Congruency between two traditional and eDNA-based sampling methods in characterising taxonomic and trait-based structure of fish communities and community-environment relationships in lentic environment

Abstract

Recent developments in environmental DNA (eDNA) metabarcoding suggest that eDNA-based representation of ecological communities can be a promising tool in both fundamental ecological research and environmental assessment. However, it is less known, how eDNA performs in characterising ecological communities and community-environment relationships at the regional scale compared with traditional sampling methods. Here, we used electrofishing (EF), gillnetting (GN) and eDNA-based surveys to compare their congruency in characterising the taxonomic and trait-based structure of (oxbow) lake fish communities and their structuring mechanisms. eDNA proved to be more effective in detecting taxa in the total samples and by traits than EF and GN. Principal coordinate analysis and multiple factor analysis showed a moderate separation of communities according to sampling methods for the taxon and the trait-based structures, respectively, but eDNA samples were always located in intermediate position in the ordination plots. Procrustes analyses indicated significant among-method congruency in community structure. However, in general, eDNA-based community patterns always showed higher correlation with either the EF or the GN-based community patterns, than the two traditional methods to each other. Variance partitioning in redundancy analyses indicated large differences among the sampling methods in the importance of environmental and spatial variables in shaping metacommunity structure. These results thus suggest that the sampling method can largely influence the identified mechanisms which govern fish metacommunity organisation. Our results suggest, that eDNA metabarcoding can be the best universal method for understanding the taxonomic and trait-based organisation of lake fish metacommunities.

Keywords

• Fish sampling
• Oxbow lakes
• Variance partitioning
• Functional groups
• Metacommunity