Editor's choice: Modelling disease–coral dynamics as a way to understand long-term coral reef persistence
Article first published online: 28 APR 2009
© 2009 The Authors. Journal compilation © 2009 British Ecological Society
Journal of Applied Ecology
Volume 46, Issue 3, page 733, June 2009
How to Cite
Cadotte, M. W. (2009), Editor's choice: Modelling disease–coral dynamics as a way to understand long-term coral reef persistence. Journal of Applied Ecology, 46: 733. doi: 10.1111/j.1365-2664.2009.01656.x
- Issue published online: 28 APR 2009
- Article first published online: 28 APR 2009
Sokolow, S.H., Foley, P., Foley, J.E., Hastings, A. & Richardson, L.L. (2009) Disease dynamics in marine metapopulations: modelling infectious diseases on coral reefs. Journal of Applied Ecology, 46, 621–631.
For more than a decade now, the precipitous global decline in coral reefs has galvanized reef ecologists and spurred a necessary research programme to understand the causes of this decline (Hoegh-Guldberg 1999; Pandolfi et al. 2003; Bellwood et al. 2004). The causes are multifaceted, most probably with differing regional drivers but, overall, researchers believe they involve a complex interaction between environmental and anthropogenic stress, climate change and infectious diseases (Pandolfi et al. 2003). It is likely that increased disease prevalence results from corals being stressed, which further complicates population persistence. Thus, we need to understand disease dynamics in corals in order to fully understand the causes of decline and when recovery is probable. Since recording the appearance of disease is now included in coral monitoring, there is an opportunity to better understand the transmission dynamics and coral population consequences of disease outbreaks.
For this issue's Editor's Choice, Sokolow and colleagues use a metapopulation framework to model the long-term consequences of white plague on coral persistence in the Florida Keys, USA. Their model considers coral patches as either susceptible or infected (S–I) by white plague. The S–I metapopulation modelling revealed three possible long-term outcomes: (i) white plague becomes locally extinct and coral persists at an equilibrium number of patches; (ii) white plague lowers this equilibrium to some smaller number of patches; and (iii) both go locally extinct. Sokolow et al. show how changes in connectivity or pathogen lifespan can shift the system between the various outcomes.
To test their general modelling approach, they analysed more than a decade's worth of data on infection patterns in a region of the Florida Keys with around 1100 reef patches. By using observation-informed parameters to generate model predictions, they show that the data fit the model predictions, with one exception, a year with lower prevalence than predicted by the model. What the model indicates is that that the long-term disease dynamics in the system is one of rapid white plague colonization and expansion, followed by prolonged decline in prevalence.
This paper was selected as our Editor's Choice because it successfully combines a simple model with long-term observations, offering a potential understanding of coral reef dynamics in the presence of a patchily distributed pathogen. The paper does not argue that this is the best model, or that it can successfully predict coral dynamics at other locations or at other times. Rather, it offers a glimpse of the way forward, where explicitly defined models and parameters allow ecologists and managers a robust starting point for conceptualizing the influences of critical long-term coral dynamics and persistence.
- 2004) Confronting the coral reef crisis. Nature, 429, 827–833. , , & (
- 1999) Climate change, coral bleaching and the future of the world's coral reefs. Marine and Freshwater Research, 50, 839–866. (
- 2003) Global trajectories of the long-term decline of coral reef ecosystems. Science, 301, 955–958. , , , , , , , , , , & (
- 2009) Disease dynamics in marine metapopulations: modelling infectious diseases on coral reefs. Journal of Applied Ecology, 46, 621–631. , , , & (