Explaining spatial variability in stream habitats using both natural and management-influenced landscape predictors

Abstract

The distribution and composition of in-stream habitats are reflections of landscape scale geomorphic and climatic controls. Correspondingly, Pacific salmon (Oncorhynchus spp.) are largely adapted to and constrained by the quality and complexity of those in-stream habitat conditions. The degree to which lands have been fragmented and managed can disrupt these patterns and affect overall habitat availability and quality. Eleven in-stream habitat features were modelled as a function of landscape composition. In total, 121 stream reaches within coastal catchments of Oregon were modelled. For each habitat feature, three linear regression models were applied in sequence; final models were composed of the immutable and management-influenced landscape predictors that best described the variability in stream habitat. Immutable landscape predictors considered proxies for stream power described the majority of the variability seen in stream habitat features. Management-influenced landscape predictors, describing the additional human impacts beyond that which was inherently entwined with the immutable predictors, explained a sizeable proportion of variability. The largest response was seen in wood volume and pool frequency. By using a sequential linear regression analysis, management-influenced factors could be segregated from natural gradients to identify those stream habitat features that may be more sensitive to land-use pressures. These results contribute to the progressing notion that the conservation of freshwater resources is best accomplished by investigating and managing stream systems from a landscape perspective. © 2011 John Wiley & Sons, Ltd.