Abstract
Land management to protect streams requires knowing which parts of the landscape most strongly influence stream condition. Understanding how flow through landscapes and along streams affects such land-use impacts requires knowing the period of antecedent discharge that most strongly influences condition. Both considerations require determination of optimal weighting schemes for predictors of stream condition. We calculated forest cover weighted by flow-path distance to 572 urban, peri-urban, and rural sites—in the Melbourne, Australia, region—sampled for macroinvertebrates, and antecedent discharge weighted by time preceding each of 1,723 samples. Using mixed linear models that accounted for spatial dependence, we aimed to determine the weighting curve shape and length that best predicted macroinvertebrate assemblage composition. The best model was a function of mean annual discharge, weighted forest cover, weighted imperviousness, weighted antecedent discharge, and their interactions. Optimal weightings were exponential—half-decay distance 35 m overland (plausible range 26–50 m), and 1.0 km in-stream (0.75–1.3 km) for forest cover—, and linear over ≥4 year for antecedent discharge. Model plausibility was more affected by weighting distance than the shape of the weighting function. Regardless of weighting curve shape, riparian forest effects on macroinvertebrate assemblages are strongest within 101–102 m from the stream, and 103 m upstream. Although exponential weightings are only marginally more plausible, they are the most realistic representation of physical processes. While our conclusions should not be interpreted as recommendations for buffer widths, they provide valuable insight into the scales of influence in the region and could be used to inform management decisions.
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Acknowledgments
This study was funded by Melbourne Water and CJW by the Melbourne Waterway Research-Practice Partnership. We thank Edward Tsyrlin and Rhys Coleman for commissioning the work, and for their support and patience; Alistair Danger for assistance with compiling land use data; and Joshphar Kunapo for compiling the digital elevation models used in our analyses. The manuscript was improved by suggestions of Nick Bond, Matthew Burns, Sarah Gergel, Michael Sammonds, Edward Tsyrlin and four referees.
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Walsh, C.J., Webb, J.A. Spatial weighting of land use and temporal weighting of antecedent discharge improves prediction of stream condition. Landscape Ecol 29, 1171–1185 (2014). https://doi.org/10.1007/s10980-014-0050-y
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DOI: https://doi.org/10.1007/s10980-014-0050-y