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Scale Dependence in the Species-Discharge Relationship for Fishes of the Southeastern U.S.A.
Citation:
MCGARVEY, D. J. AND G. M. Ward. Scale Dependence in the Species-Discharge Relationship for Fishes of the Southeastern U.S.A. FRESHWATER BIOLOGY. Blackwell Publishing, Malden, MA, 53(11):2206-2219, (2008).
Impact/Purpose:
To enhance fish conservation efforts in the southeastern United States.
Description:
Species-discharge relationships (SDR) are aquatic analogues of species-area relationships, and are increasingly used in both basic research and conservation planning. SDR studies are often limited, however, by two shortcomings. First, they do not determine whether the reported SDR’s, which normally use complete drainage basins as sampling units, are scale-dependent. Second, they do not account for the effects of habitat diversity within or among samples. We addressed both problems by using discrete fish zones as sampling units in a SDR analysis. To do so, we first tested for longitudinal zonation in three southeastern (U.S.A.) rivers. In each river, we detected successive ‘lower’, ‘middle’, and ‘upper’ fish zones, which were characterized by distinct fish assemblages with predictable habitat requirements. Because our analyses combined fish data from multiple sources, we also used rarefaction and Monte Carlo simulation to ensure that our zonation results were robust to spurious sampling effects. Next, we estimated the average discharge within each zone, and plotted these estimates against their respective richnesses (log10 data). Notably, this zonal SDR fit the empirical data better than a comparable SDR that did not discriminate among longitudinal zones. We therefore conclude that the southeastern fish SDR is scale-dependent, and that accounting for within-basin habitat diversity is an important step in explaining the high diversity of southeastern fishes. Lastly, we discuss how our zonal SDR can be used to improve conservation planning. Specifically, we show how the slope of the SDR can be used to forecast potential extinction rates, and how the zonal data can be used to identify species of greatest concern.
