Improving biological condition assessment accuracy by multimetric index approach with microalgae in streams and lakes

Abstract

<p indent="0mm">The multimetric index (MMI) approach is broadly used in ecological assessment because it integrates information of various ecologically related metrics of freshwater ecosystems and provides an easily understandable score for further evaluation and management. Accounting for natural variation and disentangling covariation between natural environmental and human disturbance factors is imperative for an accurate assessment. <italic>A priori</italic> classification of sites by regions or typologies, site-specific modeling of expected reference conditions, and varying metrics in site groups are three approaches that have been used to control natural variation in ecological assessments. Researchers have recently made a lot of progress in improving biological condition assessment accuracy by the MMI approach with microalgae in streams and lakes. All existing studies support that site-specific modeling can efficiently account for natural variation and generate an MMI with good performance. However, no strong evidence has shown that diatom/blue-algae typologies are better than regionalization frameworks in accounting for natural variation in lakes or streams. Separating the natural variation explained by site-specific modeling from that of varying metrics is necessary for a thorough and accurate evaluation of the valuableness of site-grouping by typologies. The different performances of varying metrics among site groups of streams and lakes are most probably caused by the lack of representativeness of diatom metrics on biological conditions rather than the complex multi-stressor gradients in streams and rivers. This study reviewed recent progress in defining the ecological condition of lakes and streams by the MMI approach with microalgae and some concerns in using statistical techniques to compare MMI performance.