimentary
environments, or when dredging conditions exists nearby, all mechanisms might be
overwhelmed by high rates of sedimentation, or larger particle sizes, and corals get smothered
and killed. There are species that are highly tolerant to sedimentation and turbidity and do well in
constantly murky and sedimentary environments (i.e. S. siderea, S. inter septa, M. cavernosa, S.
bournoni, Mycetophyllia spp., S. hyades, Scolynia spp.). Water movement could not only affect
the particle settling velocity, but also provide an additional force to compliment the active and
passive removal processes. Colony orientation could also provide safety to species that have few
or inefficient cleaning mechanisms (i.e. agariciids).
In near-shore locations, corals can be exposed to frequent sedimentation events. Corals will
probably be exposed to a mixture of different sediment composition depending on location,
distance from shore and proximity to river mouths (Furnas, 2003), and/or dredging activities
(Dodge and Vaisnys 1977), from primarily calcium carbonate (i.e. the skeletal remains of
animals and plants), to more terrestrially-derived silica-clastic sediment, clay etc. (Larcombe and
Carter, 1998). The different types of sediments will vary in their density, weight, sphericity and
angularity. In addition to different geochemical properties, the sediments will also differ in their
organic and nutrient-related content, which can mediate effects once smothering has occurred
(Weber et al., 2012). A number of studies have examined the difference in sediment rejection
ability of corals in response to fine and coarse sediment, and rates of sedimentation. However, as
noted in Jones et al. (2016), these studies have frequently used sands, whereas even close to a
working dredge, the particle sizes are typically in the silt range (< 62 (j,m). Many studies
examining the sediment shifting ability of corals have also used silicon carbide (carborundum)
(Yonge, 1930; Bak and Elgershuizen, 1976; Stafford-Smith and Ormond, 1992; Junjie et al.,
2014; Browne et al. 2015) and as with the use of sands, the relevance of these studies for impact
prediction with dredging is uncertain.
Sediment susceptibility of each species was ranked as: LOW (*)= Species have efficient
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cleaning mechanisms (high mucus production, cilia, water ingestion, etc.), large polyps and or
morphological traits and growth forms (branching, columnar, foliose, boulder-like) that aid in
cleaning sediment and reducing sediment impact; MODERATE-LOW (**)= Some efficient
cleaning mechanisms. Moderate-high mucus production, some morphological traits (medium-to-
small shallow polyps, branches, vertical plates, etc.) that aid in reducing sediment impact;
MODERATE - HIGH (***) = Moderately susceptible to sedimentation. Low cleaning
efficiency with only moderate mucus production morphologies that usually trap some sediment.
In exposed habitats: HIGH (****) = Highly susceptible to sedimentation, poor or no cleaning
mechanisms, very low mucus production, morphologies that trap and retain sediment.
Bleaching susceptibility
Bleaching is the term used to describe the loss of all or some of the symbiotic algae and/or
photosynthetic pigments by the animal host in marine environments. This results in that the
underlying white calcium carbonate skeleton in corals for example, becomes visible through the
now translucent tissue layer. Most photic cnidarians (corals, octocorals, hydrocorals, zoanthids,
etc.) and other important reef invertebrates form mutualistic endosymbioses with the single
celled dinoflagellate algae (Symbiodinium spp.). This association is usually obligate, with the
host deriving over 80% of its energy budget from the algae photosynthesis (Muscatine and Porter
1977). The endosymbionts also play a vital role in the light-enhanced calcification of
scleractinian corals (Chalker and Barnes 1990; Moya et al. 2006). In healthy corals,
Symbiodinium typically occur at extremely high densities (>106 cells per cm2 coral tissue), but
these densities go down significantly during bleaching.
Corals are known to bleach in response to a range of environmental stressors, but since the
1980's most large-scale coral mass-bleaching events have been predominantly driven by heat
accumulation during prolonged thermal anomalies, which is now clearly related to human-
induced global warming. Excess light seems to play a key additional role (Brown 1997; Hoegh-
Guldberg 1999; Fitt et al. 2001; van Oppen and Lough 2018; Quigley et al. 2018). Small scale
bleaching could result from a variety of other stressors such as low water temperatures, ocean
acidification (Anthony et al. 2008), salinity, heavy metals, cyanide, herbicides, turbidity and
other factors (reviewed in Baker and Cunning 2015). Furthermore, it has been hypothesized that
elevated temperatures and other stressful events may trigger viral infections that contribute to
coral bleaching and disease (Harvell et al. 2007; Vega Thurber et al. 2008; Vega Thurber and
Correa 2011; Wilson et al. 2001; Levin et al. 2017; Weynberg et al. 2017). Severely bleached
corals typically starve and die unless symbiont densities recover sufficiently rapidly to meet
minimal phototrophic requirements and/or the coral has the ability to supplement its energy
demands through increased heterotrophy (Grottoli et al. 2006; Anthony et al. 2009; Hoogenboom
et al. 2012). The effect of coral bleaching has major consequences for reef productivity, reef
growth, and biodiversity (McClanahan et al. 2018).
Thermal stress on coral reefs has clearly increased over the past century (Heron et al. 2016). As
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global temperatures continue to rise, the threat to coral reefs is increasing significantly. Mass
bleaching events have become more frequent and intense and extend over larger spatial scales
impacting entire reef systems and many taxa compared to the more localized events of the past.
All five global bleaching events (1983, 1987, 1998, 2010, 2016) occurred during or just after
moderate or major El Nino years. Other important but localized events like in 2003 and 2005 in
the Caribbean also coincided with moderate El Nino (Oliver et al. 2018). Unprecedented and
prolonged ocean warming triggered what is now been widely referred to as the "worst bleaching
ever", starting in 2014, and extending well into the 2017's. The length of the event prevented
corals in many areas of the world to recover prior to experiencing another thermal stress and
bleaching the following year (van Hooidonk et al. 2016; Hughes and Kerry 2017). Large-scale
bleaching events have resulted in extensive mass coral mortalities, mostly in the Indo-Pacific,
and it is now a critical global threat to coral reefs (Baker et al. 2008; Heron et al. 2016; Hughes
et al. 2017; Oliver et al. 2018).
Coral reefs develop well within a fairly narrow range of environmental conditions (water
temperatures, light, salinity, nutrients, bathymetry, and the aragonite saturation state of seawater)
(Buddemeier and Kinzie 1976; Kleypas et al. 1999; Hoegh-Guldberg 2005). Their natural
environment, at the interface of land, sea, and the atmosphere, can vary quickly and can become
highly stressful. Reef organisms have evolved strategies to cope with most environmental
disturbances (such as tropical cyclones, thermal anomalies, etc.), and given enough time (good,
stable environmental conditions) between disturbances, reefs recover and regrowth after the
impact (Buddemeier et al. 2004). Early studies in the 1970's demonstrated just how close (within
1-2 °C) reef-building corals usually live to their upper thermal tolerance limits and how subtle
rises in temperature often led to bleaching (Coles et al. 1976; Jokiel and Coles 1977; Glynn and
D'Croz 1990). These studies and others have identified that temperature thresholds at which
corals bleach vary with the ambient water temperatures on each reef, such that corals have
adapted to their local environmental conditions over long timescales (Oliver et al. 2018).
The influence of symbiont identity and diversity on fitness of the coral host has been
increasingly recognized. To a large extent, physiological characteristics of distinct symbiont
types have been inferred from correlative studies (Quigley et al. 2018). For example, zonation of
Symbiodinium types over light gradients within colonies and between shallow and deep colonies
of Orbicella spp. suggests that distinct symbionts have distinct light sensitivities (Rowan and
Knowlton 1995; Rowan et al. 1997; Toller et al. 2001a, b; Kemp et al. 2015). Observations of
patchy bleaching within Orbicella colonies during a natural bleaching event further suggest that
variability in bleaching tolerances of the different Symbiodinium types, or that different clades of
Symbiodinum seems to have different temperature tolerances to bleaching. Bleaching o the other
hand, may be a mechanism to change Symbiodinium communities inside host tissues in favor of a
community that is better adapted to the changed environmental conditions (Buddemeier and
Fautin 1993; Baker 2001; Baker et al. 2004). However, communities in some colonies may
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change in the absence of visible bleaching (Thornhill et al. 2006a, b).
The response of individual coral colonies may be shaped by previous experience (Buddemeier
and Fautin 1993; Oliver and Palumbi 2011; McClanahan 2017). Individuals can also respond to
bleaching by changing the relative abundance of high-temperature-resistant symbiont strains
making individuals less susceptible to subsequent bleaching events (Baker 2003; Baker et al.
2004; Oliver and Palumbi 2011). Consequently, there is increasing evidence that some corals can
adjust to global warming, and, therefore, projections of the future state of coral reefs need to take
adaptation and acclimation into account (Logan et al. 2014). Predictions based on climate models
and thermal tolerance of corals suggest regular widespread catastrophic bleaching within the next
15-25 years (Hoegh-Guldberg 1999; Donner et al. 2005; Logan et al. 2014; van Hooidonk et al.
2016). However, climate models deal with large-scale atmospheric and oceanic processes, which
in themselves are highly complex with many parameters and feedback loops that are difficult to
quantify (van Oppen et al. 2018).
The most detailed descriptions of the taxa affected by bleaching come from the Caribbean where
numerous species bleached in response to higher than usual sea temperature in 2005 and 2010
(Miller et al. 2006; Weil et al. 2009a; Rogers et al. 2009; McClanahan et al. 2008). Five species
of hydrozoan (100% of the species pool), 60 species of scleractinians (90% of the species pool),
and 30 octocoral species (20% of the species pool) bleached along with other cnidarians and
sponges (McClanahan et al. 2018; Prada et al. 2010). Sub-lethal effects on individual coral reef
organisms following bleaching include reduced reproductive output, reduced growth, and
increased susceptibility to diseases and other disturbances (Lesser et al. 2007; McClanahan et al.
2018).
Bleaching susceptibility for the different species was ranked based on most published
information on intensity (pale to white) and partial (focal) or total colony affected, prevalence
levels and partial or total colony mortality during the documented Caribbean bleaching events
(McClanahan et al 2018) and personal observations through several bleaching events in the
Caribbean. Classification is as follows: LOW (*) = High resistance. Partial/total bleaching only
during extreme thermal events (>10 DHW), very low prevalence and usually no partial or
colony mortality; MODERATE-LOW (**) = Colonies loose coloration (pale) during medium-
high thermal anomalies (6-9 DHW). Low bleaching prevalence and colonies may suffer partial
mortality MODERATE-HIGH (***) = Colonies bleaching frequently even during moderate
thermal anomalies (4-6 DHW), moderate to high prevalence levels, many colonies turn white,
some partial and colony mortality. HIGH (****) = Many colonies bleach frequently, even at low
thermal anomalies (2-4 DHW). High prevalence during bleaching events, most colonies white
and usually high partial and/or colony mortality.
Disease susceptibility
Coral reef mass mortalities appear related to the more frequent, intensive, and extensive thermal
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anomalies associated with global climate change (GCC), which has triggered historically,
unprecedented bleaching events and lethal disease outbreaks affecting foundation, keystone, and
commercially important species in tropical and temperate coastal environments (Harvell et al.
1999, 2002, 2007, 2009; Aronson and Precht 2001a; Rosenberg and Loya 2004; Miller et al.
2006; Bruno and Selig 2007; Hoegh-Guldberg et al. 2007, 2017; Carpenter et al. 2008; Croquer
and Weil 2009; Lough and van Oppen 2009; Miller et al. 2009; Weil et al. 2009, 2017; Weil and
Rogers 2011; Altizer et al. 2013; Randall et al. 2014; Maynard et al. 2015; Woodley et al. 2016;
Lafferty and Hoffman 2016; Hughes et al. 2017). Unprecedented and prolonged ocean warming
triggered the longest and deadliest bleaching on record, from 2014 to 2017 (van Hooidonk et al.
2016; Hughes and Kerry 2017).
Concurrent with this, deadly disease outbreaks affecting corals and other invertebrates were
reported from tropical to temperate regions. A presumed new "white-plague type" disease called
Stony Coral Tissue Loss Disease (SCTLD) (Meyer et al. 2019), killing large numbers of corals
in a short time, was reported from southeastern Florida in 2014 (Precht et al. 2016; Walton et al.
2018), and unprecedented mass mortalities of many species of sea stars along the northwest and
northeast coasts of the USA (Fuess et al. 2015), and several other disease outbreaks affecting
oysters, lobsters, crabs, and other important economic species (Burge et al. 2014; Groner et al.
2016).
The problem is exacerbated by local/regional, anthropogenic stressors such as pollution, coastal
development, dredging, uncontrolled "ecotourism", overfishing, etc. (Burge et al. 2014; Jackson
et al. 2014). Current estimates of negative changes in shallow coral reefs are two to three orders
of magnitude faster than those during the glacial cycles of the past 420,000 years (Hoegh-
Guldberg et al. 2007). It is predicted that the top 100 m of the ocean will become 0.6-2.0 °C
warmer by the end of this century (IPCC 2014). This raises concern since the most diverse and
productive marine ecosystems lay within this depth interval, including all shallow coral reefs and
an extensive portion of upper-mesophotic coral ecosystems (MCEs) (Weil 2019).
The Caribbean is considered as a disease "Hot Spot" due to the large number of diseases
affecting reef organisms, the frequent emergence of new diseases, and the frequent disease
outbreaks (Weil et al. 2006; Weil and Rogers 2011). The major community structure and
function decline was marked by two region-wide, concurrent, highly virulent disease epizootics
in the early 1980's. These events almost wiped out two foundation scleractinian species
(Acroporapalmata and A. cervicornis), and the keystone sea urchin Diadema antillarum. White
band disease (WBD) affected the acroporids and was caused by a complex of vibrio bacteria
(Gil-Agudelo et al. 2006). The Diadema mass mortality had all the trademark characteristics of a
virulent, transmissible, bacterial or viral infection, but the putative pathogen (s), was never
identified (Lessios 2016). Populations of both acroporids and sea urchins suffered over 95%
mortalities throughout the wider Caribbean (Gladfelter 1982; Lessios et al. 1984a,b; Aronson and
Precht 2001a; Lessios 2016; Weil et al. 2005), followed by a cascade of ecological consequences
(i.e. significant loss of live coral cover, primary productivity, spatial complexity, biodiversity
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and fecundity, loss of ecological functions, increase in algal cover and biomass, etc.), finally
ending in a shift from coral- to algal-dominated communities and the loss of ecological services
to other tropical marine communities and to human beings (Aronson and Precht 2001a; Weil and
Rogers 2011). Several other disease-induced, mass mortalities of massive, plate and nodular
reef-building coral genera, and other important cnidarians in the last 30 years resulted in
additional significant loss of biomass (live coral tissue), reef structure, and diversity throughout
the region (Miller et al. 2009; Rogers et al. 2009; Weil et al. 2009a; Weil and Rogers 2011;
Bastidas et al. 2012; Jackson et al. 2014). Significant loss of fecundity due to the loss of live
coral tissue (polyps), overfishing of herbivorous fish and lack of recovery of Diadema, together
with the continuous deterioration of local environmental conditions and Global Warming is
presumably impairing the natural (and sometimes assisted) recovery of damaged coral
communities across the Caribbean (Hughes and Tanner 2000; Weil et al. 2005; Jackson et al.
2014; Tuohy etal. 2019).
Immunity is an important biological property that promotes survivorship, fitness, and
adaptability in organisms. Invertebrates, including cnidarians, possess innate, variable, and
adaptive immune responses, which help them to defend and adapt against environmental stress,
opportunistic infections and disease. Like all physiological functions, maintenance of the
immune system and function requires energy and resources, which in stressful conditions,
involve trade-offs against energetic investment in other important functions such as growth,
feeding, reproduction, etc. Several innate immunity mechanisms, including the ability to
discriminate allogenic from xenogenic tissues, have been described for corals and octocorals
(Mydlarz et al. 2008, 2010; Burge et al. 2013). Although limited in response capabilities, innate
immune responses in cnidarians include production and movement amaebocytes and effector
enzymes, small molecules that selectively bind to a protein regulating its biological activity. In
naturally infected sea fans with dense amoebocytes, for example, a concurrent increase in
prophenoloxidase (PPO) activity occurred. This is linked to the production of melanin that is
deposited along the axial skeleton to prevent the fungal hyphae (aspergillosis) from entering the
surrounding tissue (Petes et al. 2003; Mullen et al. 2006; Mylardz et al. 2008). Several
histological studies have also illustrated a series of inflammatory responses of amoebocytes to
infections in G. ventalina (Mydlarz et al. 2008). Organic extracts of most Caribbean gorgonians
lack potent, broad-spectrum antibacterial activity, suggesting that the inhibition of bacterial
growth is not the primary function of gorgonian secondary metabolites (Jensen et al. 1996).
Antibiotic production by associated, mutualistic bacteria living in the mucus layer is probably an
effective way of preventing other bacteria to compete for the resources of the energetic and
protein rich coral mucus.
Resistance (susceptibility) to each of the different diseases is determined by the innate immune
system of the host, the virulence of the pathogen, both of which vary across individuals,
populations and species, and the environmental conditions which can vary spatially and
temporarily. Establishing levels of disease susceptibility for each coral species is therefore both
difficult and problematic. The ranking can vary across populations and species as well as
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
spatially and temporarily. The disease susceptibility rankings presented in the table were based
on the published information about the number of diseases affecting each particular species, the
population/species disease prevalence and levels of mortality reported during diseases outbreaks,
in different localities and over time. This assessment also includes my personal experience after
20 years observing the emergence and impact of coral reef diseases across the wider-Caribbean.
The disease susceptibility ranking is: LOW (*) (= highly Resistant)= Never or rarely diseased,
and when diseased, very low prevalence (0-5%) and tissue/colony mortality during disease
outbreaks; MODERATE-LOW (**) susceptible to one or a few diseases only; low to moderate
prevalence values (5-10%) during disease outbreaks, low - moderate tissue mortality only;
MODERATE-HIGH (***) = Susceptible or several diseases. Frequently diseased with
medium-high prevalence levels (10-25%) during outbreaks, high partial and/or colony mortality;
HIGH (****) = Susceptible to many diseases, consistently diseased with significantly high
prevalence levels (>25%) and tissue and colony mortality during outbreaks.
Appendix Tables
Tables include (Taxa are in the same order in each table, sorted by family and then genus):
Legends
Table 1:
Table 2:
Table 3:
Table 4:
Table 5:
Taxa phylogeny and description
Traits (depth range, life history strategy, reproduction, growth rate, growth form)
Disease Susceptibility
BCG Attributes and Pathogenic Diseases
Distribution and Description
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Table: Legends
SP#: EM= Ecomorphs. HYB= Hybrid. Shallow, non-zooxanthelated, small, cryptic spp. (Caryophyllidae) not
included.
Color codes
Threatened or endangered species
Taxonomic status not fully resolved
Recently described new species
Invalid species??
Invasive species
Hydrocorals
Wide depth distribution including mesophotic habitats
BCG ATTRIBUTES
1
Description
Pristine-good
good
Somehow impacted
Impacted
Highly impacted - bad
Very bad
Ranking
low
Moderate-low
Moderate
Moderate high
High
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Life History Strategies (Criteria for ranking from the literature and personal observations and experimentation)
Weedy Species (W)= Small branching and submassive colonies of mostly brooding spp. Small corallites, low fecundity but high
survivorship. High variability in LH traits.
Competitors (C)= Large, branching, plating, fast growing spp. in shallow habitats. Broadcasters. High mortalities and susceptible
to bleaching and fragmentation
Stress Tolerant (S):. Slow growing, dome- shaped, massive, platy, Submassive growth Broadcaster with high fecundity
Generalist (G)= mixed C. S, and W strategies. Domed, platy, submassive colonies, slow growth, Brooders or broadcasters.
