Scale and the detection of land-use effects on morphology, vegetation and macroinvertebrate communities of grassland streams

1. Land‐use studies are challenging because of the difficulty of finding catchments that can be used as replicates and because land‐use effects may be obscured by sources of variance acting over spatial scales smaller than the catchment. To determine the extent to which land‐use effects on stream ecosystems are scale dependent, we designed a whole‐catchment study of six matched pairs (pasture versus native tussock) of second‐order stream catchments, taking replicate samples from replicate bedforms (pools and riffles) in each stream. 2. Pasture streams had a smaller representation of endemic riparian plant species, particularly tussock grasses, higher bank erosion, a somewhat deeper layer of fine sediment, lower water velocities in riffles, less moss cover and higher macroinvertebrate biodiversity. At the bedform scale, suspendable inorganic sediment (SIS) was higher in pools than riffles and in pasture streams there was a negative relationship between SIS and the percentage of the bed free of overhanging vegetation. Differences between stream reaches (including any interactions between land use and stream pair) were significant for SIS, substrate depth and characteristics of riparian vegetation. There were also significant differences between replicate bedforms in the same stream reaches in percentage exotic species in overhanging vegetation, percentage moss cover, QMCI (Quantitative Macroinvertebrate Community Index – a macroinvertebrate‐based stream health index) and macroinvertebrate density. 3. Significant differences among stream reaches and among replicate bedform units within the same reach, as well as interactions between these spatial units and land‐use effects, are neither trivial nor ‘noise’ but represent real differences among spatial units that typically are unaccounted for in stream studies. Our multi‐scale study design, accompanied by an investigation of the explanatory power of different factors operating at different scales, provides an improved understanding of variability in nature.