I PA/MO/R-06/167 | July ?OQ7 | www.cpa.gov/ord
United States
Environmental Protection
Agency
Stony Coral Rapid Bioassessment Protocol
J
Office of Research and Development | National Health and Environmental Effects Research Laboratory
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EPA/600/R-06/167
July 2007
www.epa.gov/ord
by
William S. Fisher
U.S. Environmental Protection Agency
Office of Research and Development
National Health and Environmental Effects Research Laboratory
Gulf Ecology Division
1 Sabine Island Drive, Gulf Breeze, FL 32561
U.S. Environmental Protection Agency
Office of Research and Development
Washington, DC 20460
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This document is a product of the Environmental Protection Agency's (EPA) Coral Reef
Biocriteria Working Group, which was initiated, organized and guided by Dr. Lesa Meng
and includes the Office of Research and Development, Office of Water, Office of
Environmental Information and EPA Regions 2, 4 and 9.
Office of Water
Heidi Bell
Kennard Potts
Treda Smith
William Swietlik
Office of and Development
Patricia Bradley
Jed Campbell
Valerie Chan
Lee Courtney
Leah Oliver
Bob Quarles
Jordan West
Office of Environmental Information
Wayne Davis
Regional Offices
Charles LoBue
Wendy Wiltse
Other
Leska Fore. Statistical Design
Aaron Hutchins, U.S. Virgin Islands
Phil Kramer. The Nature Conservancy
Cheryl McGill, University of West Florida
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Contributors. [[[ .ii
Executive Summary .................................................. vii
1. Bioassessment and Regulatory Monitoring .................................. .1
1.1 Role of bioassessment in regulatory monitoring. ....................... 1
1.2 Rapid Bioassessment Protocol for stony corals ........................ 4
1.3 Coral reef biological criteria 5
2. Coral Reef Attributes and Services ....................................... .7
2.1 Biology and distribution of coral reefs 7
2.2 Ecosystem services of coral reefs ............................... 8
2.2,7 Subsistence and commercial fishing .............................. .9
2.2,2 Tourism 9
2,2.5 Shoreline protection 10
2.2,4 Future chemical and pharmaceutical products 11
2,2.5 Biodiversity. .......................................... 11
2.2,6 Primary and secondary production 12
2.2.7 Calcium, carbonate deposition and degradation. ....................... 12
2.3 Biological attributes of coral reefs ............................. 12
2.3,1 Biological and physical measurements 13
2,3.2 Ecological and community measurements 13
2.3,3 Exposure measurements 13
3. Bioassessment Protocol for Stony Coral Condition. ......................... 17
3.1 Stony coral census ..................................... 17
3.2 Colony size and 3D surface area............................... 18
5.2.7 Estimating 3D surface area. .................................. 18
3.2.2 Geometric shapes as colony surrogates 20
3.3 Percent live coral tissue ................................... 21
3.4 Recommended monitoring protocol for stony corals. .................... 22
3.5 Optional reporting 23
3.6 Radial-belt transect .................................... 23
3.7 Synopsis. .......................................... 24
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Stony Coral Rapid Bioassessment Protocol
4. Stony Coral Condition Indicators ........................................ 25
4.1 Multiple indicators from core measurements ........................ 25
4,1,1 Coral abundance and species composition, ,..,,,,..,,,,..,,,,..,,,,. 26
4.1.2 Physical status 27
4.1.3 Biological condition ...................................... 28
4.2 Linking bioindicators to coral reef value and sustainability ................. 29
4.2.1 Indicator links to coral reef values . .............................. 29
4.2.2 Indicator links to coral reef sustainability 29
4.3 Relation to existing indicators. ............................... 32
5. Application of RBP Indicators in Regulatory Monitoring .......................... 33
5.1 Indicator responsiveness to human disturbance 33
5.2 Developing a biocriteria monitoring program ........................ 35
5.2.1 Metric variability 35
5.2.2 Management zones and reef types ............................... 35
5.2.3 Program objectives 36
5.2.4 Synopsis. ............................................ 57
References [[[ 39
Appendix A: Estimating 3D Colony Surface Area. ................................ 51
Appendix B: Converting Historical Data ...................................... 57
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Tables
Table 1-1. Terms used for defining biological condition 2
Table 1-2. The principal underpinnings of RBPs 3
Table 1-3. Process for coral reef biocriteria development 6
Table 3-1. Three recommended core measurements for stony coral surveys 22
Table 4-1. RBP coral condition indicators 26
Table 5-1. Terms used in the development of monitoring programs 33
Table 5-2. Station effects on minimum detectable differences (MDD) 35
Table 5-3. Hypothetical rotating panel monitoring strategy 37
Table A-l. Geometric surrogates and CSA solutions for various colony forms 53
Table C-l. ANOVA F and p values for different combinations of measurements ............ 59
Table C-2. P-values for Tukey comparisons for different numbers of measurements 60
Figures
Figure 1-1. Physical structures formed by reef-building stony corals are inhabited by
diverse and abundant biota. . 5
Figure 2-1. Communities of stony corals form the architecture of coral reefs 7
Figure 2-2. Corals grow through a symbiotic relationship of coral polyps and dinoflagellate algae ... .8
Figure 2-3. Coral skeletons constructed by stony coral growth provide physical habitat
for harvested fish species. 9
Figure 2-4. Reef-building stony corals provide physical habitat for diverse and unique biota
that have become valuable tourist attractions 10
Figure 2-5. Pacific island surrounded by coral reefs that protect the shoreline from wave and
current erosion 10
Figure 2-6. Coral reefs are highly productive ecosystems and principal contributors to ocean
biodiversity. 11
Figure 2-7. Various stresses upset the symbiotic relationship of corals and can cause a loss of
symbiotic algae 14
Figure 2-8. Coral reefs are affected by atmospheric and land use changes occurring at a
global scale 15
Figure 3-1. Colony size has been quantified by visual grading into volumetric size classes and
by field measurements of colony height, diameter and width 19
Figure 3-2. Rulers and meter sticks can be used to measure height, maximum diameter and
width of individual coral colonies 19
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Stony Coral Rapid Bioassessment Protocol
Figure 3-3. Loss of living tissue may not be lethal to the colony but is a sign of damage or
poor health 21
Figure 3-4. Bleaching and disease of coral colonies can be recorded simultaneously with
measurements of the Stony Coral RBP 23
Figure 3-5. A radial-belt transect is delineated at a constant distance from a fixed stake
(permanent station) or tripod 24
Figure 4-1. Population structure (size-frequency) diagrams of Diploria clivosa determined from
a pilot study in Dry Tortugas 29
Figure 4-2. All biological and physical ecosystem services are obtained directly or indirectly
from stony corals 30
Figure 4-3. Comparison of TSA and ISA can be documented for different species and stations. .... 31
Figure 4-4. Colonies of Acropora palmata exhibited lower %LT for middle and large size classes
than colonies of Montastraea faveolata 32
Figure 5-1. Sampling along a gradient of human disturbance will identify the indicators that
can serve as metrics 34
Figure 5-2. Species richness had a less consistent response to a human disturbance gradient
in St. Croix USVT than 3D CSA 34
Figure A-l. Photographic methods have been used to measure CSA for a variety of colony shapes ... 56
VI
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/ % la lime when coral reefs worldwide are in the greatest decline of their known
existence, and despite the enormous value of coral reef ecosystem services,
/ ^ there are relatively few management tools available to offset the growing
impact of human activities. Bioassessments and biocriteria can be used to protect coral
reefs in the same way they are used to protect other aquatic resources in the United
States. As authorized by the Clean Water Act, U.S. jurisdictions can implement measures
of biological integrity (bioassessmerits) to determine whether a waterbody is meeting
resource expectations. When a waterbody is found impaired, jurisdictions have the
authority to use those same measures as the basis for implementing corrective action,
including changes to human activity in the watershed and waterbody.
The Stony Coral Rapid Bioassessment Protocol (RBP) is an inexpensive, no-contact,
nontechnical underwater survey procedure designed for jurisdictions with coral
monitoring expertise on staff but with limited time and funding. The protocol focuses
on scleractinian (stony) reef-building corals because of their fundamental importance
to coral reef ecology and ecosystem value. This focus provides vital information for
reef assessment but is not intended to limit development of additional measurements
that incorporate other components and processes of the reef community. Only three
observations are required—coral identification, size, and proportion of live tissue—
all reported for each colony in the sampling transect. These simple underwater
observations have been used independently in previous monitoring programs, but when
used in combination, they provide a robust array of relevant and informative condition
indicators. A unique aspect of the RBP is conversion of colony-size measurements
to topographic three-dimensional coral surface area; this augments the number of
useful indicators and incorporates both colony and surface area approaches in coral
assessment.
A clear benefit of the Stony Coral RBP is the number and relevance of coral condition
indicators that can be calculated, indicators that represent numerous biological, physical
and ecological aspects of stony corals. For regulatory monitoring, the indicators are
screened to determine which respond to human disturbances over natural variability—
this is because the Clean Water Act is intended to protect resources against human-
induced decline, not decline resulting from natural environmental change. Indicator
responses can be influenced by a variety of factors unrelated to human disturbance and
will vary for different coral communities at different locations. Because not all indicators
will be responsive under all conditions, it is an asset to have many useful candidate
metrics to screen.
VII
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Excutive Summary
Biocriteria, or any enforceable regulations derived from bioassessments, require
scientifically sound monitoring programs capable of distinguishing impairment. Design
of the monitoring program requires a rigorous examination of metric variability,
reference conditions, reef classifications, sampling strategies and designated uses and
must be sensitive to the limitations of agency resources. Preliminary biological surveys
are needed to evaluate these monitoring variables, but once a competent monitoring
program is installed, it will serve the jurisdiction for many years and provide valuable,
long-term records of coral condition and regulatory compliance.
The principal purpose of the Stony Coral Rapid Bioassessment Protocol is to introduce
a simple and rapid coral survey method that provides multiple bioindicators to
characterize coral condition. This document offers insight on indicator relevance to
ecosystem services (societal values), reef condition and sustainability. Information
regarding regulatory programs is provided, and a few examples are presented to
describe how bioassessment indicators can be incorporated into a regulatory biocriteria
program to conserve coral resources.
VIII
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1.1 of In
Biological monitoring is used to detect status
and change in the health of living organisms and
populations. Health signifies the cumulative and inte-
grated response of organisms to both beneficial and
adverse factors in the environment. The health of
resident communities (biota.) can thus represent the
environmental status of a habitat. Measurement of
biological attributes to represent environmental sta-
tus constitutes a biological assessment (or bioassess-
ment, Table 1-1). Under the Clean Water Act (CWA),
bioassessments can be used to evaluate the condition
of a waterbody and to trigger management action if
the waterbody fails to comply with biological expec-
tations. Expectations are based largely on biological
integrity, or the ability of a waterbody to support
and maintain a balanced, integrated and adaptive
biological system having the full range of elements
and processes expected for its region (Karr and Dud-
ley 1981; Karr 1996). Elements and processes that
compose biological integrity include species compo-
sition, diversity and functional organization compa-
rable to that of natural habitats within the region. In
a regulatory context, biological integrity can be used
to enforce remediation of a waterbody that does not
meet expectations for its designated use.
The environmental status of waterbodies and
the health of organisms inhabiting waterbodies are
determined by the dynamics of physical, chemical
and biological factors in the environment. Natural
environmental factors can cause adverse biological
effects, but biological monitoring programs are pri-
marily intended to characterize the effects of anthro-
pogenic stressors, which include any "man-made
or man-induced alteration of the physical, chemi-
cal, biological or radiological integrity of water"
(CWA 1988). To apply the authority of the CWA
thus requires that indicators be more responsive to
human activities than co-occurring natural factors.
Such indicators, called metrics, exhibit a consistent
and logical change along a gradient of human activ-
ity (Table 1-1). Natural stressors also influence the
condition and sustainability of resources in a water-
body, but natural stresses are regarded as agents of
change in an adaptive biological system.
Bioassessments are used to identify impaired
waters and to measure the success of remedial
actions. Because of this, bioassessments provide a
foundation for development of an important regula-
tory tool, biological criteria (biocriteria). Biocriteria
are benchmark, guideline or threshold values that
describe the expected (or desired) biological integ-
rity of a waterbody. The criteria may be either nar-
rative expressions or numeric values adopted into
state, territory or tribal water quality standards for
assessment thresholds or restoration goals. Section 5
provides some examples of how bioassessment indi-
cators can be used in development of a biocriteria
program.
All bioassessments, including those used in bio-
criteria, are condition measurements that reflect the
cumulative and integrative effects of multiple stress-
ors. They are not exposure, stressor or performance
measurements. Bioassessments complement the U.S.
Environmental Protection Agency's (EPA) traditional
chemical-specific water quality standards because
they can identify impairment from nonchemical and
nonpoint sources of pollution. The combined use
of chemical, physical, toxics and biological criteria
in water quality standards serves to better protect
natural aquatic life and habitats.
Coral reefs occur in waterbodies that provide
a wide variety of values for human society. The
CWA requires that U.S. jurisdictions develop water
quality standards that define designated uses (such
as drinking water, recreation and fisheries) for
navigable waters and institute criteria for protecting
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Stony Coral Rapid Bioassessment Protocol
1-1. Terms used for defining biological
condition
Indicator (sometimes
termed endpoint]
Attribute
A measured characteristic that
indicates the condition of a
biological, chemical or physical
system.
Measurable part or process of a
biological system.
Metric
Multimetric index
Biological integrity
Biological criteria
Attribute empirically shown to
change in value along a gradient of
human influence. A dose-response
context is documented and
confirmed.
An index (expressed as a single
numerical value) that integrates
several biological metrics to indicate
the environmental status of a place.
Exhibiting a balanced, integrated and
adaptive biological system having the
full range of elements and processes
expected for a particular region.
Biological integrity is the product
of ecological and evolutionary
processes at a place in the relative
absence of human influence (Karr
1996).
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 U.S. jurisdictions, they become
legally enforceable standards.
Source: Karr and Chu (1999)
such uses. EPA has developed a national framework
and guidance on tiered aquatic life uses (TALU).
which refines designation of aquatic life uses along
a biological condition gradient. Use designations
stem from political and social considerations as well
as insight and appreciation of ecosystem values (ser-
vices). Prior knowledge of ecosystem services will
help to avoid inappropriately high or low waterbody
use designations. Thresholds derived for biocriteria
are based on conditions at reference sites, historical
data, empirical models and regional expert judg-
ment. For example, bioassessment data from refer-
ence, or minimally impaired, sites might provide
reasonable expectations concerning the structure
and function of the resident biological community
for that particular region.
Pursuant to the purpose of the CWA (section
101|a]), federal and state governments are required
to "restore and maintain the chemical, physical and
biological integrity of the [nation's waters," includ-
ing coral reefs, within U.S. boundaries and territo-
rial waters. The CWA imparts legal authority to
the U.S. Environmental Protection Agency (EPA) to
protect and maintain the nation's waters and water-
sheds and to derive thresholds, such as coral reef
biocriteria, for the protection of those habitats. EPA
therefore plays a key role in biocriteria development
for restoration and maintenance of biological integ-
rity in the nation's waters.
Other sections of the CWA establish various
programs and authorities for implementation of its
goals and objectives. The following are relevant por-
tions of the CWA that rely on biological monitoring
and assessment (CWA 1988):
« Section 303(c)(2)(A) provides statutory authority
for states, tribes and territories to develop water
quality standards that consist of a designated use
that supports aquatic life (e.g., corals) and recre-
ational activities, criteria to protect that use, and
an anti-degradation policy to prevent any fur-
ther loss or degradation in the system. It states,
"...[s]tate water quality standards shall protect
and enhance the quality of water and serve the
purposes of the Act, including protecting and
propagation of a balanced indigenous population
of fish, shellfish, and wildlife [fishable/swim-
mable] and recreation in and on the water."
« Section 304(a) provides statutory authority to
develop biological criteria: "EPA shall.. .develop
and publish information on methods for estab-
lishing and measuring water quality criteria for
toxic pollutants on other bases than pollutanl-by-
pollutant criteria, including biological monitor-
ing and assessment methods."
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1. Bioassessment and Regulatory Monitoring
Section 305(b) establishes a process for report-
ing information about the quality of the nation's
water resources. States and tribes are required
to assess the general status of waterbodies and
identify, in general terms, known or suspected
causes of water quality impairments, including
biological impairments. This information is
compiled into a biennial National Water Quality
Inventory sent to Congress (i.e., 305(b) Report).
