A spatial autocorrelative model for targeting stream restoration to benefit sensitive nongame fishes

Abstract

Stream restoration projects often aim to benefit aquatic biota and frequently use the reappearance of sensitive nongame fish species as a measure of restoration success. However, mitigation of human influence will only benefit a given species where static habitat characteristics are suitable for that species and where potential source populations are within the range of their dispersal capability. We used spatial autoregressive habitat models to simulate the effect of watershed-scale stream restoration on the distributions of six sediment-sensitive fish species in Wisconsin, USA, streams. These models consider the probability of occurrence of a species in a given stream segment as a function of characteristics of that segment as well as the characteristics of neighboring segments. Populations of individual species are predicted to be restorable in 0.2%–2.8% of Wisconsin streams. Streams with high restoration potential for one or more species generally have high watershed human land use but are also closely connected through the stream network to relatively undisturbed streams. These results indicate that habitat restoration for nongame stream fishes will be most effective when it builds onto existing suitable habitat because of both dispersal limitation and spatial autocorrelation of habitat characteristics.