Advancing potential of diatom indicators for stream and lake water quality assessment against nutrient-induced pollution

Algae have a long history of use in indicating ecological condition of streams and lakes. Various algae-based indicators have been developed and used in stream and lake water quality management of nutrient pollution. The aim of this work is to synthesize recent studies on using diatom indicators to assess effects of nutrient pollution in streams and lakes worldwide. Here we have reviewed the advancement of the use of diatoms in: (1) assessing the stream and lake conditions by multimetric index (MMI) method, (2) modeling excessive algal dominance in waters, and (3) tracking changes of eutrophication status of lakes. Lots of progress has been made on using algae to evaluate the condition of streams and lakes by MMI method in terms of assessment consistency and accuracy in recent years. Researchers have largely solved consistency issues of assessment from sampling design to MMI development in face of great ecological diversity. Site-specific modeling can improve assessment accuracy either in streams or in lakes. However, more studies are needed to evaluate the importance of varying diatom metrics and site classification by diatom typology. Hence, it is valuable to address to what extent the biological condition of streams and lakes are represented by diatom metrics under different levels of human disturbance. The close relationship between diatoms and other algae makes diatom metrics better predictors for modeling excessive dominance of algae than commonly used physical and chemical variables. Existing studies showed inferred-total phosphorus based on diatoms performed better on predicting Cladophora condition in streams than on modeling cyanobacteria biomass in lakes. However, more studies are needed to accurately evaluate the performance of diatom-based metrics on modeling algal dominance in streams and lakes. Using diatom-based quantitative reconstructions to track environmental change in paleolimnology is meaningful but not without problems. Therefore, we also reviewed effects of some "unconventional" environmental factors on quantitative reconstructions, such as upstream water of lakes and invasive species.