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Diatom assemblages are excellent indicators for environmental monitoring. However, enumerating diatoms using fine-level taxonomy takes considerable effort, which must be undertaken by specialist taxonomists. One alternative is to enumerate assemblages using morphological traits. In this study, we compared the accuracy of models using 20 morphological traits with those using species assemblages to infer lake water pH, salinity, depth, and total phosphorus concentrations in four data sets, each comprising over 200 lakes. Assemblages aggregated by trait combinations were used to predict environmental variables via weighted averaging regressions, and richness of trait combinations was regressed against the environmental variables. Trait-based weighted averaging regressions showed slightly lower accuracy than species-level analyses and higher accuracy than analyses at the family and sometimes genus level. Richness of trait combinations showed relationships with pH, salinity, and lake depth that were marginally stronger than relationships using species richness. Although species-level analyses are the best approach when time and budgets allow, we suggest that trait combinations could provide an alternative method for water quality assessment programs, where funds do not allow the use of specialist taxonomists or where diatoms are being used as part of a multi-indicator analysis.

Temperature–oxygen profiles, collected biweekly to monthly for ∼40 years, were used to calculate end-of-summer volume-weighted hypolimnetic oxygen (VWHO) concentrations in six small lakes located in south-central Ontario, Canada. Coherent decreases in thermocline depth and increases in hypolimnetic volume, mean hypolimnetic dissolved oxygen (DO) concentration, and VWHO were observed in five of the six study lakes. All lakes underwent an abrupt increase in VWHO and mean hypolimnetic DO after 2010. In four of the six study lakes, the highest hypolimnetic DO concentrations were observed in years where chlorophyll a concentrations were low, whereas at five of the six study lakes the highest hypolimnetic volumes were observed when dissolved organic carbon concentrations were relatively high. Warmer spring or winter air temperatures were associated with higher hypolimnetic DO concentrations at two sites, and longer ice-free periods were associated with smaller hypolimnetic volumes at two sites. These results suggest that the recent VWHO increases in the studied south-central Ontario lakes may be a function of multiple drivers that include changes in primary production, lake water transparency, and regional climatic factors.

Aquatic microorganisms are commonly used as indicators in environmental assessments. Two key aspects of sampling design for these studies are the number of sites sampled and the enumeration effort of organisms within samples. However, there has been no rigorous determination of a cost-effective balance between them. Here, we use regional diatom data sets from 207 to 493 lakes to determine the influence of sample size (lake number) and enumeration effort (valve count) on the accuracy and cost-effectiveness of commonly used environmental assessment analyses. We find that both lake number and valve count can be considerably reduced from the original data sets. However, there is considerable variation among analyses, such that a single most cost-effective sampling configuration cannot be recommended. For weighted-averaging assemblage versus environment models, we recommend 70–100 lakes and 200 valves for retaining high accuracy. For other analyses, we recommend iteratively building up data sets, using initially high (300 or more) and consistent valve counts and using subsampling to determine when the influence of either lake number or valve count plateaus. This technique is applicable to other types of microorganisms used in environmental assessments.