Data from: Hierarchical multi-taxa models inform riparian vs. hydrologic restoration of urban streams in a permeable landscape

  • Daniel C. Gwinn (Cooperative Research Centre for Water Sensitive Cities) (Creator)
  • Jennifer A. Middleton (Creator)
  • Leah Beesley (Creator)
  • Paul Close (Creator)
  • Belinda Quinton (Creator)
  • Tim Storer (Creator)
  • Peter Davies (Creator)



The degradation of streams caused by urbanization tends to follow predictable patterns; however, there is a growing appreciation for heterogeneity in stream response to urbanization due to the local geoclimatic context. Furthermore, there is building evidence that streams in mildly sloped, permeable landscapes respond uncharacteristically to urban stress calling for a more nuanced approach to restoration. We evaluated the relative influence of local-scale riparian characteristics and catchment-scale imperviousness on the macroinvertebrate assemblages of streams in the flat, permeable urban landscape of Perth, Western Australia. Using a hierarchical multi-taxa model, we predicted the outcomes of stylized stream restoration strategies to increase the riparian integrity at the local scale or decrease the influences of imperviousness at the catchment scale. In the urban streams of Perth, we show that local-scale riparian restoration can influence the structure of macroinvertebrate assemblages to a greater degree than managing the influences of catchment-scale imperviousness. We also observed an interaction between the effect of riparian integrity and imperviousness such that the effect of increased riparian integrity was enhanced at lower levels of catchment imperviousness. This study represents one of few conducted in flat, permeable landscapes and the first aimed at informing urban stream restoration in Perth, adding to the growing appreciation for heterogeneity of the Urban Stream Syndrome and its importance for urban stream restoration.,Macroinvertebrate and covariate dataTab-1: Macroinvertebrate catch data at sample sites. Tab-2: Covariate data at sample sites.Main_Data_File.xlsx,
Date made available6 Nov 2017
Date of data production6 Nov 2017

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