Parasites of coral reef fish larvae: its role in the pelagic larval stage
The pelagic larval stage is a critical component of the life cycle of most coral reef fishes, but the adaptive significance of this stage remains controversial. One hypothesis is that migrating through the pelagic environment reduces the risk a larval fish has of being parasitised. Most organisms interact with parasites, often with significant, detrimental consequences for the hosts. However, little is known about the parasites that larval fish have upon settlement, and the factors that affect the levels of parasitism. At settlement, coral reef fishes vary greatly in size and age (pelagic larval duration), which may influence the degree of parasitism. We identified and quantified the parasites of pre-settlement larvae from 44 species of coral reef fishes from the Great Barrier Reef and explored their relationship with host size and age at settlement, and phylogeny. Overall, less than 50% of the larval fishes were infected with parasites, and over 99% of these were endoparasites. A Bayesian phylogenetic regression was used to analyse host-parasite (presence and intensity) associations. The analysis showed parasite presence was not significantly related to fish size, and parasite intensity was not significantly related to fish age. A phylogenetic signal was detected for both parasite presence and intensity, indicating that, overall, closely related fish species were likely to have more similar susceptibility to parasites and similar levels of parasitism when compared to more distantly related species. The low prevalence of infection with any parasite type and the striking rarity of ectoparasites is consistent with the ‘parasite avoidance hypothesis’, which proposes that the pelagic phase of coral reef fishes results in reduced levels of parasitism.
KeywordsFish settlement Pelagic larval phase Larval fish Phylogenetic regression
We thank J. Becker, A. Crean, L. Curtis, B. Fargher, C. Jones, R. Fogelman, G. Marsden, S. Pausina, C. Vargas, volunteers and the Lizard Island Research Station staff for field assistance. The Australian Research Council and The University of Queensland funded this research.
Compliance with ethical standards
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
- Barton K (2016) MuMIn: multi-model inference. R package version 1.15.6. https://CRAN.R-project.org/package=MuMIn
- Combes C (2001) Parasitism: the ecology and evolution of intimate interactions. University of Chicago Press, ChicagoGoogle Scholar
- Geyer CJ (2011) Introduction to Markov chain Monte Carlo. In: Brooks S, Gelman A, Jones GL, Meng X (eds) Handbook of Markov chain Monte Carlo. Taylor and Francis Group, Florida, pp 3–48Google Scholar
- Gronau QF, Singmann S (2017) bridgesampling: bridge sampling for marginal likelihoods and Bayes factors. R package version 0.2-2. https://CRAN.R-project.org/package=bridgesampling
- Justine JL (2010) Parasites of coral reef fish: how much do we know? With a bibliography of fish parasites in New Caledonia. Belg J Zool 140:155–190Google Scholar
- Kavanagh KD (2000) Larval brooding in the marine damselfish Acanthochromis polyacanthus (Pomacentridae) is correlated with highly divergent morphology, ontogeny and life-history traits. Bull Mar Sci 66:321–337Google Scholar
- Khan RA (2012) Host-parasite interactions in some fish species. J Parasitol Res [ https://doi.org/10.1155/2012/237280]
- Kuris AM (2003) Evolutionary ecology of trophically transmitted parasites. J Parasit 84:S96–S100Google Scholar
- Neal RM (2011) MCMC using Hamiltonian dynamics. In: Brooks S, Gelman A, Jones GL, Meng X (eds) Handbook of Markov chain Monte Carlo. Taylor and Francis Group, Florida, pp 113–162Google Scholar
- R Core Team (2017) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
- Rohde K (1993) The ecology of marine parasites. CAB International, WallingfordGoogle Scholar
- Stan Development Team (2016) RStan: the R interface to Stan. R package version 2.14.1. http://mc-stan.org/
- Strathmann RR, Hughes TP, Kuris AM, Lindeman KC, Morgan SG, Pandolfi JM, Warner RR (2002) Evolution of local recruitment and its consequences for marine populations. Bull Mar Sci 70:S377–S396Google Scholar
- Vehtari A, Gelman A and Gabry J (2016) loo: Efficient leave-one-out cross-validation and WAIC for Bayesian models. R package version 1.1.0. https://CRAN.R-project.org/package=loo