11th ICRS Abstract book - Nova Southeastern University

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Developing An Expert System For Predicting Coral Disease Risk On Indo-Pacific
Reefs
Bette L. WILLIS* 1 , Scott F. HERON 2 , Cathie A. PAGE 3 , William J. SKIRVING 2 , C.
Mark EAKIN 2 , C. Drew HARVELL 4 , Dean M. JACOBSEN 5 , Gregg COLEMAN 6 , Ian
MILLER 6 , Hugh P.A. SWEATMAN 6
1 School of Marine and Tropical Biology and ARC Centre of Excellence for Coral Reef
Studies, James Cook University, Townsville, Australia, 2 NOAA Coral Reef Watch,
Silver Spring, MD, 3 School of Marine and Tropical Biology and ARC Centre of
Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland,
Australia, 4 Department of Ecology and Evolutionary Biology, Cornell University, Ithaca,
NY, 5 College of the Marshall Islands, Majuro, United States Minor Outlying Islands,
6 Australian Institute of Marine Science, Townsville, Queensland, Australia
Coral disease outbreaks represent an emerging risk on Indo-Pacific reefs that is likely to
escalate with ocean warming due to climate change. Building on a recent model that
links the abundance of coral disease with elevated temperature anomalies and percent
cover of coral hosts, we further refine temperature metrics to include both the duration
and magnitude of temperature anomalies and to differentiate between the effects of warm
versus cool seasonal anomalies on disease risk. Using a 9-year data set of disease records
for white syndrome on 48 reefs spanning more than 1000 km along the Great Barrier
Reef, we explore patterns in disease abundance with percent coral cover and with
deviations from both mean summer and mean winter sea surface temperatures. Analysis
showed that each of these factors is necessary but not sufficient to explain patterns in
disease abundance. The addition of winter temperature anomalies to the model improved
its explanatory power. Disease abundance was greatest in summers following mild
winters that deviated by less than 5 °C-weeks from mean winter conditions. We suggest
that cold winters may reduce pathogen loads, and consequently the likelihood of disease
outbreaks in the following summer. It is less clear why warm winters are correlated with
reduced disease abundance, but they may result in enhanced disease resistance of the
coral host. Our results indicate that predicting disease risk on Indo-Pacific reefs is
complex; nevertheless predictions based on satellite-derived sea surface temperatures can
be reasonably accurate, given knowledge of coral cover. With the incorporation of
further factors, such as current speed and host susceptibility, our aim is to provide reef
managers with an expert system for predicting disease risk on coral reefs.
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A Large Semi-Open Aquarium As A Proxy For Natural Coral Reef Ecosytems:
Insights And Implications For The Causes Of Coral Disease
Shelley L. ANTHONY* 1
1 Marine and Tropical Biology, James Cook University, Townsville, Australia
Changing water quality parameters of ocean waters have been implicated in the
occurrence of some coral diseases, and are an ongoing concern for the future health of
coral reefs. However, it is difficult and somewhat haphazard to monitor water quality
accurately and continuously in natural reef settings.
The Coral Reef Exhibit (CRE) at Reef HQ Aquarium in Townsville, Australia is the
world’s largest living coral reef aquarium, containing almost 3,000,000 litres of natural
seawater that is open to the atmosphere. The CRE supports thousands of scleractinian and
soft coral colonies, as well as other associated reef species, in a semi-closed system that
simulates a natural reef environment. This system is constantly monitored for
temperature, salinity, pH, alkalinity, dissolved oxygen, turbidity, trace elements, and
inorganic nutrients, among others. Additional and potentially complicating factors in
coral disease observations - such as snail predation - are easily controlled, making it more
efficient to examine the effects of varying conditions on the corals, fish, and other marine
organisms.
Analysis of coral mortality data from 1996-2006 in the CRE system clearly shows that
White Syndrome is the single leading cause of death for acroporids (the most sensitive
group). Extensive water quality records over the same time period were thoroughly
examined and compared to mortality data to look for correlations with White Syndrome
outbreaks. No significant correlations were apparent for any single water quality
parameter, including high temperature. Rather, I suggest that a combination of factors
may create a stressful environment, resulting in White Syndrome occurring after a
prolonged period. Preliminary evidence also indicates that episodes of poor water
circulation are a trigger for tissue sloughing in individual acroporid colonies.
Oral Mini-Symposium 7: Diseases on Coral Reefs
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Ecosystem Function And Disease Resistance in Coral Reefs: What Happens When We
Remove Key Players?
Laurie RAYMUNDO* 1 , Aileen MAYPA 2 , Andrew HALFORD 1
1 University of Guam, Mangilao, Guam, 2 University of Hawaii, Honolulu, HI
The ecological drivers of disease outbreaks are poorly understood. We tested the hypothesis that
intact, trophically-diverse marine ecosystems are less likely to sustain disease outbreaks than
over-fished systems. Marine Protected Areas (MPAs) are a best practice for managing fish
communities, so an additional benefit of this primary tool is a win-win situation for coral reef
conservation. This is challenging to test; few MPAs are consistently well-managed so that
significant increases in fish diversity can occur. We surveyed 7 reefs containing both an MPA
and a fishing ground in the central Philippines for coral disease prevalence and fish taxonomic
distinctness. All MPAs had less disease and taxonomic distinctness on par with, or richer than,
expected. Conversely, fished reefs contained more disease and fish assemblages of higher
variability and lower distinctness. Our findings show that protection from fishing confers
protection from disease outbreaks. At present, this is the only option available for managing
coral diseases.
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Advancing The Global Coral Disease Database
Emily CORCORAN* 1 , Andy BRUCKNER 2 , Nicola BARNARD 3 , Michael STRONG 4 , Craig
MILLS 5
1 One Ocean Programme, UNEP-WCMC, Cambridge, United Kingdom, 2 Coral Reef
Conservation Program, NOAA, Silverspring, MD, 3 ICRAN, Cambridge, United Kingdom,
4 Informatics, UNEP-WCMC, Cambridge, United Kingdom, 5 Spatial Analysis, UNEP-WCMC,
Cambridge, United Kingdom
The Global Coral Disease Database (GCDD) was launched by NOAA and UNEP-WCMC in
2000. Over the last seven years, this partnership has worked to compile and organise published
data on the occurrence of coral disease, benefiting managers, scientists and other stakeholders
through the provision of the first compilation on the global observations of coral diseases. The
database currently contains 7813 data points from 66 countries across the world since 1970,
25% of these data points are observations since 2000.
Whilst excellent advances have been made in developing the GCDD (http://www.unepwcmc.org/GIS/coraldis/),
there exists a need to address the recurrent challenges of quality,
accessibility, and completeness of the data, to ensure that this unique GIS tool meets its fulfil
potential as a critical global repository for coral reef disease information.
A new twelve-month phase of work will be initiated at ICRS 11 to improve the relevance and
importance of the database to users through consultation and a comparative analysis of user
needs, information holdings, and data collection. Through partnerships with data collection
programmes, and the establishment of an expert advisory group, the project will raise the profile
and value of the GCDD to stakeholders, build confidence in the holdings, and provide a
mechanism for quality assurance of the data collected. A new visual interface will be
demonstrated which will enhance the visibility and functionality of the GCDD with an
improved look, feel and progression towards a more sophisticated online analysis. Such analysis
would allow ad-hoc spatial querying and analysis, and the manipulation of the coral disease
data alongside key biodiversity datasets, such as the World Database on Protected Areas.
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