No abstract

Habitat fragmentation drives biodiversity loss in rivers around the world. Although the effects of anthropogenic barriers on river connectivity are well known, there has been little research on the ways in which stream drying may alter connections among habitats and resources. Given that stream drying is increasing in many regions, there is a pressing need to understand the effects of drying on habitat fragmentation. Here, we quantify spatiotemporal drying patterns under current and future climate scenarios in the Upper Blue River Basin, Oklahoma. We used a hydrologic model to simulate daily streamflow for nine climate scenarios. For each scenario, we calculated metrics of streamflow temporal continuity (dry days, dry periods, and dry period duration) and spatial connectivity (wetted length, number of dry stream fragments, length of dry stream fragments, and dendritic connectivity index) from simulated daily streamflow. We found that stream drying is likely to increase in all future climate scenarios and that increases in stream drying reduce connectivity. However, the effects of stream drying on connectivity were highly nonlinear. Specifically, we observed a threshold around which a small increase in stream drying led to a rapid drop in connectivity. We also found that the greatest increases in stream drying were not associated with the highest emission scenarios, underscoring the complex linkages among climate, water availability, and connectivity. Given that connectivity is essential to ecosystem structure and function, we discuss water management strategies informed by impacts of stream drying.

DNA‐based aquatic biomonitoring methods show promise to provide rapid, standardized, and efficient biodiversity assessment to supplement and in some cases replace current morphology‐based approaches that are often less efficient and can produce inconsistent results. Despite this potential, broad‐scale adoption of DNA‐based approaches by end‐users remains limited, and studies on how these two approaches differ in detecting aquatic biodiversity across large spatial scales are lacking. Here, we present a comparison of DNA metabarcoding and morphological identification, leveraging national‐scale, open‐source, ecological datasets from the National Ecological Observatory Network (NEON). Across 24 wadeable streams in North America with 179 paired sample comparisons, we found that DNA metabarcoding detected twice as many unique taxa than morphological identification overall. The two approaches showed poor congruence in detecting the same taxa, averaging 59%, 35%, and 23% of shared taxa detected at the order, family, and genus levels, respectively. Importantly, the two approaches detected different proportions of indicator taxa like %EPT and %Chironomidae. DNA metabarcoding detected far fewer Chironomid and Trichopteran taxa than morphological identification, but more Ephemeropteran and Plecopteran taxa, a result likely due to primer choice. Overall, our results showed that DNA metabarcoding and morphological identification detected different benthic macroinvertebrate communities. Despite these differences, we found that the same environmental variables were correlated with invertebrate community structure, suggesting that both approaches can accurately detect biodiversity patterns across environmental gradients. Further refinement of DNA metabarcoding protocols, primers, and reference libraries–as well as more standardized, large‐scale comparative studies–may improve our understanding of the taxonomic agreement and data linkages between DNA metabarcoding and morphological approaches.