Assessing individual components of biodiversity, such as local or regional taxon richness, and differences in community composition is a long‐standing challenge in ecology. It is especially relevant in spatially structured and diverse ecosystems. Environmental DNA (eDNA) has been suggested as a novel technique to detect taxa and therefore may allow to accurately measure biodiversity. However, we do not yet fully understand the comparability of eDNA‐based assessments to classical morphological approaches. We assessed may‐, stone‐, and caddisfly genera with two contemporary methods, namely eDNA sampling followed by molecular identification and kicknet sampling followed by morphological identification. We sampled 61 sites distributed over a large river network, allowing a comparison of various diversity measures from the catchment to site levels and providing insights into how these measures relate to network properties. We extended our data with historical morphological records of total diversity at the catchment level. At the catchment scale, identification based on eDNA and kicknet samples detected similar proportions of the overall and cumulative historically documented richness (gamma diversity), 42% and 46%, respectively. We detected a good overlap (62%) between genera identified from eDNA and kicknet samples at the regional scale. At the local scale, we found highly congruent values of local taxon richness (alpha diversity) between eDNA and kicknet samples. Richness of eDNA was positively related to discharge, a descriptor of network position, while kicknet was not. Beta diversity, a measure of dissimilarity between sites, was comparable for the two contemporary methods and is driven by species replacement and not by nestedness. Although eDNA approaches are still in their infancy and optimization regarding sampling design and laboratory work is still needed, our results indicate that it can capture different components of diversity, proving its potential utility as a new tool for large sampling campaigns across hitherto understudied complete river catchments.

DNA metabarcoding is increasingly used for the assessment of aquatic communities, and numerous studies have investigated the consistency of this technique with traditional morpho‐taxonomic approaches. These individual studies have used DNA metabarcoding to assess diversity and community structure of aquatic organisms both in marine and freshwater systems globally over the last decade. However, a systematic analysis of the comparability and effectiveness of DNA‐based community assessment across all of these studies has hitherto been lacking. Here, we performed the first meta‐analysis of available studies comparing traditional methods and DNA metabarcoding to measure and assess biological diversity of key aquatic groups, including plankton, microphytobentos, macroinvertebrates, and fish. Across 215 data sets, we found that DNA metabarcoding provides richness estimates that are globally consistent to those obtained using traditional methods, both at local and regional scale. DNA metabarcoding also generates species inventories that are highly congruent with traditional methods for fish. Contrastingly, species inventories of plankton, microphytobenthos and macroinvertebrates obtained by DNA metabarcoding showed pronounced differences to traditional methods, missing some taxa but at the same time detecting otherwise overseen diversity. The method is generally sufficiently advanced to study the composition of fish communities and replace more invasive traditional methods. For smaller organisms, like macroinvertebrates, plankton and microphytobenthos, DNA metabarcoding may continue to give complementary rather than identical estimates compared to traditional approaches. Systematic and comparable data collection will increase the understanding of different aspects of this complementarity, and increase the effectiveness of the method and adequate interpretation of the results.

Hammerhead ribozymes are self-cleaving RNA molecules capable of regulating gene expression in living cells. Their cleavage performance is strongly influenced by intra-molecular loop–loop interactions, a feature not readily accessible through modern prediction algorithms. Ribozyme engineering and efficient implementation of ribozyme-based genetic switches requires detailed knowledge of individual self-cleavage performances. By rational design, we devised fluorescent aptamer-ribozyme RNA architectures that allow for the real-time measurement of ribozyme self-cleavage activity in vitro. The engineered nucleic acid molecules implement a split Spinach aptamer sequence that is made accessible for strand displacement upon ribozyme self-cleavage, thereby complementing the fluorescent Spinach aptamer. This fully RNA-based ribozyme performance assay correlates ribozyme cleavage activity with Spinach fluorescence to provide a rapid and straightforward technology for the validation of loop–loop interactions in hammerhead ribozymes.

Predicting how ecological communities will respond to environmental change is challenging but highly relevant in this era of global change. Ecologists commonly use current spatial relationships between species and environmental conditions to make predictions about the future. This assumes that species will track conditions by shifting their distributions. However, theory and experimental evidence suggest that species interactions prevent communities from predictably tracking temporal changes in environmental conditions on the basis of current spatial relationships between species and environmental gradients.We tested this hypothesis by assessing the dynamics of protist species in replicated two-patch microcosm landscapes that experienced different regimes of spatial and temporal environmental heterogeneity (light vs. dark). Populations were kept in monocultures or polycultures to assess the effect of species interactions. In monocultures, abundances were predictable on the basis of current environmental conditions, regardless of whether the populations had experienced temporal environmental change. But in polycultures, abundances also depended on the history of the environmental conditions experienced. This suggests that because of species interactions, communities should respond differently to spatial versus temporal environmental changes. Thus, species interactions likely reduce the accuracy of predictions about future communities that are based on current spatial relationships between species and the environment.