Reproductive pattern-mode Gametogenesis
Sexual Pattern
G = gonochoric
H= hermaphroditic
Reproductive Mode
B= Brooder
S= Spawner (broadcaster)
Mixed pattern (MP)
Mixed mode (MM)
? = Unknown
Number of
gametogenetic cycles
per year
Spawning
Number of spawning
events per reproductive
season
Spawning-Brooding season:
SU= Summer
FA= Fall
SP= Spring
Wl = Winter
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Growth form Growth rates
BO = boulder Data on growth rates of
MA = massive the different species is
SM = sub-massive from the literature
CR = crustose
PL = plates
BL = thin blades /foliose
CO = Columns
SP = Single polyp
Single species might show different
growth forms depending on habitat,
competition and environment
Growth
Size
Very fast = species with max
growth rates above 10 cm/year.
Fast = Species with max growth
rates between 2 and 10
cm/year.
Slow = species with maximum
growth rates between 0.5 and 2
cm/year.
Very Slow = Species with
maximum growth rates below
0.5 cm/year
Very small = 1 -10 cm in
diameter
Small = 10-30 cm in
diameter
Medium = 30-80 cm in
diameter
Large = 80 - 200 cm in
diameter
Very Large = > 200 cm in
diameter
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Ranking
Sediment Susceptibility
Bleaching Susceptibility
Disease Susceptibility
LOW I
MODERATE-
LOW (**)
MODERATE -
HIGH (***)
Species have efficient cleaning
mechanisms (high mucus production, cilia,
water ingestion, etc.), large polyps and or
morphological traits and growth forms
(branching, columnar, foliose) that aid in
reducing sediment impact
Some efficient cleaning mechanisms.
Moderate-high mucus production, some
morphological traits (medium-to-small
shallow polyps, branches, vertical plates,
etc.) that aid in reducing sediment impact.
HIGH
Highly resistant species. Partial/total
bleaching only during extreme thermal
events (> 10 DHW), very low prevalence
and usually no partial or colony mortality
Colonies loose coloration (pale) during
medium-high thermal anomalies (6-9
DHW). Low bleaching prevalence and
colonies may suffer partial mortality
Moderately susceptible to sedimentation. Colonies bleaching frequently even during
Low cleaning efficiency with only moderate thermal anomalies (4-6 DHW),
moderate mucus production morphologies moderate to high prevalence levels, many
that usually trap some sediment. In
exposed habitats.
Highly Susceptible, poor or no cleaning
mechanisms, very low mucus production,
morphologies that trap and retain
sediment.
colonies turn white, some partial and
colony mortality.
Many colonies bleach frequently, even at
low thermal anomalies (2-4 DHW). High
prevalence during bleaching events, most
colonies white and high partia/ colony
mortality
Highly Resistant. Never or rarely diseased,
and when diseased, very low prevalence
(0-5%) and tissue/colony mortality during
disease outbreaks
Susceptible to one or a few diseases onf-
low to moderate prevalence values (5-
10%) during disease outbreaks, low -
moderate tissue mortality only
Susceptible or several diseases. Frequently
diseased with medium-high prevalence
levels (10-25%) during outbreaks, high
partial and/or colony mortality.
Susceptible to many diseases, consistently
diseased with significantly high prevalence
levels (>25%) and tissue and colony
mortality during outbreaks.
Criteria for ranking derived from the literature and personal observations and experimentation
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Ranking Sediment Susceptibility
Bleaching Susceptibility
Disease Susceptibility
BCG 1
BCG 2 - 3
BCG 3 - 4
BCG 5
Highly resistant to sedimentation.
Efficient cleaning mechanisms and/or
favorable morhologies.
Highly resistant, only bleach under Low susceptibility. Almost never diseased,
extreme, long thermal anomalies. Colonies Low prevalence (0-5%) and no little tissue
usually show pale coloration. mortality during ourbreaks.
Usually affected by high sedimentation Do not bleach frequently, only under high
events. Low sediment-related mortality. thermal anomalies. Colonies mostly pale,
with a few white.
Usually affected by sedimentation. Some Susceptible, bleaching frequently. Some
sediment- related mortality colonies turn white.
Highly sudceptible to sedimentation. Highly suceptible to increase/decrease
Frequent sedimentation-related mortality temps. Most colonies turn white.
susceptible to one or a few diseases onf-
low to moderate prevalence values (5-
10%) during disease outbreaks, low -
moderate tissue mortality only.
Moderate-to-high susceptibility to several
diseases. Frequently diseased, high
prevalence (10-25%) during outbreaks and
high partial and/or colony mortality
Susceptible to many diseases, consistently
diseased with significantly high prevalence
levels (>25%) and tissue and colony
mortality during outbreaks.
Criteria for ranking derived from the literature and personal observations and experimentation
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PATHOGENIC DISEASES
NOTE: Disease is a dynamic process so, it is difficult to characterize into
definitive categories or hierarchies These will change spatially and
temporarily as host immune responses and pathogen virulence varies
and adjust, and/or inducing environmental factors change. A
population/species could be highly susceptible to one or two diseases,
showing high prevalence and high tissue and/or colony mortality, and
moderately susceptible or resistant to other diseases, showing low
prevalence and mortality (i.e Acrporids with WBD, WPX, CCI; Orbicella
spp. with WPD, CYBD, DSD). Others that were highly susceptible to one
or many diseases in the past, no have resistant populations developed
from the survivors (right genetic combination). These, may or may not
be susceptible to newly emergent diseases (new pathogens).
Most Common coral diseases
BBD = Black Band Disease
WBD= White Band Disease
WPD = White Plague Disease
CYBD= Caribbean Yellow Band Disease
DSD = Dark Spots Disease
WPX = White Pox/White Patches/ Serriatosis
GAN = Growth Anomalies (Hyperplasias and hypoplasias)
CCI= Caribbean Ciliate Infection
RBD = Red Band Disease
IMS = Intra costal Mortality Syndrome
SCTLD = Stony Coral Tissue Loss Disease
OTH = Other syndromes not characterized
BCG equivalent
(*) = 1 = Very low susceptibility = Highly resistant. Rarely showing disease signs
Very low prevalence and mortality during outbreaks.
(**) = 2-3 = Moderate-low. Susceptible to one or few diseases;
low to moderate prevalence values during outbreaks, low - moderate tissue mortality.
(***) = 3-4= Moderate-high. Colonies frequently showing signs of disease.
High prevalence and mortality during outbreaks.
(****) = 5 = low resistance. Consistently diseased, susceptible to many diseases.
High prevalence during outbreaks. High mortality.
BCG Coding
1-2 (*) = Very low to low - (Highly resistant). Rarely showing disease signs of one or a couple of the common diseases
Very low prevalence and mortality during outbreaks.
3-4 (**) = moderate-low - intermediate. Few colonies diseased regularly.
Intermediate prevalence's and low mortality during outbreaks
5 (***) = high (low resistance) Colonies frequently showing signs of disease.
High prevalence and mortality during outbreaks.
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Table 2: Taxa Phylogeny and Description
SPECIES NAME
SP#
FAMILY
FORMER/OTHER USED NAME
COMMON ENGLISH
NAME
COMMON SPANISH
NAME
Stephanocoenia
intersepta
1
Astrocoeniidae
Stephanocoenia michelini
Blushing star coral
Coral estrella poligonal
Acropora cervicornis
2
Acroporidae
staghorn coral
Cuerno de venado
Acropora sp.
EM
Acroporidae
A. cervicornis
Thick staghorn coral
Cuerno de venado grueso
Acropora palmata
3
Acroporidae
elkhorn coral
Cuerno de alee
Acropora prolifera
HYB
Acroporidae
A. cervicornis
fused staghorn
Cuerno de venado hybrido
Undaria ten uifolia
4
Agariciidae
Agaricia agaricites
Thin leaf lettuce coral
Coral lechuga bifacial
delgado
Undaria agaricites
5
Agariciidae
Agaricia agaricites
Low relief lettuce coral
Coral lechuga incrustante
Undaria humilis
6
Agariciidae
Agaricia agaricites f. humilis
Low relief lettuce coral
Coral lechuga incrustante
Undaria purpurea
7
Agariciidae
Agaricia agaricites f. purpurea
Lettuce coral
Coral lechuga intrincada
Undaria carinata
EM
Agariciidae
Agaricia agaricites f. carinata
Lettuce coral
Coral lechuga compacta
Undaria crassa
EM
Agariciidae
Agaricia agaricites f. crassa
Lettuce coral
Coral lechuga bajo relieve
Undaria danae
8
Agariciidae
Agaricia agaricites f. danae
Bifacial lettuce coral
Coral lechuga bifacial
grueso
Undaria pusilla
9
Agariciidae
Agaricia agaricites, A. fragilis
Small criptic lettuce coral
Coral lechuga criptico
pequeno
Agaricia fragilis
10
Agariciidae
A. agaricites
Fragile saucer coral
Coral lechuga plato fragil
Agaricia fragilis
EM?
Agariciidae
Agaricia fragilis
Fragile saucer coral
Coral lechuga plato fragil
Agaricia lamarcki
11
Agariciidae
Whitestar sheet coral
Coral de estrellas blancas
Agaricia grahamae
12
Agariciidae
Agaricia sp.
Dimpled sheet coral
Coral plato incrustado
Agaricia undata
13
Agariciidae
Scroll plate coral
Coral plato enrollado
Leptoseris cailleti
14
Agariciidae
Helioceris cailleti
Foliose lettuce coral
Coral lechuga foliosa
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Table 2: Taxa Phytogeny and Description
SPECIES NAME
SP#
FAMILY
FORMER/OTHER USED NAME
COMMON ENGLISH
NAME
COMMON SPANISH
NAME
Helioceris cucullata
15
Agariciidae
Leptoseris cucullata
Sunray lettuce coral
Coral lechuga rayo de sol
Dendrogyra cylindrus
16
Meandrinidae
Pillar coral
Coral pilar o columnar
E usmilia fastigiata
17
Meandrinidae
Smooth flower coral
Coral flor amarilla
Eusmilia fastigiata f
flagellata
EM
Meandrinidae
Eusmilia fastigiata
Smooth flower coral
Coral flor amarilla
Dichocoenia stokesii
18
Meandrinidae
Elliptical star coral
Coral estrella eliptica
Dichocoenia stellaris
EM
Meandrinidae
Dichocoenia stokesii
Uniserial elliptical
Coral estrella eliptica
Meandrina meandrites
19
Meandrinidae
Meandrina memorialis
Maze coral
Coral laberinto
Meandrina Jacksoni
20
Meandrinidae
Meandrina meandrites, M.
memorialis
White valley maze coral
Coral laberinto valles
blancos
Meandrina danae
21
Meandrinidae
Meandrina brasiliensis
Butterprint rose coral
Coral laberinto pequeno
Meandrina sp.
EM
Meandrinidae
Meandrina meandrites
Maze coral
Coral laberinto
Goreaugyra memorialis
?
Meandrinidae
Meandrina memorialis
Deep Columnar Maze
coral
Coral laberinto profundo
Colpophyllia natans
22
Mussidae
Boulder brain coral
Coral cerebro valle
angosto
Colpophyllia
amaranthus
23
Mussidae
Colpophyllia natans
Brain coral
Coral cerebro de valle
ancho
Colpophyllia
breviserialis
EM
Mussidae
Colpophyllia natans
Brain coral
Coral cerebro de valles
cerrados
Pseudodiploria clivosa
24
Mussidae
Diploria clivosa
Knobby brain coral
Coral cerebro noduloso
Pseudodiploria strigosa
25
Mussidae
Diploria strigosa
Symmetrical brain coral
Coral cerebro simetrico
Diploria
labyrin thiformis
26
Mussidae
Grooved brain coral
Coral cerebro con surcos
Favia fragum
27
Mussidae
Golfball coral
Coral bola de golf
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Table 2: Taxa Phytogeny and Description
SPECIES NAME
SP#
FAMILY
FORMER/OTHER USED NAME
COMMON ENGLISH
NAME
COMMON SPANISH
NAME
Manicina areolata
28
Mussidae
Rose coral
Coral Rosa
Manicina mayori
EM
Mussidae
Manicina areolata
Rose coral
Coral Rosa Grande
Isophyllia sinuosa
29
Mussidae
Sinuos cactus coral
Coral cactus sinuoso
Isophyllia rigida
30
Mussidae
Isophyllastrea rigida
Rough cactus coral
Coral cactus rugoso
Isophyliia multiflora
EM
Mussidae
Isophyliia sinuosa
Sinuos cactus coral
Coral cactus sinuoso
Mycetophyllia ferox
31
Mussidae
Rough cactus coral
Coral cactus colinas
continuas
Mycetophyllia aliciae
32
Mussidae
Knooby cactus coral
Coral cactus valle amplio
Mycetophyllia
lamarckiana
33
Mussidae
Ridged cactus coral
Coral cactus valle ancho
Mycetophyllia danana
34
Mussidae
Deep valley cactus coral
Coral cactus valle
profundo
Mycetophyllia resii
35
Mussidae
Ridgeless cactus coral
Coral cactus piano
Scolymia cubensis
36
Mussidae
Solitary disk corals
Coral solitario pequenio
Scolymia lacera
37
Mussidae
Solitary disk corals
Coral solitario grande
Scolymia wellsi
38
Mussidae
Scolymia cubensis
solitary disk corals
Coral solitario
Scolymia nsp.
EM
Mussidae
Scolymia cubensis
Solitary red coral
Coral solitario rojo
Mussa angulosa
39
Mussidae
Scolymia lacera
Atlantic mushroom coral
Coral hongo polipos
grandes
Orbicella annularis
40
Merulinidae
Montastraea annularis
Lobed star coral
Coral estrella columnar
Orbicella faveolata
41
Merulinidae
Montastraea faveolata
Mountainous star coral
Coral estrella masivo
Orbicella franksi
42
Merulinidae
Montastraea franksi
Boulder star coral
Coral estrella rugoso
Montastraea
cavernosa
43
Montastraeidae
Great star coral
Coral estrella calices
grandes
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Table 2: Taxa Phytogeny and Description
SPECIES NAME
SP#
FAMILY
FORMER/OTHER USED NAME
COMMON ENGLISH
NAME
COMMON SPANISH
NAME
Montastraea nsp.
EM
Montastraeidae
Montastraea cavernosa
Large polyped star coral
Coral estrella calices
grandes
Pontes astreoides
44
Poritidae
Mustard hill coral
Coral mostaza
Pontes colonensis
45
Poritidae
Porites astreoides
Honeycom plate coral
Coral panal plato
Pontes porites
46
Poritidae
Clubtip finger coral
Coral dedo grueso
Pontes furcata
47
Poritidae
Porites porites
Branching finger coral
Coral dedo
Porites divaricata
48
Poritidae
Porites porites
Thin finger coral
Coral dedo fino
Porites nsp.
EM
Poritidae
Porites branneri
Blue crust coral
Coral azul crustoso
Madracis decactis
49
Pocilloporidae
Ten ray star coral
Coral de 10 septos
noduloso
Madracis formosa
50
Pocilloporidae
Madracis decactis
Eight-ray star coral
Coral de ocho septos
ramoso
Madracis carmaby
51
Pocilloporidae
Madracis formosa
Ten ray finger coral
Coral de diez septos
ramoso
Madracis pharensisf
luciphogous
52
Pocilloporidae
Madracias pharensis
Ten ray crustose coral
Coral de diez septos
incrustante
Madracis pharensisf.
luciphylla
EM
Pocilloporidae
Madracis pharensis
Ten ray massive coral
Coral de diez septos
masivo
Madracis senaria
53
Pocilloporidae
Madracias pharensis
Six-ray star coral
Coral de seis septos
submasivo
Madracis auretenra
54
Pocilloporidae
Madracis mirabilis, M. asperula
Yellow pencil coral
Coral lapiz amarillo
Madracis asperula
EM
Pocilloporidae
Madracis mirabilis
Deep yellow pencil coral
Coral lapiz profundo
Madracis myriaster
55
Pocilloporidae
Madracis mirabilis
Deep yellow pencil coral
Coral lapiz profundo
Oculina diffusa
56
Oculinidae
Diffuse ivory coral
Coral marfil difuso
Oculina varicosa
57
Oculinidae
Oculina diffusa
Large ivory coral
Coral marfil largo
R-24
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 2: Taxa Phytogeny and Description
SPECIES NAME
SP#
FAMILY
FORMER/OTHER USED NAME
COMMON ENGLISH
NAME
COMMON SPANISH
NAME
Oculina valecienesi
58
Oculinidae
Small ivory coral
Coral marfil corto
Oculina robusta
59
Oculinidae
Robust ivory coral
Coral marfil robusto
Siderastraea siderea
60
Siderastreidae
Massive starlet coral
Coral estrellado masivo
Siderastrea radians
61
Siderastreidae
Lesser starlet coral
Coral estrellado pequeno
Siderastrea stellata
EM
Siderastreidae
Siderastrea siderea
Lesser starlet coral
Coral estrellado
submasivo
Cladocora arbuscula
62
"Incertae sedis"
Tube coral
Coral tubo
Solenastrea bournoni
63
"Incertae sedis"
Smooth star coral
Coral estrella liso
Solenastrea hyades
64
"Incertae sedis"
Knobby star coral
Coral estrella noduloso
Tubastraea coccinea
65
Dendrophylliidae
Tubastraea aurea; T.
tenuillamellosa
Orange cup coral
Coral copa naranja
Tubastraea micranthus
66
Dendrophylliidae
Green cup coral
Coral copa verde ramoso
Tubastraea aurea
EM
Dendrophylliidae
T. tenuillamellosa, T. coccinea
Orange Cup Coral
Coral copa naranja
Millepora alcicornis
1
Milleporidae
Branching fire hydrocoral
Coral de fuego ramoso
Millepora complanata
2
Milleporidae
Millepora alcicornis
Blade fire hydrocoral
Coral de fuego piano
Millepora striata
3
Milleporidae
Striated fire hydrocoral
Coral de fuego estriado
Millepora squarrosa
4
Milleporidae
Millepora complanata
Box fire hydrocoral
Coral defugo submasivo
Stylaster roseus
5
Milleporidae
Rose lace coral
Hydrocoral rosado
R-25
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 3: Traits
SPECIES NAME
Stephanocoenia
intersepta
Acropora cervicornis
Acropora sp.
Acropora palmata
Acropora prolifera
Undaria ten uifolia
Undaria agaricites
Undaria humilis
Undaria purpurea
Undaria carinata
Undaria crassa
Undaria danae
Undaria pusilla
Agaricia fragilis
Agaricia fragilis
Agaricia lamarcki
Agaricia grahamae
Agaricia undata
Leptoseris cailleti
Helioceris cucullata
Dendrogyra cylindrus
Depth
Range
(m)
5-35
0-20
0 -10
0-20
0 -10
0-20
0-50
0-25
15
15
15
15
0 -10
10-50
5-30
10-80
30 - 80?
20 - 80?
35 - 80?
5-50?
1-20
Life
Hist-
ory
Strat-
egy
c
c
c
c
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
G
Yearly
Gameto-
genesis
Spawning/
brooding
events
season
Growth
form
Growth
rate
(cm/year)
Growth
Mean size
1-2
1-2
1-2
1-2
1-2
>1
>6
>6
>1
?
?
>1
>1
>1
>1
>1
?
?
?
?
1
SU
su
SU
su
su
SP-SU-
FA
SP-SU-
FA
SP-SU-
FA
SU-FA?
?
?
SU-FA?
SU-FA?
SU-FA?
?
SU-FA
?
?
?
?
SU
MA-CR
BR
BR
BR-CR
BR
FO-BL
SM-CR
PL-CR
PL-CR
FO-BL
FO-BL
SM-FO
CR-FO
CR-FO
CR-FO
PL-CR
PL-CR
PL-CR
FO-BL
PL-CR
CO-CR
0.1-2
4-37
8-25
2.5-20
7-32
0.8
0.08 -0.2
?
?
?
?
0.8-1.16
?
?
?
0.4-0.6
?
?
?
?
0.5 - 1.8
Slow-fast
Very fast
Very fast
Very fast
Very fast
Slow
Very Slow
Very Slow
Very Slow
?
?
Slow
Slow
?
?