Section 303(d) requires that states and tribes pre-
pare and submit lists of specific waterbodies that
currently violate or have the potential to violate
water quality standards, including designated
uses and numeric or narrative biocriteria. Those
waterbodies listed as failing to meet the water
quality standards require a total maximum daily
load (TMDL) designation. The TMDL process
quantifies the loading capacity of a waterbody for
a given stressor and ultimately provides a quanti-
tative means to allocate pollutant loads. A. TMDL
is suitable for chemical as well as nonchemical
stressors, such as sediment deposition or physical
alteration of habitat.
Section 319 establishes a voluntary nonpoint
source control program by which jurisdictions
can control impacts of runoff using guidance and
information regarding different types of nonpoint
source pollution. Bioassessment protocols are
particularly effective for characterizing cumula-
tive and integrated effects of multiple stressors
such as those from nonpoint sources.
Section 402 makes it illegal to discharge any pol-
lutant to waters of the United States from a. point
source unless authorized by a National Pollutant
Discharge Elimination System (NPDES) permit. A
permit is required in any case where a discharger
could cause a water quality violation, including
biological impairments.
Section 301(h) describes a Waiver Program that
allows marine dischargers to defer secondary
treatment if they can show that discharge does
not adversely affect biological communities. As
part of this program, extensive biological moni-
toring is required to detect any effects on the
biological communities.
Section 403(c) requires that all ocean dischargers
provide an assessment of the biological commu-
nity in the area surrounding the discharge.
« Other federal acts that apply to coral reef protec-
tion and biocriteria include the Ocean Dumping
Act (MPRSA), the Rivers and Harbors Act, and
the Coastal Zone Management Act, as well as
various programs adopted by states, tribes and
territories.
Biomonitoring and bioassessment can be
employed in all the above programs, and the Stony
Coral RBP can be used when coral reefs are the
target resource. Biological monitoring is also an
indispensable aspect of problem formulation and
effects characterization in ecological risk assessment
(USEPA 1992).
Because of this high regulatory relevance, bio-
assessment procedures and biocriteria programs
have been recommended for several aquatic sys-
tems. Technical guidance has been prepared for
streams and rivers (Plafkin et al. 1989; USEPA 1990;
Klemm and Lazorchak 1995; Davis et al. 1996; Har-
bour et al. 1999; USEPA 2002), estuarine and near
coastal waters (USEPA 1997; USEPA 2000a), and
lakes and reservoirs (USEPA 1998). A summary of
the purpose and history of bioassessment protocols
and biocriteria is presented in Barbour et al. (1999).
One reason for the success of biocriteria programs
is the development of efficient and informative rapid
bioassessment protocols (RBP; Table 1-2). However,
no bioassessment procedures or regulatory biomoni-
toring programs (such as biocriteria.) have yet been
developed or recommended for protection of coral
reefs.
1-2. The principal underpinnings of RBPs
• Cost-effective, yet scientifically valid, procedures for
biological surveys
* Provisions for multiple site investigations in a field
season
• Quick turnaround of results for management decisions
» Scientific reports are easily translated to management
and the public
« Environmentally benign procedures
Source: Barbour et al. (1999)
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Stony Coral Rapid Bioassessment Protocol
1.2 for
The Stony Coral RBP is designed to provide
inexpensive tools to characterize the condition of
coral reefs and determine whether waterbodies sup-
port biological integrity for a designated aquatic life
use. Data from RBPs have been used (Barbour el al.
1999) to accomplish the following:
« Characterize the severity of waterbody
impairment
• Help identify sources of impairment
• Evaluate the effectiveness of control actions and
restoration activities
« Support use attainability studies and cumulative
impact assessments
« Characterize regional biotic attributes of refer-
ence conditions
Existing RBPs (e.g., Plafkin et al. 1989; USEPA
1997; USEPA 1998; Barbour et al. 1999) advocate an
integrated assessment that compares habitat (e.g.,
physical structure, flow regime), water quality and
biological measures with empirically defined refer-
ence conditions (using reference sites, historical data,
and models). Reference conditions are established
through systematic monitoring of minimally dis-
turbed field sites that represent the natural range of
variation in water chemistry, habitat, and biological
conditions (Gibson et al. 1996). Reference conditions
are important for defining expectations (e.g., best-
case scenarios) and amending those expectations
when conditions are altered by large-scale stressors,
such as global climate change or acid rain, that can-
not be controlled by local management activities.
Several factors are considered in selecting
organisms as biological indicators. Indicator organ-
isms should be reasonably abundant, well-distribut-
ed, easily identified to species and not be subject to
human exploitation (Jameson et al. 1998). The Stony
Coral RBP focuses on a single, phylogenetic group
rather than the multiple taxa of other assessment
protocols. It is an initial effort that can be expanded
to include other taxa as information and procedures
are developed. However, stony corals are a dominat-
ing influence in the reef ecosystem because they
build and maintain the physical infrastructure that
supports all other organisms in the community.
Consequently, they are considered by many to be
primary indicator organisms for coral reef condition
(Birkeland 1987; Brown 1988; Jones and Kaly 1996;
Done 1997; Kramer 2003; Fisher et al. 2007a). Loya
(1972) offered the following justification for a stony
coral focus:
A coral reef constitutes probably the
most complex community of the marine
environment. It is actually an association of
several thousand species of different kinds
of animals which occupy various ecological
niches. A. correspondingly complex com-
munity on dry land is, perhaps, the tropi-
cal-rain forest. Corals constitute the basic
framework and substrate for many other
organisms which penetrate the skeletal mass
(sponges, polychaetes, sipunculides, bivalves
and gastropods). Corals also provide shelter
for many fishes as well as various species of
polychaetes, crustaceans, mollusks and echi-
noderms. It is, therefore, of primary interest
to obtain an adequate understanding of the
coral-community structure as the first step
for a better understanding of the complex
of interspecific relations between corals and
other organisms living in close association
with them (Loya 1972, p. 100)
Stony corals, oysters, seagrasses and other habi-
tat-forming biota are unique in that their survival,
growth and reproduction dramatically influence
the success of the entire community and ecosystem
(Figure 1-1).
The Stony Coral RBP provides a quick, reliable
and inexpensive means to characterize the biologi-
cal condition of coral reefs. It relies on three rapid
observations (colony identification, colony size and
proportion of live tissue) that have been adapted
from existing coral reef monitoring programs. When
combined, these three measurements generate mul-
tiple indicators that characterize the value and sus-
tainability of coral reefs and are likely to be respon-
sive to effects of human disturbance.
Assessment of stony corals using the RBP will
not address all issues relevant to resource manage-
ment. In particular, measurements made only on
stony corals, while reflecting reef status, cannot
directly address questions related to other taxa (e.g.,
overfishing). Moreover, the indicators provide an
instantaneous reflection of grossly observable coral
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1. Bioassessment and Regulatory Monitoring
Figure 1-1. Physical structures formed by reef-building stony corals are inhabited by diverse and abundant biota.
characteristics—they do not provide information on
physiological function or identify causes of impair-
ment. Additional indicators or direct measurements
are needed to identify causes, potential resolutions
and avenues for remediation and restoration. It is
also unlikely that RBP bioindicators will serve as a
conventional early warning system for reef degra-
dation because they might not respond quickly to
environmental change. However, the strength of the
RBP in regulatory monitoring lies in setting levels of
expected conditions that conserve the resource over
a long term. It is anticipated that the Stony Coral
RBP will eventually be integrated with community,
ecosystem function and exposure methods to gener-
ate comprehensive multimetric indices, such as an
index of biotic integrity (Karr 1991; Jameson et al.
2001). Such indices can also be used as biocriteria
and could ultimately fulfill some early warning or
even causal objectives.
1.3
There is great potential for coral reef biocriteria
in U.S. jurisdictions, but implementation requires
scientifically defensible assessment protocols and
monitoring strategies. Numerous workshops and
publications have addressed methods to measure
coral reef condition, usually with a focus on devel-
opment of rapid, reliable, low-cost monitoring
approaches (UNESCO 1984; Aronson et al. 1994;
Rogers et al. 1994; Crosby et al. 1996; Bruckner and
Burrows 2005). The Stony Coral RBP consolidates
and integrates some of these approaches for regula-
tory bioassessment and biocriteria.
Jameson et al. (1998) prepared an overview
of potential methods to develop biological crite-
ria for coral reef ecosystems. In particular, they
evaluated the existing information, the scientific
gaps and underscored the connection among coral
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Stony Coral Rapid Bioassessment Protocol
reefs, seagrass beds and mangrove forests. They
introduced assessment tiers for comprehensive char-
acterization of reef ecosystems; these ranged from
desktop screening of data and information (tier 0)
to rigorous field surveys repeated over time (tier
3). The importance of biological measurements in
marine management programs was emphasized
and biocriteria were characterized as scientifically
sound, cost-effective tools to protect sensitive bio-
logical communities and sustain the chemical, physi-
cal and biological integrity of an ecosystem. Karr
and Chu (1997) provided a template for development
of biocriteria that stressed (1) habitat classification,
(2) metric selection, (3) sampling protocols, (4) ana-
lytical procedures and (5) communication. The tem-
plate was expanded by Jameson et al. (1998) into
a step-by-step procedure (Table 1-3) that provided
a foundation for future development of coral reef
biocriteria.
1-3. Process for coral reef biocriteria
development
1. Preliminary classification of coral reef ecosystem
2. Biological survey
3. Final classification of coral reef ecosystem
4. Metric evaluation and index development
5. Biocriteria development
6. Implementation of a monitoring and assessment
program
7. Protective and remedial management action
8. Continual monitoring and periodic reviews
Source: Jameson etal. 1998
The credibility of water quality standards is
highest when criteria are developed within the con-
text of a scientifically sound, long-term monitoring
program. Achieving a sound monitoring program
requires an initial study, sometimes called a biologi-
cal survey (Table 1-3), to characterize and optimize
the numerous variables that influence a monitoring
design. Variables include metric selection, sample
numbers and sampling unit size, reef classifications,
variability within reef types, management zones,
responsiveness of metrics to gradients of human
activity and expectations based on reference condi-
tion. A comprehensive biological survey will provide
the information to generate a competent and effi-
cient monitoring design and is therefore crucial to
any bioassessment program.
The Stony Coral Rapid .Bioassessment Protocol
addresses only the sampling methods applicable to
development of a scientifically defensible, long-term
monitoring program. Different sampling approaches
are also being examined for use in biocriteria devel-
opment (e.g., American Samoa; Houk et al. 2005).
While this document does not provide guidance on
biocriteria development, there are a few examples
of how RBP indicators can be used for that pur-
pose (Section 5). Reviews of coral reef classifica-
tion systems (Jameson et al. 2003a) and methods to
develop reference conditions (Jameson et al. 2003b)
are already available, and additional guidance on
monitoring designs, waterbody use designations and
selection of thresholds (levels of expectation) for
biocriteria is anticipated.
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2.1
Fossil records Indicate that corals appeared on
Earth more than 400 million years ago (Allen and
Steene 1996). Existing reef-building corals are stony
corals of the Order Scleractinia (Phylum Cnidaria,
Class Anthozoa, Subclass Hexacorallia; Humann and
DeLoach 2002). The primary biological unit of a
coral is the sessile polyp, which reproduces by donal
expansion (multiplication of individual polyps) and
facilitates deposition of a calcium carbonate skeleton
that supports the colony as it grows (Fagerstrom
1987). Colony size and morphology varies among
and within species, often dependent on depth and
hydrologic factors. Corals of many different species
aggregate in communities (Figure 2-1) and establish
complex, three-dimensional architectures that form
a reef (Stoddart 1969). Although coral reefs vary-
in size, type and extent, shallow-water reefs are
generally classified into (1) fringing reefs that are
parallel to and near the shoreline, (2) barrier reefs
that run parallel to the shoreline but are deeper
and sometimes at the edge of the continental shelf
and (3) patch reefs that are small and separated
from adjacent land and reef masses (Humann and
DeLoach 2002; Turgeon et al. 2002; Bruckner and
Burrows 2005). Reef ecosystems include both the
skeletal, or geological, component of corals and its
diverse community of biological residents.
Many shallow-water corals are hermatypic,
or reef-building. They flourish through an oblig-
atory symbiosis of animal tissue (polyps) and
pholosynthelic dinoflagellate algae (zooxanlhellae)
-
''•pjiiiiiii^"- '""lijp ::"*,""*js*iij£i
Figure 2-1.
Communities of stony corals form the architecture of coral
reefs in the Caribbean Sea (left) and Pacific Ocean (above).
-------
Stony Coral Rapid Bioassessment Protocol
belonging to the genus Symbiodinium (Figure 2-2;
Yonge and Nicholls 193'ia, 1931b; Pearse and
Muscatine 1971; Muscatine 1973). Reliance on photo-
synthetic activity of the zooxanthellae limits the
distribution of hermatypic coral to shallow depths
that are penetrated by light (photic /one). The sym-
biotic algae provide organic compounds (sugars)
to coral polyps, which metabolize them for energy
production. This energy is used primarily to facilitate
calcification processes required for growth and main-
tenance of the coral skeleton (Gattuso et al. 1999).
The polyps, in return, provide the zooxanthellae
with inorganic nitrogen, phosphorus and a secure,
well-lit shelter (Goreau and Goreau I960).
Coral reefs occur predominantly in shallow
(50m or less), warm (20 to 30 degrees Celsius) and
generally clear waters throughout the tropic and
subtropic seas (between 30 °N and 30 °S). They lie
adjacent to approximately 100 countries and terri-
tories (Wilkinson 2002), and reefs are estimated to
Figure 2-2. Corals grow through a symbiotic relationship
of coral polyps (top) that are inhabited by
dinoflagellate algae (Symbiodinium spp., often
called zooxanthellae) that can also be free living
(bottom).
cover 284,300 km2 worldwide (Spalding et al. 2001),
or roughly 1 percent of the available area of con-
tinental shelf. Coral surface area coverage within
U.S. jurisdictional waters has been estimated at
19,702 km2 (Boesch et al. 2000; Turgeon et al. 2002).
Coral reefs included in U.S. jurisdictions are distrib-
uted along states, territories, and commonwealths
in the Caribbean Sea, Western Atlantic Ocean, Gulf
of Mexico and Pacific Ocean. Information regard-
ing the U.S. distribution of corals, their manage-
ment and regional condition is contained in reports
produced by the National Oceanic and Atmospheric
Administration (Turgeon et al. 2002; Waddell 2005).
2.2 of
Enormous value is attributed to coral reefs
of the world. Some ecosystem services are linked
to economic outcomes (e.g., fishing, tourism, bio-
prospecting, construction material, shoreline pro-
tection) and are estimated to contribute as much
as $375 billion annually to the world economy
(Costanza et al. 1997; Wilkinson 2002). There are
also social and cultural values attributed to coral
reefs, especially in island jurisdictions (Copp 1950;
Holmes 1974). Other services are related to stability
and integrity of the biological community (e.g., bio-
diversity, trophic complexity, primary production).
Proliferation of human populations along coastlines,
accompanied by resource extraction and water qual-
ity degradation, threatens the sustainability of these
services (Wilkinson 1996). Nearly half a billion peo-
ple, or 8 percent of the total global population, live
within 100 km of coral reefs (Bryant et al. 1998).
This demographic is not without adverse effect.
Coral reefs in Florida and the Caribbean basin
have experienced unprecedented levels of bleaching,
disease and mortality during the past three decades
(Jaap et al. 2000; Wheaton et al. 2001; Gardner et
al. 2003; Kramer 2003). Stressors believed to have
led to this decline include elevated water tempera-
ture, increased exposure to solar radiation, novel
and opportunistic pathogenic microorganisms and
degraded water quality, all of which might be relat-
ed in some manner to global changes in climate,
land use or human activity in coastal areas (Atwood
et al. 1992; Hoegh-Guldberg 1999). The conse-
quences of continued stress on corals are dimin-
ished growth and reproduction, loss of coral tissue,
algal overgrowth of denuded skeleton and eventual
disintegration of the skeleton through biological and
8
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2. Coral Reef Attributes and Services
physical erosion. Loss of coral and coral skeleton
limits the capacity of coral reefs to provide the eco-
system services for which they are valued and has
led to calls for greater resource protection. Principal
benefits and assets of coral reefs are briefly summa-
rized in the following sections.
