Nursery Function Drives Temporal Patterns in Fish Assemblage Structure in Four Tropical Estuaries
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Despite estuary-to-estuary differences in assemblage composition, fish faunas of tropical Indo-Pacific estuaries show parallel patterns of temporal change, suggesting a common set of ecological drivers. One potentially important driver is the interaction of different patterns of occupancy by functional groups that display different life-history patterns. However, most studies that have considered temporal change lack the detail needed to understand life-history utilisation. Most have focussed on changes in catch per unit effort (CPUE) or probability of encounter, with only one study going further and investigating changes in size structure and then only for a single estuary. One of the reasons for this lack of detail is the large volume of work needed to collect comprehensive data on size structures of species rich assemblages across multiple estuary systems over time. To overcome the logistical limitations on data collection, we used joint patterns of change in CPUE and mean biomass per fish (BPF) as proxies for changes in size structure. We investigated how different life-history strategies contributed to overall temporal patterns of assemblage change across four tropical Indo-Pacific estuaries. The three life-history strategies displayed characteristically different patterns in CPUE and BPF and the relationships between CPUE and BPF that reflect differences in the way that the three groups use estuaries. These different patterns interacted to produce complex assemblage patterns that are likely to be sensitive to location-specific differences in the mix of species from each group, providing at least part of the explanation for the site-specific fish assemblage structures that are characteristic of tropical estuarine fish fauna.
KeywordsLife history Recruitment Nursery ground Estuary Fish Monitoring
We thank the many volunteers who made the field work for this project possible. The work was supported by a Marine and Tropical Sciences Research Facility (MTSRF) research grant. Research was conducted under James Cook University Ethics Approval A1210.
- Bacheler, N.M., J.E. Hightower, S.M. Burdick, L.M. Paramorec, J.A. Buckela, and K.H. Pollock. 2010. Using generalized linear models to estimate selectivity from short-term recoveries of tagged red drum Sciaenops ocellatus: effects of gear, fate, and regulation period. Fisheries Research 102: 266–275.CrossRefGoogle Scholar
- Baker, R., and T.J. Minello. 2011. Trade-offs between gear selectivity and logistics when sampling nekton from shallow open water habitats: a gear comparison study. Gulf and Caribbean Research 23: 37–48.Google Scholar
- Blaber, S.J.M. 2002. ‘Fish in hot water’: the challenges facing fish and fisheries research in tropical estuaries. Journal of Fish Biology 61A: 1–20.Google Scholar
- BOM. 2009. Australian Bureau of Meterology. Australian Department of Environment, Water, Heritage and the Arts, Canberra. http//www.bom.gov.au. Accessed 5 Dec 2011.
- Breiman, L., J. Friedman, R. Olshen, and C. Stone. 1984. Classification and regression trees. Belmont: Wadsworth International Group. 358 pp.Google Scholar
- Deegan, L.A., J.E. Hughes, and R.A. Rountree. 2000. Salt marsh ecosystem support of marine transient species. In Concepts and controversies in Tidal Marsh Ecology, ed. M.P. Weinstein and D.A. Kreeger, 333–365. Dordrecht: Kluwer Academic Publishers.Google Scholar
- Froese, R., and D. Pauly. 2010. FishBase: World Wide Web electronic publication. www.fishbase.org. Accessed 5 Dec 2011.
- Stevens, P.W. 2006. Sampling fish communities in saltmarsh impoundments in the northern Indian River Lagoon, Florida: Cast net and culvert trap gear testing. Florida Scientist 69:135–147.Google Scholar