Aquatic insects occur in both benthic and hyporheic habitats of lotic ecosystems. Although aquatic insects are typically assumed to inhabit benthic environments, they also utilize the hyporheic zone as a refuge from extreme conditions, predation, or drying. However, most studies examining insects in the hyporheic zone have focused either on single mesohabitat units (i.e., riffles) or relatively short reach-based approaches, with few investigations at larger scales. This highlights the need to understand relationships between benthic and hyporheic insect communities and to determine how those assemblages differ under specific environmental conditions, especially at large spatial scales (i.e., whole watersheds).
From 2021 to 2022, we sampled aquatic insects in the benthos and hyporheos at 64 riffle sites across 9 rivers across Texas, USA, along with a suite of site-specific environmental and hydrologic variables (e.g., dissolved oxygen, water temperature, conductivity, dissolved nutrients, discharge, hydraulic conductivity). Sites span wide hydrologic, geologic, land use, climatic, and ecoregion gradients, from sandy mainstem rivers in wet east and dry north Texas to rocky groundwater-dominated streams in sub-tropical central and semi-arid western Edwards Plateau. Using this dataset of paired benthic – hyporheic samples, we investigated relationships between benthic and hyporheic insect communities, asking whether the hyporheic insect community comprises consistent taxonomic or functional subsets of the benthic community across all river basins, or if the two communities vary independently. We also investigated relationships between environmental conditions and abundance and diversity of insects in the hyporheic zone.
The study is the first to investigate relationships between insect communities in the benthic and hyporheic zones across multiple large watersheds, and to quantify relationships between the two communities across large spatial, hydrologic (e.g., river position), and environmental gradients. Our results will support models that seek to understand how aquatic ecosystems will change under future environmental conditions, thus supporting more effective management and restoration of aquatic ecosystems.