2.2.1
Coral reef and adjacent open water fisheries
once supplied the major animal protein source for
many island populations (Wilkinson 1996). Coral
reef fisheries, in spite of declining catch per unit
effort, account for about 9 million metric tons of
food worldwide, equal to 10 percent of the world's
fisheries. For some Pacific island and Caribbean
communities, coral reef seafood once provided
more than 80 percent of the animal protein con-
sumed (Pernetta and Hill 1982). High abundance
and diversity of commercially harvested reef fish are
highly dependent on coral structures (Figure 2-3).
The three-dimensional coral skeletons that form the
reef topography provide habilal for fish protection,
predation and breeding (Bruckner and Burrows
2005). Subsistence and recreational fishing, as well
as aquarium trade industries, are therefore tightly
linked to the structural habitat provided by coral
reefs (Luckhurst and Luckhurst 1978; Roberts and
Ormond 1987; Done et al. 1996; Lirman 1999; Fer-
reira et al. 2001; Perkol-Finkel et al. 2006).
Coral reef ecosystems are highly attractive
to tourists seeking relatively pristine, unique and
diverse habitats teeming with colorful and mor-
phologically diverse organisms. Tourism value of
coral reefs includes the aesthetic, recreational and
economic aspects of fishing, boating, scuba diving
and snorkeling al reef locations (Figure 2-4). Socio-
economic conditions worldwide are influenced by-
income derived from tourism (Reaser et al. 2000).
In the Caribbean in 1990. coral reefs provided 2-6
percent of the gross national product for many
island states (Dixon 1993). In Florida alone, reef
tourism brought one million visitors in 1990 and
Figure 2-3. The three-dimensional coral skeletons constructed by stony coral growth provide physical habitat for numerous
recreationally and commercially harvested fish species.
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Stony Coral Rapid Bioassessment Protocol
Figure 2-4. Reef-building stony corals provide physical habitat for diverse and unique biota that have become valuable
tourist attractions.
$46.5 million (Dixon 1993); a more recent study esti-
mated annual visitation for 2000-2001 to be 18 mil-
lion people and an annual use value of $227 million
(Johns et al. 2001). In Hawaii, recreation and tourism
related to coral reefs bring an estimated $364 million
in annual economic benefits (Cesar et al. 2002).
2,2,3
The same coral structures that provide habitat
to marine communities also protect coastal shore-
lines from wave and current erosion (Pernetta 1992;
Costanza et al. 1997). Ecological value from this
natural protection of estuaries, lagoons and pro-
ductive coastlines (Figure 2-5) is substantial. Often
overlooked is the economic value, which could over-
reach the economic impacts of all other ecosystem
services combined—coastal reinforcement and
Figure 2-5. Pacific island surrounded by coral reefs that
protect the shoreline from wave and current
erosion.
10
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2. Coral Reef Attributes and Services
protection barriers were once estimated at $10 mil-
lion per linear kilometer (Costanza et al. 1997).
products
Untapped chemical and pharmaceutical prod-
ucts exist within the diverse biota of coral reef
ecosystems. Extracting novel compounds from
biological organisms (bioprospecting, biomining)
has shown particular promise for human health
applications. Biochemicals produced by many reef
species are currently being used for health care
products, medical procedures, and pharmaceuticals.
About half the potential pharmaceuticals currently
under development are from the ocean (Carte 1996;
Fenical 1996; Hay and Fenical 1996) and many of
these are from coral reef organisms. Because only a
small portion of coral reef biota has been described
(approximately 10 percent; Reaka-Kudla 1996), there
is considerable potential for discovery of novel
chemicals (Adey 2000).
Coral reefs are complex and highly productive
biological systems. A reef is more than an aggrega-
tion of corals—the complex physical structure creat-
ed by corals provides habitat for a uniquely diverse
and interactive biotic community (Figure 2-6). In the
Indo-Pacific alone, there are more than 719 different
species of hard corals and 690 species of soft corals.
This coral community provides essential habitat to
4,000 different marine fish and thousands of inver-
tebrate species (Spalding et al. 2001). In all, it is esti-
mated that roughly a million species are dependent
on, or contribute to, coral reef ecosystems (Reaka-
Kudla 1996).
Although coral reefs are sometimes compared
to tropical rainforests as major storehouses of
Figure 2-6. Coral reefs are highly productive ecosystems and principal contributors to ocean biodiversity.
11
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Stony Coral Rapid Bioassessment Protocol
biodiversity, 32 of the 34 recognized animal phyla
are found on coral reefs compared to only 9 phyla in
tropical rainforests (Wilkinson 2002). Much of this
diversity can be directly attributed to the complex
skeletal infrastructure, which provides a high num-
ber and heterogeneity of habitat niches (Loya 1972;
Sebens 1994; Bruckner and Burrows 2005). Even a
single coral head provides habitat for a rich commu-
nity (Grassle 1973). Reef inhabitants are also relatively
unique, possibly a consequence of geographic and
genetic isolation. Caribbean and Indo-Pacific reefs
have few species in common, and many species are
geographically limited in range (Boesch et al. 2000).
Symbiotic algae (zooxanthellae) that inhabit coral
polyps provide energy through photosynthesis. Zoo-
xanthellae occur at densities of more than lOVcm2
on coral surfaces and are among the dominant pri-
mary producers in reef communities (Muscatine 1980,
1990). Gross carbon fixation of coral reefs is relatively
high (estimated at 700 x 1012 g C/yr globally), and
most of this is quickly and efficiently recycled to
secondary producers within the reefs (Crossland et
al. 1991). Corals thus provide not only the habitat,
but also a portion of the energy for a diverse and
abundant biological community (Lewis 1977, 1981).
2.2,7
Skeletal growth of stony corals requires biologi-
cally mediated precipitation of inorganic carbon.
Carbon is available to symbiotic algae from bicar-
bonate ions dissolved in sea water and from the
respiratory activity of polyps (Muscatine 1990). With
photosynthesis, carbon is fixed and used for gener-
ating new zooxanthellae, respiration and transloca-
tion into skeletal structures (Pearse 1970; Pearse
and Muscatine 1971). Fixation rates have been esti-
mated at 9 kg CaCO3 m2/yr (Chave et al. 1972; Stearn
et al. 1977). The ability to fix inorganic carbon
places corals among those organisms that influence
oceanic CO2 cycling and several related aspects of
seawater chemistry (Kirizie and Buddemeier 1996).
One potential adverse effect of increased CO2 in
the atmosphere (from anthropogenic activities) is
reduced calcification rates in corals (Gattuso et al.
1999; Kleypas et al. 1999).
Degradation of coral skeletons by physical and
biological erosion supplies the surrounding sea floor
with sand and other particulate sediments (Scof-
fin et al. 1980; Hutchings 1986). Thus, coral reefs,
and stony corals in particular, influence substrate
composition throughout the world. Coral sand is
mined for a variety of landscaping and recreational
purposes.
23
Many different biological measurements and
approaches have been used to quantify coral reef
attributes (e.g., Kinzie and Snider 1978; Rogers et
al. 1994; Risk et al. 2001; Bruckner and Burrows
2005). This variety has necessarily spawned a num-
ber of method comparisons (e.g., Weinberg 1981;
Dodge et al. 1982; UNESCO 1984; Chiappone and
Sullivan 1991; Foster et al. 1991; Rogers and Miller
2001; Brown et al. 2004). The two biological indica-
tors most often reported in coral reef assessments
are live coral cover and diversity of benthic cover
(Jameson et al. 1998), both of which have been mea-
sured using a variety of protocols, survey designs
and calculations. Despite the many disparities, all
biological monitoring is intended to promote scien-
tific understanding or inform decisions by resource
managers.
Assessment monitoring compares the existing
condition of a resource with an expected (refer-
ence, target) condition and provides a means to
detect change over time. Assessment endpoints,
the biological indicators, are field measurements or
calculations from field measurements that charac-
terize the attributes of a resource or ecosystem for
interpretation (Table 1-1). The relative merit of each
indicator depends on how well differences in condi-
tion can be detected over time or among stations,
reefs or regions, and how relevant the indicator is to
a management question. If metrics and assessment
endpoints reflect common perceptions of the values,
management decisions are more easily instituted
and enforced (Jackson et al. 2000).
For convenience, existing field measurements
of coral are divided into three categories for discus-
sion—coral condition (biological and physical char-
acteristics of corals), ecological condition (reef com-
munity characteristics) and environmental stressors
(exposure of coral reefs to anthropogenic or natural
stresses). The Stony Coral RBP provides indicators
of coral condition only (see Sections 3 and 4), but
all three categories are summarized in the following
paragraphs. A comprehensive biocriteria program, at
12
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2. Coral Reef Attributes and Services
least as envisioned by Jameson et al. (1998), would
include components from all three categories.
2.3.1
Biological status of corals can be measured in
ways common to most organisms, including meta-
bolic rates (e.g., growth, photosynthesis), health and
life stage. Measurements of live tissue and denuded
skeleton can also be made; a coral colony is com-
posed of multiple interconnected polyps, and the
colony can survive even when large areas of the
polyps have died. Skeletal deposition is an ecologi-
cally important measurement—it represents addi-
tional coral structure and new habitat for the reef
community.
The physical status of coral colonies can be
captured by measurements of three-dimensional
size, shape and structural complexity (e.g.. sur-
face area of hollows, ridges, caverns). Size might
be related to colony age or at least life-stage (e.g.,
new recruit) and can be used to generate size-fre-
quency distributions for particular populations or
for a coral community. The physical status of coral
communities has been depicted through measure-
ments of coral cover (the amount of coral per unit
of sea floor), coral density, relief (height of colonies
in a reef), topography (rugosity or complexity) and
extent. The geographic extent of coral communities
is often used to define the perimeter of a reef eco-
system, which is sometimes delineated using side-
scan sonar (Kendall et al. 2004).
Physical status of corals has been measured on
the basis of independent colonies or their surface
area, and sometimes both are simultaneously quan-
tified (Chiappone and Sullivan 1991). There are dear
benefits to both approaches—surface area methods
provide estimates of skeleton and coral quantity,
and colony-based methods characterize genetically
distinct organisms, each with varying potential to
survive, grow and reproduce. The more versatile
and robust programs, including the Stony Coral RBP,
will incorporate both approaches.
2,3.2
measurements
Many aspects of the reef community can be
measured to characterize ecological well-being. Reef
ecological measurements are important because
they can represent a greater portion of ecosystem
services. Changes in reef communities can reflect
upward or downward trends in sustainability,
which is the retention of reef values over time.
Measurements supporting ecological and community
indicators are both structural (e.g., benthic cover,
diversity) and functional (e.g., productivity,
herbivory).
Benthic cover is among the most-reported com-
munity measurements. Its relevance is rooted in the
concept of competition for space between corals and
macroalgae. When coral tissue dies, the skeleton is
left bare and available for colonization. Macroalgae
can out-compete coral recruits for the substrate if
sufficient nutrient is available and herbivorous fish
and invertebrates (e.g., sea urchins) are lacking
(Hughes 1989; Chazottes et al. 1995; Tanner 1995).
This can result in a shift of community composition
from coral to algal domination (Nairn 1993; Szmant
2002). Such a shift, often linked to anthropogenic
activity, is considered adverse because non-coral col-
onizers contribute to coral bioerosion and eventual
destruction of coral skeletons (Ilutchings 1986).
Whereas ecological and community measure-
ments are important aspects of coral reef condition,
they are subject to interpretations that sometimes
require additional investigation. For example, it
is generally believed that eutrophication leads to
greater algal growth and bioerosion of coral colo-
nies (Hutchings 1986). Yet, sediment runoff, which
often accompanies nutrients from the watershed,
can inhibit algal colonization by covering available
substrate (Hutchings et al. 2005). Similarly, measure-
ment of benthic cover can be misleading as an indi-
cator of coral condition—interpretation of results is
confounded by herbivory, and nutrient availability
and coral loss can occur for many reasons unrelated
to competition with macroalgae. Interpretations of
ecological and community measurements might
require more supporting evidence than can be easily
provided in a rapid bioassessment.
There are numerous natural and anthropogenic
factors that adversely affect corals and coral reefs
(e.g., Richmond 1993; Dubinsky and Stambler
1996; Wilkinson 1996; Hughes and Connell 1999).
Stress generated by exposure to these adverse
factors can be acute or chronic, and repetitive
exposures decrease the likelihood of coral recovery.
Consequences of stress include coral bleaching
(loss of photosynthetic algae, Figure 2-7), greater
13
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Stony Coral Rapid Bioassessment Protocol
susceptibility to disease, diminished growth and
reproduction, and partial or complete mortality.
Anthropogenic coral stressors include efflux of
terrestrial material (nutrients, contaminants, sedi-
ments and microorganisms), resource extraction
(fishing, bio-prospecting), physical damage (divers,
boats), habitat alteration (dredging, coastal develop-
ment) and introduced and invasive species. Stressors
could also include natural conditions such as dis-
ease and wave energy (Turgeon et al. 2002). Storm
wave damage to corals, for example, has been esti-
mated using maximum wave height (Dollar 1982;
Storlazzi et al. 2002; Jokiel et al. 2004).
Climate change is often cited as a coral stressor.
Elevated oceanic temperatures during the past half-
century have been at least partially attributed to
increasing concentrations of greenhouse gases from
burning of fossil fuels (IPCC 2001; Levitus et al.
2000, 2001). Climate change encompasses a variety
of physical and chemical stresses to corals, includ-
ing temperature, ultraviolet radiation, sea level rise,
storm damage and an oceanic carbonate shift that
reduces the ability of corals to deposit calcified skel-
eton. Climate change also influences weather pat-
terns that interact with global changes in land use
to create additional stressors from the watershed
(Figure 2-8).
Exposure measurements are not required for
development of biocriteria and are not explored in
this document. However, exposure measurements
are needed to determine causality when bioassess-
merits reveal an impaired waterbody (USEPA 2000b).
Isolating a single cause of impairment is difficult
because human disturbance is multidimensional.
- "^ 'r-
Figure 2-7. Various stresses upset the symbiotic relationship of corals and can cause a loss of symbiotic algae. This leaves a
colony, such as the Dip/one? strigosa pictured here, with a bleached appearance as the white coral skeleton shows
through the translucent polyps.
14
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2. Coral Reef Attributes and Services
C02
Sea
UVI
TEMP
PAR
Figure 2-8. Several atmospheric and land use changes are occurring at a global scale, with cumulative
and interactive effects on coral reefs. Carbon dioxide (CO2), carbonate ion in sea water
(HCO '), ultraviolet radiation (UVR), temperature (TEMP), photosynthetically active
radiation (PAR).
Because controlled experiments are Infrequently relationships, and Jameson and Kelty (2004) have
possible, linking degradation to cause is often reviewed many potential methods to measure stress
correlative. Beyers (1998) has suggested a weight- exposures.
of-eviden-ce approach to evaluate cause-effect
15
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Stony Coral Rapid Bioassessment Protocol
16
-------
It is no coincidence that indicators of stony
coral condition have been incorporated into nearly
all coral reef monitoring programs. The intent of
any bioassessmenl program is to employ practical,
affordable measurements that generate ecologically
relevant endpoints to support management deci-
sions, enforcement and performance evaluation
(Jackson el al. 2000; Jameson el al. 2001). Stony
corals are directly responsible for most ecosystem
services, so indicators of stony coral condition
are very likely to be informative, transparent and
authoritative.
A principal objective of the Stony Coral RBP is
to provide an efficient, inexpensive, nondestructive
method that generates useful indicators for manage-
ment programs. Three core observations are recom-
mended—species census, colony size and the pro-
portion of live tissue on individual colonies. While
additional observations and measurements are not
precluded, a variety of useful indicators can be cal-
culated from these three observations alone. The
observations have been made in other programs
(for example, Lang 2003; TNG 2006; Bruckner and
Bruckner 2007), but two aspects—colony-to-surface
area conversions and topographic three-dimensional
(3D) surface area—are unique to the RBP.
Most existing methods quantify coral abun-
dance by counting colonies or estimating surface
area, both of which produce indicators relevant to
coral condition. The surface area approach is used
to estimate, for example, the proportion of live coral
cover, whereas a census (colony approach) provides
indicators related to abundance and density. Both
approaches are incorporated in the RBP, which con-
verts size measurements made on each colony to
surface area.
The potential of the Stony Coral RBP to serve
as a regulatory bioassessment protocol has been
examined in a pilot study (Fisher et al. 2007a), a
modified survey of the Florida Keys (Fore et al.
