Nutrient-diffusing substrata were used to determine if periphyton communities in lakes of different benthic productivity respond similarly to nutrient inputs, and if their responses corresponded with inference models developed from a calibration set of 32 Irish lakes. In addition, the attributes of the periphyton community most effective for detecting changes in periphyton associated with nutrient addition were examined. P-addition treatments had significantly higher algal biovolume than N-addition or control treatments. Canonical correspondence analysis using nominal variables to define treatments indicated that both nutrient addition and lake (= benthic productivity) significantly affected taxonomic composition and the proportion of algal growth forms. The more productive lakes had a greater relative abundance of filamentous chlorophytes, cyanobacteria, and mobile and stalked diatoms. Within lakes, nutrient addition was associated with an increase in filamentous chlorophytes and decreases in nonmobile prostrate growth forms and Achnanthes minutissima. Transfer functions from previously developed inference models were capable of inferring relative differences in total P concentrations among the lakes but lacked precision when predicting responses to nutrient addition. The relationship between normalized size spectra of algae and nutrient status was contradictory. Algae were significantly larger in nutrient-addition treatments within one lake. However, among lakes, larger size classes were most abundant in the least productive lake. Overall, the results indicate that increased nutrient loading should increase periphyton area-specific biovolume, increase filamentous chlorophytes, and potentially shift size spectra to larger classes over a broad range of benthic productivities in hardwater lakes. Changes in algal growth form appeared to be the most expedient attribute to measure when using periphyton communities to assess nutrient loading. Examining the response of benthic freshwater communities to experimental addition of nutrients in situ may help to better refine calibration sets and improve inference models, especially if the data set is restricted to lakes with similar watershed-scale characteristics.
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