Skip to main content

Main menu

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
    • Front Matter Portal
    • Journal Club
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses
  • Submit
  • Submit
  • About
    • Editorial Board
    • PNAS Staff
    • FAQ
    • Accessibility Statement
    • Rights and Permissions
    • Site Map
  • Contact
  • Journal Club
  • Subscribe
    • Subscription Rates
    • Subscriptions FAQ
    • Open Access
    • Recommend PNAS to Your Librarian

User menu

  • Log in
  • My Cart

Search

  • Advanced search
Home
Home
  • Log in
  • My Cart

Advanced Search

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
    • Front Matter Portal
    • Journal Club
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses
  • Submit
Letter

Susceptibility of coral-disease models

Adan G. Jordán-Garza, Erinn M. Muller, Scott G. Burman, and Robert van Woesik
  1. Department of Biological Sciences, Florida Institute of Technology, Melbourne, FL 32901-6988

See allHide authors and affiliations

PNAS May 17, 2011 108 (20) E110-E111; https://doi.org/10.1073/pnas.1102711108
Adan G. Jordán-Garza
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Erinn M. Muller
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Scott G. Burman
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Robert van Woesik
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: rvw@fit.edu
  • Article
  • Figures & SI
  • Info & Metrics
  • PDF
Loading

The scarcity of empirical data on marine diseases highlights the need for epidemiological models that explain patterns and processes. Yakob and Mumby (1) used a generic susceptible-infected model to describe the prevalence of white plague type II disease on a coral population (Dichocoenia stokesii). They compared their model with the metapopulation model of Sokolow et al. (2). Yakob and Mumby (1) stated that rapid population turnover explained the observed oscillations in disease prevalence. Previous marine-disease models have largely ignored life-history traits. Indeed, systems subjected to high return periods of stress can be dominated by weedy species with rapid turnover rates. Although the Yakob and Mumby (1) model incorporated life-history traits and fits the data better than the model of Sokolow et al. (2), we find four conceptual inconsistencies within their model.

First, Yakob and Mumby (1) indicated that recruitment increased with the availability of settlement space. The loss of coral colonies usually has the opposite effect, reducing recruitment (3). Similarly, D. stokesii most likely suffered recruitment reduction after the initial disease outbreak, because no D. stokesii recruits were observed over a 7-y period following the initial outbreak (4). Therefore, it is unlikely that high recruitment could drive rapid population turnover, as suggested by Yakob and Mumby (1), and, in turn, explain the observed dynamics of white plague type II prevalence. Moreover, the model was highly sensitive to recruitment rate changes. Increasing recruitment by ∼8% offset the second peak in disease prevalence, whereas decreasing recruitment by the same amount removed the second peak entirely (Fig. 1A).

Fig. 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig. 1.

A series of examples displaying the sensitivity of the model of Yakob and Mumby (1) to changes in recruitment (A) and mortality (B). Solutions for the original Yakob and Mumby model (solid black lines in A and B) are reproduced with the original parameterizations of recruitment (r = 0.25), natural and disease-induced mortality (μ1 = 0.2125 and μ2 = 0.05, respectively), transmission rate (β = 1), and reduced recruitment rates associated with infected colonies (σ = 0.5). Within a metapopulation context, recruitment represents the colonization of uncolonized sites; μ1 quantifies the probability of site extinction under natural conditions, and μ2 quantifies the probability of site extinction under disease conditions. The original white plague type II data (4) are also presented (circles with 95% confidence intervals). The broad overlapping 95% confidence intervals of the data, especially between 2001 and 2004, and the lack of information in 1999 and 2000 suggest that the second peak in disease prevalence could be an artifact generated by the model. Disease prevalence was the total number of sites with the disease divided by the total number of surveyed sites each year (2). The disease data were fitted to each model, and the residual sum of squares (RSS) was reported. (A) Results are shown by slightly altering (±0.02 or ±8% relative change) the recruitment value (r = 0.23 is represented by the hatched line, r = 0.27 is represented by the dotted line); all other parameters are the same as in the original model of Yakob and Mumby (1). (B) Model values are displayed when natural and disease-induced mortality are switched, where μ1 = 0.05 and μ2 = 0.2125; all other parameters are the same as in the original model. Reducing recruitment, a likely scenario when coral densities decrease, eliminated the oscillating pattern. Increasing recruitment increased the oscillation frequency. Changing the mortality parameters produced a model with a higher oscillating frequency and lower amplitude, which continued to decrease over time, reaching equilibrium when the disease became endemic. In all cases, changing the parameters resulted in a worse-fitting model (i.e., higher RSS).

Second, the authors parameterized natural mortality (21%) more than four times higher than disease-induced mortality (5%). White plague type II is one of the most aggressive coral diseases, potentially killing tissue at several centimeters per day. Such virulence can cause colony mortality within days of initial infection. Therefore, disease-induced mortality should be modeled substantially higher than natural mortality, but doing so radically changes the outcome of the model (Fig. 1B). Clearly, the model presented is not robust to variations in the input parameters.

Third, the model of Yakob and Mumby (1) parameterized the transmission rate at 100%. The authors argued that higher transmission rates among Pacific Ocean acroporids can cause differences in disease dynamics between the oceans; however, transmission rates higher than 100% are not possible.