2006a; Fisher et al. 2007b) and an initial biologi-
cal survey at St. Croix. U.S. Virgin Islands (Fore et
al. 2006b, 2006c). Although the RBP has not been
validated In Pacific Ocean reefs, the three core
observations should be relatively straightforward.
Differences in colony morphology, however, could
require unique conversions for colony size measure-
ments and assignment of topographic surface area
(see Appendix A).
3.1
In a coral census, each stony coral colony within
the transect perimeter is identified to species or at
least genus (e.g., English et al. 1994; Allen and Steene
1996; Veron 2000; Humann and DeLoach 2002). Con-
ventions must be adopted in advance to determine
which colonies will be included in the census. For
the Stony Coral RBP, common rules are applied
(Santavy et al. 2001; Lang 2003; Fisher et al. 2007a):
1. Colonies must be greater than 10 cm (any
dimension, including live tissue and denuded
skeleton) to be included in the census. The
main reason for this convention is that smaller
colonies are often difficult to identify and
enumerate, which can lead to long dive times
and more measurement errors while providing
only limited information. Smaller colonies should
be included for recruitment assessments, but in
such cases, a simple tally and a generic surface
area assignment would be more efficient than
measuring each colony.
2. Colonies are included in the census if at least
50 percent of the colony lies within the transect
perimeter. Any colony large enough to span the
17
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Stony Coral Rapid Bioassessment Protocol
transect perimeter should be included, even
if the majority of the colony lies outside the
perimeter.
3. Colonies are included in the census even if the
living portion of the coral is less than 10 cm and
occurs outside the transect perimeter.
•I. Corals are included in the census if they can be
identified at the genus level. Species-level iden-
tification better supports indicators related to
community composition. Inability to identify the
colony, whether because of size, algal overgrowth
or loss of distinguishing characteristics, excludes
the colony from the census.
5. Data (colony size and live tissue estimates) are
collected from the entire colony, not merely from
the portion that lies within the transect perimeter
or only from the tops (aerial view) of colonies.
There are relatively few reasons to exclude a
stony coral species from census. A recent survey
performed in the Florida Keys excluded lesser star-
lei corals (.Siderastrea radians) because they were
small, difficult to count and provided no vertical
relief (Fisher et al. 2007b). Branching fire corals
(Millepora alcicornis) (hydrocorals) were also
excluded because they were more often encrust-
ing than reef-building. In contrast, blade fire corals
(M. complanata) were included because they sup-
plied relatively permanent vertical structure to the
reef. Any exceptions must be clearly documented for
comparability among programs, particularly if the
species occur regularly in the area. While individual
managers might have different objectives, the value
of all bioassessment programs is increased when the
same methods and approaches are used by many.
In most cases, visual distinction of coral colo-
nies is not difficult. Connell (1973) characterized
individuals as any colony growing independent of its
neighbors. Sometimes, however, two colonies of the
same species grow together and the line of separa-
tion is indistinct. If tissue separation is not visible or
two separate morphological shapes are not identifi-
able, this is documented as a single organism (see
AGRRA Program, Lang 2003). Some coral colonies
break, and the fragments form independent colonies.
Although these are genetically identical, they are
regarded as distinct organisms because they have
varying potential for survival, growth and reproduc-
tion. The most difficult challenge is when patches
of live tissue, separated by dead areas, occur on a
colony skeleton. The patches could be surviving
remnants of the colony or could be young recruits.
Unless it can be reasonably concluded that the
patches belong to the same colony, they are consid-
ered independent biological entities (Connell 1973).
3.2 3D
Surprisingly few monitoring programs measure
or even estimate the size of coral colonies. Part of
the reason for this is that many programs use linear
transect methods, rather than a colony-based cen-
sus, to estimate coral cover. Yet, size is an extremely
important coral attribute. Size discriminates the
contribution of each colony and species to com-
munity habitat, biomass, photosynthetic activity.
metabolism and calcium carbonate deposition. Col-
ony size is indispensable when considering growth.
reproduction, population dynamics and community
interactions.
Various means have been used to quantify col-
ony size (Figure 3-1). Some have estimated the cubic
volume of colonies using predetermined size classes
(Fisher et al. 2007a, 2007b), and others have mea-
sured a colony dimension (Lang 2003; Houk 2005).
While measuring is more time-consuming (Figure
3-2), it provides continuous distributions for analy-
sis of population structure. Measurement of three
coral dimensions has been applied in disease stud-
ies (Bruckner and Bruckner, in press), in pilot sur-
veys by the Florida Reef Resilience Program (TNG
2006) and in biocriteria development surveys in the
U.S. Virgin Islands (Fore et al. 2006c). Each of these
studies has measured the same three dimensions:
height (greatest colony distance perpendicular to the
substrate), maximum diameter (planar diameter with
greatest aerial projection onto the substrate) and
width (diameter orthogonal to the maximum diam-
eter measured at the center of the colony). Some
studies have measured maximum width, which does
not necessarily occur at the center of the colony.
Either is acceptable if consistent.
3,2.1 3D
With few exceptions, coral studies have quan-
tified coral surface area in only two dimensions.
Coral cover, for example, is estimated as the planar
projection of colonies on the underlying substrate as
18
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3. Rapid Bioassessment Protocol/or Stony Coral Conditions
Figure 3-1. Colony size has been quantified by visual grading into volumetric size classes (left). In this example colony
(Dipbria strigosa), volume was better approximated by the larger 10L cube than the 1L cube. The surface
area assigned to this colony (five sides of the 10L cube) was 2,3113 cm2. Colony size can also be quantified by
actual field measurement of height (h), diameter (d), and width (w) from an aerial view (right). When analyzed
photographically (Appendix A) this colony measured h = 22.9 cm d = 36.1 cm and w = 29.8 cm, with a surface
area of 1,976.9 cm2.
Rulers and meter sticks can be used to measure
height, maximum diameter and width of
individual coral colonies. Each measurement
brings greater accuracy to size estimates but
requires more underwater time and effort.
19
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Stony Coral Rapid Bioassessment Protocol
viewed from above (aerial view). This approach does
not account for height or structural complexity of
the colony. Among the several reasons to migrate to
3D quantification of corals is the role of topographic
surface area in coral reef ecology. This was empha-
sized by Dahl (1973):
The production, occupation, and
destruction of surface area are, there-
fore, basic reef processes, and the balance
between them is an essential aspect of the
reef ecosystem. The efficient production of
surface is a primary function of many reef
organisms, and the control of surface by
secondary occupants is a basic competitive
force and a major determinant of reef com-
munities (p. 240).
Surface area should be measured along all three
dimensions because all three support these basic
reef processes. A 3D approach provides a more real-
istic quantification of physical structure (community
habitat), live coral (reproduction and growth) and
bare skeleton available for recruitment or erosion.
Energy transfers occur across the epithelial mem-
branes of coral polyps, so topographic surface area
is a rate determinant for photosynthesis, feeding, car-
bonate deposition, growth, and reproduction (Dahl
1973). These physiological and ecological relation-
ships are fundamental to development of useful coral
reef ecosystem and sustainability models, and our
coral measurements should reflect this significance.
Although appealing, 3D values for coral surface
area are not easy to obtain because corals have dif-
ferent shapes. Substantial morphological variation
occurs, even within species and particularly with
depth (Goreau 1963; Barnes 1973). Most procedures
to measure 3D topographic surface area have been
developed for laboratory use (e.g.. Marsh 1970;
Hughes and Jackson 1985; Meyers and Schultz 1985;
IIoegh-Guldberg 1988; Ben-Zion et al. 1991; Stimson
and Kinzie 1991; Tanner 1995). All these laboratory
methods are time-consuming, destructive and unus-
able for rapid underwater surveys.
Several investigators have estimated 3D values
for surface area using geometric surrogates (Szmant-
Froelich 1985; Roberts and Ormond 1987; Babcock
1991; Alcala and Vogt 1997; Bak and Meesters 1998;
Fisher et al. 2007a). New photographic techniques
employ 3D colony reconstruction to estimate coral
surface area with high accuracy (Bythell et al. 2001;
Cocito et al. 2003), and this approach has now been
successfully applied to four species of field corals
(Courtney et al. 2007).
3.2,2 os
Bioassessment monitoring usually character-
izes condition across relatively broad spatial areas.
For these programs, reasonable approximations are
often more effective than accurate measurements
because the time saved by approximation can be
used to increase the number of locations sampled.
Several studies, noted above, demonstrated the use
of geometric shapes to approximate 3D values for
surface area. In most cases, morphological dimen-
sions of the colony were simply entered into the
surface area formula for a representative geometric
shape. For example, the average radius (r) of a
hemispheric colony can be used to calculate 2nr2.
the 3D colony surface area (CSA) of a bottomless
hemisphere (the bottom is eliminated so that esti-
mates are made for only the above-substrate portion
of the coral colony). While many colony shapes are
straightforward, some geometric surrogates might
require experimentation and validation. Various
approaches are reviewed in Appendix A, including
a discussion of appropriate scale and level of accu-
racy. Appendix B addresses the potential conversion
of historical two-dimensional coral data to 3D units.
Ultimately, statistical comparison will play a
large role in developing methodology for different
monitoring programs. For example, three colony
dimensions (height, diameter and width) might be
measured in the first few years of a monitoring pro-
gram; then, analysis of the data might indicate that
only two measurements are needed to achieve the
same programmatic objectives. This was the case
when data were examined from a pilot study of
the Florida Reef Resilience Program (Appendix C).
Monitoring data could also be examined to determine
whether measurements are needed for small colonies.
Because the influence of small colonies on surface
area indicators is comparatively minor, they could all
be assigned the same surface area (e.g., an average
obtained from a subset of small colonies). Regardless
of the strategy, procedures to approximate CSA must
be guided by efficiency (optimal accuracy and survey
time) over the entire course of the survey. This is
true for all aspects of the survey, but it is particularly
important for measurements of colony dimension,
which are relatively time consuming.
20
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3. Rapid Bioassessment Protocol/or Stony Coral Conditions
33
The proportion of live coral tissue on a colony
reflects the cumulative, integrated effect of both
beneficial and adverse environmental factors. Sub-
stantial portions of coral tissue can die without
lethal consequences to the colony (Figure 3-3), but
tissue loss reduces the chance of colony survival and
reduces the capacity to augment biomass through
growth and reproduction. In most studies the dead
proportion of a colony, the portion that lacks tissue
where tissue once existed, is estimated and reported
as partial mortality (Sudara and Snidvongs 1984;
Brown and Howard 1985; Brown 1988; Dustan 199-1;
Ginsburg et al. 1996; Bak and Meesters 1998). Esti-
mates of either live or dead (denuded) coral propor-
tions will serve the same purposes because they are
converse estimates. The RBP uses a live proportion,
percent live tissue (%LT), because the values are
used in calculations for live surface area (LSA). Both
the proportion and amount of live tissue are useful
indicators of colony health.
Several protocols have been used to estimate
the proportion of denuded surface on a colony. Gins-
burg et al. (1996) and Lewis (1997) graded corals
as < 1/3 dead, 1/3-2/3 dead, and > 2/3 dead. Some
have used a quartile system (0-25, 26-50, 51-75
and 76-100 percent live or dead), and the value
for each colony is reported as the midpoint of the
quartile range (12.5, 38, 63 and 88 percent, respec-
tively). Because colonies at the extremes of 0 per-
cent live tissue and 100 percent live tissue can be
easily distinguished, an expanded quartile system
would provide six categories (0, 1-25, 26-50, 51-75,
76-99 and 100 percent; Fisher et al. 2007b). The
Atlantic and Gulf Rapid Reef Assessment Program
(Lang 2003) reports partial mortality in 10 percent
increments in the mid-ranges, and approaching
Figure 3-3. Loss of living tissue on a colony is not necessarily lethal to the colony; it is, however a sign of damage or poor
health, and if substantial portions of live tissue are lost, the colony will ultimately succumb.
21
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Stony Coral Rapid Bioassessment Protocol
extremes progressively reports in 5 percent, 2 per-
cent and, finally, 1 percent intervals.
3.4
for
Drawing from the above information, an RBP
for characterizing condition of stony corals can be
recommended. The protocol is intended for use in
a long-term biocriteria monitoring program, which
requires exploratory biological surveys to inform
and mold the monitoring design and strategy (Sec-
tion 1.2). Biological surveys provide data to address
reef classifications, metric variability, size and num-
ber of sampling units and reference conditions.
Consequently, these preliminary surveys are indis-
pensable to developing an efficient and defensible.
long-term monitoring program.
The following protocol is recommended
(Table 3-1). Three core observations are reported for
each stony coral colony within the transect perim-
eter—species identification, size and percent live
tissue. Trained and experienced personnel should
determine species identification. Initially, size
should be determined by measuring three colony
dimensions, height, maximum diameter and width.
All three measurements should be made until the
effect of reducing the number of measurements
can be determined for each size-related indicator
(Appendix C). Measurements can be eliminated
for consistently small species or for all small colo-
nies—these can be tallied and assigned a common,
approximate surface area. This should not radically
alter results and could save valuable time, especially
in reefs with many small colonies. Larger colonies
should be measured because they have greater influ-
ence on the biological and physical endpoints. Per-
cent live coral can be estimated in 10 percent incre-
ments (recommended), using six categories (i.e., 0
percent, 100 percent and quartile ranges of 1-25
percent, 26-50 percent, 51-75 percent and 76-99
percent) or variable intervals such as progressively
finer intervals near the extremes (Lang 2003). Statis-
tical comparison of endpoints will illustrate which
methods have sufficient accuracy to discriminate dif-
ferences across reef types and management zones.
It is essential that all three observations—
colony identification, size and proportion of live
tissue—be made on every colony that occurs within
the transect perimeter. For example, measuring a
subset of the coral population for size and a differ-
ent subset for percent live coral tissue dramatically
decreases the number and value of indicators that
can be calculated. Consistent data collection and
calculation for each colony ensures that the charac-
teristics and contributions of different species can
be delineated.
3-1. Three recommended core measurements for stony coral surveys
1. Identify colonies in transect to species (or at least to genus)
« Colonies >. 10 cm, any dimension
« More than 50% of the colony is within the transect perimeter or crosses it completely
• Colonies < 10 cm can be tallied (recruitment data)
2. Measure three colony dimensions; height, maximum diameter and width
• Fewer measurements possible as warranted
• Small colonies can be tallied and assigned a common surface area
« Substitute measurements as needed for specific geometric surface area solutions
(e.g., # branches, # columns; Appendix A)
3. Visually estimate the percent live tissue on the colony in 10% increments
• Estimates based on the total (3D) colony surface area
• If preferred, a minimum of six percentage intervals can be used
• Either live or dead proportions can be recorded (converse values)
22
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3. Rapid Bioassessment Protocol/or Stony Coral Conditions
3.5
The recommendation for three core observations
is not intended to exclude others. Measurements of
additional reef attributes should, in fact, be included
if dive time permits. For example, evidence of dis-
ease or coral bleaching (Figure 3-4) could easily be
noted for each colony during the survey. This requires
additional expertise and that surveys be performed at
the same lime each year when disease is at its peak
(index period). If the consequence of recent bleaching
and disease events is an objective, the survey might
differentiate between old and recent tissue mortality
(Lang 2003; TNC 2006). The line tender (Section 3.6)
could conduct a census offish, echinoderms, sea stars
or soft corals within the transect perimeter or in the
surrounding area. These will ultimately be useful for
developing community-based and multimetric biocri-
teria. A potentially valuable addition to the survey is
to make a video recording or a series of still pictures
of the reef or transect—not necessarily to validate
measurements but to visually document changes that
occur over time. This complementary evidence could
be useful for communicating the extent of degrada-
tion or improvement to public stakeholders.
3.6
A radial-belt transect has been used very suc-
cessfully with the Stony Coral RBP. Other survey
approaches, as long as they employ a transect area
(not a transect line), should be equally appropriate.
In previous studies, radial-belt transects were delin-
eated by two circles 8m and 10m from permanent
stakes at each station (Santavy et al. 2001; Fisher
et al. 2007a). A 2-m high center pole is placed over
a short, permanent stake with a lightweight line
attached to a pivot on the upper half of the pole.
One diver, the line tender, holds the line above the
tops of the colonies and pulls the end of the line
away from the stake. Weighted flags or beads are
clipped to the line 8m and 10m from the pole to
mark the 2-m belt width (Figure 3-5). An underwa-
ter buoy is placed at the start point. The line tender
maintains a taut line while the surveyor records all
corals that fall within the 8-1 Om belt marked by the
beads. Both divers proceed around the circumfer-
ence of the circles until reaching the underwater
(start/stop) buoy.