Slow
?
?
?
?
Slow
Med - Lg
Lg - V. Lg
Lg - V. Lg
Lg - V. Lg
Lg - V. Lg
Med - Lg
Sm
Sm - Med
Med
Sm
Sm
Med - Lg
V. Sm
Sm
Sm
Lg - V. Lg
Lg - V. Lg
Lg - V. Lg
Sm - Med
Sm - Med
Lg - V. Lg
R-26
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 3: Traits
SPECIES NAME
Depth
Range
(m)
Life
Hist-
ory
Strat-
egy
REPRO-
DUCTION
pattern-
mode
Yearly
Gameto-
genesis
Spawning/
brooding
Growth
form
Growth
rate
(cm/year)
Growth
Mean size
events
season
Eusmilia fastigiata
5-25
G
G-S
1
1
su
BR
0.7
Slow
Med
Eusmilia fastigiata f.
flagellata
5 -15
G
G-S
1
1-2
su
BR
0.7
Slow
Med
Dichocoenia stokesii
5-20
G
G-S
1
1-2
SU-FA
SM-CR
0.2
Very Slow
Med
Dichocoenia stellaris
10-20
G
? - B
>1
?
SU-FA
SM-CR
0.2
Very Slow
Med
Meandrina
meandrites
3-40
W
MP - B
1
>1
SU-FA
MS-
SM-PL-
CO
0.1-0.3
Very Slow
Med
Meandrina Jacksoni
3-25
W
G-S
1
1-2
SU-FA
SM-
MA-CR-
PL
0.1-0.3
Very Slow
Med
Meandrina danae
10-30
W
MP-S
1
1-2
SU-FA
SM
?
Very Slow
V. Sm
Meandrina sp.
5-30
W
MP - B
?
?
?
SM
?
Very Slow
Sm
Goreaugyra
memorialis
>30
W
?
—
CO
—
—
Colpophyllia natans
1-25
S
H -S
1
1-2
SIJ f A
BO-
MA-CR
0.3 - 1.1
Slow
Med - Lg
Colpophyllia
amaranthus
5-20
S
H -S
1
1-2
SU-FA?
BO-
MA-CR
0.3 - 1.1
Slow
Med - Lg
Colpophyllia
breviserialis
5-20
S
H -S
1
1-2
SU-FA
BO-
MA-CR
?
Slow
Med - Lg
Pseudodiploria clivosa
0-5
S
H -S
1
1-2
SU-FA
CR-SM
0.3 - 1.0
Slow
Med - Lg
Pseudodiploria
strigosa
1-30
S
H -S
1
1-2
SU-FA
BO-
MA-CR
0.33 -1.0
Slow
Med - Lg
Diploria
labyrin thiformis
3-25
S
H -S
1
1-2
SU-FA
BO-
MA-CR
0.3-0.75
Slow
Med - Lg
R-27
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 3: Traits
SPECIES NAME
Depth
Range
(m)
Life
Hist-
ory
Strat-
egy
REPRO-
DUCTION
pattern-
mode
Yearly
Gameto-
genesis
Spawning/
brooding
Growth
form
Growth
rate
(cm/year)
Growth
Mean size
events
season
Favia fragum
0 -10
s
H - B
7-10
12
year-
around
SM-CR
0.5
Slow
V. Sm
Manicina areolata
1-20
w
H - B
1
>1
SP-SU
SM
0.3 - 1.2
Slow
Sm
Manicina mayori
10-20
w
H - B
?
?
?
SM-CR
0.3 - 1.2
Slow
Sm
Isophyllia sinuosa
5-20
w
H - B
1
>1
SP-SU
SM-CR
0.5
Slow
Sm
Isophyllia rigida
5-20
w
H - B
1
>1
SU-FA
SM-CR
0.3
Very Slow
Sm
Isophyliia multiflora
10-20
w
?
?
?
?
SM-CR
?
Very Slow
Sm
Mycetophyllia ferox
5-25
w
H - B
2-4
>2
FA-WI
PL-CR
?
Slow
Sm - Med
Mycetophyllia aliciae
10-50
w
H - B
2-4
>2
WI-SP
PL-CR
?
Slow
Med - Lg
Mycetophyllia
lamarckiana
10-30
w
H - B
2-4
>2
WI-SP
PL-CR
?
Slow
Sm - Med
Mycetophyllia danana
10-30
w
H - B
2-4
>2
WI-SP
PL-CR-
SM
?
Slow
Sm - Med
Mycetophyllia resii
20-60
w
?
?
?
PL
?
Slow
Med - Lg
Scolymia cubensis
5-25
w
H - B
1
>1
SU-FA
SM-SP
?
Slow
V. Sm
Scolymia lacera
10-30
w
H - B
?
?
?
SM-SP
?
Very slow
V. Sm - Sm
Scolymia wellsi
15-35
w
H - B
1
>1
?
SM-SP
?
Very slow
V. Sm
Scolymia nsp.
> 20m
w
H - B
?
?
?
SM-SP
?
Very slow
V. Sm
Mussa angulosa
5-25
w
H - B
?
>1
?
BR-SM
?
Very slow
Med - Lg
Orbicella annularis
1-25
G
H -S
1
2-3
SU-FA
CO-BO-
SM
0.4-1.4
Slow
Med - V. Lg
Orbicella faveolata
1-25
G
H -S
1
2-3
SU-FA
BO-
MA-
SM-CR
0.5 - 1.2
Slow
Med - V. Lg
R-28
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 3: Traits
SPECIES NAME
Depth
Range
(m)
Life
Hist-
ory
Strat-
egy
REPRO-
DUCTION
pattern-
mode
Yearly
Gameto-
genesis
Spawning/
brooding
Growth
form
Growth
rate
(cm/year)
Growth
Mean size
events
season
Orbicella franksi
Montastraea
cavernosa
10-45
3-90
G
S
H -S
G-S
1
1
2-3
1
SU-FA
SU
BO-
MA-
SM-CR
BO-SM-
CR
0.15-0.6
0.2 - 1.1
Slow
Slow
Med - V. Lg
Med - Lg
Montastraea nsp.
10-30
S
G -S
1
1
SU
BO-SM-
CR
0.2-0.7
Slow
Med - Lg
Pontes astreoides
1-50
W
MP-B
2-7
>5
SP-SU-
FA
CR-SM-
PL
0.19-1.4
Slow
Med
Pontes colonensis
5-20
W
? - B
?
?
?
PL-CR-
SM
?
Slow
Sm
Pontes porites
1-30
W
G- MP -B
2-5
>2
SP-SU-
FA
BR
0.8-3.3
Fast
Med - V. Lg
Pontes furcata
1 -12
W
G - B
2-5
>2
SP-SU-
FA
BR
0.9-5.3
Fast
Med - V. Lg
Porites divaricata
0 -15
W
G - B
?
?
SP-SU-
FA
BR
?
Fast
Med - V. Lg
Porites nsp.
0-5
W
?
?
?
SM-CR
?
Slow
V. Sm - Sm
Madracis decactis
5-50
W
H - B
1
>1
SP-SU-
FA
BR-SM
?
Slow
Sm - Med
Madracis formosa
15-30
W
H - B
1
>1
SP-SU-
FA
BR
?
Slow
Sm 1 - Lg
Madracis carmaby
>30
w
H - B
1
>1
SP-SU-
FA
BR
?
Slow
Sm - Med
Madracis pharensisf
luciphogous
5-30
w
H - B
1
>1
SP-SU-
FA
SM-CR
?
Very slow
Sm
R-29
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 3: Traits
SPECIES NAME
Depth
Range
(m)
Life
Hist-
ory
Strat-
egy
REPRO-
DUCTION
pattern-
mode
Yearly
Gameto-
genesis
Spawning/
brooding
Growth
form
Growth
rate
(cm/year)
Growth
Mean size
events
season
Madracis pharensisf.
luciphylla
10-50
w
H - B
1
>1
SP-SU-
FA
CR-SM
?
Very Slow
Sm
Madracis senaria
10-30
w
H - B
1
>1
SP-SU-
FA
CR-SM
?
Slow
Sm - Med
Madracis auretenra
1-30
w
H - B
1
>1
SP-SU-
FA
BR
0.7-2.4
Fast
Med - V. Lg
Madracis asperula
30 -150
w
?
?
?
?
BR
2.0
Fast
Sm
Madracis myriaster
30 -150
w
?
?
?
?
BR
?
?
Sm
Oculina diffusa
2-25
w
G-S
?
?
?
BR-CR
1.2-2.2
Fast
Sm - Med
Oculina varicosa
5-20
w
G-S
?
?
SU-FA?
BR-CR
?
?
Sm - Med
Oculina valecienesi
5-20
w
G-S
?
?
?
BR
?
?
Sm
Oculina robusta
10-30
w
G-S
?
>1
?
BR-CR
?
?
Sm
Siderastraea siderea
1-50
s
G-S
1
1
SU
CR-BO-
SM
0.2-0.9
Slow
Med - Lg
Siderastrea radians
0-5
w
G - B
2-5
>2
SP-SU-
FA?
CR-SM
0.15 -1.8
Slow
V. Sm - Sm
Siderastrea stellata
5-25
c
?
?
?
?
CR-SM
?
Slow
Sm
Cladocora arbuscula
3-20
c
H -S
1
1-2
SU-FA
BR
?
?
Sm - Med
Solenastrea bournoni
3-20
s
G-S
?
?
SU-FA
MA-BO
0.9
Slow
Med - Lg
Solenastrea hyades
10-25
s
? - B
?
?
SU-FA?
SM
0.2
Very Slow
Sm - Med
Tubastraea coccinea
3-25
w
H - B
?
>3
SP-SU-
FA
CR
?
?
Sm
Tubastraea
mi era nth us
10-40
w
? - B
?
?
?
CR
?
?
Med
Tubastraea aurea
5-30
w
H - B
?
?
?
CR
?
?
Sm
Millepora alcicornis
1-40
c
G - B
?
?
?
BR-CR
0.2-0.75
Slow
Med-V. Lg
R-30
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 3: Traits
SPECIES NAME
Depth
Range
(m)
Life
Hist-
ory
Strat-
egy
REPRO-
DUCTION
pattern-
mode
Yearly
Gameto-
genesis
Spawning/
brooding
Growth
form
Growth
rate
(cm/year)
Growth
Mean size
events
season
Millepora complanata
2-40
c
G - B
?
?
?
PL-CR
00
O
ro
O
Slow
Lg - V. Lg
Millepora striata
5 -15
c
G - B
?
?
?
BR
Slow
Med-Lg
Millepora squarrosa
5 -15
w
G - B
?
?
?
SM-CR
2.24
Fast
Sm - Med
Stylaster roseus
3-50
w
G - B
?
?
?
BR
Slow
Sm
R-31
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 4: Disease Susceptibility
SPECIES NAME
BBD
WBD
WPX
WPD
CYBD
DSD
GAN
RBD
CCI *
IMS
**
SCTLD
***
OTH
BLE
N
OVER-
ALL
BCG
ATRIB.
Stephanocoenia
intersepta
**
*
* * *
**
*
*
**
*
* * *
9
**
3-4
Acropora cervicornis
**
* * *
**
*
**
*
* * *
7
* * *
3-4
Acropora palmata
*
* * *
* * *
*
**
*
* * *
8
* * *
2-3
Acropora prolifera
**
*7
*
*
**
3
*
4
Acropora sp.
*
* * *
**
2
**
4
Undaria tenuifolia
*
*
**
*
* * *
5
*
4-5
Undaria agaricites
**
**
*
*
**
*
*
* * *
8
**
3-4
Undaria humilis
*
**
*
*
* * *
5
*
5
Undaria purpurea
*
**
**
3
*
5
Undaria carinata
?
*
**
3
*
Undaria crassa
?
?
**
3
*
Undaria danae
*
**
*
*
*
*
* * *
7
**
4-5
Undaria pusilla
*
*
* * *
3
*
4-5
Agaricia fragilis
*
*
*
*
* * *
5
**
5
Agaricia fragilis
(Bermuda)
**
*
**
3
*
5
Agaricia lamarcki
*
**
*
*
*
**
6
**
4
Agaricia grahamae
*
*
**
3
*
4-5
Agaricia undata
*
*
**
3
*
4-5
R-32
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
SPECIES NAME
BBD
WBD
WPX
WPD
CYBD
Leptoseris cailleti
*
Helioceris cucullata
*
*
Dendrogyra cylindrus
**
* * *
Eusmilia fastigiata
Eusmilia fastigiata f.
flagellata
**
*
Dichocoenia stokesii
*
* * *
Dichocoenia stellaris
*
*
Meandrina
meandrites
**
* * *
Meandrina Jacksoni
**
* * *
Meandrina danae
*
Meandrina sp.
(Bermuda)
*
* * *
Goreaugyra
memorialis
—
—
—
—
—
Colpophyllia natans
Colpophyllia
amaranthus
**
**
* * *
* * *
*
*
Colpophyllia
breviserialis
**
**
Pseudodiploria clivosa
Pseudodiploria
strigosa
* * *
* * *
**
* * *
*
*
GAN
RBD
CCI *
IMS
**
SCTLD
***
OTH
BLE
N
OVER-
ALL
BCG
ATRIB.
**
2
*
5
*
*
* * *
5
*
5
*
*
**
**
* * *
7
* * *
1-2
**
*
**
4
**
4-5
*
* * *
**
3
**
4-5
* * *
*
*
5
**
4
*
*
3
**
5
*
*
* * *
*
**
8
**
4
*
*
*
* * *
**
8
*
4-5
*
2
*
5
*
*
**
5
*
5
—
—
—
—
—
—
—
—
—
*
*
*
* * *
8
**
3
*
*
**
7
**
4
*
* * *
5
**
3-4
**
*
*
**
7
*
3-4
**
**
*
*
7
**
3-4
R-33
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 4: Disease Susceptibility
SPECIES NAME
BBD
WBD
WPX
WPD
CYBD
DSD
GAN
RBD
CCI *
IMS
**
SCTLD
***
OTH
BLE
N
OVER-
ALL
BCG
ATRIB.
Diploria
* * *
* * *
*
*
**
* * *
*
**
8
**
labyrin thiformis
3-4
Favia fragum
*
* * *
*
*
* * *
5
*
5
Manicina areolata
*
*
**
3
*
5
Manicina mayori
*
1
?
Montastraea
**
**
*
*
*
**
* * *
*
*
9
*
cavernosa
4-5
Montastraea
**
**
*
**
* * *
*
*
7
*
nsp.(Large polyps)
5
Isophyliia sinuosa
*
**
*
3
*
5
Isophyllia rigida
*
**
**
3
*
4-5
Isophyliia multiflora
?
*
1
*
4-5
Mycetophyllia ferox
**
* * *
*
**
*
*
6
**
4
Mycetophyllia aliciae
**
*
*
3
*
5
Mycetophyllia
*
**
*
*
*
c;
*
lamarckiana
J
5
Mycetophyllia danana
**
*
*
3
*
5
Mycetophyllia resii
?
*
1
*
5
Scolymia cubensis
*
*
*
3
*
5
Scolymia lacera
*
*
2
*
5
Scolymia wellsi
*
*
2
*
5
Scolymia nsp.
*
1
*
1-2
Mussa angulosa
*
*
**
3
*
1-2
R-34
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 4: Disease Susceptibility
SPECIES NAME
BBD
WBD
WPX
WPD
CYBD
DSD
GAN
RBD
CCI *
IMS
**
SCTLD
***
OTH
BLE
N
OVER-
ALL
BCG
ATRIB.
Orbicella annularis
* * *
* * *
* * *
* * *
*
**
*
* * *
*
* * *
10
* * *
1-2
Orbicella faveolata
* * *
* * *
* * *
**
*
*
*
**
* * *
*
* * *
11
* * *
1-2
Orbicella franksi
**
* * *
* * *
*
*
*
**
* * *
*
*
10
**
4
Porites astreoides
**
*
*
*
*
5
*
4-5
Porites colonensis
?
?
Porites porites
*
*
*
*
* * *
5
**
2-3
Porites furcata
*
*
**
3
*
5
Porites divaricata
*
**
2
*
5
Porites nsp.
*
1
?
Madracis decactis
**
*
*
3
*
5
Madracis formosa
*
*
2
*
5
Madracis carmaby
*
1
*
5
Madracis pharensisf
*
*
¦j
*
luciphogous
£-
5
Madracis pharensisf.
*
1
*
luciphylla
1
Madracis senaria
**
*
*
3
*
5
Madracis auretenra
**
*
*
**
4
*
5
Madracis asperula
?
?
?
Madracis myriaster
?
?
?
Oculina diffusa
**
**
2
*
5
Oculina varicosa
**
1
*
5
R-35
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 4: Disease Susceptibility
SPECIES NAME
BBD
WBD
WPX
WPD
CYBD
DSD
GAN
RBD
CCI *
IMS
**
SCTLD
***
OTH
BLE
N
OVER-
ALL
BCG
ATRIB.
Oculina valecienesi
*
**
2
*
5
Oculina robusta
*
1
*
5
Siderastraea siderea
**
* * *
* * *
**
**
* * *
6
**
1-2
Siderastrea radians
*
* * *
**
*
**
5
*
4-5
Siderastrea stellata
*
**
**
*
4
*
5
Cladocora arbuscula
*
**
2
*
5
Solenastrea bournoni
**
* * *
* * *
**
4
*
4-5
Solenastrea hyades
?
?
?
Tubastraea coccinea
*
1
?
5
Tubastraea
"P
•p
mi era nth us
?
Tubastraea aurea
*
1
?
?
Millepora alcicornis
* * *
*
*
* * *
4
*
1-2
Millepora complanata
*
* * *
*
*
* * *
4
*
3-4
Millepora striata
**
1
*
5
Millepora squarrosa
**
*
* * *
3
*
5
Stylaster roseus
**
**
2
*
5
R-36
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 5: BCG Attributes and Pa
hogenic Diseases
SPECIES NAME
Sediment
Susceptibility
BCG
ATTRIBUTE
Stephanocoenia
intersepta
Acropora cervicornis
Acropora sp.
Acropora palmata
Acropora prolifera
Undaria tenuifolia
Undaria agaricites
Undaria humilis
Undaria purpurea
Undaria carinata
Undaria crassa
Undaria danae
Undaria pusilla
Agaricia fragilis
Agaricia fragilis
Agaricia lamarcki
Agaricia grahamae
Agaricia undata
Leptoseris cailleti
Helioceris cucullata
Dendrogyra cylindrus
Eusmilia fastigiata
Eusmilia fastigiata f
flagellata
**
**
* * *
**
**
* * * *
* * * *
* * * *
* * *
* * *
**
* * * *
* * *
* * *
* * * *
* * * *
* * * *
**
* * * *
2-3
2-3
3-4
2-3
2-3
5
5
5
3-4
3-4
2-3
5
3-4
3-4
5
5
5
2-3
5
1-2
2-3
2-3
BCG
ATTRIBUTE
Disease
Susceptibility
BCG
ATTRIBUTE
PATHOGENIC DISEASES
3-4
3-4
4-5
3
5
4-5
4-5
3-4
5
5
4-5
5
5
5
5
4-5
4-5
5
4-5
4-5
4-5
* * *
**
* * *
**
*
**
**
*
?
?
**
*
*
*
**
*
*
?
*
* * *
2-3
3-4
2-3
4-5
2
1-2
2-3
2
1
2
1
1
1
2-3
1
1-2
1
4-5
4
WPD - DSD - RBD - CCI - OTH -
SCTLD
WBD - BBD - WPX - RBD - GAN -
CCI - OTH
WBD - BBD - RBD - CCI - OTH
WBD - WPX - CCI - GAN - OTH
WBD - CCI - OTH
WPD-CCI
WPD - RBD - DSD-CCI
WPD-CCI-RBD-DSD
WPD - RBD
?
?
WPD - BBD-RBD
WPD
WPD - BBD - RBD
WPD - RBD
WPD - RBD-OTH
WPD - OTH
WPD - OTH
?
