Controlling for hydrologic connectivity to assess the importance of catchment- and reach-scale factors on macroinvertebrate community structure
Understanding landscape influences on stream ecosystems is a challenging task due to the spatial complexity and connectedness of stream networks. Here, we control for longitudinal connectivity to provide a robust test of the relative importance of reach- and catchment-scale factors in determining macroinvertebrate community structure in southwestern Pennsylvania streams. We determined that sites separated by ≤510 m along the stream network had significantly correlated macroinvertebrate community scores. After controlling for this spatial autocorrelation, a partial least squares regression identified two factors that together accounted for 32% of the variation in community scores. In this model, two reach-scale factors—habitat assessment score and stream pH—were the most important factors for predicting a stream’s macroinvertebrate community score. However, landscape diversity was also important. Landscape diversity is a catchment-scale factor that was highly correlated with percent pasture/hay and measures of habitat fragmentation. Our results provide support for the idea that stream communities in undisturbed areas are heavily influenced by reach-scale characteristics. Furthermore, our results indicate that Pennsylvania natural resource managers should consider habitat score and stream pH after accounting for spatial autocorrelation when identifying restoration targets for impacted streams.
KeywordsLand use Hydrologic connectivity Spatial autocorrelation Benthic macroinvertebrates Pennsylvania Total Biological Score
We thank the Pennsylvania Department of Environmental Protection for funding this research (Disclaimer: The views expressed in this manuscript do not necessarily reflect the views of this agency). We thank Tom Hann and Lucy Powell for their help in delineating watersheds, calculating catchment land use, and for assistance with preliminary analyses. We also thank Anthony Iannacchione and Erin Pfeil-McCullough for their assistance with data interpretation. Lastly, we thank Dan Bain for assistance with data analysis, interpretation, and for his comments on draft versions of this manuscript.
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