The survey area of the 8m-10m transect is
2 - it82) = 113.1 m2. However, sampling unit
Figure 3-4. Observations of bleaching and disease can be made simultaneously with
measurements for the Stony Coral RBP but require disease expertise. Here, bleaching
from an unknown cause has left a Siderasfrea slderea colony with a mottled
appearance.
23
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Stony Coral Rapid Bioassessment Protocol
A
_.
5R*
Figure 3-5. A radial-belt transect is established with a fixed stake (permanent station) or temporary tripod (left) at its
center. A line is extended from the center and held above the colonies by the line tender (right). Weighted flags
or beads are suspended from the line to mark the 2-m width of the belt transect).
size can be unique to each program and should be
determined from the biological survey. Previous
work indicated that a 50 m2 transect, which can be
obtained from a 3m-5m radial belt, was sufficient to
distinguish significant differences among reefs (Fore
et al. 2006a, 2006c). It is important that the outer
radius of the belt be at least 5m to overcome aggre-
gation of species (Loya 1972. 1978).
A radial-belt transect is suggested for many rea-
sons. (1) It can be established and surveyed quickly.
At permanent stations, the center pole is designed to
slip over the embedded stake (Santavy et al. 2001)
which holds it vertical. For temporary stations (no
stake), a weighted tripod is used to hold the cen-
tral pole vertical. The procedure does not require
multiple lines or grids, and lines do not need to be
moved or re-set for different measurements. (2) A
survey performed using a radial-belt transect reduc-
es the risk of coral tissue damage because the line
tender elevates the line above the colonies. (3) The
sampling unit size can be altered by simply increas-
ing or decreasing the radii of the belt. This allows
the same fixed stations to be used for multiple
objectives. More importantly, it provides a consis-
tent procedure for different sampling unit sizes. It is
possible that large transects (e.g., 8m-10m belt) are
more effective for trend detection (more compara-
tive information), and small transects (e.g., 3m-5m
belt) are more effective for status (more stations can
be sampled). (4) Finally, the radial-belt transect is a
very safe survey approach. Buddy divers are always
close together and one diver, the line tender, is able
to maintain an awareness of the surroundings while
the surveyor focuses on documenting coral condi-
tion. The line tender can also take pictures or tally-
other key reef organisms, such as soft corals, sea
urchins and conchs.
3.7
The Stony Coral RBP was specifically designed
to support bioassessments preformed by jurisdic-
tions with coral monitoring expertise but with lim-
ited resources and personnel. Surveyors are required
to establish transects, identify colonies by species,
measure colony dimensions and estimate the pro-
portion of live coral on each colony. In nearly all
cases, even with high coral densities, stations have
been successfully surveyed by two divers (one sur-
veyor and one line tender) on a single dive. Data
can be entered directly into a spreadsheet with for-
mulas pre-set to instantaneously calculate indicator
values; therefore, feedback on transects and reef
characteristics is immediate. The protocol requires
no costly technical instrumentation or expertise, so
the magnitude of a monitoring program is restricted
only by available surveyors and line tenders. Techni-
cal transfer of RBP methods is uncomplicated, and
data collected by trainees has been found to closely
match data from experienced surveyors (Fore et al.
2006c). Indicators that are generated from the RBP
and their application to coral reef management are
discussed in the remaining sections.
24
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The three core measurements described in Sec-
tion 3 are used to calculate a variety of biological
condition indicators relevant to coral reef value and
sustainability and necessary for regulatory bioas-
sessments. Valuation of the reef and its services, as
reflected in several RBP indicators, is a fundamental
component of use designation. For example, indi-
cators like LSA and taxa richness can identify rich
and healthy reefs that provide abundant ecosystem
services. These reefs would reasonably be assigned
use designations requiring high levels of resource
protection (see Section 1.1). Indicators are also
essential for establishing protective standards. Once
a waterbody use is designated, criteria are estab-
lished to ensure that existing ecosystem services are
sustained or improved. These protective criteria are
based on expected or desired responses of specific
indicators (metrics) that are sensitive to human dis-
turbance. Levels of protection are then derived from
metric values obtained at reference sites. Indicators
are, thus, indispensable elements of regulatory bio-
assessment and their development an essential com-
ponent of any monitoring program.
4.1
Measurements and observations become
indicators when they are used to characterize a
meaningful aspect of coral condition. Although
relatively simple, the three core observations of
the RBP can be used to derive several traditional
and several unique condition indicators relevant to
coral reef value and sustainability. Those described
here (Table 4-1) are not exhaustive—others can be
derived from the same field data (e.g., Fore et al.
2006c) or with additional data. Not all indicators
calculated from the three measurements will be
useful for every management purpose. Indicators
to be used for regulatory action, for example, must
be screened for power of detection and response
to human disturbance (Section 5.1). An important
feature of the RBP is that it provides multiple indi-
cators for screening. During development of bio-
criteria for freshwater streams, only 16 acceptable
fish and invertebrate metrics were identified out of
178 indicators that were screened (Fore 2003). So,
not all indicators will be sufficiently sensitive to
anthropogenic factors, and each might be more or
less responsive under different environmental, reef
and stressor situations. It is a clear advantage then
to calculate multiple indicators from the relatively
simple RBP field observations.
The indicators listed here are condition indica-
tors. It is re-emphasized that condition indicators
do not identify causes of change. Diagnostic assess-
ment is different than condition assessment and usu-
ally employs physical, biomarker, geochemical and
weight-of-evidence approaches to associate coral
degradation with nutrients, sediments, contaminants
and other anthropogenic stresses (Beyers 1998; Risk
et al. 2001). Condition indicators are used to identify
impaired waterbodies, and exposure or diagnostic
indicators are used to identify the cause of impair-
ment. Exposure and diagnostic indicators have been
reviewed (Jameson and Kelty 200-1) and are not dis-
cussed here.
Many traditional and some novel coral indica-
tors are provided by the RBP. Novel indicators are
largely drawn from 3D CSA estimates, which are
used to calculate total surface area (TSA), live sur-
face area (LSA) and other indicators that incorpo-
rate these values. One such indicator, 3D total coral
cover (3DTC), could be used to supplant the con-
ventional chain-transect method for estimating coral
topography (i.e., rugosity, Appendix B).
For organizational convenience, indicators are
introduced in categories of abundance and com-
position, physical status and biological condition
(Table 4-1). All are derived from the three core mea-
surements: Abundance and composition are derived
25
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Stony Coral Rapid Bioassessment Protocol
Table 4-1, RBP coral condition Indicators1
Abundance Composition
Abundance: number of colonies
Density: number of colonies per m2 sea floor
Relative species abundance: abundance of a particular species per total abundance
Species (taxa) richness: number of species occurring in a reef or region
Species frequency: proportion of sites where a species occurs
Species diversity: index of taxa richness and relative abundance
Protected species: richness and abundance of protected coral species
Community composition: relative richness or abundance of a species or group of species with some discretionary biological or
physical attribute (e.g., tolerance)
Physical Status
Colony surface area (CSA): 3D skeletal surface area of an entire colony (m'-)
Total surface area (ISA): I CSA for all colonies at a transect, station or reef
3D total coral cover (3DTC): TSA per m2 sea floor
Average colony surface area (AvCSA): TSA / # colonies
Population structure: colony size distribution for a species compared to colony number or other attribute
Community structure: colony size distribution for all species compared to colony number or other attribute
Biological Condition
Percent live tissue (%LT): proportion of live coral tissue on each colony
Average percent live tissue (Av%LT): I %LT / # colonies
Colony live surface area: live tissue on a colony (mj) = CSA x [%LT / 100])
Live surface area (ISA): ! colony live surface areas at a transect, station or reef (m2)
3D live coral cover (3DLC): LSA per m2 sea floor
Percent Live Surface Area (%LSA): comparative ratio of live and total surface area = ([LSA / TSA] x 100)
1 Indicators are derived from three core observations on stony coral colonies and can represent cumulative or average values for
transects, stations and reefs or for a particular species or group of species.
from coral identity, physical status from colony size
and biological condition from proportion of live tis-
sue (%LT). Indicators are calculated from observa-
tions on individual colonies and combined to obtain
cumulative or average values for transects, sites,
reefs or a particular species.
4.1.1
composition
Coral abundance and species composition
varies from region to region, reef to reef, and even
within a reef Composition can be influenced
by depth, hydrologic patterns and a variety of
other environmental conditions. The stony coral
community can thus be characterized by the
presence and abundance of different species.
Because colonies are identified to species in the
RBP, values can be aggregated for community
characteristics or applied to distinct populations.
Indicators related to abundance and composi-
tion are calculated from the transect census. Abun-
dance is simply the number of distinct, independent
coral colonies and does not account for size differ-
ences. Abundance can be represented by density,
which is abundance normalized by the area of sea
floor surveyed (number of corals per m2 sea floor).
26
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4. Stony Coral Condition Indicators
Coral density characterizes the proximity of colo-
nies to one another—a factor that affects disease
epizootiology (transmission of infective agents),
sexual reproduction (dispersion of gonochoric gam-
etes) and recruitment (settling of planula larvae).
Coral abundance can be differentiated by species to
obtain relative species abundance, which is the
proportion of colonies for one species relative to the
abundance of all species combined. This indicator is
apparently useful even with patchy distribution and
large population shifts (Jameson et al. 2001).
Species identification is used to characterize
coral community composition. The total number of
species encountered in a reef is reported as species
richness or taxa richness. This attribute is often
used to demonstrate the ecological complexity of
a community. Species richness is not generally cal-
culated for single transects because it is meaning-
ful only for relatively large spatial areas (Magurran
1988). Because it generally increases with greater
sampling effort, species richness is sometimes
assigned the asymptote of the rarefaction curve.
which depicts the number of new species encoun-
tered with additional transects (Peet 1974; Aronson
et al. 1994). In some instances, species richness has
been reported as the number of species per unit
area of sea floor (Chou 1984). However, while pro-
viding some spatial context, this endpoint is also
influenced by the sampling unit size and number
of sites surveyed. Species frequency is the propor-
tion of sites, relative to the overall number sampled,
where a particular species occurred. This indica-
tor is a presence-or-absence observation and does
not physically quantify coral abundance or colony
size. While infrequently used, species frequency is
intended to characterize the geographic distribution
and range of a species.
A species diversity index is often suggested
as a means to integrate species richness and rela-
tive abundance (or evenness among species); it
characterizes the variety and abundance of different
types of organisms that inhabit an area. The index
incorporates the number of species present and the
proportion of individuals in each species. There is
greater diversity for reefs with more coral species,
and there is greater diversity for an even distribu-
tion of individuals among the species. Many diver-
sity, evenness and community similarity indices are
available (Simpson 1949; Pielou 1966; Chou 1984),
but the one that is most often cited is the Shannon
or Shannon-Weaver Diversity Index (Shannon 1949):
Diversity Index (//') = - \(Pi x lnl\) + (P, x InP,} +
(P. x InP.) .... (Pn x lnPnJl
where In is natural log, P is the proportion of indi-
viduals of each species relative to the total number
of individuals in species 1 through n. Because P is
a proportion of the total, diversity does not express
the actual abundance of any species—a reef with
many colonies could have the same diversity as a
reef with few colonies. Stony coral diversity can be
calculated using proportions of individuals, propor-
tions of live coral cover (Chou 1984; Aronson et al.
1994), proportions of total skeletal surface area and
proportions of live coral surface area (Fisher et al.
2007a), each potentially addressing a different infor-
mation need. Aronson et al. (1994) recommended
that diversity indices should be calculated from coral
cover because of the vast size differences among
coral colonies and because colony fragmentation
and fusion obscure the identification of individuals.
Although still widely reported, species diversity indi-
ces have several disadvantages (Hurlbert 1971) and
are often replaced with species richness and relative
species abundance. These indicators provide the
same information and are less ambiguous (Karr and
Chu 1999).
The number and abundance of protected spe-
cies are particularly important in waterbody valua-
tion because listed species carry special protection
requirements. Several potential indicators stem from
community composition data, which describe rich-
ness or abundance of a species or a group of species
on the basis of some discretionary characteristic. As
environmental conditions change in a habitat, com-
munity composition might shift from intolerant to
tolerant, from large to small, brooder to broadcaster
or from slow-growing to fast-growing species.
4.7.2
Indicators of physical status are derived from
estimates of colony size. Colony size is important—
larger colonies and larger reefs increase the protec-
tion of shorelines from erosion, the habitat available
to reef communities, the amount of calcium car-
bonate sequestered by coral skeletons and, assum-
ing a high proportion of live tissue, the amount of
live coral available for photosynthesis, growth and
27
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Stony Coral Rapid Bioassessment Protocol
reproduction. Colony size is also an important ana-
lytical tool. For a particular species, size is generally
related to colony age, and size-frequency distribu-
tions can provide insight to historical and possibly
future condition.
Colony surface area (CSA) is the 3D topo-
graphic surface area of the entire colony, includ-
ing both living and denuded portions. Volumetric
size classes or measured colony dimensions can
be converted into estimates of 3D CSA (m2) using
geometric equations or conversion factors defined
by colony morphology (Section 3.2; Appendix A).
Total surface area (TSA) is a summation of CSA
for all colonies in a station or reef and reflects the
coral surface area available as community habitat.
TSA normalized by transect area (TSA per m2 sea
floor) becomes 3D total coral cover (3DTC), which
is an indicator of stony coral topography and com-
plexity. It is calculated from stony corals only and
does not account for rocks, ridges, mounds, spurs,
grooves, crests or other physical structures that also
provide sea floor complexity. If overall reef relief is
a monitoring objective, the chain transect method
(Appendix B), which is sometimes used to measure
2D contours of both coral and non-coral structures,
can be employed (Porter 1972; Risk 1972). TSA can
also be normalized by the number of colonies at a
station or reef to obtain an average colony surface
area (AvCSA; mVcolony).
Physical data on individual coral colonies pro-
vide several avenues to examine population struc-
ture. Colony size, at least within a species, is a prac-
tical reflection of relative colony age (Connell 1973;
Hughes and Jackson 1980; 1985), so analysis of the
number of individuals within a particular size class
(size-frequency distribution) can reflect changes that
have occurred in the population over time. Popula-
tion structure can also be analyzed as size-surface
area (Figure 4-1) because the RBP provides 3D CSA
estimates. Size-frequency characterizes the numeric
relation between small and large (presumably young
and old) colonies and size-surface area characterizes
the distribution of surface area between small and
large colonies. Similar comparisons can be made
for changes in %LT over various size distributions
as an indication of size-related condition of colonies
(Section 4.1.3). A size-frequency distribution of all
colonies in the reef, regardless of species, represents
the community structure, which reflects the het-
erogeneity of coral sizes available for habitation by
fish and invertebrate populations.
Several indicators of biological condition are
derived from estimating the proportion of live tissue
on a coral colony. Percent live tissue (%LT) reflects
the cumulative influences of beneficial and adverse
environmental conditions. The converse observation,
partial mortality (%), has been reported in many
studies (Brown and Howard 1985; Brown 1988;
Dustan 1994; Gome/ et al. 1994; Ginsburg et al.
1996; Lewis 1997; Endean et al. 1988; Lang 2003). It
is important to note that, while the two perspectives
are converse, estimates of partial mortality are often
made from 2D aerial perspectives (tops of colonies)
rather than the whole colony.
Estimates of percent live tissue (%LT) on indi-
vidual colonies can be averaged for a station or reef
(Av%LT). This indicator does not account for colony
size but characterizes the average condition of indi-
vidual colonies across a reef. Just as important, %LT
is used to calculate colony live surface area (= CSA
x [%LT / 100]), which reflects the amount of coral
tissue on a single colony. Single colony values can
be summed to obtain the live surface area (LSA)
on a transect, station or reef that is available for
growth, reproduction, and colonization by photo-
synthetic zooxanthellae. LSA can be normalized per
unit of substratum to generate 3D live coral cover
(3DLC; m2 live coral per m2 sea floor). This indicator
can be compared with historical two-dimensional
(213) live coral data using coarse conversion factors
or geometric surrogates (Appendix B). Or, if diame-
ter and width measurements are made on each coral
colony, the traditional 2D LSA can be directly calcu-
lated from RBP measurements. Percent live surface
area can be calculated as a convenient means to
compare live and total 3D CSAs (%LSA = [LSA / TSA]
x 100) of colonies within transects, reefs or regions.