WPD - OTH
WPD - CYBD - BBD - GAN - OTH ¦
SCTLD
WPD - BBD-CCI-SCTL
WPD-CCI
R-:
¦37
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
SPECIES NAME
Sediment
Susceptibility
BCG
ATTRIBUTE
Bleaching
Susceptibility
BCG
ATTRIBUTE
Disease
Susceptibility
BCG
ATTRIBUTE
PATHOGENIC DISEASES
Dichocoenia stokesii
**
2-3
* * *
3-4
* * * *
4-5
BBD-WPD-SCTLD
Dichocoenia stellaris
**
2-3
* * *
3-4
* * *
4
WPD - BBD
Meandrina meandrites
**
2-3
* * *
4
* * *
4
BBD-WPD-SCTLD
Meandrina Jacksoni
**
2-3
* * *
4
**
3
BBD - WPD - RBD- SCTLD
Meandrina danae
*
1-2
*
1-2
*
1
WPD
Meandrina sp.
**
3
**
3
**
2
WPD - BBD
Goreaugyra memorialis
-
-
-
-
-
-
-
Colpophyllia natans
* * *
3
* * *
3-4
* * * *
4-5
BBD - WPD - DSD -RBD - GAN -
CCI - SCTLD
Colpophyllia
amaranthus
* * *
3
* * *
4
* * *
4
BBD - WPD - RBD- OTH - SCTLD
Colpophyllia
breviserialis
* * *
3
* * *
3-4
* * * *
4-5
BBD - RBD-WPD - DSD-CCI-
SCTLD
Pseudodiploria clivosa
*
1-2
*
2
* * *
2-3
BBD-WPD-DSD-GAN-OTH-SCTLD
Pseudodiploria strigosa
**
2-3
*
2
* * *
2-3
BBD-WPD-CYBD-DSD-RBD-CCI-
GAN-OTH-SCTLD
Diploria
labyrin thiformis
**
2-3
* * *
3-4
* * * *
4-5
BBD-WPD-CYBD-RBD-CCI-GAN-
OTH-SCTLD
Favia fragum
*
1-2
* * *
3-4
*
1
BBD-WPD - DSD-OTH
Manicina areolata
*
1-2
**
3
*
1
WPD - OTH
Manicina mayori
**
2-3
**
3
?
?
Isophyllia sinuosa
**
2-3
*
1-2
*
1-2
BBD-WPD-OTH
Isophyllia rigida
* * *
3-4
*
1-2
*
1-2
BBD-WPD-OTH
Isophyliia multiflora
**
3
?
?
?
?
Mycetophyllia ferox
**
2-3
**
3
* * *
2-3
BBD - WPD - OTH - SCTLD
Mycetophyllia aliciae
**
2-3
*
1-2
**
2-3 | WPD - OTH - SCTLD
R-38
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 5: BCG Attributes and Pa
hogenic Diseases
SPECIES NAME
Sediment
Susceptibility
BCG
ATTRIBUTE
Bleaching
Susceptibility
BCG
ATTRIBUTE
Disease
Susceptibility
BCG
ATTRIBUTE
PATHOGENIC DISEASES
Mycetophyllia
**
lamarckiana
* * *
3-4
*
1-2
2
WPD - RBD
Mycetophyllia danana
* * *
3-4
*
1-2
**
1-2
WPD
Mycetophyllia resii
**
1-2
*
1-2
*
1-2
WPD - OTH
Scolymia cubensis
*
1
**
1-2
*
1-2
WPD
Scolymia lacera
*
1
*
1
*
1
WPD
Scolymia wellsi
*
1
*
1-2
?
?
Scolymia nsp.
*
1
*
1-2
?
?
Mussa angulosa
**
1-2
*
1-2
**
1-2
WPD - OTH - SCTLD
* * * *
BBD-CYBD-WPD-DSD-RBD-CCI-
Orbicella annularis
*
2
* * * *
4-5
4-5
GAN-OTH-SCTLD
* * * *
BBD-CYBD-WPD-DSD-RBD-CCI-
Orbicella faveolata
**
3
* * * *
4-5
4-5
GAN-OTH-SCTDL-IMS
* * *
BBD-CYBD-WPD-DSD-GAN-CCI-
Orbicella franksi
**
3
* * *
4-5
4
OTH-SCTLD-IMS
Montastraea
**
BBD-WPD-DSD-CYBD-CCI-GAN-
cavernosa
*
1-2
**
3
2-3
RBD-OTH-SCTLD-IMS
Montastraea nsp.
*
1-2
**
2
**
2-3
BBD - WPD - DSD - OTH - SCTLD -
IMS
Porites astreoides
* * *
3-4
*
1-2
**
2-3
BBD - RBD- WPD- CCI - OTH
Porites colonensis
* * *
1-2
*
1-2
?
?
Porites porites
*
1-2
* * *
4-5
**
2-3
WPD - OTH
Porites furcata
*
1-2
**
3
*
1-2
WPD
Porites divaricata
*
1-2
**
3
*
1
WPD - OTH
Porites nsp.
* * *
4
**
3
*
1-2
WPD
Madracis decactis
**
3
*
1-2
*
1-2
WPD - OTH
Madracis formosa
**
3
*
1-2
*
1
WPD - OTH
Madracis carmaby
**
3
*
1
?
?
R-:
¦39
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
SPECIES NAME
Sediment
Susceptibility
BCG
ATTRIBUTE
Bleaching
Susceptibility
BCG
ATTRIBUTE
Disease
Susceptibility
BCG
ATTRIBUTE
PATHOGENIC DISEASES
Madracis pharensisf
* * *
4
*
luciphogous
*
1-2
1
WPD-OTH
Madracis pharensisf.
* * *
A
*
i
luciphylla
Madracis senaria
* * *
4-5
*
1-2
*
1-2
WPD-GAN
Madracis auretenra
*
1-2
**
2-3
**
1-2
WPD - OTH
Madracis asperula
?
*
1
?
?
?
Madracis myriaster
?
*
1
?
?
?
Oculina diffusa
*
1
**
3
*
1
WPD - OTH
Oculina varicosa
*
1
**
3
?
?
Oculina valecienesi
*
1
* * *
3-4
?
?
Oculina robusta
*
1
* * *
3-4
?
?
* * *
BBD - DSD - WPD -RBD - CCI -
Siderastraea siderea
**
1-2
* * *
3-4
4
OTH - SCTLD
Siderastrea radians
*
1
**
3
*
1-2
BBD - DSD-WPD
Siderastrea stellata
*
1-2
**
2-3
*
1
WPD-GAN
Cladocora arbuscula
*
1
**
3
*
1
WPD
Solenastrea bournoni
**
2-3
**
3
**
2
BBD - WPD - DSD - OTH - SCTLD
Solenastrea hyades
**
1-2
?
?
?
?
?
Tubastraea coccinea
* * * *
5
*
1
WPD
Tubastraea micranthus
* * *
4-5
?
1
?
Tubastraea aurea
* * * *
5
*
1
WPD - OTH
Millepora alcicornis
**
2-3
* * * *
5
**
2
WPD - OTH - GAN
Millepora complanata
**
2-3
* * * *
5
**
3-4
BBD-WPD-OTH
Millepora striata
* * *
4-5
* * *
4-5
?
?
Millepora squarrosa
* * *
4-5
* * * *
5
?
?
Stylaster roseus
*
1-2
* * *
4-5
?
?
R-
¦40
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 6: Distribution and Description
SPECIES NAME
GEOGRAPHIC
DISTRIBUTION
OBSERVATIONS AND COMMENTS
Stephanocoenia
intersepta
Wider Caribbean
Common but not highly abundant in northern Caribbean. Abundant in western and southern
Caribbean. Small to medium sized colonies with smooth surface, deep, poligonal calices and tan
to greenish coloration.
Acropora cervicornis
Wider Caribbean
except Bermuda
Eadangered species (ESA-IUCN). Two conspicuous morphologies in the Caribbean, this one has
thin, long branches, frequent lateral branching and fast growth. Good recovery reported for
many localities but still impacted by WBD outbreaks, high predation rates by fireworms (H.
carunculata) and snails (C. abbreviata. C. caribbaea), algae overgrowth and damselfish are major
problems.
Acropora sp.
Central and
southern Caribbean
Needs taxonomic verification. This thick growth form has been observed growing side by side
with the thin, commom A. cervicornis. Common in the southern Caribbean
Acropora palmata
Wider Caribbean
except Bermuda
Endangered species (ESA-IUCN). Recovering is been slow in most localities. Still affected by WBD-
like signs, algae overgorwth and damselfishand fireworm predation
Acropora prolifera
Wider Caribbean
except Bermuda
Hybrid taxon between A. cervicornis and A. palmata. Mophology depends on which parental
species donated the egg or sperm. Dense, finger-like, short branches form compact colonies that
seem more resistant to WBD-like infections and damselfish colonization.
Undaria ten uifolia
Central and Western
Caribbean
One of 3 bifacial agaricids. Thin corallum forn large wide and vertical colonies that can
monopolize extensive habitats. Most common in north-central, south central and western
Caribbean.
Undaria agaricites
Wider Caribbean
except Bermuda
Submassive, crustose colonies.
Undaria humilis
Wider Caribbean
except Bermuda
Small, massive-crustose colonies with reticulated high ridges and closed valleys with few calices
Undaria purpurea
Wider Caribbean
except Bermuda
Reticulated ridges and closed valleys with few mouths inside.
Undaria carinata
Western Caribbean
Needs taxonomic varification. Posibly endemic to south central America
Undaria crassa
Western Caribbean
Needs taxonomic verification. Posibly endemic to south central America and Colombia
R-41
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 6: Distribution and Description
SPECIES NAME
GEOGRAPHIC
DISTRIBUTION
OBSERVATIONS AND COMMENTS
Undaria danae
Wider Caribbean
except Bermuda
Thick bifacial blades with a foliose/plate base. Abundant in well exposed, deeper (12-25m)
habitats.
Undaria pusilla
Western and Central
Caribbean
Small, cryptic thin crusts with low ridges, short valleys and small calices. In shallow, well exposed
habitats
Agaricia fragilis
Wider Caribbean
except Bermuda
Small, dark-colored, round/oval plates with low ridges and long valleys with tiny calices.
Agaricia fragilis
Bermuda
Posible endemic species for Bermuda - different from A. fragilis in the Caribbean
Agaricia lamarcki
Agaricia grahamae
Agaricia undata
Leptoseris cailleti
Wider Caribbean
except Bermuda
Wider Caribbean
except Bermuda
Wider Caribbean
except Bermuda
Wider Caribbean
???
Wide depth distribution, from 10 to 70 m depth
Needs genetic verification - mesophotic deep coral
Mesophotic species
Mesophotic to deep water coral
Helioceris cucullata
Wider Caribbean
except Bermuda
A slightly different form called "formae contracta" has been described for some localities.
Dendrogyra cylindrus
Wider Caribbean
except Panama and
Bermuda
Threatened species.
E usmilia fastigiata
Wider Caribbean
except Bermuda
Typical faceoloid (Flower-like) colony, with separate, large calices calices and intratentacular
division. Tan to yellow.
Eusmilia fastigiata f
flagellata
Caribbean
Meandroid, ellongated calices with several mouths that could be the early stages of
intratentacular budding.
Dichocoenia stokesii
Wider Caribbean
Small to mediun sized (40cm) colonies with elongated calices and wide coenosteum. Typically
orange-yellow or pale.
Dichocoenia stellaris
Wider Caribbean
Needs Taxonomic verification
R-42
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 6: Distribution and Description
SPECIES NAME
GEOGRAPHIC
DISTRIBUTION
OBSERVATIONS AND COMMENTS
Meandrina
meandrites
Wider Caribbean
except Bermuda
Thick septa and deep narrow valleys - Possibly not in Bermuda since the taxon there is diferent
Meandrina Jacksoni
Wider Caribbean
except Bermuda
Recently described. Crustose/plate coralla, wide, pale valleys and low ridges
Meandrina danae
Wider Caribbean
except Bermuda
Confused with M. brasiliensis which is endemic to Brazil
Meandrina sp.
Bermuda
This is probably a different, endemic species. Needs taxonomic verification
Goreaugyra
memorialis
Only specimen
found in the
Bahamas
The only existing specimen is a short column with wide ambulacra and deep valleys on the side.
The top morphology and calical structure are similar to M. meandrites. Specimen collected in
deep waters in the Bahamas.
Colpophyllia natans
Wider Caribbean
except Bermuda
Large boulder and crustose coralla
Colpophyllia
amaranthus
Wider Caribbean
except Bermuda ??
Probably restricted distribution. Common in north and southern Caribbean
Colpophyllia
breviserialis
Wider Caribbean
except Bermuda
Needs taxonomic verification (genetic). Low abundances and mixed morphology colonies with
C.natans type common.
Pseudodiploria
clivosa
Wider Caribbean
Shallow water mostly. Crustose to submassive colonies with irregular, bumpy surface
Pseudodiploria
strigosa
Wider Caribbean
Crustose, platy and hemispherical meandroid colonies. Narrow ridges and eep valleys, no
ambulacra.
Diploria
labyrin thiformis
Wider Caribbean
Mostly round hemispherical colonies with wide ridges and ambulacra, and deep narrow valleys.
Mostly orange-yellow
Favia fragum
Wider Caribbean
Round small corallum, abundant in shallow, protected (back reef) habitats
Manicina areolata
Wider Caribbean
except Bermuda
Lives on sediment areas, like Thallasia beds.
Manicina mayori
??
Needs genetic and more ecological data
Isophyllia sinuosa
Wider Caribbean
These two are considered to belong to a single genus: Isophyllastrea
Isophyllia rigida
Wider Caribbean
except Bermuda
These two are considered to belong to a single genus: Isophyllastrea
R-43
-------
The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Table 6: Distribution and Description
SPECIES NAME
GEOGRAPHIC
DISTRIBUTION
OBSERVATIONS AND COMMENTS
Isophyliia multiflora
Caribbean ??
Rare growth form with closed valleys. Needs taxonomic verification.
Mycetophyllia ferox
Wider Caribbean
except Bermuda
Mediun sizes plates with narrow ridges acros whole colony, opne and closed valleys
Mycetophyllia aliciae
Wider Caribbean
except Bermuda
Shallow, wide valleys, discontinuous ridges.
Mycetophyllia
lamarckiana
Wider Caribbean
except Bermuda
Deep and wide valleys, discontinuous, wide ridges
Mycetophyllia
danana
Wider Caribbean
Deep and narrow valleys, continuous, wide ridges
Mycetophyllia resii
Wider Caribbean
Deep water species. Flat plates with no ridges across corallum.
Scolymia cubensis
Wider Caribbean
Small, single polyps in criptic areas of the reef. Multicolored.
Scolymia lacera
Wider Caribbean
except Bermuda
Largest, singke polyp species in the Caribbean. Fleshy polyps up to 15-20 cm in diameter.
Multiple coloration
Scolymia wellsi
Eastern Caribbean
??
Endemic to Brazil, presence in Caribbean needs Taxonomic verification
Scolymia nsp.
North Gulf of
Mexico ??
Under study. Only observed in the Flower Gardens
Mussa angulosa
Wider Caribbean
except Bermuda
Large polyps growing in a faceoloid growth form. Intratentacular division. Multicolored.
Orbicella annularis
Wider Caribbean
except Bermuda
Recently reclassified into a different family. Threatened species (ESA-IUCN)
Orbicella faveolata
Wider Caribbean
Recently reclassified into a different family. Threatened species (ESA-IUCN))
Orbicella franksi
Wider Caribbean
Recently reclassified into a different family. Threatened species (ESA-IUCN)
Montastraea
cavernosa
Wider Caribbean
Wide depth distibution.
Montastraea nsp.
Wider Caribbean
except Bermuda
Under study. Morphometric, ecological and behavioral data indicates is different from small
polyped M. cavernosa
Porites astreoides
Wider Caribbean
Wide depth distribution and colormorphs
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Table 6: Distribution and Description
SPECIES NAME
GEOGRAPHIC
DISTRIBUTION
OBSERVATIONS AND COMMENTS
Pontes colonensis
Endemic to south-
west Caribbean
Submassive, and thin plates. Dark brown or olive green with bright calices
Pontes porites
Wider Caribbean
Thick, long or short branches
Pontes furcata
Wider Caribbean
except Bermuda
Thinner branches than P. porites, dichotomous and long. Back lagoonal habitats and slopes.
Porites divaricata
Wider Caribbean
except Bermuda
Short, thin, dichotomous branches, back and lagoonal reefs and seagrass habtats and sometimes
found in front reef slopes. Yellow tan and grey colorations.
Porites nsp.
Central Caribbean
Common small crustose, smooth, bluish species found in shalow, exposed habitats of central
Caribbean. P. branneri is endemic to Brazil. Under study.
Madracis decactis
Wider Caribbean
Short, green-gray nobby branches. Wide depth distribution
Madracis formosa
Wider Caribbean
Long, chocolate brown sometimes flattened branches, yellow calices. Dee pslopes and sandy
areas
Madracis carmaby
Curacao and
southern Caribbean
only??
Short, brown or olive green rounded branches, smaller colonies than M. formosa
Madracis pharensisf
luciphogous
Wider Caribbean
except Bermuda
Taxon without zooxanthellae
Madracis pharensisf.
luciphylla
Wider Caribbean
except Bermuda
Needs taxonomic verification. Taxon with zooxanthelae in deep, exposed habitats.
Madracis senaria
Wider Caribbean
except Bermuda
Semi criptic, submassive colonies with five exerted primary septa that are distinctive, diagnostic
traits
Madracis auretenra
Wider Caribbean
Long, thing pale to yellow branches. Incorrectlky clasified as M. mirabilis.
Madracis asperula
Caribbean ??
Needs taxonomic verification. Deep reef and mesophotic coral comunities
Madracis myriaster
Caribbean ??
Deep reef and Mesophotic coral communities
Oculina diffusa Wider Caribbean
Can form large thickets in protected habitats
Oculina varicosa Wider Caribbean
Short, thick branches and small colonies.
„ . Wider Caribbean
Oculina vaiecienesi
except Bermuda
Restricted to the cnetral and southern Caribbean
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Table 6: Distribution and Description
SPECIES NAME
GEOGRAPHIC
DISTRIBUTION
OBSERVATIONS AND COMMENTS
^ , Florida - Eastern
Oculina robusta
coast US
More common in temperated environments - azooxanthellated
Siderastraea siderea
Wider Caribbean
Wide depth and habitat distribution
Siderastrea radians
Wider Caribbean
Small, crustose and round colonies in shallow water habitats
Siderastrea stellata
Endemic to Brasil
???
Needs Taxonomic verification
Cladocora arbuscula
Wider Caribbean
except Bermuda
Short branching polyps, associated with soft bottoms and seagrasses
Solenastrea bournoni
Wider Caribbean
except Bermuda
Round, hemispherical medium sized colonies. Brownish to green coloration.
Solenastrea hyades
Wider Caribbean
except Bermuda
limited distribution, murky environments, small corallum
Tubastraea coccinea
Wider Caribbean
except Panama and
Bermuda
Uncertain taxonomic status. Caribbean taxon (T. aurea) Genetic verification needed to separate
from T. coccinea
Tubastraea
mi era nth us
Northern Gulf of
Mexico - Hispaniola
Invasive species, mostly in northern Gulf of Mexico, Dominican Republic
Tubastraea aurea
Wider Caribbean
except Bermuda
Uncertain taxonomi status, being called T. coccinea but evidence of genetic, morphometric
differences exist (Weil unpub)
Millepora alcicornis
Wider Caribbean
Hydrozoan
Millepora
complanata
Wider Caribbean
Hydrozoan
Millepora striata
Western Caribbean
Only ??
