Assessing changes in stream macroinvertebrate communities across ecological gradients using morphological versus DNA metabarcoding approaches

Freshwater macroinvertebrates provide valuable indicators for biomonitoring ecosystem change in relation to natural and anthropogenic drivers. DNA metabarcoding is an efficient approach for estimating such indicators, but its results may differ from morphotaxonomic approaches traditionally used in biomonitoring. Here we test the hypothesis that despite differences in the number and identity of taxa recorded, both approaches may retrieve comparable patterns of community change, and detect similar ecological gradients influencing such changes. We compared results obtained with morphological identification at family level of macroinvertebrates collected at 80 streams under a Water Framework Directive biomonitoring program in Portugal, with results obtained with metabarcoding from the ethanol preserving the bulk samples, using either single (COI-M19BR2, 16S-Inse01, 18S-Euka02) or multiple markers. Metabarcoding recorded less families and different communities compared to morphotaxonomy, but community sensitivities to disturbance estimated with the IASPT index were more similar across approaches. Spatial variation in local community metrics and the factors influencing such variation were significantly correlated between morphotaxonomy and metabarcoding. After reducing random noise in the dissimilarity matrices, the spatial variation in community composition was also significantly correlated across methods. A dominant gradient of community change was consistently retrieved, and all methods identified a largely similar set of anthropogenic stressors strongly influencing such gradient. Overall, results confirm our initial hypothesis, suggesting that morphotaxonomy and metabarcoding can estimate consistent spatial patterns of community variation and their main drivers. These results are encouraging for macroinvertebrate biomonitoring using metabarcoding approaches, suggesting that they can be intercalibrated with morphotaxonomic approaches to recover equivalent spatial and temporal gradients of ecological change.