Unlike Av%LT, %LSA incorporates CSA (m2), so larg-
er colonies in the reef have a greater influence on
the indicator value. This calculation is similar to pre-
viously reported vitality indices (Brown and Howard
1985; Brown 1988; Dustan 1994; Gomez et al. 1994;
Ginsburg et al. 1996) but incorporates 3D, rather
than 2D, colony measurements.
28
-------
4. Stony Coral Condition Indicators
-
.2
o
o
u
*
120 if
100 1
80 -i
60--
40 -h
20 ~f
0 -!-
Z::::::/
1
/.
: -f=.
I:::,:::::::
10
2
;; .^la
y '~J f |^J --£? jip
50 100 200
(I)
25-
20-
15-
10-
5
0-
-
I P, E5P
1 10 50 100 200
Size Class (L)
Figure 4-1. Population structure (size-frequency) diagrams of Diploria divosa determined from a pilot study in Dry Tortugas
(Fisher et al. 2007a). Population structure analysis can be performed using colony data (size-abundance, left) or
surface area data (size-surface area, right). In this study, corals were graded into five different volumetric size
classes (L = Liters).
4,2 tO
Indicators generated from the Stony Coral RBP
are linked to the values (services) and sustainabil-
ity of coral reefs. Because stony corals are respon-
sible for the physical infrastructure of coral reefs,
measurements that characterize their physical and
biological condition explain key attributes and func-
tions of the reef ecosystem (Section 1.3). Linkage to
resource value supports designation of waterbody
uses and facilitates the communication and enforce-
ment of management and regulatory activities.
Indicators developed for management applications
should have both ecological significance and strong
ties to ecosystem values. The latter is a clear asset
for public understanding and acceptance of manage-
ment decisions to protect the resources (Suter 1990;
Gentile and Slimak 1992; Fisher et al. 2001). Indica-
tor linkage to sustainability is essential for estab-
lishing conservation benchmarks and targets. Stony
coral protection is intrinsic to coral reef protection:
it is very unlikely that reef values will be sustained
if stony corals are not protected (Figure 4-2).
42.1 to reef
The physical structure provided by corals as
community habitat is fundamental to the renowned
biological abundance and diversity of coral reef
ecosystems (Section 2.2). Coral structure is there-
fore indirectly responsible for substantive economic
benefits, including fishing and tourism. The amount
of coral structure available for habitat is represented
by two indicators, TSA and 3DTC, both of which are
derived from 3D CSA estimates. Recreational and
subsistence fisheries benefit from coral species rich-
ness and community structure (McCormick 1.994).
Tourism benefits from coral communities with high
abundance, density, species richness, species diver-
sity, protected species, and reefs with high CSA—all
valued by divers and snorkelers. Several ecosystem
functions are represented by the RBP indicators.
ISA and 3DLC characterize the quantity of live coral
polyps potentially able to support zooxanthellae,
grow and reproduce.
All these indicators can be considered when
establishing designated uses for waterbodies. For
example, if 80 percent of coral species found in an
entire region occur at a single reef, if a threatened
species is present or if reef topographic complexity
is high, the reef might become a high priority for
management protection.
42.2 to
sustainability
The proportion of live tissue on a coral colony
(%LT) is a simple indicator of colony health. It does
not indicate the physiological health of the remain-
ing live tissue, but it reflects the cumulative loss
of tissue relative to the colony's status at its peak.
Hughes and Connell (1999) surmised that some
level of tissue mortality is expected as corals grow-
larger; however, large portions of denuded skeleton
undoubtedly signal a serious decline from an earlier
29
-------
Stony Coral Rapid Bioassessment Protocol
Figure 4-2. Stony corals form the infrastructure of a coral reef habitat and all biological and physical ecosystem services are
obtained directly or indirectly from their sustained existence.
condition. Percent ISA also reflects colony health by
comparing amounts of live and total coral. Percent
LSA is the conceptual converse of a mortality index
(dead coral coventotal coral cover) proposed by
Gome/, et al. (1994) and based on 213 planar estimates
of tissue loss. Either calculation could, be used to illu-
minate a contention of Ginsburg et al. (1996) that less
living than dead coral would be evidence of serious
reef decline. In a pilot survey at Key West, Florida,
Acropora palmata and several sampling stations
exhibited %LSA lower than 50 percent (Figure 4-3).
Changes in reef condition might also be
revealed by changes in coral community composi-
tion, which characterizes the distribution, arrange-
ment and abundance of different coral species (Loya
1972, 1976) and could include consideration of size
(Rylaarsdam 1983), recruitment (Porter et al. 1981)
and mortality (Hughes 1996). Community com-
position encompasses several possible indicators
relevant to different situations. Fewer species, less
diversity, a shift to more tolerant species and dimin-
ishing abundance of rare species could all indicate
degrading environmental conditions (Jameson et
al. 2001). It is likely that highly fecund, fast-grow-
ing and generally short-lived genera such as Forties
and Agaricia will prosper after an environmental
disturbance (Tomascik and Sander 1987). Aspects
of coral community structure have been used to
characterize spatial zonation of corals (Loya 1972;
Odum and Odum 1955), effects of specific stressors
(e.g., Odum and Odum 1955; Loya 1976; Porter et
al. 1981; Hughes and Jackson 1985; Done 1992; Bak
and Nieuwland 1995) and even to propose a zoning
strategy for marine reserves (Reigl and Reigl 1996).
LSA is linked to reef sustainability because it
indicates the physical potential for coral growth and
reproduction. Large corals produce more tissue in
absolute quantities than small corals growing at the
same rate. More live coral also means that greater
biomass is available for gamete production. In fact, a
threshold colony size (live tissue) might be required
for successful reproduction (Kojis and Quinn 1985;
Szmant-Froelich 1985; Soong and Lang 1992; Soong
1993).
30
-------
4. Stony Coral Condition Indicators
500 -
400
~ 300 -
E
2 200-
100-
* Species
25% ISA
50% ISA ,'' I
175%ISA_ ^-"
,f""""
„""""' .---- — " •
PAST,^^^_,,--«"'" . • '
jrftll^-MCAV""""
0 100 200 300 400 500
TSAm2
200 -
150
100-
50
Species
-25% ISA
-50% USA
75% ISA
WS02^.-
::.--**""
VRKOI...
SO
100 150
TSAm2
SK01
200
Figure 4-3. Comparison of TSA and ISA (m2) documented for different species (left) and stations (right) from surveys
performed at 14 stations near Key West, Florida. Lines represent 25%, 50% and 75% values for %LSA. Elkhorn
coral, Acropora palmata (ARAL) had the greatest TSA of all species encountered at these stations, but %LSA was
less than 50%. Other species, including Montastmea faveolata (MFAV), Siderastrea siderea (SSID), M, cavernosa
(MCAV) and Ponies astreoides (PAST) provided substantial surface area to the reef. The PAST population
retained a %LSA greater than 75%. Station SK01 had the highest TSA but less ISA than station WS02. Percent
ISA was less than 25% for station RK03 and greater than 75% for WS02. Source: Fisher et al. (2007b).
For reef sustainability, new coral skeleton must
be deposited (whether by growth or recruitment) at
least as fast as it is degraded (Ilutchings 1986). The
Stony Coral RBP does not provide growth and deg-
radation rates, but it does estimate the quantity of
live coral with potential for growth and, conversely,
the quantity of dead coral surfaces vulnerable to
erosion. As sustainability models are developed,
growth rates (Lewis et al. 1968; Buddemeier and
Kirizie 1976) and degradation rates (Hatchings 1986)
for particular species, reef types and geographic
zones will become critical information.
Insights to reef sustainability can also be
gained from examination of population structure,
or the size-frequency distributions of different spe-
cies (Babcock 1991; Bak and Meesters 1998). For
example, the number of small (young) colonies (e.g.,
Figure 4-1) could indicate recruitment success and
represent the foundation for future growth. Patterns
of population structure are likely to be influenced
by chronic environmental degradation (Meesters
et al. 2001). Another indicator that can be derived
from population structure is size-related condition,
a comparison of %LT with the size of the colony. For
example, Lewis (1997) analyzed Siderastrea siderea
to demonstrate declining proportions of live tissue
on larger colonies, a finding that is apparently quite
common (Hughes and Connell 1999; Figure 4-4).
Bak and Meesters (1998) used the same approach to
compare mortality patterns of various species.
High species diversity usually implies integrity
and stability in a community (Odum 1971). This
association has been controversial (Hurlbert 1971;
Peet 1974; Karr and Chu 1999) and has not been
well-documented or defended for corals (Rogers et
al. 1983). The use of species richness and relative
species abundance could capture the same inform-
ation with less ambiguity (Karr and Chu 1999).
High species richness and even distribution of
colonies among species is believed to maximize
resource acquisition al different trophic levels, retain
resources within the ecosystem and reduce the
risk of dramatic changes in ecosystem processes in
response to directional or stochastic variation in the
environment (Chapin et al. 2000).
Indicators calculated from RBP observations
could eventually be applied to sustainability models.
Protocols that do not incorporate colony number or
colony size or provide only 2D CSA estimates will
contribute little to dynamic ecosystem models. At
a mini mum, useful models will require estimates
of physical reef structure that serves as habitat,
biomass to estimate the potential for coral growth
and reproduction, and rates of skeletal accretion
and erosion. Ultimately, sustainability models will
improve use designation and protection criteria by
incorporating projections of future coral condition.
31
-------
Stony Coral Rapid Bioassessment Protocol
so-
so-
v 70
a eo-
«J
40
30
20-
10-
0
1 10 50 100
(L)
200
Figure 4-4. Colonies of Acropora palmata (dark bars) exhibited much lower %LT
for middle and large size classes (> SOL volume) than colonies of
Montastraeafaveolata (light bars) on reefs near Key West, Florida. The
data were collected in 2003; hurricanes, bleaching and disease before
the survey are likely to have caused severe damage to existing colonies.
Colonies apparently recruited after the damage (< 10L volume)
exhibited higher %LT. Source: Fisher et al. (2007a).
4.3 to
Most of the Stony Coral RBP indicators are
familiar to coral reef researchers and resource man-
agers. For example, indicators derived from spe-
cies identification and enumeration can be found
throughout the literature. These have been mea-
sured using quadrats, point-quarter methods (Loya
1978; UNESCO 1984; English et al. 1994), line tran-
sects (Loya 1978), belt transects and video transects
(Jaap et al. 2000; Wheaton et al. 2001; Brown et al.
2004; Jokiel et al. 2004). The various methods have
led to some inconsistencies; for example, reports
of species diversity have been calculated from both
colony number and live coral cover (Aronson et al.
1994). Indicators related to the proportion of live
tissue are less frequent, but all apply some categori-
cal system for estimating percent live tissue and
denuded skeleton on individual colonies (Grigg and
Dollar 1990; Dustan 1994; Gomez et al. 1994; Gins-
burg et al. 1996; Meesters et al. 1996; Lewis 1997;
Lang 2003; Fisher et al. 2007a). Largely because of
its use in the Atlantic and Gulf Rapid Reef Assess-
ment Program (Lang 2003), most coral research-
ers are well aware of partial mortality and related
measurements.
Methods to quantify coral size are less fre-
quently incorporated. One reason for this could be
the highly favored, linear-transect method to estimate
2D projected surface area from an aerial view. The
linear-transect method does not always account
for individual colonies, much less the size of those
colonies. Yet, both surface area and colony indicators
represent attributes useful for characterizing coral
condition. The Stony Coral RBP capitalizes on
geometric surrogates to obtain surface area from
colony measurements (Appendix A) and thereby
takes advantage of both surface area and colony-
based indicators. Geometric surrogates provide 3D
CSA estimates, which improves traditional indicators
of live coral cover and topographic complexity.
Historic 2D data, however, must be converted to
3D values for comparisons (Appendix B).
32
-------
Indicators derived from the Stony Coral RBP are
useful for characterizing coral condition, but their
ultimate significance will be realized through regu-
latory monitoring programs that establish a direct
link between indicator responses and regulatory
action. Section 1 described the many regulatory pro-
grams and objectives that can benefit from the RBP.
This section describes two examples of how RBP
indicators can be evaluated and applied to biocrite-
ria monitoring, a regulatory tool with high potential
for protection of coral reefs. The examples include
metric screening and developing an effective and
defensible monitoring strategy. There are many other
aspects related to biocriteria development that are
not addressed here but will be the subject of future
guidance. A brief summary of monitoring terms
used in this section is provided (Table 5.1).
5.1 to
The CWA is intended to protect resources
against human-induced decline, not decline result-
ing from natural environmental change. Intrinsic to
a biocriteria program then is the need to ascertain
and document which indicators are most affected
by anthropogenic stressors. No matter how compel-
ling the underlying biology for particular indicators
might be, only those that represent human-induced
degradation can trigger management action. Biocri-
teria programs, consequently, are derived from these
indicators, which are then called metrics.
Evaluating indicators for response to human
disturbance can be relatively straightforward (Fore
et al. 2006b). An area of human disturbance is
located, and sampling sites are selected at and away
from the center of the area to represent a stressor
gradient (Figure 5-1). If the bioindicator changes in
a consistent and logical manner across this gradi-
ent, it is very likely responsive to the disturbance.
Spacing of the stations depends on the intensity and
scale of the disturbance, and stations are selected by
judgment, not probability (Section 5.2.3). Repetition
of the sampling gradient for each reef type or habi-
tat will increase confidence in the results. For many
situations, it might not be necessary to document
the exposure (e.g., quantify the sediment, nutrients,
or contaminants) as long as a point source or area of
human activity is localized and apparent. However,
water quality measurements might lead to identifica-
tion of which stressors are causing the impairment.
5-1. Terms used in the development of monitoring programs
Status: An estimate, or snapshot, of existing resource conditions; e.g., the live coral cover within a region.
Trend: Change in resource condition over time; e.g., the 3D live coral cover declined by x% over S years.
Target population: The resource about which information is needed, including a precise definition of the elements of the
resource to be measured and a description of their spatial distribution; e.g., stony corals greater than than 10 cm in size living in
the near shore environment of St. Croix island at a depth less than 10 meters.
Sampling unit: The individual item or area that will be measured or characterized during sampling; e.g., all the stony corals
existing within a belt transect. The sampling unit is also called the population element.
Probability-based survey design: The process of selecting data collection sites where every site or element of the target
population has a known, nonzero probability of being selected.
Adapted from EPA Aquatic Resources Monitoring: http:llwww.epa.govlnheerllarmlterms.htm
33
-------
Stony Coral Rapid Bioassessment Protocol
_ Industrial area
Stations
Different habitat
Area of disturbance ~100 m
\
A
Figure 5-1. To test which indicators can serve as metrics,
sampling is targeted across a gradient of
human disturbance, such as an industrial area.
Metrics will show a consistent improvement in
coral condition for stations increasingly distant
from the center of disturbance.
Source: Fore et al. (2006b).
8
.2
*
/
6
5
4
3
2
1
* CO
O
*
o
• • *
« * *
* *
•
o o o o o
o o o
from (m)
6
#»»%,
1= 5
* *
According to Karr and Chu (1999), taxa rich-
ness has been found to be consistently responsive to
human disturbance gradients in freshwater systems.
However, a biological survey of corals along the
southern shore of St. Croix found TSA more respon-
sive (Fore et al. 2006c; Figure 5-2). It is noted that
this approach could selectively identify only those
metrics that are responsive to point-source, rather
than nonpoint sources. Also, it is difficult to apply
this approach to screen mobile Indicator organisms
(e.g.. fish) that could move in, out and within the
disturbance gradient.
There Is no limit to the number of indicators
that can be screened or metrics that can be used
to develop biocriteria. Indicator responsiveness Is
likely to vary with different reefs, coral communi-
ties and human stressors. A clear benefit of the RBP
is that the same three core measurements provide
several indicators, any one of which could serve as a
metric in a variety of different circumstances.
(m2)
Figure 5-2. Coral condition indicators measured at
increasing distances from the center of human
disturbance (industrial docks at St. Croix,
USVI) showed species richness (top) to have
a less consistent response than total 3D CSA
(m2; bottom). Source: Fore et al. (2006c); open
(> 6 m) and closed (< 6 m) points represent
different depths. Prevailing currents moved
west (left on graphs).
34
-------
5. Application o/RBP Indicators in Regulatory Monitoring
5,2 a
The first step toward developing a defensible
biocriteria monitoring program is to evaluate and
document the metrics that could be used (above).
