Partitioning the variation in stream fish assemblages within a spatio-temporal hierarchy
Ben Stewart-Koster A C , Mark J. Kennard A , Bronwyn D. Harch B , Fran Sheldon A , Angela H. Arthington A and Bradley J. Pusey AA eWater Cooperative Research Centre, Australian Rivers Institute, Griffith University, Nathan, Qld 4111, Australia.
B CSIRO Mathematical and Information Sciences, 120 Meiers Road, Indooroopilly, Qld 4068, Australia.
C Corresponding author. Email: b.stewart-koster@griffith.edu.au
Marine and Freshwater Research 58(7) 675-686 https://doi.org/10.1071/MF06183
Submitted: 4 October 2006 Accepted: 8 May 2007 Published: 31 July 2007
Abstract
This paper describes the relative influence of (i) landscape scale environmental and hydrological factors, (ii) local scale environmental conditions including recent flow history, and (iii) spatial effects (proximity of sites to one another), on the spatial and temporal variation in local freshwater fish assemblages in the Mary River, south-eastern Queensland, Australia. Using canonical correspondence analysis, each of the three sets of variables explained similar amounts of variation in fish assemblages (ranging from 44 to 52%). Variation in fish assemblages was partitioned into eight unique components: pure environmental, pure spatial, pure temporal, spatially structured environmental variation, temporally structured environmental variation, spatially structured temporal variation, the combined spatial/temporal component of environmental variation and unexplained variation. The total variation explained by these components was 65%. The combined spatial/temporal/environmental component explained the largest component (30%) of the total variation in fish assemblages, whereas pure environmental (6%), temporal (9%) and spatial (2%) effects were relatively unimportant. The high degree of intercorrelation between the three different groups of explanatory variables indicates that our understanding of the importance to fish assemblages of hydrological variation (often highlighted as the major structuring force in river systems) is dependent on the environmental context in which this role is examined.
Additional keywords: canonical correspondence analysis, flow regime, habitat, spatial autocorrelation, variance partitioning.
Acknowledgements
The research presented in this paper formed part of an Honours Dissertation by the senior author in the Australian School of Environmental Studies, Griffith University. Funding support was provided by the eWater Cooperative Research Centre, the former CRC for Freshwater Ecology and the former Land and Water Resources Research and Development Corporation (LWRRDC). We thank Steve Mackay for assistance with field sampling and Nick Marsh for advice on hydrological statistics. We also thank Erin Peterson for providing useful comments on an earlier draft of the manuscript.
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