Hydrozoan, restricted distribution to the western Caribbean
Millepora squarrosa
Central and outhern
Caribbean
Hydrozoan
Stylaster roseus
Wider Caribbean
except Bermuda
Hydrozoan
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Appendix S - Generalized Stressor Gradient
Leah Oliver
The BCG expert panel discussed the concept of a generalized stressor axis (GSA) and concluded
that three stressors should be considered for coral reefs based on a broad body of supporting
literature and their cumulative knowledge that deleterious impacts on reef health and biota are
associated with increases in: (1) land-based sources of pollution, (2) fishing pressure, and (3)
global climate change-associated thermal anomalies. A summary of their recommendations is
shown in Appendix Q).
Here, additional information about these stressors is presented including some of the research
efforts that demonstrate their connections with reef health, caveats associated with applying each
to predict reef condition decline, and data needs to further develop a coral reef BCG for
maximum regulatory effectiveness.
Land-based sources of pollution.
EPA began stressor axis research by testing distance to a source of human disturbance as a proxy
for exposure of coral reefs to anthropogenic impacts on the island of St. Croix (Fisher et al.
2008). For this study, each disturbance area had numerous sources of human disturbance such as
high-traffic shipping, intense near-coastal urban development, sewage treatment and
commercial/industrial activities. Surveys of stony coral condition and extent showed increased
impairment associated with greater levels of anthropogenic disturbance, diminishing with greater
distance from the disturbance, thus establishing a key relationship between anthropogenic stress
and the condition of reef-building corals and indirectly, the condition of reef-dependent fauna.
This study established responsiveness of stony coral indicators (Fisher et al. 2007) to human
disturbance, consistent with other research in the Caribbean and around the world relating reef
condition to environmental gradients (Smith et al. 2008; Jupiter et al. 2008; Golbuu et al. 2008;
Maina et al. 2011). A clear and intuitive connection between distance from robust centers of
multiple disturbances and coral condition was demonstrated that laid the groundwork for further
research on specific stressors.
Subsequent efforts applied a Landscape Development Intensity (LD1) index which demonstrated
a link between land-based human activity and coral reefs in USVI (Oliver et al. 201 1; Oliver et
al. 2018). The LDI is an integrated measure of the intensity of human activities in a landscape or
watershed, estimated by calculating the input of nonrenewable energy to different land use
parcels. To calculate the LDI index, land use / land cover (LULC) raster data available from the
National Land Cover Dataset (Homer et al. 2015) is reclassified from LULC categories to
corresponding LDI coefficients (Brown and Vivas 2005). Coefficients represent energy inputs
associated with activities specific to land uses, for e.g. agricultural lands cultivated for row crops
are usually tilled, treated with fertilizer and pesticides, and harvested using petroleum-fueled
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tractors, hydraulic sprayers, or airplanes. These energy inputs are reflected in a higher LDI
coefficient than that for lands cultivated for pasture/hay crops, which typically require less
mechanized vehicles and reduced energy inputs. The premise that ecological communities are
affected by cumulative human impacts in the surrounding watershed as quantified by the LDI
index was shown for wetlands (Brown and Vivas 2005). The LDI index was demonstrated to be
an effective landscape indicator of human impact for St. Croix and St. Thomas corals and was
included in a multi-stressor conceptual model developed for Puerto Rico (Figure la).
The LDI index incorporates numerous human impacts that are negatively associated with coral
reef condition including land conversion for industry, urban development and agriculture. These
activities tend to increase sediment, nutrient and chemical pollution reaching coral reefs.
Potential application of the LDI in a regulatory context supported by a BCG framework could
involve setting LDI threshold values commensurate with sustainable reef condition for coastal
watersheds, and if biological condition of coral reefs falls below target levels, land use change
analysis could be conducted to determine possible origins of stressors to corals (EPA 2016, Ch
5). Analysis of land use / land cover data layers periodically released on a national scale (Homer
et al. 2015) can reveal changes in land use that result in higher LDI index. Potential impacts to
coastal resources from intensification of human impact or from proposed mitigation efforts can
be modeled by reclassifying land use data to hypothetical scenarios and examining
corresponding LDI index values. The LDI index can be calculated for different sized basins to
suit the spatial distribution of coral reefs or other coastal resources of concern, and / or adapted
for application to land areas of special concern where near-coastal development threatens
valuable coastal resources. A limitation of LDI in its integrative nature is that specific stressors
are not obvious without some understanding of the technical details behind the index. If
incorporated in communications such as stakeholder engagement in developing coral reef
management approaches, some care towards explaining the LDI or any multi-stressor index
should be taken.
Sedimentation is an important stressor on coral reef ecosystems and was included in narrative
rule development for the coral reef BCG (Bradley et al. 2014). Near-coastal coral reefs evolved
in shallow water where sediment naturally enters the ocean and have mechanisms such as mucus
production that vary by species (see Appendix M) that can clear sediment to some extent.
Sediment can smother corals, inhibit photosynthesis by reducing available light, limit growth
rates and disrupt interactions with reef-dependent fish through loss of structural habitat (see
Appendix Q for examples of sediment effects on corals and fish).
Deleterious impacts to coral ecosystems from sediment exposure often stem from increased
sediment loading to coastal environments from land clearing for development and loss of
riparian vegetation that slows the pace of runoff. Sediment resuspension also contributes to
increased exposure and is exacerbated by human activity in coastal ports where high traffic from
cruise ships, industrial shipping and recreational boating can result in repeat exposure to
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sediment present in shallow coral habitats (Kisabeth et al. 2014). A benthic sediment threat
(BST) model developed by WRI and NOAA's (2006) "Summit to Sea" analysis was applied in
an EPA reef survey conducted in 2010 on Puerto Rico's south shore. The BST was derived from
estimated sediment production on land using soil type and relative erodibility, precipitation data
and slope, coupled with an inverse distance weighting function to simulate sediment threat to
coastal habitats expected to disseminate further from shore without accounting for current or
wind effects. The Shannon-Weiner diversity index for stony coral communities at 76 sites was
inversely correlated with BST (Oliver LM, unpublished data) and principal components analysis
suggested inverse relationships between BST and stony coral indicators (Oliver et al. 2013). The
BST was included in multivariate analysis of fish BCG metrics and results suggested that
increased BST was associated with reduced BCG level, supporting application of this type of
sediment model in a BCG context (Bradley et al. 2020).
Elevated levels of nutrients including nitrogen and phosphorus from both non-point and point
sources are established reef stressors (Fabricius 2005) that should be incorporated as a
comprehensive GSA is built. These dissolved contaminants are highly variable and
characterizing relevant exposure requires sufficient temporal sampling to capture long-term
trends and at a spatial scale relevant to reef management decisions. The Australian government's
approach to integrated management of the Great Barrier Reef provides such an example in the
Marine Monitoring Program for Inshore Water Quality which monitors total suspended solids,
chlorophyll a, phosphorus, nitrogen and pesticides on a regular basis and during high-flow
events. Calculations of stressor contributions from catchment runoff and river transport are
components of the coral reef adaptive management plan.
Water quality monitoring under the U.S. Clean Water Act provides limited data to inform a
GSA. For example, in 2018, 104 Puerto Rico coastal sites were sampled under auspices of the
Clean Water Act for potential exceedances of chemical and nutrient criteria linked to designated
uses in waterbodies. Monitoring of waterbodies for potential impairments under the CWA is
done every other year, a periodicity too infrequent to inform a reef BCG stressor gradient, and
site locations are not related to reef locations. Even a robust water quality monitoring program
cannot protect coral reefs without species specific dose-response relationships to facilitate
chemical or nutrient criteria setting to ensure sustainability of reefs and ecosystem services they
provide to humans.
Improving estimates of the influence of land-based stressors on coral reefs requires better
understanding of transport mechanisms that deliver sediment, nutrient and chemical pollution to
reef habitats. Relationships described here between high-LDI watersheds and reefs adjacent to
those watersheds employed simple assumptions such as reefs located adjacent to a watershed are
affected by that watershed, large-scale ocean currents should be incorporated when possible, and
effects are generally dissipated with greater distance from shore (Oliver et al. 2011, 2018). In
contrast with stream ecosystems where the BCG has been successfully applied (Hausmann et al.
2016; Gerritsen et al. 2017), quantifying a generalized stressor axis for coastal ecosystems that
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accounts for all relevant stressors presents numerous challenges. Stream ecosystems have one-
directional transport of pollutants with consistent downstream dilution, an assumption that does
not apply to coastal systems. Upon entering the coastal environment, nonpoint runoff and river
borne contaminants generally dissipate with increasing distance from shore-based sources, but
quantifying stressor delivery to reefs requires an understanding of hydrological influences, runoff
dynamics, variable ocean currents, bathymetry, and wind. Accounting for near-shore ocean
current patterns, wind, and bathymetry is needed to enhance understanding of the fate and
transport of pollutants in the near-coastal environment. For Caribbean reefs, the finest-scale
ocean current data is available via high-frequency radar for Puerto Rico's west coast. An array of
ocean current- and wind-sensing buoys provides general current patterns around the island,
operated by the Caribbean Coastal Ocean Observing System (CARICOOS), a regional
component of the U.S. Ocean Observing System. This system is undergoing improvements that
may be applicable to pollutant transport modeling, such as recent improvements that build from
the CARICOOS system to forecast a 3-day timespan of ocean currents, water levels, temperature
and salinity (Solano et al. 2018). Expanding high-frequency radar and/or buoy networks to cover
near-coastal areas in all Caribbean islands would be helpful in predicting impacts of land-based
stressors on coral reefs at a scale that is compatible with reef distribution around these islands.
Numerous approaches are available that could apply as the GSA axis for Caribbean corals is
developed. Sediment and nutrient discharge from Puerto Rico rivers were analyzed by Warne et
al. (2005) using stream gage and water quality data in an island-wide characterization of runoff
and stressor delivery. Distinct regions of Puerto Rico were described that highlight the
importance of rainfall and watershed characteristics such as topography in determining sediment
delivery. Remote sensing and aerial imagery may be integrated with water quality analysis to
estimate catchment production of land-based stressors such as sediment, transported to Great
Barrier Reef coral habitats via river plumes (Devlin and Schaffelke 2009). Watershed modeling
of sediment yield using the Soil and Water Assessment Tool (SWAT) for the Rio Grande de
Anasco in west Puerto Rico was coupled with remote sensing and aerial photography to better
understand the extent and transport of sediment plumes in this area (Ramos-Scharron and Gilbes
2014). Tools such as remote sensing will continue to improve as will methods to map the extent
and health of reef systems.
Larger-scale sediment plume modeling to predict potential delivery to Indonesian reefs offers an
approach to coupling watershed sediment production with an ocean transport model that
accounts for current dynamics and particle settling (Rude et al. 2015). Watershed sediment
production was coupled with an ocean transport model that included a sediment settling
component, and due to the large scale of interest, ocean current data from globally available
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HYCOM (Global Hybrid Coordinate Ocean Model) data at approximately 8.3 km resolution
could be applied.
Models such as the BST could be improved by validating with field data to develop realistic
functions for offshore sediment transport. Sediment cores collected on the south coast of Puerto
Rico were evaluated using radionuclide and percent carbonate analysis to estimate trends in
sediment accumulation and extent of offshore transport of terrigenous sediment (Ryan et al.
2008). Cores represent years of sediment deposition and provide a useful historical surrogate.
Sediment trap studies also provide an indication of shore to shelf sediment transport (Hernandez
et al 2009) and illustrate the importance of sediment resuspension as a stressor to corals. These
examples focused on reef areas off the coast of La Parguera and could contribute to developing
sediment decay functions for analogous areas, where there are no major rivers and rainfall is
generally low.
Fishing Pressure.
Over-fishing has dramatically altered the composition of biological communities on Caribbean
coral reefs and seagrass beds. Large herbivores and carnivores such as turtles, groupers and
sharks that were historically abundant are now ecologically extinct (i.e., populations are so
greatly reduced relative to past levels that they no longer fulfill former ecological/functional
role). The reduction of these species has resulted in "trophic level dysfunction" (Steneck et al.
2004), with food chains now dominated by small fishes and invertebrates (Hay 1984, 1991;
Knowlton et al. 1990; Jackson 1997).
In addition to direct effects on fish populations and trophic stability, fishing pressure indirectly
disrupts coral reef ecosystems through reduced herbivory which exacerbates other impacts on the
health and ecological fitness of stony corals.
For Caribbean fisheries, spatial data that encompasses all types of fishing pressure is needed for
optimal development of a BCG-based regulatory framework. For example, in his PhD thesis,
Ruiz Valentin (2013) evaluated fishing pressure on the island of Puerto Rico based on i) total
commercial fishery landings, ii) commercial fishing effort, iii) number of traps per fishing zone,
and iv) recreational fishing, using the geographic location of marinas and boat ramp densities per
square kilometer. Shivlani and Koeneke (2011) estimated commercial Puerto Rico fishing effort
based on interviews with fishers (Figure lc). Participants were asked to map fishing areas they
used and the number of trips to each. Along with commercial fishing, recreational fishing data
(Lopez-Perez et al. 2013) must be incorporated towards a complete accounting of fishing
pressure on reef ecosystems, as summarized in a historical context for Puerto Rico by
Appeldoorn et al. (2015).
Global climate change (GCC) Associated Thermal Anomalies.
Hermatypic corals form the essential structure of reef ecosystems in warm, shallow, oligotrophic
waters and have evolved with low natural variability in physical parameters such as temperature,
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pH, alkalinity and calcium carbonate saturation state (Hoegh-Guldberg et al. 2007; Eakin et al.
2009). Growth of coral reefs depends upon the balance between symbiotic algae or
"zooxanthellae" of genus Symbiodinium and coral tissues they inhabit, a relationship that is
disrupted by minor deviations in temperature from geographically specific tolerance ranges
(Coles et al. 1976). Coral "bleaching" or zooxanthellae loss occurs when the thermal tolerance
limit of corals and their symbiotic algae is exceeded (Hoegh-Guldberg 1999). In addition to
temperature, ocean acidification shifts equilibrium of the calcification process and affects corals'
ability to build calcium carbonate skeletons (Kleypas et al. 2006).
Global-scale changes in climate that are associated with coral bleaching are not within the
regulatory scope of Caribbean jurisdictions but their inclusion in a coral GSA is critical to
capture all relevant stressors. Temperature stress may act synergistically with human impacts
(Hoegh-Guldberg et al. 2007) that can be regulated by reducing coral resilience. Understanding
thermal conditions at scales compatible with regulatory goals is an important component in
decisions related to fishing regulations, near-coastal development and runoff control. Thermal
history is among the most important factors influencing coral reef resilience and NOAA's Coral
Reef Watch Program (CRW) uses satellite data to provide current and past reef environmental
conditions to identify areas at risk for coral bleaching (Eakin et al. 2009, 2010; Muniz-Castillo et
al. 2019). Several thermal history metrics have been developed on a global scale that effectively
predict likelihood of bleaching in real time, including degree heating weeks (DHW) which
indicates the number of weeks that average ocean temperatures have been exceeded. Of
particular interest for the coral reef BCG-GSA are experimental products that CRW has
developed with support from the NOAA Coral Reef Conservation Program - thermal history
metrics including SSTA for coral reef management at higher resolution (Muniz-Castillo et al.
2019). SSTA represents positive or negative deviations from average monthly climatology,
which is based on historical records of mean monthly night-time SST values (Liu 2014). Sea
surface temperature anomalies (SSTA) are shown in Figure lb as average from 2014-2016 at 5-
km resolution for Puerto Rico.
Several issues require additional research to develop a GSA that incorporates synergistic effects
of thermal stress with other stressors. For example, the frequency and duration of thermal
anomalies associated with impaired coral resilience, and how these interact with land-based
pollution from precipitation-related, pulsed events needs to be better understood. Species-
specific responses to thermal stress must be incorporated (see Appendix M). Further
development of CRW thermal history data products will provide information on frequency of
events and historic patterns that can be analyzed with other stressors and related to reef condition
(Hughes and Connell 1999). Incorporating the long recovery times of coral reefs and the overall
ability of the system to recover (resilience) must also be considered.
The Stress Axis.
The x-axis of the BCG framework, the Generalized Stress Axis or GSA, conceptually describes
the range of anthropogenic stress that may adversely affect aquatic biota in a particular area. It is
a theoretical construct that seeks to represent the cumulative stress that may influence biological
condition. A spatially explicit approach to stressor integration including land-based pollution,
thermal anomalies, and fishing pressure was developed for Puerto Rico (Figure Id). Land-based
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pollution was represented by the LDI, calculated for HUC12 watersheds to capture variation in
the intensity of human activity on a scale proportional to coastal reefs (Figure 2). The LDI was
mapped with a hypothetical maximum offshore buffer distance of 10 km and an assumption of
diminished effects further from shore including a 50% reduction from 2-7 km offshore, and a
70% reduction from 7-10 km offshore. Thermal anomaly data as the SSTA from NOAA's Coral
Reef Watch Program (CRW) represented deviations from average climatology for 2014 - 2016
and has the smallest resolution of thermal history data products of 5 km. Commercial fishing
intensity data at a resolution of 3.3 km was provided by Manoj Shivlani, derived from
engagement with fishers who were asked to estimate a maximum number of trips to each grid
cell employing gear types nets, lines, traps and dive gears (spear guns and hand gathering).
Mapping multiple stressors for Puerto Rico coral reefs underscored data needs described above
for each stressor and demonstrated technical aspects of combining data types into an integrated
index. For example, although the LDI is shown with an island-wide influence buffer that
indicates reduced impact of land-based stressors further from shore, these distances are only
hypothetical and do not incorporate ocean currents, wind or bathymetry (Figure la). NOAA sea
surface temperature anomaly (SSTA) data as shown in Figure lb included all deviations from
average whether high or low and might be tailored for specific exposure periods such as summer
months when positive SSTA values are often associated with coral bleaching on larger scales.
Commercial fishing data was spatially analyzed from direct recounts of fishers (Figure lc), but
ideally recreational fishing would be represented as well as more recent commercial fishing data.
By re-scaling these stressor estimates as 0-3 and adding them, the resulting integrated stressor
map (Figure Id) illustrates where some Puerto Rico reefs could experience stress from one of
these 3 stressors but not from all. Coral reefs off Puerto Rico's south shore for 2014-2016
experienced relatively less thermal stress compared to the north but are adjacent to intense land
development and/or fishing. The ability to examine single stressors that comprise a
comprehensive GSA as well as the cumulative stressor gradient support a regulatory approach
that can compare scenarios on a local scale such as infrastructure investments to control runoff in
a context that includes other factors where such projects are most likely to achieve goals.
Integrating stressors should incorporate the best available understanding of interactions whether
additive, synergistic or antagonistic into weighting factors for each.
Typically, states have defined a stress gradient using single stressors or a combination of known,
measurable stress gradients that in reality represent a portion of the stressors impacting a water
body. The conceptual GSA provides a framework to assist in developing the most
comprehensive stress gradient as possible to relate diminished levels of biological condition to
increased stressors. A well-defined, quantitative GSA and the underlying data used to develop it
may serve as a nexus between biological and causal assessments, thereby linking management
goals and selection of management actions for protection or restoration. Systematic testing of
technical approaches to define and apply a GSA to BCG development has not been conducted.
Opportunities in the future may include piloting methods for application of national, regional, or
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basin-scale databases and methods to support efforts to quantify a GSA for a specific geographic
region and water body type.
Here, the BCG is applied to coral reef ecosystems of Caribbean territorial islands. This serves as
an exemplar to apply the approach to other coastal and marine resources that are at risk from a
multitude of stressors. Seagrass and mangrove habitats occur in shallow waters close to the
coastline, where risk of exposure from anthropogenic activities on land are highest (Figure 2).
Decision-makers and stakeholders of any jurisdiction can come together and define relationships
between gradients of biotic condition and gradients of anthropogenic stress that incorporate their
best collective knowledge and strive to meet common conservation goals. Once strata of
biological condition and relative stressor impacts are established, the BCG provides a flexible
framework for continual improvement to solidify causal relationships and incorporate the best
available data for stressors and resource condition as it becomes available. Jurisdictions can set
resource management goals tied to BCG biological condition linked to their needs that account
for societal, economic and ecosystem service values in currencies. The BCG framework is a
systematic, effective process that facilitates multiple stakeholder involvement and is transferrable
to coastal and marine resources that must be protected to preserve ecological integrity and
sustainable provision of ecosystem services.