Next, it must be determined which of these can
detect significant change associated with human
influence. This requires a monitoring program
optimized around the variability of the metrics, the
number of management zones and reef types, the
objectives of the program and the monitoring capac-
ity of the resource agency Consequently, the moni-
toring strategy is generated in iterative steps, start-
ing with preliminary studies (biological surveys) of
the target population.
5.2.1
Data collected from individual sampling units
(stations) need to be sufficient to characterize con-
dition and detect differences at a level relevant to
the monitoring objectives but within the resource
constraints of the monitoring agency. Metrics that
are highly variable will require larger sampling units
or more sampling stations to detect differences.
The size of the sampling unit can be determined by
comparing variances obtained with different sized
survey transects. In the U.S. Virgin Islands, the size
of radial-belt transects was examined by comparing
variances among transect quadrants, which were
established by placing subsurface buoys N, S, E, and
W of the transect center (Fore et al. 2006c). Data
were examined for variance differences between
one-quarter, one-half and three-quarter transects
with the full transect. They found that a full tran-
sect did not appreciably improve (decrease) variance
over a half transect; sampling only half of the radial
transect reduced sampling time substantially.
The number of stations to be sampled can be
investigated through power analysis. In the above
study (Fore et al. 2006c), power analysis was per-
formed to calculate the minimum detectable dif-
ference for each candidate metric as it related to
the number of stations sampled. In this example
(Table 5-2), colony number would have to change by
17 for statistical significance (p = 0.1 for a one-sided
ttesf) if five stations were sampled in a reef type or
management zone, but this minimum detectable dif-
ference would decrease to 12 and 9 colonies if more
stations (10 and 15, respectively) were sampled. Taxa
richness would have to differ by three species if five
stations were sampled, but only by one if 15 stations
were sampled. In all cases, a higher sampling effort
lowered the mean detectable difference (increased
the sensitivity of the metric). Yet, more sampling
increases cost in time and effort, so resource manag-
ers must optimize these factors in the monitoring
strategy. It is possible, too, that minimum detectable
differences for certain metrics are too high to have
any functional relevance to reef management.
5-2. Station effects on minimum detectable
differences (MDD)1
# Colonies
s Taxa
% Live coral (colonies)
Total SA (nf)
Living SA (rrr)
• % LSA
Average colony SA (m2)
17
3
13
4
4
20
0.34
12
2
9 I
3 1
3 1
20
0.23 I
9
1
7
2
2
10
0.19
^ViDD were calculated from a biological survey in St. Croix, U.S. Virgin
Islands; values represent how much a candidate metric would have to
change for statistical significance (p = 0.1 for a one-sided t test) if 5,10,
or 15 stations were sampled in each zone. Source: adapted from Fore
et al. (2006c).
5.2.2
The number of stations to be sampled is a criti-
cal element in developing the monitoring strategy.
Stratification by management zone or reef type will
increase the required number of sampling stations.
Monitoring objectives and metric data should there-
fore be examined carefully to eliminate any unnec-
essary stratification. There will be little flexibility
in determining the number of management zones,
which generally reflect different waterbody use
designations and require individual analysis; but the
necessity for different reef types (classifications) can
be determined through analysis of metric variability.
Classification of a biological resource is used
to reduce natural variation in measured attributes
(Gibson et al. 1996; Gerritsen et al. 2000). Classifica-
tion partitions the resource into ecological units for
which expectations in structure, function and, most
35
-------
Stony Coral Rapid Bioassessment Protocol
importantly, measured attributes are similar. Proper
classification increases the precision of measured
indicators, adding power and value to ecosystem
assessments (Gibson et al. 2000). Moreover, classi-
fication provides a structure for synthesizing data
across regions and jurisdictions (Madden and Gross-
man 2004). While no unifying scheme has emerged,
there are many possible approaches for coral classi-
fication (UNESCO 1984; Jameson et al. 1998, 2001,
2003a; Mumby and Harborne 1999).
For all its virtues, classification can be costly if it
increases the number of samples necessary for statis-
tically significant results. Despite human tendencies
to group similar objects, classification might not be
relevant to regulatory monitoring unless it substan-
tially improves data precision (see Kurtz et al. 2006).
It is, therefore, counterproductive to automatically
classify reefs on the basis of a scheme or perceived
differences. Instead, data analysis can determine
whether classification is warranted. The many mea-
surable differences in reef geomorphology, hydro-
dynamics and composition might not necessarily
have a substantive effect on metric responses.
One means to reduce metric variability associ-
ated with reef type is to exclude unnecessary reef
types from the target population (Table 5-2). For
example, watershed effects might best be evaluated
by reefs close to shore, so offshore habitat types
could be excluded. Some reef types might occur in
surge zones that are difficult to sample. These can
be excluded from the target population and greater
focus placed on those reefs that are more easily
sampled.
5,2,3
The core measurements of the Stony Coral RBP
can be used for a variety of monitoring objectives,
and useful data can be collected using most sam-
pling designs, transect types and classification sys-
tems. Coral monitoring programs typically include
three types of sampling objectives: (1) assessing the
current status, (2) detecting trends over time and
(3) evaluating conditions at specific locations (tar-
geted or judgment sampling). These approaches dif-
fer in the manner in which sampling units (stations)
are selected, defined and interpreted (Fore et al.
2006c). Status assessment is best accomplished with
random selection of sampling locations every year;
trend detection can be accomplished with randomly
selected stations that are revisited in subsequent
years (at least until temporal variability is character-
ized); and targeted sampling is accomplished at pur-
posely selected locations to address specific man-
agement questions.
Federal and national programs such as EPA's
Environmental Monitoring and Assessment Program
(now National Coastal Assessment) often assess
status to characterize the condition of large regional
areas (Larsen 1997). Stations are randomly selected
but will not be repeated in subsequent years, so the
locations are not permanently marked. The principal
advantage of random site selection is that any
summary statistics derived from a random sample
will be unbiased for the entire population, including
all possible sites in the defined region that were
not sampled. This means that randomly selected
sites can be used to represent the entire region. For
status assessment, a larger number of sites at the
cost of a smaller transect area might be preferable.
In contrast, jurisdictions could have local man-
dates to identify sites and sources of degradation
and to develop management responses that mitigate
local effects. While overall regional condition might
be useful for CWA reporting requirements, local
resource managers also need to know which water-
bodies are degraded (Hall et al. 2000). For targeted
sampling, stations are selected to fulfill a particular
objective and locations often marked for return visits
(permanent or fixed stations). Targeted sample mon-
itoring is used, for example, to compare particular
reefs, to characterize trends in threatened species,
to monitor effects of pollution sources (existing or
pending) or to evaluate the success of management
activities. Targeted sampling can be used to address
management issues raised through status and trend
monitoring. Because they are not randomly selected,
data from targeted sites are applicable only to those
sites and cannot be used to more widely represent a
reef, management zone, or region.
Managers at every level are interested in trend
assessments to signal whether a resource is improv-
ing or declining. The goal is to detect change in con-
dition through time should change occur. Regres-
sion is the recommended statistical model for trend
detection in which the variable of interest (e.g., total
live coral) is regressed against time. The greatest
power to detect temporal trend is found by compari-
son of a particular station with itself (Larsen et al.
1995; Urquhart et al. 1998). This emphasizes tem-
poral variability by eliminating among-site (spatial)
36
-------
5. Application o/RBP Indicators in Regulatory Monitoring
variability, which can be measured separately. Sta-
tions for trend monitoring, whether they were tar-
geted or randomly selected, can be permanently
marked for repeat sampling. Larsen et al. (2001)
have described how to maximize the probability
of detecting a trend by balancing sampling effort
among sites, replicates and repeat visits. Depending
on results from initial surveys, trend detection could
be optimal with fewer sites and larger transects.
Regional patterns of reef condition are fun-
damental to characterizing the extent and severity
of decline and developing hypotheses of causality
(Ginsburg and Glynn 1994). Yet, disparity among
monitoring designs has resulted in duplication of
effort and squandered opportunities to integrate
local and regional data. In general, existing stud-
ies have employed an array of sampling methods
focused on local, rather than regional, coral condi-
tion. Consequently, statistical comparisons at larger
spatial scales are impossible (Kramer 2003). Both
local and regional monitoring objectives could be
more easily fulfilled if sampling for local monitoring
programs were designed to accommodate regional
objectives. That is, monitoring programs can be
designed so that a subset of randomly selected local
stations could serve regional objectives.
All three sampling approaches can be incor-
porated in a framework that allocates sampling
effort proportionately to both regional and local
needs (Fore et al. 2006b). In a hypothetical example
(Table 5-3) where annual sampling needs outstrip
the agency's capacity, the three monitoring designs
were allocated across 4 years in a rotating panel
(rotating basin). In this example, where the agency
can survey only 60 stations a year, different zones
are sampled each year, and 60 targeted stations are
sampled in the fourth year to investigate hypotheses
that are expected to emerge. In this scenario, status
for each region is documented every fourth year.
5-3. Hypothetical rotating panel monitoring
strategy1
Zone
Zone 2
Zone 3
Targeted
Total
20
60
20
60
I 10 trend
I 30 status
I 20 60
I 60 60
'A rotating strategy is depicted for a jurisdiction with three geographic
or management zones and a sampling limit of 60 stations per year. The
strategy involves re-sampling stations in each geographic region every
4 years and includes status, trend and targeted sampling. The fourth
year of the rotating panel provides targeted testing to address specific
local questions or hypotheses generated from earlier monitoring. This
approach can serve both local and regional objectives. Source: Fore et
al. (2006b).
There are several factors that must be con-
sidered in developing a regulatory monitoring pro-
gram. Those factors, briefly introduced here, include
screening indicators for metrics (responsive to
human disturbance), determining the sensitivity of
metrics to changes in coral condition, selecting an
appropriate sampling design for local and regional
objectives and incorporating the design into a
sampling strategy that can be realistically completed
and sustained by the responsible resource agency.
Other significant aspects of regulatory monitoring
include assigning designated uses, prioritizing
questions to address and setting levels of expected
condition (e.g., biocriteria).
37
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Stony Coral Rapid Bioassessment Protocol
38
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Among others, Dahl (1973) stressed the impor-
tance of topographic, rather than planar, surface
area for quantifying structural arid physiological
aspects of coral reefs. 3D CSA can be estimated
for any coral colony, even if only one morphologi-
cal measurement is known. How it is estimated
depends on requirements of scale and accuracy. The
scale must be relevant to project assessment ques-
tions, and the level of accuracy must balance statisti-
cal significance with overall efficiency.
Relevant scales for 3D CSA. Selecting the
appropriate scale for surface area analysis is a sig-
nificant concern but generally straightforward. Dahl
(1973) offered the following:
There are multiple levels of surface
features depending on the scales at which
they are considered. The earth, at one scale
a smooth sphere, includes mountains which
have boulders covered with microscopic
ridges, and so on. The scale of surface varia-
tion becomes significant when it approaches
the scale of the phenomenon being mea-
sured. Surface area is, thus, a relative mea-
sure depending on the scale considered. The
benthic surface area of significance to a large
organism will be different from (and far less
than) that important to bacteria, (p. 241)
He indicated that for coral reefs, there are at
least three scales of functional significance—reef,
individual colony and colony surface (polyp scale).
Various indicators of topography (surface features
of an object or place) are measured at the reef
scale and are intended to represent the physical
habitat available for reef communities. Measure-
ments of reef-scale topography most often (although
not always) include corals plus non-coral geologic
deposits such as rock, uncolonized hardbottom, and
spur-and-groove or buttress-and-canyon formations.
The non-coral components are relatively stable and,
except for ship groundings and anchor damage,
unaltered by most human stressors. Existing indica-
tors of reef topography employ measures of coral
height (ID) or vertical contour (2D rugosity), both of
which fail to capture the most reliable estimator of
physical habitat—the entire CSA measured in three
dimensions.
The RBP estimates the physical habitat of a reef
by summing CSA measurements of individual colo-
nies. This approach was introduced by Dahl (1973)
to estimate quantities of benthic algae and was later
applied by Roberts and Ormond (1987) and Alcala
and Vogt (1997). Summation is adopted in the RBP
because it simultaneously provides reef-scale and
colony-scale indicators; no additional lines, methods
or transects are needed. Total (live plus dead) and
LSA estimated for each colony can be used for colo-
ny-scale indicators (e.g., size-frequency distributions)
and combined for reef-scale indicators (e.g., 3DTC).
Physiological processes of corals, such as respi-
ration and algal photosynthesis, are best examined
at the colony surface (polyp) scale because this is
where the measured activities occur. Dahl (1973)
suggested that polyp-scale estimates could be made
by summing contributions calculated at different
scales. In other words, the polyp-scale surface area
of a colony can be estimated by adding the surface
area of polyps (determined by subsampling) to CSA
measured at the colony scale. Finer scales, as noted
51
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Stony Coral Rapid Bioassessment Protocol
earlier, generate larger surface areas but are not nec-
essarily more correct. The abundance and diversity
of harvestable fish are influenced more by physical
habitat provided by reefs and individual colonies
than by polyps.
Other scales might be relevant. For example,
Roberts and Ormond (1987) selected a 1-cm resolu-
tion for fish habitat studies. A slightly larger scale
might be used to estimate surface area of finger
corals. Coral fingers, small branches from the main
body of the colony, might not be important as ref-
uge for large, harvestable fish but are important
for small prey fish and invertebrates. Finger-scale
surface area estimates could be made by combining
CSA with surface area of fingers per square meter of
colony (fingers are fairly regular across the surface
of a coral). A decision to use this approach would
depend on the importance of prey species to the
assessment questions and the dominance of finger
corals in the reef.
Accuracy of CSA estimates. Selecting an
appropriate level of accuracy for measurements in
a monitoring program is an iterative process. An
appropriate level balances the objectives of the pro-
gram against the amount of time and effort required
for greater accuracy. Even if greater accuracy
increases statistical power, this advantage is lost if
too few stations are sampled. Accuracy is not, in
itself, the objective of a monitoring program. Coarse
estimates might be sufficient to distinguish signifi-
cant differences for monitoring objectives. Dahl
(1973) noted that for coral surface estimates,
...absolute accuracy is almost never
required, particularly when the areas them-
selves are so highly variable. What is needed
initially is a meaningful basis for compari-
sons and generalizations, and this can usu-
ally be achieved with careful approximation.
(p. 241)
The level of accuracy for each monitoring pro-
gram must be appropriate for the monitoring objec-
tives and feasible within constraints of time and
cost. Several methods are available to approximate
CSA, including some that provide low (e.g., volu-
metric surrogates), medium (geometric surrogates)
and high (photographic reconstruction) levels of
accuracy.
A coarse volumetric surrogate was recently
used to estimate CSA (Fisher et al. 2007a). Regard-
less of species and morphology, coral colonies
were visually graded into boxes (cubes) of different
predetermined 3D size classes (Figure 3-1). CSA
was assigned as the surface area of five sides of the
box (omitting the bottom, which is not functionally
relevant as community habitat or ISA). Grading
colonies according to volumetric size was very rapid,
supplied useful information on coral size and LSA,
and readily distinguished differences in physical
indicators (e.g., TSA and LSA, Figure 4-3) across
geographic zones and reef types in the Florida
Keys (Fisher et al. 2007b). While coarse colony size
estimates might be very effective for most of the
indicators included in the Stony Coral RBP, analysis
of population structure is limited when using
predetermined size classes.
Geometric surrogates have been used by many
to estimate CSA (Dahl 1973; Szmant-Froelich 1985;
Roberts and Ormond 1987; Alcala and Vogt 1997;
Bak and Meesters 1998; Meesters et al. 2001). In
this approach, various colony dimensions (usually
height, diameter and width, Figure 3-D are mea-
sured and applied to species-specific (or morpho-
logically dependent) geometric solutions for surface
area. The simplest example is the hemispheric shape
of massive corals. Colony dimensions are used to
determine radius (r), which is applied to 27tr2, the
geometric solution for a (bottomless) hemisphere.
Solutions for prolate and oblate hemispheres can be
used when height is much greater or much less than
the projected radius of a colony (Szmant-Froelich
1985). Fore et al. (2006c) used either a hemisphere
or a cylinder as a surrogate, depending on the ratio
of colony height to average radius. Alcala and Vogt
(1997) applied geometric solutions to six different
colony growth forms (Table A-l). The surrogates
selected will likely vary in different programs and
are influenced by the number and type of under-
water measurements that will be made.
