Baseflow physical characteristics differ at multiple spatial scales in stream networks across diverse biomes
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Spatial scaling of ecological processes is facilitated by quantifying underlying habitat attributes. Physical and ecological patterns are often measured at disparate spatial scales limiting our ability to quantify ecological processes at broader spatial scales using physical attributes.
We characterized variation of physical stream attributes during periods of high biological activity (i.e., baseflow) to match physical and ecological measurements and to identify the spatial scales exhibiting and predicting heterogeneity.
We measured canopy cover, wetted width, water depth, and sediment size along transects of 1st–5th order reaches in five stream networks located in biomes from tropical forest to arctic tundra. We used hierarchical analysis of variance with three nested scales (watersheds, stream orders, reaches) to identify scales exhibiting significant heterogeneity in attributes and regression analyses to characterize gradients within and across stream networks.
Heterogeneity was evident at one or multiple spatial scales: canopy cover and water depth varied significantly at all three spatial scales while wetted width varied at two scales (stream order and reach) and sediment size remained largely unexplained. Similarly, prediction by drainage area depended on the attribute considered: depending on the watershed, increases in wetted width and water depth with drainage area were best fit with a linear, logarithmic, or power function. Variation in sediment size was independent of drainage area.
The scaling of ecologically relevant baseflow physical characteristics will require study beyond the traditional bankfull geomorphology since predictions of baseflow physical attributes by drainage area were not always best explained by geomorphic power laws.
KeywordsGeomorphology Nested ANOVA Scaling Grasslands Temperate forest Boreal forest
We thank Kyle Arndt, Ford Ballantyne, John Brant, Phillip Bumpers, Jason Coombs, Cindy Fifield, Derrick Jent, Audrey Mutschlecner, Katie Norris, Claire Ruffing, Geoff Schwaner, Ryan Sleeper, Chao Song, Rachel Voight for help with field measurements. This research was funded by US NSF Macrosystems grant #EF1065255. This is publication 16-134-J from the Kansas Agricultural Experiment Station.
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