Fourth, although the ultimate goal of modeling is to generate scale-invariant equations, applying population models [e.g., the model of Yakob and Mumby (1)] to metapopulation data [e.g., those presented by Sokolow et al. (2)] may misalign critical spatial, temporal, and environmental processes. Instead of suggesting that coral populations can evade disease through rapid turnover, it may be more fruitful to incorporate potential adaptive-like immune systems (5) into coral-disease models. It may be just as appropriate to conceptualize some coral diseases as noncontagion systems that express disease prevalence in relation to environmental thresholds, especially in a rapidly warming ocean.

Footnotes

  • ↵1A.G.J.-G, E.M.M., S.G.B., and R.v.W contributed equally to this work.

  • ↵2To whom correspondence should be addressed. E-mail: rvw{at}fit.edu.
  • Author contributions: A.G.J.-G., E.M.M., S.G.B., and R.v.W. analyzed data; and A.G.J.-G., E.M.M., S.G.B., and R.v.W. wrote the paper.

  • The authors declare no conflict of interest.

References

  1. ↵
    1. Yakob L,
    2. Mumby PJ
    (2011) Climate change induces demographic resistance to disease in novel coral assemblages. Proc Natl Acad Sci USA 108:1967–1969.
    OpenUrlAbstract/FREE Full Text
  2. ↵
    1. Sokolow SH,
    2. Foley P,
    3. Foley JE,
    4. Hastings A,
    5. Richardson LL
    (2009) Disease dynamics in marine metapopulations: Modeling infectious diseases on coral reefs. J Appl Ecol 46:621–631.
    OpenUrlCrossRef
  3. ↵
    1. Hughes TP,
    2. et al.
    (2000) Supply-side ecology works both ways: The link between benthic adults, fecundity, and larval recruits. Ecology 81:2241–2249.
    OpenUrlCrossRef
  4. ↵
    1. Richardson LL,
    2. Voss JD
    (2005) Changes in a coral population on reefs of the northern Florida Keys following a coral disease epizootic. Mar Ecol Prog Ser 297:147–156.
    OpenUrlCrossRef
  5. ↵
    1. Reed KC,
    2. Muller EM,
    3. van Woesik R
    (2010) Coral immunology and resistance to disease. Dis Aquat Organ 90:85–92.
    OpenUrlCrossRefPubMed
PreviousNext
Back to top
Article Alerts
Email Article

Thank you for your interest in spreading the word on PNAS.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Susceptibility of coral-disease models
(Your Name) has sent you a message from PNAS
(Your Name) thought you would like to see the PNAS web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Susceptibility of coral-disease models
Adan G. Jordán-Garza, Erinn M. Muller, Scott G. Burman, Robert van Woesik
Proceedings of the National Academy of Sciences May 2011, 108 (20) E110-E111; DOI: 10.1073/pnas.1102711108

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Susceptibility of coral-disease models
Adan G. Jordán-Garza, Erinn M. Muller, Scott G. Burman, Robert van Woesik
Proceedings of the National Academy of Sciences May 2011, 108 (20) E110-E111; DOI: 10.1073/pnas.1102711108
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Mendeley logo Mendeley
Proceedings of the National Academy of Sciences: 108 (20)
Table of Contents

Submit

Sign up for Article Alerts

Jump to section

  • Article
    • Footnotes
    • References
  • Figures & SI
  • Info & Metrics
  • PDF

You May Also be Interested in

Setting sun over a sun-baked dirt landscape
Core Concept: Popular integrated assessment climate policy models have key caveats
Better explicating the strengths and shortcomings of these models will help refine projections and improve transparency in the years ahead.
Image credit: Witsawat.S.
Model of the Amazon forest
News Feature: A sea in the Amazon
Did the Caribbean sweep into the western Amazon millions of years ago, shaping the region’s rich biodiversity?
Image credit: Tacio Cordeiro Bicudo (University of São Paulo, São Paulo, Brazil), Victor Sacek (University of São Paulo, São Paulo, Brazil), and Lucy Reading-Ikkanda (artist).
Syrian archaeological site
Journal Club: In Mesopotamia, early cities may have faltered before climate-driven collapse
Settlements 4,200 years ago may have suffered from overpopulation before drought and lower temperatures ultimately made them unsustainable.
Image credit: Andrea Ricci.
Click beetle on a leaf
How click beetles jump
Marianne Alleyna, Aimy Wissa, and Ophelia Bolmin explain how the click beetle amplifies power to pull off its signature jump.
Listen
Past PodcastsSubscribe
Birds nestling on tree branches
Parent–offspring conflict in songbird fledging
Some songbird parents might improve their own fitness by manipulating their offspring into leaving the nest early, at the cost of fledgling survival, a study finds.
Image credit: Gil Eckrich (photographer).

Similar Articles

Site Logo
Powered by HighWire
  • Submit Manuscript
  • Twitter
  • Facebook
  • RSS Feeds
  • Email Alerts

Articles

  • Current Issue
  • Special Feature Articles – Most Recent
  • List of Issues

PNAS Portals

  • Anthropology
  • Chemistry
  • Classics
  • Front Matter
  • Physics
  • Sustainability Science
  • Teaching Resources

Information

  • Authors
  • Editorial Board
  • Reviewers
  • Subscribers
  • Librarians
  • Press
  • Site Map
  • PNAS Updates
  • FAQs
  • Accessibility Statement
  • Rights & Permissions
  • About
  • Contact

Feedback    Privacy/Legal

Copyright © 2021 National Academy of Sciences. Online ISSN 1091-6490