52
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Appendix A: Estimating 3D Colony Surface Area
Table A'l. Geometric surrogates and CSA solutions for various colony forms1
Massive
Free living
Branching
Columnar
Tabulate
Foliose
Hemisphere
Hemisphere
Cylinder
Cylinder
Cylinder
semi-circle; right triangles
2m-2
2nr
(2nrh)(# branches)
(2nrh)(# columns)
(2irrh)(# branches)
(irr2) / 2 + y2(bh)(# plates)
1 Geometric solutions for various colony forms were described by Alcalaand Vogt (1997). Because of the radial
growth of coral colonies, planar (overhead view) 2D-SA solutions for all morphological forms were assumed nr'
(circle), where r=radius, h=height, b=base of triangle, IT = 3.14.
1
A roughly hemispherical colony measures 0,6 m high, 1.5 m diameter and 1,2 m width, Radius is
estimated as the from all three dimensions (r = [0,6 + 0.75 + 0.6] / 3 = 0.65) and surface
calculated as 2nr2 (hemisphere), or (2 x 3,14 x [0,652]) = 2.65 m2.
53
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Stony Coral Rapid Bioassessment Protocol
2:
A large, flat colony lies across the transect perimeter. It extends 6 m in diameter, 3 m width
and is 30 cm in height. The closest geometric surrogate is a rectangle for which the surface area
solution is the sum of surface areas for each of the five sides above the sea floor. SA = (6m x 3m)
+ 2(6m x 0.3m) + 2(3m x 0.3m) = 23.4m2.
.3m
3:
Another large colony, 6m diameter and 3m width, lies across the transect perimeter but, unlike
the rectangular colony described above, is shaped more like a half-cylinder lying on its side. The
surface area solution for a cylinder is 2rtr2 +27trh, half of which would represent the above sea
floor surface area of the colony (= rtr2 +nrh). In this case, r = 1.5m and h = 6m, so colony SA =
(3.14 x [1.5]2 + 3.14 x 1.5 x 6) = 35.3 m2.
54
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Appendix A: Estimating 3D Colony Surface Area
4:
The surface area of a large hemispherical finger coral was calculated from height, diameter and
width dimensions (see first example) as SA = 15,1 m2. If estimates were needed at the finger
scale, the surface area of fingers would be added. The amount to be can be determined
by measurements on a subpopulation of fingers to determine height, radius and density. In this
example, height and radius of the fingers are applied to the formula for a cylinder, 2nrh (the ends
of the cylinder are not included), to obtain an average addition of 0.015 m2 per finger. Density
of fingers was found to average 13 per 0.1 m2 or 130 per m2. Fingers therefore add 0.015 x 130 =
1.95 m2 per m2 coral. The surface area of the colony at the fingers scale is 15.1 + (1.95 x 15.1} =
44.5 m2, or nearly three times the surface area estimated at the colony scale.
0.015m
Because very large colonies have such a high
influence on TSA for a station, it might be worth-
while to calculate them individually. However, most
colonies can be approximated using a common
surrogate for the particular species or morphologi-
cal type. For example, surface areas for Caribbean
Diploria and Montaslraea colonies are very closely-
approximated by a hemispherical surrogate (Court-
ney et al. 2007). Once surrogates are assigned, geo-
metric solutions for each species can be entered in
a spreadsheet and surface areas can be calculated
automatically. It is likely that several species will
have similar colony morphology (e.g., hemisphere),
so only a few solutions might be needed.
The most accurate methods to estimate CSA
rely on virtual 3D reconstruction of coral colonies
from digital photographs (Bythell et al. 2001; Cocito
et al. 2003). Using this approach, multiple photo-
graphs are taken from various positions and angles
around the coral colony. Images are downloaded
into commercial software packages where they are
oriented and aligned to form a 3D model of the
colony (Figure A-l). Height, diameter, width, surface
area and volume of the colony are obtained from the
reconstructed model with relatively high accuracy.
Because the procedure is time consuming, it is not
recommended for field monitoring programs. How-
ever, useful conversion factors are generated when a
sufficient number of colonies of a particular species
or morphological type are analyzed.
Courtney et al. (2007) have applied the photo-
graphic method to specimens of Caribbean Diploria
and Montastraea to generate genus-specific conver-
sion factors that allow accurate estimates of CSA
from underwater colony measurements (i.e., height,
diameter or width). They found the hemisphere to be
a very accurate surrogate for these genera, demon-
strating high correlation (R2 = 0.99) when surface area
55
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Stony Coral Rapid Bioassessment Protocol
was calculated (2nr2) using an average colony radius
derived from all three morphological dimensions.
Additional species and morphological types are being
examined by the same authors in the same manner.
For the more complex morphological forms (e.g.,
branched colonies, Figure A-l), the reconstructed
models provide a means to explore surrogate geome-
tries that can be resolved with the fewest, or easiest,
underwater measurements. Although tedious and
time consuming, only one comprehensive set of
colony reconstructions for a particular species or
morphological type is required for most monitoring
objectives. As an example, Caribbean programs can
now reasonably assign a hemispheric conversion for
CSA of Diploria and Monatastraea colonies without
any additional research.
Figure A-1. Photographic methods have been used to measure CSA for a variety of colony shapes (Courtney
et al. 2007). Colonies are photographed in the field (left) from multiple positions and angles. Scale
bars and reference objects (billiard balls) are placed so that images can be correctly oriented and
reconstructed (right) using commercial software. Living and dead surface area (e.g., brown and
white in top photographs) can be delineated and quantified. Colony dimensions can be accurately
determined from the reconstructed models. Dimensions for the small elkhorn coral shown in the
bottom figures are height = 42.2 cm, maximum diameter = 52.5 cm, width = 32.2 cm,
CSA = 3445 cm2, volume = 671 cm3, and the 2D planar footprint is 954 cm2 (surface index = 3.6).
Source: Lee Courtney, EPA.
56
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Geometric surrogates are used in the Stony
Coral RBP to provide 3D rather than traditional 2D
estimates of stony coral surface area. Methods are
also needed to convert historical indicators, includ-
ing live coral cover and topographic complexity
(rugosity), to 3D units.
Conversion from 2D to 3-D. Live coral
cover measured in 2D is the indicator most often
employed in monitoring programs (Jameson et al.
1998). In fact, there are sufficient live coral cover
data to allow meta-analysis and regional docu-
mentation of changes in coral condition (Gardner
et al. 2003; Kramer 2003). Live coral cover refers
to the proportion (%) of live coral relative to the
total amount of sea floor surveyed and is a value
obtained from either 2D quadrats or ID linear tran-
sects. Even if measured in ID, live coral cover is
intended to represent the 2D planar proportion of
coral relative to all other substrata (e.g., sand, veg-
etation, rock) when viewed from above.
Despite this widespread use and substantial
historical data, 2D sampling techniques can lead to
deceptive interpretations, including gross under-
estimation of live coral and its potential to grow
and reproduce (Dahl 1973; Alcala and Vogt 1997).
Also, Randall (1963) and several others have noted
that errors are introduced when comparing fish
abundance and diversity to planar 2D rather than
topographic surface area. There has always been
some uncertainty in measurements of 2D coral cover
because of the many different methods employed.
In some studies, coral cover is measured as the total
area of the quadrat in which any live coral occurs
(Gomez and Alcala 1984). In others, the entire
colony projection is reported regardless of the pro-
portion of live tissue; in still others, only the live
portion of the colony is reported. In the AGRRA
program (Lang 2003), live coral cover is estimated
by linear transect and partial mortality (percent
live coral) is determined from a planar overhead
view that does not account for live tissue and bare
skeleton on the sides of coral colonies. These incon-
sistencies in application are often avoided in direct
method comparisons (Section 2.3) so that results
across methods usually appear to be compatible. In
several studies, there is no description of whether
live or total coral was reported. Perhaps before
recent catastrophic declines, reports of coral cover
were presumed to be living coral.
Realistic quantification of coral must incorpo-
rate three dimensions (Dahl 1973; Alcala and Vogt
1997). and several means are available to convert
historical 2D data. The easiest but least satisfying
way is to invoke a generic conversion factor. Odum
and Odum (1955) assumed that surfaces of all reef
objects were 3X the horizontal area and Risk (1972).
perhaps contemplating a highly detailed scale,
assumed a 100-fold difference. The best experimen-
tal evidence was provided by Alcala and Vogt (1997),
who reported that TSA for corals across a 257 m2
study site averaged 5X the planar surface area. This
is a reasonable value at the colony scale, so 2D live
coral cover data could be genetically multiplied by
5 to obtain 3DLC. It would assume, however, that
community composition was similar to that sampled
by Alcala and Vogt.
A refinement of this approach is to assign spe-
cific conversion factors to particular morphologi-
cal shapes. Dahl (1973) defined the 3D:2D surface
area as the surface index, which varies for differ-
ent morphological types. The surface index (SI) of
hemispherical colony, for example, is SI = 2?tr2 /Ttr2
= 2. Colonies with greater complexity exhibit higher
surface indices. For example, Alcala and Vogt (1997)
assigned branched colonies SI = 6.88, and free liv-
ing forms SI = 1.92. Photographic methods noted in
Appendix A showed Diploria were an average SI =
2.6 (range 1.4 to 4.1), and Montastraea were an aver-
age SI = 3.0 (range 1.9 to 5.2) (Courtney et al. 2007).
Reasonable conversion factors can be obtained or
57
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Stony Coral Rapid Bioassessment Protocol
estimated for most coral morphologies. In contrast
to a generic conversion factor, species-specific (or
morphology-specific) conversion factors improve the
accuracy of conversions across stations and reefs
with variable community composition.
It is possible to calculate 2D live coral cover
from RBP data. With radial growth, the 2D geo-
metric solution is a circle projected on the planar
substrate, or SA = m2, where r is derived from the
average of colony diameter and width. Using this
approach, there should be reasonable similarities
between the RBP and other coral cover methods.
As an example, a 2004 RBP survey in the Florida
Keys (Fisher et al. 2007b) used a coarse volumetric
approach to colony size, which was used to docu-
ment 3DLC values. However, 21) values could also
be calculated from the data using a simple conver-
sion factor. Across the 29 sampling stations, 213 live
coral cover was calculated as 6.5%, which is nearly
identical to 6.6% found in a 2004 survey of 160 sta-
tions using videographic methods (Florida's Coral
Reef Monitoring Project; Beaver et al. 2004). Simi-
larly, width and diameter dimensions of colonies in
an RBP assessment in southeast Florida were used
to calculate 2D live coral cover at 0.7-1.3 percent
(Fisher, unpublished), and videographic methods for
the same area documented 0.9-1.3 percent live coral
cover (SECREMP 2005).
Colony and reef topography. As noted in
Appendix A, measures of reef topography (topog-
raphy = surface features) characterize the amount
and type of habitat provided by corals and non-coral
structures for the greater reef community. Methods
that estimate 2D live coral cover are not intended
to, and do not, reflect reef topography because coral
height and physical complexity are ignored. Yet it is
well known that the vertical dimension is essential
to flourishing reef communities (Dahl 1973; Luck-
hurst and Luckhurst 1978; Roberts and Ormond
1987; Ferreira et al. 2001; Scheffers et al. 2003). In
fact, some studies have used coral height as an esti-
mator of community habitat (Chou 1984; McCormick
1994; Lang 2003). The term complexity is used to
describe surface features which, for individual colo-
nies, might be defined as surface area:volume. Like
topography, complexity can also be applied at the
reef scale, which would be measured as surface area
per square meter of sea floor, or 3DTC.
Several studies have applied a rugosity index
to estimate physical habitat provided by a reef (Por-
ter 1972; Risk 1972; Luckhurst and Luckhurst 1978;
Aronson et al. 1994; McCormick 1994; Rogers et al.
1994; Chiappone et al. 2001; Lang 2003; Jokiel et
al. 2004). The rugosity index is a 2D measurement
applied as a reef-scale indicator of topography and
is determined using a chain-transect method that
compares the length of a chain draped along the
coral colonies of a reef to the length of a taut line
across the same linear distance. The procedure is
time-consuming, and its application varies depend-
ing on how meticulously the line is placed within
the nooks and hollows of each rock and colony.
In most studies, the chain-transect method is per-
formed independently of a linear transect, but in
some cases, the methods have been combined into
a single-chain-transect protocol (Rogers et al. 1994).
This inconsistency can confound data comparisons,
particularly among reefs with high reef topography.
The rugosity index estimates complexity by
subsampling a 2D contour of each coral colony (and
non-coral substrata) along the draped line. This gen-
erates a unitless value that can be used for relative
comparisons across stations and reefs. The chain-
transect method estimates topography by extrapola-
tion (much as ID linear transect data are extrapo-
lated to estimate 2D live coral cover). While rugosity
accounts for the important vertical dimension, it
captures only one horizontal dimension. The chain
can lie across any part of a colony but never across
the entire colony. It is, therefore, difficult to com-
pare chain-transect data to RBP data for individual
colonies. However, comparisons at the reef-scale are
possible but have not been performed.
There are clear benefits for migrating to RBP
colony-based summations for estimates of reef topo-
graphy. The estimates are made in 3D rather than in
2D contours or ID heights; estimates are made on
individual colonies, and values can be attributed to
different species; estimates focus only on the coral
component of reef structure (the component that is
managed) and exclude the non-coral components.
Measurement of 3D CSA, necessary for calculation
of 3DTC, is used in several other indicators and can
be applied in value and sustainability models; there
are no additional sampling requirements beyond
those used to obtain all other RBP indicators (i.e.,
no additional chain-transect to exclusively collect
complexity data).
58
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Different procedures can be used to address
varying objectives of a monitoring program. Usually
under consideration is the value of spending more
time in the field (dive time is a primary concern) for
more information or greater accuracy in field mea-
surements. It was proposed (Section 3.4) that three
colony dimensions should be measured initially and
then analyzed to determine whether all three are
actually needed to fulfill the objectives of the pro-
gram. Such an example is provided here.
In a pilot survey, the Florida Reef Resilience
Program (TNG 2006) measured three colony dimen-
sions for each colony encountered in transects from
seven different subregions of the Florida Keys reef
tract. One objective of the monitoring program was
to compare reef TSA among the seven subregions.
Hence, the subregions were compared first through
analysis of variance (ANOVA) and then Tukey's com-
parison test. Analyses were performed for seven
different calculations of radius on the basis of com-
binations of one, two and three measurements of
colony dimension.
As described for the Stony Coral RBP, the
Florida Reef Resilience Program measured colony
height (h), maximum diameter (d) and width (w).
Estimates of colony radius were derived from height,
diameter (d / 2) and width (w / 2). One estimate
or an average of combined estimates was applied
to a hemispheric surrogate to calculate CSA and
reef TSA. Data from all seven combinations were
analyzed to identify any differences among regions.
Results from ANOVA (Table C-l) and Tukey's
comparison test (Table C-2) indicate that for this
monitoring objective, it would be reasonable to
measure only two colony dimensions, especially if
height was one of the two. It is even possible that
a single colony measurement could be used if that
single measurement is maximum diameter. Both of
these modifications to the monitoring protocol could
save valuable dive time. These data and calculations
are preliminary and provided only as an example;
they are not intended as a recommendation for other
monitoring programs.
C-1. ANOYA F and p values for different
combinations of measurements1
2.38 1
3.94 I
2.56 I
2.16 I
0.035
0.002
0.025
0.054
1 Different combinations of measurements (height h; radius from
diameter r,;; and radius from width r,v) were used to determine colony
radius. Radius values were used in a hemispheric model (2irr2)
to calculate CSA and TSA for the reefs. One-way ANOVA tests
revealed significant differences in mean log reef surface areas when
59
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Stony Coral Rapid Bioassessment Protocol
C-2. P-¥alues for Tukey comparisons for different numbers of measurements1
Palm Beach v. Lower Keys
Palm Beach v Middle Keys
0.029
0.046
0.022
0.039 i
0.027
0.049 !
0.050
0.064
•»
0.026
0.051
0.040
0.049
H
0.068 ;
0.089
Palm Beach v. Upper Keys
Transition
Palm Beach v. Broward
County
Palm Beach v. Northern
Transition
Palm Beach v. Upper Keys
0.136
0.223
0.269
0.295
0.156
0.329
0.184
0.278
0.456
0.297
0.285
0.281
0.324
'Tukey comparisons were made between Palm Beach and six other subregions for estimates using 3, 2 and 1 measurements to define radius (r)
for calculating the hemispherical surface area. P-values < 0.05 are in bold. Additional comparisons among other regions detected no significant
differences, and results are not shown.
60
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