Periphyton, water quality, and land use at multiple spatial scales in Alberta rivers

• Published in: Canadian journal of fisheries and aquatic sciences 2005-06, Vol.62 (6), p.1309-1319
• Main Authors: Carr, Geneviève M, Chambers, Patricia A, Morin, Antoine
• Format: Article
• Language: English
• Subjects: Animal and plant ecology; Animal populations; Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Chlorophyll; Exploitation and management of natural biological resources (hunting, fishing and exploited populations survey, etc.); Fish; Fresh water ecosystems; Freshwater; Fundamental and applied biological sciences. Psychology; Human population density; Human populations; Land use; Nutrient concentrations; Population density; Prediction models; Rivers; Streams; Synecology; Variability; Variance analysis; Water quality
• ISSN: 0706-652X; 1205-7533
• DOI: 10.1139/f05-044

The ability of land use to replace water quality variables in predictive models of periphyton chlorophyll a was tested with a 21-year data set for Alberta rivers. Nutrients (total dissolved P and NO 2 + NO 3 ) explained 23%–24% of the variability in seasonal chlorophyll a, whereas land use (human population density) explained 25%–28% of the variability. The best models included the combination of total dissolved P and population density, explaining 32%–34% of periphyton chlorophyll a variability. However, analysis of variance of chlorophyll a by ecoregions and ecozones explained about as much variability (28%–30%), and the inclusion of an ecoregion term into the regression models showed a diminished importance of land use as a predictor of chlorophyll a, with best models based on the combination of nutrients and ecoregion and explaining up to 43%–44% of periphyton chlorophyll a variability. Within ecoregions, land use was sometimes a good surrogate for nutrient data in predicting chlorophyll a concentrations. Overall, land use is a suitable surrogate for nutrients in regression models for chlorophyll a, but its inclusion in general models may reflect regional differences in nutrient–chlorophyll relationships rather than true land use effects on chlorophyll a.