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Figure SI. (from Oliver etal. 2016) a. Hvdrologic Unit Code (HUC12) watersheds of Puerto Rico and associated
LDI values. Offshore buffer zones show attenuated LDI value with increased distance from shore, b. NOAA Sea
Surface Temperature Anomaly (SSTA), mean of monthly composites from 2014-2016. c. Total fishing effort modeled
as maximum possible trips to each grid cell (Shivlani and Koeneke 2011). d. Integrated stressor index was
calculated by re-scaling all three stressors (0-1) and summing for a maximum possible value of 3.
Commercial Fishing Effort
MS- 1000
tm 1001 - 2500
~ 2501 - 3000
H 5001 - 10000
M 10001 - 13876
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Figure S2. Hydrologic Unit Code (HUC12) watersheds of SE Puerto Rico and associated LDI values, and coastal
habitats from Kendall et al. 2001. Coastal cities of SE Puerto Rico shown for reference.
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Appendix T - Investigating BCG Attribute VII for Evaluating Stony Coral
Condition and Disease Impacts.
Final Report, U.S. Geological Survey Interagency Agreement DW-14-92426101
Note: This is a Restricted-File Interagency Report (RFFIR). The text cannot be modified. The
authors welcome discussion - please submit any discussion comments in an email, citing the line
number that you are commenting upon.
Task: Development of Tools to Assess the Biological Condition in Streams,
Rivers, Wetlands, Estuarine, and Near Coastal Aquatic Systems
Subtask: Biological Criteria Program—Development of Biological
Condition Gradient (BCG) for Coral Reef Ecosystems
Final Report 2020
Caroline S Rogers, PhD., U.S. Geological Survey, Wetland and Aquatic Research Center, St.
John, U.S. Virgin Islands, Caroline rogers@usgs.gov
Deborah L. Santavy, PhD., U.S. Environmental Protection Agency (US EPA), Office of
Research and Development (ORD), Center for Environmental Measurement and Modeling
(CEMM), Gulf Ecosystem Measurement and Modeling Division (GEMMD), Gulf Breeze,
Florida 32561, santavy.debbie@epa.gov
Christina Horstmann, MS, ORISE Participant, Oak Ridge Institute for Science
Education Participant, US EPA, ORD, CEMM, GEMMD, Gulf Breeze, Florida
32561, horstmann.christina@epa.gov
"Any use of trade, firm, or product names is for descriptive purposes only and does not imply
endorsement by the U.S. Government."
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Executive Summary
The Biological Condition Gradient (BCG) model can be used to provide a foundation for managers to
make informed decisions in cases involving coral reefs. Coral reefs are often referred to as "the rain
forests of the sea." Although this is usually in reference to the high diversity that characterizes both
of these ecosystems, the comparison is particularly appropriate because it is the corals and the trees
that create the ecosystems, and the condition of these organisms (along with the actual species
characteristics) will drive the ecosystem services that the forests and reefs provide. In this sense, the
reefs are more similar to this structurally complex terrestrial ecosystem than to the freshwater
systems, including rivers, streams, and lakes, to which the BCG framework model previously has
been applied.
Coral reef managers look to scientists to provide a foundation for making informed decisions when
assigning value to different coral reef systems. The critical information is the species composition,
the particular species that are present (for example, major framework-building species versus
"weedy" species with smaller, more fragile colonies), the abundance (numbers of individuals or
"cover"), and the condition (intact, diseased, bleached, or overgrown by algae). Beyond the data that
can be obtained from standard monitoring, the net calcification of a reef area would be valuable to
know—that is, is the reef accreting or eroding?
The susceptibilities/tolerances of coral species to different anthropogenic stressors cannot be
determined in a rigorous way because the scientific knowledge is still very limited. Coral species
cannot be rigorously assigned to different attributes (I-V) that will be accurate over all stressors or
even just to sedimentation/turbidity stress.
This discussion focuses on sedimentation and, to a lesser degree, warming seawater temperatures
(thermal stress). Numerous other factors can adversely affect corals and other reef organisms.
Examples include those factors that humans can control, such as vessel groundings and use of
destructive fishing gear, and other factors out of human control, such as physical damage from
storms.
Diseases are sometimes, but not always, associated with elevated temperatures and thermal stress;
some research suggests links with pollution and degraded water quality, but more research is needed.
More declines in living coral have been associated with diseases than any other factor.
Organism (coral) condition, the subject of this report, is particularly important in the context of coral
reefs because framework-building corals are colonial, modular organisms that create the physical
architecture of the reef and can persist for decades in spite of partial mortality. The species present
(with the exception of Acroporapalmata and Orbicella species [spp.]) are of less importance in
general than the condition of the colonies and their responses as documented by long-term
monitoring, when feasible.
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"A Practitioner's Guide to the Biological Condition Gradient" (U.S. Environmental Protection
Agency, 2016) focused on freshwater systems, and the six levels described do not include any
mention of diseases or any other organism condition before level 5.
We recommend that organism condition be specifically mentioned in all levels of the BCG for coral
reefs with reference to prevalence of tissue loss diseases. The ongoing devastation from stony coral
tissue loss disease (initially in Florida and now in Puerto Rico and the U.S. Virgin Islands, as well as
elsewhere in the Caribbean) is of paramount concern.
Benthic experts did not link disease prevalence explicitly to the six BCG levels. We propose the
following for consideration and further discussion: level 1 (0-1 percent); level 2 (greater than [>] 1-
5 percent); level 3 (>5-10 percent); level 4 (>10-20 percent); level 5 (>20-30 percent); and level 6
(>30 percent).
The presence and condition of Acroporapalmata and Orbicella spp can provide a better basis for
evaluating the overall condition of a reef area in the study locations used for this exercise than the
status of other coral species. The presence of "standing dead" Acropora palmata provides insights
into the "ecological history" of a reef site. (Occurrence is confined typically to depths less than 10
meters because this species does not usually occur in greater depths.) The number of coral species
(diversity, richness) is informative but not defining.
For this discussion, the focus has been on fore reef zones in Puerto Rico < 20 m deep for which U.S.
EPA monitoring data for 2010 and 2011 were available.
Although we acknowledge their obvious importance when evaluating overall reef condition,
physiological changes to coral hosts or microbiota (with the exception of bleaching) are not
addressed at length in this report, which focuses on visible changes in structure.
The application of the BCG model to coral reefs differs from that in freshwater systems. For
example, the relative abundance of different coral species, including the major framework builders, is
more indicative than the presence/absence of species with different tolerances/rarity/sensitivities that
are considered indicators of the various BCG levels in freshwater systems.
To be useful, the BCG approach should allow managers to evaluate, rank, and (or) compare
different reef areas that are or were subject to various stressors. The evaluation of a site could differ
greatly depending on whether or not it was based on a single survey (a "snapshot") or on successive
surveys of randomly selected permanent sampling units (transects) in a long-term monitoring
program (Rogers and Miller, 2016).
Intr
The U.S. Environmental Protection Agency (U.S. EPA) has successfully used the Biological
Condition Gradient model (BCG) to assess the biotic condition of freshwater streams, lakes, and
wadeable river ecosystems (EPA 2016). Inherent in the BCG approach is the concept of a gradient
of biological responses to the cumulative effects of multiple anthropogenic stressors (fig. 1). Our
objective is to evaluate the feasibility of using this approach to characterize the biological condition
of Caribbean coral reefs in a consistent way that aids managers in making informed environmental
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decisions. With this goal in mind, several workshops and webinars were conducted by the EPA
with a group of scientists considered experts in this field (referred to as "experts" hereafter)
(Bradley et. al. 2014b).
Figure 1. Conceptual model of the Biological Condition Gradient. The relation between stressors and their cumulative
effects on the biota is likely nonlinear.
The BCG framework illustrates biological condition as observable or measurable changes in an
ecosystem in response to anthropogenic stress. The BCG describes a gradient of six biological
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condition levels, ranging from undisturbed or natural (BCG level 1) to highly disturbed or degraded
conditions (BCG level 6) (fig. 1). Changes are described by departures from natural or undisturbed
condition using observable biological and ecological attributes and metrics. The biological
condition or BCG condition level is developed using metrics for each of six BCG condition levels
(1-6) using the generic descriptions defined in table 1.
Natural structure & function of biotic community maintained
Minimal changes in structure & function
Evident changes in structure and
minimal changes in function
Moderate changes in structure &
minimal changes in function
Major changes in structure
moderate changes in function
Severe changes in structure & function
Low
Level of Stressors
High
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Table 1: General descriptions of the Biological Condition Gradient levels (modified from Davies and Jackson, 2006), used as guidelines by expert panel to describe
narrative condition levels for coral reefs referred to BCG levels 1-6.
BCG
level
General changes
Descriptions
Level 1
Natural or native condition
Native structural, functional, and taxonomic integrity is preserved; ecosystem function is preserved
within the range of natural variability. BCG Level 1 represents biological conditions as they existed (or
still exist) in the absence of measurable effects of stressors, and it provides the basis for comparison to
the next five levels.
Level 2
Minimal changes in structure of the biotic
community and minimal changes in
ecosystem function
Virtually all native taxa are maintained with some changes in biomass and/or abundance; ecosystem
functions are fully maintained within the range of natural variability. Level 2 represents the earliest
changes in densities, species composition, and biomass that occur during a slight increase in stressors
(such as increased temperature regime or nutrient enrichment).
Level 3
Evident changes in structure of the biotic
community and minimal changes in
ecosystem function
Evident changes in structure of the biotic community and minimal changes in ecosystem function—
Some changes in structure due to loss of some rare native taxa; shifts in relative abundance of taxa, but
intermediate sensitive taxa are common and abundant; ecosystem functions are fully maintained
through redundant attributes of the system. Level 3 represents readily observable changes that, can
occur in response to organic enrichment or increased temperature.
Level 4
Moderate changes in structure of the
biotic community with minimal changes
in ecosystem function
Moderate changes in structure because of replacement of some sensitive-ubiquitous taxa by more
tolerant taxa but reproducing populations of some sensitive taxa are maintained; overall balanced
distribution of all expected major groups; ecosystem functions largely maintained through redundant
attributes.
Level 5
Major changes in structure of the biotic
community and moderate changes in
ecosystem function
Sensitive taxa are markedly diminished; conspicuously unbalanced distribution of major groups from
distributions expected; organism condition shows signs of physiological stress; ecosystem function
shows reduced complexity and redundancy. Increased buildup or export of unused materials. Changes
in ecosystem function (as indicated by marked changes in food web structure and guilds) are critical in
distinguishing between Levels 4 and 5.
Level 6
Severe changes in structure of the biotic
community and major loss of ecosystem
function
Extreme changes in structure; wholesale changes in taxonomic composition; extreme alterations from
normal densities and distributions; organism condition is often poor; ecosystem functions are severely
altered. Level 6 systems are taxonomically depauperate (low diversity or reduced number of
organisms) compared to the other levels.
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The characteristics used to define each BCG level are referred to as BCG attributes (I-X), and they
were selected to measure biological condition as recommended by an expert panel of scientists. The
generalized descriptions of 10 attributes defined and used for freshwater systems are in table 2. In
stream and river biological assessments, most surveys are conducted at the spatial scale of a site or
reach, and temporal scales can range from a season to a single sampling event. Many of the
freshwater BCG attributes span these spatial and temporal scales. Spatial scale attributes at a site
include measures or indicators of stressor sensitivities of various taxonomic compositions and
community structures (BCG attributes I-V), non-native species (BCG attribute VI), organism
condition (BCG attribute VII), and organism and system performance (BCG attribute VIII). At
larger temporal and spatial scales, physical-biotic interactions (attributes IX and X) are also
included because of their importance for evaluating longer-term impacts, determining restoration
potential, and tracking recovery in specific water bodies (EPA 2016).
The objectives for this subtask are to define, develop, and apply BCG attribute VII (organism
condition) to coral reef ecosystems, targeting scleractinian corals. This attribute considers the
condition of corals at the colony, population (single species), and community (all coral species)
levels. This report presents recommended characteristics for assessing coral condition exposed to
human disturbances, including changing climate.
Modifi ¦ i< 11 i ¦ if > . i iifiwr-i i -||'|>ii<. ", ii 1 > i i x I
In attempts to apply the BCG framework to benthic organisms on coral reefs, it became clear that
BCG attributes I-V, as defined for freshwater streams and wadeable rivers, required significant
modification. The freshwater BCG attributes are based on community structure and
compositional complexity which typically include measures of the number, type, and proportion
of individual taxa within an assemblage (for example, benthic macroinvertebrates, algae, fish,
and so forth) to characterize the biological sensitivity to cumulative effects of multiple stressors.
BCG attributes I-V consider which taxa are highly, intermediately, or minimally sensitive to
anthropogenic stressors, focusing on the presence or absence (and in some cases the relative
abundance) of taxa.
Coral reef experts concluded that many benthic, sessile marine invertebrates on coral reefs are
modular organisms and must be considered differently than solitary (individual) organisms1 that
are more highly organized and mobile, such as insect larvae and macroinvertebrates residing in
freshwater systems (Santavy et. al. 2016). Responses of coral populations and communities to
increasing stress do not appear to be incremental or to follow a predictable sequence of changes
reflected by species turnover and replacement as documented in freshwater stream benthic fauna.
With increasing anthropogenic disturbance, coral species are unlikely to be replaced by other
coral species with the same functional roles but different stressor tolerances. In higher quality
freshwater systems, sensitive taxa and their larvae persist, but they are replaced in lower quality
streams by more tolerant taxa or those with more "adaptable" life strategies. In contrast, a coral
1A solitary organism lives independently and has all of the functions needed to survive and reproduce (Jackson, 1977).
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colony subjected to a stressor often loses only some of its tissue, resulting only in partial colony
mortality (fig. 2).
The tolerance levels and responses of many coral species to exposures to individual and
cumulative stressors are largely unknown, as are the life history characteristics for many. As a
result, the coral reef experts were reluctant to assign all scleractinian species to a BCG attribute
level ranging from I-V reflecting different sensitivities to stressors such as increasing
temperature and sedimentation. Consequently, the experts included many aspects of coral colony
condition (currently undefined in BCG attribute VII for coral reefs) when developing narrative
BCG condition levels (1-6) for which more data are available. There is a need to formally
consider and recommend descriptions, metrics, and indicators to incorporate into a coral reef
BCG. The generalized descriptions for BCG attributes pertaining to organism condition are as
follows: VII—"anomalies of the organisms; indicators of individual health (for example,
deformities, lesions, tumors); and VIII—"processes performed by ecosystems, including primary
and secondary production; respiration; nutrient cycling; decomposition; their
proportion/dominance; and what components of the system carry the dominant functions, for
example, shift of lakes and estuaries to phytoplankton production and microbial decomposition
under disturbance and eutrophication" (table 2; Davies and Jackson, 2006).
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Table 2. Biological and other ecological attributes used to characterize the freshwater streams
Biological Condition Gradient (BCG) (Modified from Davies and Jackson, 2006).
Attribute
Description
1. Historically documented,
sensitive, long-lived, or
regionally endemic taxa
Taxa known to have been supported according to historical, museum or archeological
records, or taxa with restricted distribution (occurring only in a locale as opposed to a
region), often due to unique life history requirements (e.g., Sturgeon, American Eel,
Pupfish, Unionid mussel species).
II. Highly sensitive (typically
uncommon) taxa
Taxa that are highly sensitive to pollution or anthropogenic disturbance. Tend to occur
in low numbers, and many taxa are specialists for habitats and food type. These are
the first to disappear with disturbance or pollution (e.g., most stoneflies, Brook Trout
[in the east], Brook Lamprey).
III. Intermediate sensitive
and common taxa
Common taxa that are ubiquitous and abundant in relatively undisturbed conditions
but are sensitive to anthropogenic disturbance/pollution. They have a broader range
of tolerance than Attribute II taxa and can be found at reduced density and richness in
moderately disturbed stations (e.g., many mayflies, many Darter fish species).
IV. Taxa of intermediate
tolerance
Ubiquitous and common taxa that can be found under almost any conditions, from
undisturbed to highly stressed stations. They are broadly tolerant but often decline
under extreme conditions (e.g., filter-feeding caddisflies, many midges, many Minnow
species).
V. Highly tolerant taxa
Taxa that typically are uncommon and of low abundance in undisturbed conditions but
that increase in abundance in disturbed stations. Opportunistic species able to exploit
resources in disturbed stations. These are the last survivors (e.g., tubificid worms,
Black Bullhead).
VI. Non-native or
intentionally introduced
species
Any species not native to the ecosystem (e.g., Asiatic clam, zebra mussel, Carp,
European Brown Trout). Additionally, there are many fish native to one part of North
America that have been introduced elsewhere.
VII. Organism condition
Anomalies of the organisms; indicators of individual health (e.g., deformities, lesions,
tumors).
VIII. Ecosystem function
Processes performed by ecosystems, including primary and secondary production;
respiration; nutrient cycling; decomposition; their proportion/dominance; and what
components of the system carry the dominant functions (for example, shift of lakes
and estuaries to phytoplankton production and microbial decomposition under
disturbance and eutrophication).
IX. Spatial and temporal
extent of detrimental
effects
The spatial and temporal extent of cumulative adverse effects of stressors (for
example, groundwater pumping in Kansas resulting in change offish composition from
fluvial dependent to sunfish).
X. Ecosystem connectivity
Access or linkage (in space/time) to materials, locations, and conditions required for
maintenance of interacting populations of aquatic life; the opposite of fragmentation.
For example, levees restrict connections between flowing water and floodplain
nutrient sinks (disrupt function); dams impede fish migration, spawning.
BCG Attributes
Two of the BCG attributes are relevant to this task. They are described below verbatim as presented
in "A Practitioner's Guide to the Biological Condition Gradient: A Framework to Describe
Incremental Change in Aquatic Ecosystems" (EPA 2016). Although this task focuses primarily on
BCG attribute VII, that attribute cannot be considered in complete isolation from BCG attribute
VIII, as they are now described.
Attribute VII: Organism Condition
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Organism condition is an element of ecosystem function, expressed at the level of anatomical or
physiological characteristics of individual organisms. Organism condition includes direct and
indirect indicators such as fecundity, morbidity, mortality, growth rates, and anomalies (for
example, lesions, tumors, and deformities). Some of these indicators are readily observed in the
field and laboratory, whereas the assessment of others requires specialized expertise and much
greater effort.
Organism condition can also change with season or life stage or occur as short-term events making
assessment difficult. The most common approach for State programs is to forego complex and
demanding direct measures of organism condition (for example, fecundity, morbidity, mortality,
disease, growth rates) in favor of indirect or surrogate measures (for example, percent of organisms
with anomalies, age or size class distributions) (Simon, 2003). Organism anomalies in the BCG vary
from naturally occurring incidence in levels 1 and 2 to higher than expected incidence in levels 3
and 4. In levels 5 and 6, biomass is reduced, the age structure of populations indicates premature
mortality or unsuccessful reproduction, and the incidence of serious anomalies is high. This attribute
has been successfully used in stream indices based on the fish assemblage (Yoder and Rankin, 1995;
Sanders et. al. 1999).
unl ,i i I Dsy i ii
Ecosystem function refers to any processes required for the performance of a biological system
expected under naturally occurring conditions. Naturally occurring conditions have been interpreted
typically as those conditions found in undisturbed to minimally disturbed sites, but some processes
can be sustained under moderate levels of disturbance. Examples of ecosystem functional processes
are primary and secondary production, respiration, nutrient cycling, and decomposition. Assessing
ecosystem function includes consideration of the aggregate performance of dynamic interactions
within an ecosystem, such as the interactions among taxa (e.g., food web dynamics) and energy and
nutrient processing rates (e.g., energy and nutrient dynamics) (Cairns, 1977).
