The Development of an aquatic habitat classification system for lakes

1993 ◽  
Vol 30 (09) ◽  
pp. 30-4980-30-4980
1985 ◽  
Vol 49 (1) ◽  
pp. 19 ◽  
Author(s):  
Rebecca J. Howard ◽  
Joseph S. Larson

2011 ◽  
Vol 68 (9) ◽  
pp. 1954-1962 ◽  
Author(s):  
Rachel Przeslawski ◽  
David R. Currie ◽  
Shirley J. Sorokin ◽  
Tim M. Ward ◽  
Franziska Althaus ◽  
...  

Abstract Przeslawski, R., Currie, D. R., Sorokin, S. J., Ward. T. M., Althaus, F., and Williams, A. 2011. Utility of a spatial habitat classification system as a surrogate of marine benthic community structure for the Australian margin. – ICES Journal of Marine Science, 68: 1954–1962. This study tests whether a continental-scale classification of Australian benthic habitats (termed “seascapes”) and the interpolated environmental data from which they are derived are useful as abiotic surrogates of biodiversity at a local [tens of kilometres, Great Australian Bight (GAB)] and regional scale [hundreds of kilometres, Western Australian (WA) margin]. Benthic invertebrate community structure is moderately associated with specific seascapes in both the GAB (R = 0.418) and WA margin (excluding hard substrata, R = 0.375; all substrata, R = 0.313). Mud content, seafloor slope, and seafloor temperature are significantly correlated with invertebrate communities at both scales, with disturbance and primary production correlated with GAB communities. Seascapes are not consistently useful surrogates because the strength and significance of relationships between seascapes and community structure differs among seascapes, regions, and spatial scales. Nevertheless, a national system of seascapes is an appropriate surrogate for broad-scale benthic invertebrate community patterns when biological data are limited, provided the uncertainty is acknowledged and, where possible, an assessment made of each seascape's ability to differentiate biological communities. Further refinement of seascape derivations may include updated and additional environmental data (particularly for hard vs. soft substrata) and validation among biological datasets from a range of habitats and scales.


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