Trait selection strategy for functional diversity in freshwater systems: A case framework of macroinvertebrates

The rapid and continuous loss of biodiversity highlights the urgent need for research on functional diversity. Although the study of functional diversity has exploded in the past two decades, there is no clear guidance on how traits should be selected for index calculation, which significantly influences functional diversity results. To fill this gap, we explored how the functional diversity of freshwater macroinvertebrates has been estimated over the past 20 years and how it differs across continents and water bodies. We found that Europe is the absolute centre of research in this area and that most of the research comes from studies of European lotic waters. By fitting cumulative frequencies to the number of articles using different numbers of traits, our results showed that approximately 80% of the studies used no more than 12 traits to estimate functional diversity. Furthermore, by exploring the use frequency of numbers and types of traits in different regions and water bodies and combining them with trait grouping, we recommend the use of traits evenly from four trait groups to calculate functional diversity indices. This selection strategy can contribute to the unification of functional diversity estimations and comparative studies of different regions, thus helping to better understand and manage biodiversity loss worldwide.

Automated summary

The rapid and continuous loss of biodiversity highlights the urgent need for research on functional diversity. However, there is no clear guidance on how traits should be selected for index calculation, which significantly influences the results. In this study, we explored the estimation of functional diversity of freshwater macroinvertebrates over the past 20 years and found that Europe is the center of research in this area. We recommend the use of traits evenly from four trait groups to calculate functional diversity indices, which can contribute to the unification of estimations and comparative studies of different regions.