Additionally, ecosystem function includes aspects of all levels of biological organization
(individual, population, and community condition). Altered interactions between individual
organisms and their abiotic and biotic environments might generate changes in growth rates,
reproductive success, movement, or mortality. These altered interactions are ultimately
expressed at ecosystem levels of organization (for example, shifts from heterotrophy to
autotrophy, onset of eutrophic conditions) and as changes in ecosystem process rates (for
example, photosynthesis, respiration, production, decomposition).
At this time, the level of effort required to directly assess ecosystem function is beyond the
means of many State monitoring programs. Instead, in streams and wadeable rivers, most
programs rely on taxonomic and structural indicators to make inferences about functional status
(Karr et. al. 1986). For example, shifts in the primary source of food might cause changes in
trophic guild indices or indicator species. Although direct measures of ecosystem function are
currently difficult or time consuming, they might become practical in the future (Gessner and
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Chauvet, 2002). The BCG conceptual model includes an attribute for ecosystem function for
future application.
Recommendations for Defining Ambiguous or Unclear Terms in the
Definition of BCG Attributes VII and Villi
When applying the BCG framework to coral reef ecosystems, we suggest that these attributes may
require some further specification and clarification. For example, the distinction between "direct"
and "indirect" measures of organism condition is not entirely clear in the definitions (EPA 2016). It
is also helpful to differentiate between structural and functional characteristics. Odum (1962)
provided the following definitions:
"By structure we mean: 1) The composition of the biological community including
species, numbers, biomass, life history and distribution in space of populations; 2) the
quantity and distribution of the abiotic (non-living) materials such as nutrients, water,
etc.; and 3) the range, or gradient, of conditions of existence such as temperature, light,
etc."
"By function we mean 1) the rate of biological energy flow through the ecosystem, that is,
the rates of production and the rates of respiration of the populations and the community;
2) the rate of material or nutrient cycling, that is, the biogeochemical cycles,
3) biological or ecological regulation including both regulation of organisms by
environment (as, for example, in photoperiodism) and regulation of environment by
organisms (as, for example, in nitrogen fixation by microorganisms) "
In addition, partial or entire mortality and the presence of disease lesions can be seen
macroscopically in the field (structural), while changes in coral growth and fecundity (functional)
cannot. Thermal stress can lead to bleaching, and prolonged bleaching can result in reduced growth
and reproductive failure (Szmant and Gassman, 1990; Weil et. al. 2009a). Although only incidence
is mentioned in the current description of attribute VII, prevalence is also important and more often
documented. Incidence is the number of new diseased individuals in a specified population during a
specified time period, and prevalence is the percent of diseased individuals in a population at a
point in time (Stedman, 2006). Incidence is a rate and conveys information about the risk of
contracting the disease, whereas prevalence indicates the proportion of individuals affected at a
particular time.
ii ¦ „> .I ,1 > i i x I i ">,- -id .I > .I -I : i.it
What can we learn about the overall condition of a coral reef by examining individual coral
colonies? Can we quantify and characterize different reef conditions based on an evaluation of
numerous colonies from several coral species at a single point in time or over several successive
surveys? Diseases certainly are a primary focus for attribute VII. Diseases are often referred to as
causes of coral mortality, but they are in fact the end result of sometimes unknown stressors, such
as nutrient input. Burial by sediments and physical damage from storms and anchors are other
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examples of conspicuous changes to corals that would influence the evaluation/ranking of a reef
area.
Physical damage to corals can result from storms but also from vessel groundings, careless
snorkelers or SCUBA divers, and fishing gear. Physical damage to corals from major storms can
increase disease prevalence (Bright et. al. 2016). Coral species differ in their vulnerability to
damage, with branching species more likely to become fragmented. Anchor damage can result in
complete pulverization of coral colonies (Rogers and Garrison, 2001). In some coral species,
however, fragmentation can result in an increase in colonies and in wider distribution.
Most scientists agree that a combination of changing climate and destructive human actions are
contributing to degradation of coral reefs (Intergovernmental Panel on Climate Change, 2014).
Climate change has many components, including elevated ocean temperature, sea level rise, and
increased intensity and perhaps frequency of major storms and hurricanes. The BCG workshop
experts made a critical decision to include increasing seawater temperature associated with
changing climate as an anthropogenic stressor in developing the BCG model for coral reefs.
Rising seawater temperature is one of the most significant stressors affecting coral reefs globally
today. Reports of up to 40 percent coral mortality caused by elevated temperature with associated
bleaching have occurred on the northern portion of the Great Barrier Reef since January 2016
(Hughes et. al. 2018; Eakin et. al. 2019). More alarming forecasts predict that coral bleaching
episodes are expected to become more frequent in the future (Hoegh-Guldberg, 1999; Eakin et. al.
2019; Skirving et. al. 2019).
The greatest loss in coral cover in the last 50 years on reefs in the U.S. Virgin Islands and Puerto
Rico has been from an outbreak of diseases following bleaching associated with the highest
seawater temperatures on record in the Caribbean in 2005. More than 90 percent of the corals
bleached in late summer of 2005, with some recovery occurring as temperatures cooled in
November 2005. A subsequent coral disease outbreak resulted in losses of more than 60 percent of
the coral cover by 2007 (Miller et. al. 2009). A similar pattern of bleaching, recovery, and disease
was seen in Puerto Rico at that time (Ballantine et. al. 2008; Weil et. al. 2009b). This illustrates
how regional stressors, such as high seawater temperatures for extended periods of time, often have
greater effects on coral reef ecosystems compared to local stressors such as sewage runoff which
would affect smaller areas. When regional and local stressors are present, the outcome on the coral
communities is usually much more severe than when single stressors act independently (Hoegh-
Guldberg et. al. 2007).
Ocean acidification, decreasing pH caused by increasing atmospheric carbon dioxide, is another
major concern that can result from climate change. Global warming associated with changing
climate fuels the increase in the frequency and severity of hurricanes. Hurricanes Irma and Maria,
both in September 2017, were especially destructive in shallow, nearshore areas in Puerto Rico and
the U.S. Virgin Islands. However, declines in coral cover have been linked more to coral diseases
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than any other stressor, with the potential for even more loss of living coral with the advance of
Stony Coral Tissue Loss Disease (Weil 2019).
^v.ponse-' -h ors
One of the many challenges of applying BCG attributes I-V to coral reefs is the essential nature of
corals themselves—modular, colonial organisms, portions of which can persist over time after other
portions die. A coral colony with only one-half of the skeleton covered with live tissue can survive
for decades, whereas one-half of a fish or a mayfly will not persist at all. In some cases, coral
colonies die partially, and new tissue regenerates over the skeleton making it impossible to tell that
the coral ever lost any tissue at all (fig. 2).
Evaluating coral condition is complicated by the fact that re-sheeting can occur, hiding any evidence
that there was mortality in the first place. In other cases, loss of coral tissue occurs gradually and
inconspicuously in the absence of any obvious disease or predation and without exposure of distinct
white skeletal areas reflecting loss of coral tissue revealing the underlying skeleton (fig. 3a-d). This
situation may result from some type of coral/algal interaction or even transfer of a pathogen from
the algae (Nugues et. al. 2004). Only very careful and frequent (photographic) monitoring of
individual colonies over time (weeks or months) would discern such situations. In general, loss of
coral tissue from any cause is followed by settlement of filamentous algae which is followed by
macroalgae, particularly when grazing rates by herbivorous fish and urchins are low. Macroalgae
can inhibit settlement of coral recruits contributing to overall reef decline (McCook et. al. 2001;
Jompa and McCook, 2002; Diaz-Pulido et. al. 2010).
Morbidity2 and mortality3 follow very different mechanisms in clonal and solitary organisms, such
that in solitary organisms the mortality is complete; none of the organism is functional. If affected
by disease, morbidity can lead to mortality, depending on which organs are affected. In modular
organisms, the mortality of individual polyps can be a sign of morbidity, but infection with disease
does not necessarily lead to total mortality of the colony. Furthermore, the death of a colony does
not always mean the extinction of that particular genotype. If ramets (physically separated colonies
of the same genotype resulting from asexual reproduction) are dispersed over the reef, the genet
(genotype) has a higher probability of surviving the disturbance.
Diseases
Coral diseases are increasing in number and severity (Weil and Rogers 2011). Burge and others
(2013) noted: "The biological and physical changes to the world's oceans, coupled with other
anthropogenic influences, will likely lead to more opportunistic diseases in the marine
environment." Disease has a broad definition. Based on Stedman (2006 and earlier references
therein), Peters (1997) defined disease as "any impairment (interruption, cessation, proliferation, or
other disorder) of vital body functions, systems, or organs," and added that "Diseases are usually
characterized either by (1) an identifiable group of signs (observed anomalies indicative of disease),
and/or (2) a recognized etiologic or causal agent, and/or (3) consistent structural alterations (e.g.
2 Morbidity is the state of being ill or in diseased state (Stedman, 2006).
3 Mortality is another term for death (Stedman, 2006).
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developmental disorders, changes in cellular composition or morphology and tumors)." Diseases
result from complicated interactions among the host, the environment, and an abiotic or biotic
agent. The number of diseases of scleractinian corals and octocorals in the Caribbean/western
Atlantic exceeds 20 (Sutherland et. al. 2004; Weil, 2004; Weil and Rogers, 2011; Weil et. al. 2017)
with other less well defined or characterized conditions referred to as "compromised health
conditions" (Raymundo et. al. 2008; Weil and Hooten, 2008).
Bleaching is a disease under the definition presented above. For the purposes of this report, we
use the term disease in almost all cases to refer to cases where tissue is lost originating from a
lesion, and the term bleaching to refer to the appearance of coral colonies that have lost the
symbiotic zooxanthellae or zooxanthellae pigments (fig. 4), a condition which does not
necessarily lead to morbidity and mortality.
Corals only have few visible signs of stress. Thermal stress leads to paling or bleaching with
recovery possible if the stress is removed over a short enough time period. Bleaching is a sign of
stress, typically a thermal anomaly (high or low temperatures), but corals can recover. There are
degrees of bleaching, with colonies ranging from slightly pale, to blotched and completely white.
Single surveys of bleaching cannot provide a complete picture of the reefs condition. In general,
it is not as alarming as the appearance of new disease lesions.
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Figure 2. A colony of Colpophvllia natans in St. John. U.S. Virgin Islands (a) with no sign of disease (August 8S
2009), (b) with while plague disease and firewonn predation (February 15, 2010), and (c) after tissue regenerated
over the exposed skeleton (re-sheeting) (November 25,2012).
Coral species differ in their susceptibility to thermal stress and therefore in the likelihood of
bleaching and mortality (McClanahan et. al. 2009) (fig. 5). Within the Caribbean, different coral
species and even different colonies within a species can host several different symbiotic algal
Symbiodiniiim clades and therefore exhibit dissimilar responses to thermal stress (Thornhill et. al.
2014; Kemp et. al. 2015). Susceptibility to bleaching is not equivalent to likelihood of mortality.
Many diseases are associated with bright white bands, patches, and irregular areas where the
coral skeleton is exposed following loss of tissue and are characterized based on these lesions:
the shape (for example, linear), the location (for example, near the apex, base), virulence (fast,
slow), and distribution (for example, multifocal) (Work and Aeby, 2006). In some cases, red,
black, and white bands and dark spots are on the colonies. Pathogens include bacteria, ciliates
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
(Sweet and Sere, 2015), and viruses (Soffer et. al. 2014), although pathogens have been
identified for only a few diseases (Weil and Rogers, 2011).
A few diseases have been particularly devastating in Puerto Rico: black band, white plague, and
Caribbean yellow band. Coral diseases are complicated, involving not only the coral host but also
the associated symbiotic zooxanthellae and other microorganisms and the environment. A coral can
be infected with a disease before showing visible signs. Some studies document shifts in microbial
communities over time as coral colony condition changes, and others compare microbial
communities found in nondiseased corals with those in stressed or diseased corals (Frias-Lopez et.
al. 2002, 2004; Pantos et. al. 2003; Pantos and Bythell, 2006; Sekar et. al. 2006; Bourne et. al. 2008;
Sunagawa et. al. 2009; Tracy et. al. 2015). When corals become bleached and (or) diseased,
pathogenic microbes sometimes replace beneficial microbes (Ritchie, 2006). Diseased samples
were similar in bacterial community composition in colonies from Florida and the U.S. Virgin
Islands; in contrast, major differences in bacterial assemblages were found from apparently healthy
colonies of Orbicella faveolata and Orbicella franksi and on those with signs of white plague, but
not between the two coral species (Roder et. al. 2014). Recent comprehensive discussions of coral
diseases include Weil and Rogers (2011) and Raymundo and others (2008). In the Pacific, a large
number of conditions are grouped simply under the term "white syndromes," but in the Caribbean,
some diseases are distinct enough to warrant more specific names, such as white band disease,
black band disease, dark spots disease, and Caribbean yellow band disease. In many cases it is
unclear if different pathogens are producing the same signs, or if different signs appear in response
to the same pathogen in different species or under varying environmental conditions. The case of
the pathogen for white pox illustrates that the etiology of a disease can change over time, further
complicating efforts to diagnose understand the causes of, and eventually respond to and attempt to
manage stressors linked to coral diseases (Sutherland et. al. 2016). The severity of white pox, for
example has varied during the past 20 years, with greater mortality of entire coral colonies in the
earlier years.
Diseases are affecting almost all coral species, including the "foundation" species, those that are
most responsible for the physical architecture of coral reefs (Szmant and Gassman, 1990; Aronson
and Precht, 2001a; Sutherland et. al. 2004; Weil et. al. 2009a, b; Ruiz-Moreno et. al. 2012; Rogers
and Miller, 2013). In some cases, these "structural engineers" have had disproportionately higher
mortality during bleaching and (or) disease events (Croquer and Weil, 2009; McClanahan et. al.
2009; Miller et. al. 2009; Weil et. al. 2009a, b; Bastidas et. al. 2012; Bruckner, 2012; Ruiz-Moreno
et. al. 2012).
A particularly devastating disease, called Stony Coral Tissue Loss Disease (SCTLD) has been
ravaging reefs along the Florida Reef Tract since 2014 (Precht et. al. 2016; Gintert et. al. 2019;
Weil 2019). The Atlantic and Gulf Rapid Reef Assessment website (http://www.agrra.org) provides
updates on spatial distribution and other aspects of the disease. A video available at
https://youtu.be/H-WIs4J2oW8 provides helpful background information about SCTLD. In January
2019, this or a similar disease was observed off western St. Thomas, and over the course of 1 year,
it spread east to western St. John. Ballast water from a ship out of Florida was released in waters
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
near where this disease was first observed in St. Thomas and may be linked to this outbreak (U.S.
Coast Guard, 2019). This disease is affecting almost all coral species except the acroporids.
Research continues on identification of the pathogen which could provide clues as to a possible link
between water quality and the disease. Monitoring of coral colonies near a large construction
project at Port Miami (Florida) documented more mortality from disease than from dredging effects
(Gintert et. al. 2019).
The actual causes of most coral diseases remain elusive. Increasing seawater temperatures, high
sedimentation, untreated sewage effluent, introduced pathogen species, and more frequent and (or)
intense storms could all lead to more coral loss from diseases. Although diseases have been
observed far from major human population centers, some links between diseases and human-caused
stressors like sedimentation and nutrient runoff have been proposed (Weil et. al. 2002; Kaczmarsky
et. al. 2005; Wooldridge and Done, 2009; Sutherland et. al. 2010). Some studies have linked
specific pathogens to diseases; some of these pathogens are linked to human actions, and therefore,
are presumably manageable (Sutherland et. al. 2010).
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Figure 3. Orbicella fmeolata colony with increasing loss of tissue in the absence of conspicuous disease, St. John.
U.S. Virgin Islands: (a) March 30, 2013; (b) May 18, 2014; (c) May 31, 2015; (d) June 16, 2015; and (e) October 2,
2015.
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
Figure 4. Bleached colonies of (a) Orbicella annularis and (b) Acroporapalmata. (Photographs by E. Muller, U.S.
Geological Survey.)
Figure 5. Coral species differ in their susceptibility to bleaching (following thermal stress) as seen in these
adjacent Colpophyllia natans (upper) and Diploria labvrinthiformis (lower) colonies.
Prevalence
As noted earlier, "A Practitioner's Guide to the Biological Condition Gradient" (EPA 2016)
describes BCG levels 1-6 for freshwater systems. The guide makes no specific mention of organism
condition until level 5. Increasing degradation from level 1 to level 6 is based on changes in richness
and density of taxa with varying degrees of rarity and tolerance. The description for level 5 states
"organism condition shows signs of physiological stress" and "changes in organism condition
(attribute VII) may include significantly increased mortality, depressed fecundity, and/or increased
frequency of lesions, tumors, and deformities" (EPA 2016). This is the first mention of di seases in
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
the guide. Given the importance of organism condition for corals, the building blocks of coral reefs,
we recommend that prevalence values be proposed for each of the six levels. Note that the term
"prevalence" is strictly used for populations of single species, but some scientists find "overall" or
"community level" prevalence, here defined as the number of coral colonies of all species with
disease, which is a useful characterization (Rogers 2010).
Benthic experts did not discuss disease prevalence but we suggest the following for further
consideration: level 1: 0 to 1 percent; level 2: >1 to 5 percent; level 3: >5 to 10 percent; level 4: >10
to 20 percent; level 5: >20 to 30 percent; level 6: > 30 percent.
If we accept that some disease is likely to occur even in the absence of any major stressors, what are
"normal" levels of disease prevalence? Strictly, prevalence should be calculated separately for each
coral species and each disease combination, but often scientists have presented prevalence values for
all species and diseases combined. Yee et al. (2011) cautioned investigators about considering the
underlying assumptions when prevalence was calculated by pooling data from different coral species
and assuming similarities in disease susceptibility when interpreting disease risk. They demonstrated
the potential erroneous outcomes from using simulated data to assess the ability of standard statistical
methods (binomial and linear regression, analysis of variance) to detect a significant environmental
effect on pooled disease prevalence with varying species abundance distributions and relative
susceptibilities to disease.
Prevalence values of less than 10 percent have been referred to as "low," but if these are calculated
annually from the same reef and different colonies are diseased at each survey, clearly there should
be cause for alarm because this could signal higher disease incidence and a potential epizootic.
Santavy and others (2005) found that reporting the prevalence of diseases at both the population and
community levels was a useful biological indicator for coral reef condition. For example, 79 percent
of the reefs in South Florida had less than 6 percent of the coral colonies diseased, whereas only 2.2
percent of the sampled area had a maximum prevalence of 13 percent diseased coral colonies at any
single location. Santavy and others (2005) suggested a background of 6 percent coral disease
prevalence for the Florida Keys during the early 2000s but cautioned that many factors must be
considered and more detailed and frequent studies must be completed to increase certainty.
Weil and Rogers (2011) present prevalence values for individual coral species and diseases ranging
from 0.002 percent for white patch disease (white pox) to 25 percent for white band disease -II
(table 3). Higher values for white patch disease on Acroporapalmata have been reported from St.
John (Muller et. al. 2008; Rogers and Muller, 2012) and from Florida (Sutherland et. al. 2016).
Few studies examine prevalence or coral loss from diseases over long periods of time. As one
example, the U.S. National Park Service (NPS) scientists are conducting long-term monitoring of
coral reefs in parks in Florida and the U.S. Virgin Islands (Biscayne National Park, Dry Tortugas
National Park, Virgin Islands National Park, and Buck Island Reef National Monument). The
primary focus has been on changes in cover of corals and other benthic organisms. Since about
2005, NPS scientists have also been recording the number and total area of disease lesions by coral
species along each long-term transect, usually once a year. These data can be compared over time
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
and among sites. They provide a measure of virulence (severity) and overall prevalence of disease
(but not by coral species).
Sedimentation Stress
Ranking of coral species by sensitivity to turbidity, and sediment deposition requires caution. Many
papers make references to "sediment tolerant" coral species or interpret their findings with
differential sensitivity in mind (Erftemeijer et. al. 2012), but a closer look reveals that the evidence
for differential response to increased levels of sedimentation is quite limited. Controlled laboratory
studies cannot reflect the wide range of field conditions, and field studies are typically based on
rather small sample sizes.
