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Advances in the aquatic sciences
RESEARCH ARTICLE

Edge patterns in aquatic invertebrates explained by predictive models

Peter I. Macreadie A B F G , Rod M. Connolly C , Gregory P. Jenkins A D , Jeremy S. Hindell A E and Michael J. Keough A
+ Author Affiliations
- Author Affiliations

A Department of Zoology, University of Melbourne, Parkville, Vic. 3010, Australia.

B Victorian Marine Science Consortium, Queenscliff, Vic. 3225, Australia.

C Australian Rivers Institute: Coast & Estuaries, and School of Environment, Griffith University, Gold Coast, Qld 4222, Australia.

D Marine and Freshwater Fisheries Research Institute, Department of Primary Industries, Queenscliff, Vic. 3225, Australia.

E Arthur Rylah Institute, Department of Sustainability and Environment, Heidelberg, Vic. 3084, Australia.

F Department of Environmental Sciences, University of Technology, Broadway, NSW 2007, Australia.

G Corresponding author. Email: petermacreadie@gmail.com

Marine and Freshwater Research 61(2) 214-218 https://doi.org/10.1071/MF09072
Submitted: 31 March 2009  Accepted: 5 August 2009   Published: 25 February 2010

Abstract

Predictive frameworks for understanding and describing how animals respond to habitat fragmentation, particularly across edges, have been largely restricted to terrestrial systems. Abundances of zooplankton and meiofauna were measured across seagrass–sand edges and the patterns compared with predictive models of edge effects. Artificial seagrass patches were placed on bare sand, and zooplankton and meiofauna were sampled with tube traps at five positions (from patch edges: 12, 60 and 130 cm into seagrass; and 12 and 60 cm onto sand). Position effects consisted of the following three general patterns: (1) increases in abundance around the seagrass–sand edge (total abundance and cumaceans); (2) declining abundance from seagrass onto sand (calanoid copepods, harpacticoid copepods and amphipods); and (3) increasing abundance from seagrass onto sand (crustacean nauplii and bivalve larvae). The first two patterns are consistent with resource-distribution models, either as higher resources at the confluence of adjacent habitats or supplementation of resources from high-quality to low-quality habitat. The third pattern is consistent with reductions in zooplankton abundance as a consequence of predation or attenuation of currents by seagrass. The results show that predictive models of edge effects can apply to aquatic animals and that edges are important in structuring zooplankton and meiofauna assemblages in seagrass.

Additional keywords: current flow, edge distribution, plankton tube traps, predictive model, seagrass.


Acknowledgements

We thank T. Smith, R. Watson and M. Reardon for field assistance, J. Smith and M. Palmer for laboratory assistance, the people of Roytal Enterprises for constructing ASUs and the referees for their insightful comments on the manuscript. Funding was provided through grants from the Australian Research Council (R.C., J.H., G.J.), CSIRO (P.M. with D. Smith), Holsworth Wildlife Foundation (P.M.), and a Nancy Millis Research Award (P.M.). Research was done under University of Melbourne Animal Ethics and Department of Primary Industries Fisheries permits, using the facilities of the Victorian Marine Science Consortium.


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