Some publications provide information on vulnerabilities of coral species to various stressors, but
limited data are available (Erftemeijer et. al. 2012; National Oceanic and Atmospheric
Administration, 2012). Many studies have documented responses of corals to stressors that are not
macroscopic (visible) but rather involve microscopic changes, such as shifts in microbial
communities (Vega Thurber et. al. 2009) and gene expression (DeSalvo et. al. 2008). There may be
techniques in the future which will allow an evaluation of the coral conditions which are sublethal
or not visible (Ricaurte et. al. 2016).
Although we are still exploring the evidence for varying sensitivities and their applicability to the
BCG, currently the assigning of different attribute levels to coral species does not appear to be an
effective foundation for ranking a reef site. We suggest that the condition of the coral colonies of the
major framework-building species is the most informative indicator of the overall status of a reef site.
Coral species vary in their overall morphology, growth rates, maximum size, and other
characteristics. Some species contribute far more to the structure and function of a reef than others,
such as the large branching, massive, and brain corals. Corals in the genus Orbicella (formerly
Montastraea) often contribute more to the living "cover" on Caribbean coral reefs than many of the
other species (Kemp et. al. 2015).
Coral Demographics
Models that predict the population dynamics of solitary organisms incorporate age-dependent rates
of birth, death, and migration into and out of the population. However, such models do not apply to
sessile clonal organisms such as corals with variable rates in growth, recruitment (settlement and
survival), fission, fusion, and partial mortality along with high longevity (Hughes and Connell
1987). The combined effects of growth, partial mortality, and recruitment, all of which can be
affected by environmental conditions, might be noticeable through shifts in population structure
(Meesters et. al. 2001). By quantifying these parameters, studies can detect gradual decreases in the
condition of communities and can potentially provide information about a reefs future state (Smith
et. al. 2005). Size-frequency distributions (numbers of colonies within each size class) can help
reveal small- or large-scale processes in the population and in the drivers of those processes
(Hughes and Connell, 1987; Hughes and Tanner, 2000; Gilmour, 2004; Smith et. al. 2005; Edmunds
and Elahi, 2007). Size-frequency distributions vary with the type, intensity, and frequency of the
stressor or environment to which the populations have been exposed (Gilmour, 2004). When an
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The BCG for Puerto Rico and USVI Coral Reefs - Appendices
entire hard coral community is assessed, the sizes within "age classes" vary due to the differences in
growth rate, maximum colony size, and resilience among coral species (Hughes, 1984).
Colony size is an important life-history trait, but age and size are not well correlated in corals
because of partial mortality and fusion (Hughes, 1984; Hughes and Jackson, 1985). Stressors
that reduce colony size have consequences for reproduction and population dynamics because
the number of fertile polyps in colonies determines their fecundity and larger colonies tend to
have more sexually mature polyps (Hughes, 1984; McClanahan et. al. 2008; Harrison, 2011). A
lack of juveniles might be attributed to low survivorship of post-settlers due to multiple
environmental/biological stressors, especially the conditions at the time of mass spawning and
settlement, which will influence survival of larvae.
Because population size structure is greatly influenced by the environment, it can be used in some
cases as evidence of an unfavorable or degraded habitat (Meesters et. al. 2001; Gilmour, 2004;
Alvarado-Chacon and Acosta, 2009). However, populations dominated by small individuals may
indicate either a population with high recruitment or one that has high fragmentation of larger
colonies due to environmental stress. If no small colonies are found, conditions are not favorable
for successful settlement and recruitment, and the population cannot sustain itself (Bak and
Meesters, 1999; Alvarado-Chacon and Acosta, 2009). Many studies have found that populations
are dominated by larger colonies at degraded sites, likely because of a lack of recruitment and (or)
low survival of small colonies (Bak and Meesters, 1998; Meesters et. al. 2001; Smith et. al. 2005;
McClanahan et. al. 2008). Overall, a balanced range of size classes is advantageous to maintain a
functioning reef (Alvarado-Chacon and Acosta, 2009).
To understand the processes that drive size-frequency distributions of populations, it is important
to determine how environmental conditions affect individuals of different sizes. Besides the life-
history characteristics of each species, colony size is highly influenced by the environment and the
associated stressors (Hughes, 1984; Meesters et. al. 2001). It has been suggested that small
colonies are more susceptible to instantaneous or acute whole-colony mortality and if partially
injured, their chances of recovery are low (Hughes and Connell, 1987; Hughes and Tanner, 2000).
This could be due to smaller colonies having lower amounts of energy reserved and less material
to transfer to damaged polyps (Hughes and Connell, 1987). Therefore, if there is a stressor, small
colonies have a high probability of either escaping injury or dying completely, whereas large
colonies have a low chance of escaping at least some partial mortality. Certain stressors such as
sediment burial or overgrowth by competitors are more likely to harm small colonies. These two
stressors are usually seen as indicators of poor water quality; therefore, large numbers of small
colonies could indicate good water quality (Smith et. al. 2005).
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Table 3. Coral reef diseases in the western Atlantic Ocean (modified from Weil and Rogers, 2011). [Year, year reported/observed;
P/A, pathogen/agent identified, Y (yes) or N (no); CO, corals; OC, octocorals; HY, hydrocorals; SP, sponges; ZO, zoanthids; CCA,
crustose coralline algae; DE, depth distribution; m, meter; PR, average community prevalence; %, percent; TM, tissue mortality rate;
mm/day, month/day; - not observed; GD, geographic distribution; WA, western Atlantic; WC, wider Caribbean; VI, Virgin Islands;
FL, Florida; BE, Bermuda; CA, Caribbean; BA, Bahamas; ME, Mexico; PR, Puerto Rico; CU, Curacao; CY, Caymans]
Number of taxa showing disease signs
Disease Acronym Year P/A (Brazilian species)
CO
OC
HY
ZO
SP
CCA
DE
(m)
PR (%)
TM
(mm/day)
GD
Bleaching
BL
1911
N
62
29
5
2
8
-
0-100
0.2-85
-
WA
Coral growth anomalies
CGA
1965
N
10
8
1
-
-
-
0-25
-
-
WC
Black band disease
BBD
1973
Y
19(4)
6
-
-
-
-
0-25
0.3-6
3-10
WA
White band disease-I
WBDI
1977
N
2
-
-
-
-
-
0-10
0.1
-
WC
White plague disease-I
WPDI
1977
N
12
-
-
-
-
-
10-21
3.6
3.1
FL
Shut Down reaction
SDR
1977
N
6
-
-
-
-
-
5-12
-
-
FL
White band disease-II
WBDII*
1982
Y
3
-
-
-
-
-
1-25
0.1-25
3-30
WC not BE
Red band disease
RBD
1984
Y
13(1)
5
-
-
-
-
2-20
-
1
WA
Acropora serriatosis1
ASER*
1992
Y
1
-
-
-
-
-
0-5
0.002
15
CA,FL,BA
Caribbean yellow banda
YBD *
1994
Y
11
-
-
-
-
-
3-20
1-24
0.1-0.4
WC
White plague disease-II
WPDII*
1995
Y
41(5)
-
2
-
-
-
3-30
0.9-18
3-30
WA
Aspergillosis
ASP*
1996
Y
-
9
-
-
-
-
1-25
1.9
0.1-2.5
WA
Dark spots disease
DSD
2001
N
11(1)
-
-
-
-
-
1-25
1.1
-
WA
Caribbean white syndromes2
cws
2004
N
15
-
2
1
3
-
2-25
-
-
WCa
Caribbean ciliate infection
CCI
2006
Y
21
-
-
-
-
-
2-25
-
-
WCa
Octocoral growth anomalies
OGA
1977
Y
-
8
-
-
-
-
2-22
-
-
WC
Gorgonia labyrinthulomycosis3
LAB
2008
Y
-
2
-
-
-
-
4-20
-
-
FL, PR
Multi-focal purple spots4
MFPS
2015
Y
-
-
-
-
-
3-22
-
-
ME,FL,CA
Briareum bleaching necrosis
BBN
1998
N
-
2
-
-
-
-
5-15
-
-
FL, PR
Briareum wasting syndrome
BWS
1999
N
-
2
-
-
-
-
5-15
-
-
FL,PR,CU
Gorgonia wasting syndrome
GWS
2010
N
-
1
-
-
-
-
3-20
10
-
PR
Palythoa wasting syndrome
PAWS
2008
Y
-
-
-
-
-
-
3-10
-
-
WC
Erythropodium wasting syndrome
EWS
2005
N
-
1
-
-
-
-
3-22
-
-
PR-CY-CU
Phyllogorgia wasting syndrome
PWS
2013
N
-
1
-
-
-
-
5-12
73
-
BR
Crustose-Coralline white syndrome
CCWB
2004
N
-
-
-
-
-
3
1-20
1-6
0.1-2
wca
Crustose-Coralline lethal orange dis.
CCLOD
2008
N
-
-
-
-
-
1
12-22
-
-
PR,CY,ME
Other coral syndromes5
OCS
-
N
15
-
-
-
-
-
1-25
-
-
WA
Other octocoral syndromes5
OOS
-
-
-
8
-
-
-
-
3-20
-
-
WC
* Koch's postulates fulfilled.
1 White patch disease is also termed white pox and patchy necrosis.
2 White syndromes include several patterns of tissue loss exposing bands, stripes, blotches, or irregular shapes of clean skeleton (different from the other "white" diseases) with very low prevalence.
3 Purple spots produced by an unknown protozoan (Labyrinthulomycota.
4 Health conditions of other corals and octocorals include unhealthy-looking tissues with some degree of mortality, low prevalence and limited geographic distribution with no pathological or
etiological information.
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a Includes Flower Gardens Banks National Marine Sanctuary. Western Atlantic distribution includes the wider Caribbean and Brazil. Bleaching-affected species from Brazil have not been included .
T-23
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Unfortunately, size-frequency distributions are still not considered a strong measure of coral
reef condition. They can be ambiguous and hard to interpret, more so if no historical
information from the reef is available. For example, increasing frequencies of small colonies
can either be the result of recruitment (and [or] fragmentation) and survivorship, which is a
beneficial process, or a result of partial mortality, which is the result of a stressor (Miller et. al.
2016). Especially if a population is only measured once, it can be misleading because
populations are strongly influenced by recent events and the processes that influence size
structure are often temporally variable. Measuring long-term size-frequency distribution
fluctuations in response to different types and levels of disturbance can provide much better
insights into population dynamics than a single size-frequency distribution alone.
Programs such as the Florida Reef Resilience Program and the Atlantic and Gulf Rapid Reef
Assessment only started implementing colony size surveys in the early 2000s (Fisher et. al.
2008; Miller et. al. 2016). Measuring coral demographics can provide vital information on a
population that more traditional percent cover surveys cannot. Ideally, long-term surveys of
size-frequency measurements and of percent cover would be done together to provide a more
accurate indication of the condition of a reef.
The Importance of Context
The condition of the coral colonies must be included when ranking coral reefs or reef zones in
terms of their position along a stress gradient (levels 1-6 in the BCG model). In fact, we
suggest that the condition of the coral colonies of the major framework-building species is the
single most informative indicator of the overall status of a reef site. Rules developed for
application of the BCG model for evaluating and ranking the reefs should not be considered
individually or in isolation; context will be vitally important here. A recently proposed rule
states that reefs at level 2 would have a coral cover of >45 percent (table 4). The coral cover
for the reference (natural) condition has not been defined, partly because high-quality data,
collected randomly from numerous and widely distributed reefs, are not available. Coral cover
on Caribbean reefs now (as of 2012) ranges from 2.8 percent to 53.1 percent (mean of 16.8
percent) (Jackson et. al. 2014, p. 65).
To be useful, the BCG approach should allow managers to evaluate, rank, and (or) compare
different reef areas that are or were subject to various stressors. The evaluation of a site could
differ greatly depending on whether it was based on a single survey (a "snapshot") or on
successive surveys in a long-term monitoring program.
Recommendation:
To gain insights into how the coral experts derived scores for different reefs, it would be
valuable to get their opinion on different hypothetical habitats. For example, how would they
evaluate the following habitats (assuming each reef has the same number of colonies)? How
would the evaluations and the rankings change with different coral species present?
• A reef with 75 percent coral cover and with 90 percent of the corals bleached.
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• A reef in which 10 percent of the colonies of one framework-building (or other)
species has disease versus a reef in which 10 percent of the colonies of all species
have disease.
• A reef with 75 percent coral cover and with 50 percent of the corals exhibiting new
diseases.
• A reef with 50 percent coral cover and 75 percent of the colonies with high
levels of old partial mortality.
• A reef with 25 percent coral cover with colonies showing no visible signs of disease
or effects of other stress.
• A reef with 50 percent of the corals exhibiting white plague disease versus a reef
with 75 percent of the corals exhibiting black band disease.
The BCG is "a framework to describe incremental change in aquatic ecosystems" (EPA 2016).
What evidence is there that coral reefs change incrementally? Are there "thresholds" that
separate levels 1 to 6? Experts concluded that algal cover might be useful for determining
"thresholds or tipping points for BCG levels for coral benthic community assessments"
(Bradley and Santavy, 2016, p. B-70). Very few papers document changes in percent cover or
disease prevalence over time, and most are from the U.S. Virgin Islands (Muller et. al. 2008;
Miller et. al. 2009; Rogers and Muller, 2012). These papers can be examined carefully to see if
any thresholds are revealed.
Recommendation:
Have the experts examine the data from the NPS long-term (randomly selected, permanent)
monitoring transects collected during the last 15-20 years. Data are in Miller and others (2009)
and in NPS Inventory and Monitoring Annual reports.
• Select individual transects (perhaps ones that differ the most) and examine how
the rankings compare.
• Compare results from before and after the 2005/2006 bleaching and disease event to
reveal any consistent patterns. Are these patterns in agreement with the report by
Jackson and others (2014)?
• Are there declines in coral cover over time with comparable macroalgal increases?
Despite considerable discussion about phase shifts, some review papers do not support
this as a general pattern in the Caribbean (Bruno et. al. 2009).
While further investigation into the scientific literature might provide more clues as to
species resistance to different stressors, it is not evident that corals can be assigned as
readily as many other organisms to a particular location on the response gradient. The
condition of the major reef-building genera should be given the highest priority.
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Table 4. Benthic coral reef Biological Condition Gradient (BCG) narrative rules proposed by
the expert panel, but not thoroughly vetted. This table is still under discussion and
development by benthic experts.
[>, greater than, >, greater than or equal to; cm, centimeter; <, less than or equal to; spp., more than one
species; sp., species]
Narrative
BCG Level 2
Stony corals
• >45 percent live cover of coral in fore reef habitat
• Minimal recent mortality in large reef-building genera (Orbicella, Pseudodiploria,
Colpophyllia, Acropora, Dendrogyra, P. pontes)
• Normal frequency distribution of colony sizes within each species size range to
include large, medium, and small colonies (>4 cm) and presence of recruits (<4 cm)
• Species composition and diversity composed of sensitive, rare species (Isophyllia,
Isophyllastrea, Mycetophyllia. Eusmilia, Scolymia) present in appropriate habitat type
• Very low or just background levels of disease, tissue and skeletal anomalies, and
bleaching
• Large Orbicella (fore reef), Acropora (back reef, reef crest, reef slope) colonies
dominate reef structure within respective zones
Rugosity
• High rugosity resulting from large living coral colonies, producing spatial and
topographical complexity
Macroinvertebrates
• Diadema abundant
• Reef macroinvertebrates (e.g., Lobsters, crabs, conch) common and abundant
• Low levels of invertebrate coral predators (Coralliophila spp, Hermodice sp)
Algae
• Minimal fleshy, filamentous, and cyanobacterial algae present
• Crustose coralline algae present, with some turf algae
Sponges
• Phototrophic sponges dominate (abundant)
• Low frequency of Clionid boring sponges
BCG Level 3
Stony corals
Rugosity
• >25 percent live cover of coral in appropriate habitat
• Higher percentage of tissue loss with signs of recent mortality especially on large
reef-building genera (Orbicella, Pseudodiploria, Colpophyllia, Acropora, Dendrogyra)
• Frequency distribution of colony sizes within each species size range starting to
become skewed to include fewer very large, medium and small colonies (>4 cm)
and lower number of recruits than expected (<4 cm)
• Species composition and diversity: sensitive, rare species present in appropriate
habitat. Moderate abundance of hydrocorals in shallower habitats
• Low to moderate levels of disease andbleaching
• Orbicella and Acropora colonies still dominant (within respective reef
geomorphological zones)
• Moderate to high rugosity or reef structure resulting from large living reef-forming
and dead coral colonies, producing spatial complexity (or topographical heterogeneity)
Macroinvertebrates
• Diadema present abundant
• Reef macroinvertebrates (e.g., Lobsters, octopus, conch) present, low densities
• Minimal to moderate presence of fleshy, filamentous, and cyanobacterial algae cover
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Algae
• Crustose coralline and turf algae present
• Phototrophic sponges present and abundant
Sponges
• Low cover and abundance of Clionid boring sponges
BCG Level 4
Stony corals
• >15 percent live cover of coral in appropriate habitat
• Moderate amount of recent partial or total colony mortality on reef-
building genera (Orbicella, Pseudodiploria, Acropora, Dendrogyra]
• Mix of sizes: large colonies may be absent, primarily medium and small colonies
• Species composition and diversity: sensitive spp may be absent (Agaricia,
Mycetophyllia, Colpophyllia, Isophyllia, etc.), more tolerant spp present (Montastraea
cavernosa, Siderastrea siderea, Porites astreoides; P. porites at least some reef-
building corals present but not dominant (primarily Orbicella)
• Moderate to high levels of disease and potential bleaching on corals and sea
fans/branching gorgonians
Rugosity
• Rugosity due to old mostly dead coral structure
Macroinvertebrates
• Palythoa may be present, but not dominant
Algae
• Moderate to high amount of fleshy, filamentous and cyanobacterial algae cover
Sponges
• Moderate cover and abundance of Clionid boring sponges
BCG Level 5
Stony corals
• >1 percent live cover of coral in appropriate habitat
• High recent tissue mortality on corals present or organisms absent. Low amount
of live tissue remains.
Rugosity
• Low rugosity, and that which is present may be due to old dead coral structure
Algae
• Coral cover mostly replaced by fleshy, filamentous and cyanobacterial algae
Macroinvertebrates
• Palythoa dominant
Sponges
• Highest presence of Clionid boring sponges
• Low abundance and size of phototrophic sponges,non-phototrophic dominant
EndNote Bibliographic Database
Dr. Rogers and Dr. Santavy combined their electronic reference libraries (more than 2,000
EndNote references) relating to coral reef organism condition, coral diseases, and responses to
different anthropogenic stressors and began building the bibliographic database by selecting
pertinent articles. In addition, Christina Horstmann searched for papers on coral reef stressors
through Google Scholar and also by checking citations in the bibliographies of papers that were
already in the database. Overall, the database has 783 references, 90 percent of which have
Portable Document Format (PDF) files attached and 95 percent of which are journal articles.
There are 51 groups that organize key topics. Within those groups there are two main stressor
categories: stressors related to climate change (266 references) and land-based stressors (180
references). The main groups related to organism condition are disease and bleaching, and
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those categories have about 370 references. Most references fall into multiple groups.
References are labeled as field studies, lab studies, metadata studies, or reviews. The lab
studies have quantitative data with specific species and stressor intensities, whereas 75 percent
of the field studies are observational and involve multiple stressors on the community level.
References are also sorted by location, with 80 percent of studies done in the Caribbean. In
addition, about 280 references are government reports and general coral reef ecology studies
which include topics such as community structure and biodiversity. In studies that focus on
specific stressors, the coral species and the stressor type, intensity, duration, and effects are all
provided to aid in possibly identifying thresholds for the coral species.
Acknowledgments
Our thanks to Ernesto Weil (University of Puerto Rico) and Amanda Demopoulos (U.S.
Geological Survey) for their constructive comments during their reviews of this report.
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