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Abstract Despite its far-reaching implications for conservation and natural resource management, little is known about the color of environmental noise, or the structure of temporal autocorrelation in random environmental variation, in streams and rivers. Here, we analyze the geography, drivers, and timescale-dependence of noise color in streamflow across the U.S. hydrography, using streamflow time series from 7504 gages. We find that daily and annual flows are dominated by red and white spectra respectively, and spatial variation in noise color is explained by a combination of geographic, hydroclimatic, and anthropogenic variables. Noise color at the daily scale is influenced by stream network position, and land use and water management explain around one third of the spatial variation in noise color irrespective of the timescale considered. Our results highlight the peculiarities of environmental variation regimes in riverine systems, and reveal a strong human fingerprint on the stochastic patterns of streamflow variation in river networks. 

Abstract Rivers are efficient corridors for aquatic animals, primarily under the assumption of perennial flow. However, the recognition that river drying is a common and widespread phenomenon requires reexamining animal movement through river networks. Intermittent rivers and ephemeral streams have been overlooked when studying animal movement, even though approximately 60% of the global river network dries. In the present article, we extend the current focus of river ecology by integrating the effects of drying on the movement of aquatic and terrestrial animals. Moreover, we introduce a conceptual model that challenges the current bias, which is focused on perennial waterways, by encompassing animal movement across hydrologic phases (nonflowing, flowing, dry, rewetting) and habitats (aquatic, terrestrial). We discuss their corridor function in conservation and restoration planning and identify emerging research questions. We contend that a more comprehensive and inclusive view of animal movement in dry channels will advance ecological understanding of river networks and respective conservation efforts. 

Abstract Studies of stream macroinvertebrates traditionally use sampling methods that target benthic habitats. These methods could underestimate biodiversity if important assemblage components exist outside of the benthic zone. To test the efficacy of different sampling methods, we collected paired reach‐wide benthic and edge samples from up to 10 study reaches in nine basins spanning an aridity gradient across the United States. Edge sampling targeted riparian‐adjacent microhabitats not typically sampled, including submerged vegetation, roots, and overhanging banks. We compared observed richness, asymptotic richness, and assemblage dissimilarity between benthic samples alone and different combinations of benthic and edge samples to determine the magnitude of increased diversity and assemblage dissimilarity values with the addition of edge sampling. We also examined how differences in richness and assemblage composition varied across an aridity gradient. The addition of edge sampling significantly increased observed richness (median increase = 29%) and asymptotic richness (median increase = 173%). Similarly, median Bray–Curtis dissimilarity values increased by as much as 0.178 when benthic and edge samples were combined. Differences in richness metrics were generally higher in arid basins, but assemblage dissimilarity either increased or decreased across the aridity gradient depending on how benthic and edge samples were combined. Our results suggest that studies that do not sample stream edges may significantly underestimate reach diversity and misrepresent assemblage compositions, with effects that can vary across climates. We urge researchers to carefully consider sampling methods in field studies spanning climatic zones and the comparability of existing data sets when conducting data synthesis studies. 

River ecosystems are highly biodiverse, influence global biogeochemical cycles, and provide valued services. However, humans are increasingly degrading fluvial ecosystems by altering their streamflows. Effective river restoration requires advancing our mechanistic understanding of how flow regimes affect biota and ecosystem processes. Here, we review emerging advances in hydroecology relevant to this goal. Spatiotemporal variation in flow exerts direct and indirect control on the composition, structure, and dynamics of communities at local to regional scales. Streamflows also influence ecosystem processes, such as nutrient uptake and transformation, organic matter processing, and ecosystem metabolism. We are deepening our understanding of how biological processes, not just static patterns, affect and are affected by stream ecosystem processes. However, research on this nexus of flow-biota-ecosystem processes is at an early stage. We illustrate this frontier with evidence from highly altered regulated rivers and urban streams. We also identify research challenges that should be prioritized to advance process-based river restoration. 

Abstract River scientists strive to understand how streamflow regimes vary across space and time because it is fundamental to predicting the impacts of climate change and human activities on riverine ecosystems. Here we tested whether flow periodicity differs between rivers that are regulated or unregulated by large dams, and whether dominant periodicities change over time in response to dam regulation. These questions were addressed by calculating wavelet power at different timescales, ranging from 6 hr to 10 years, across 175 pairs of dam‐regulated and unregulated USGS gages with long‐term discharge data, spanning the conterminous United States. We then focused on eight focal reservoirs with high‐quality and high‐frequency data to examine the spectral signatures of dam‐induced flow alteration and their time‐varying nature. We found that regulation by dams induces changes not only in flow magnitude and variability, but also in the dominant periodicities of a river's flow regime. Our analysis also revealed that dams generally alter multi‐annual and annual periodicity to a higher extent than seasonal or daily periodicity. Based on the focal reservoirs, we illustrate that alteration of flow periodicity is time varying, with dam operations (e.g., daily peaking vs. baseload operation), changes in dam capacity, and environmental policies shifting the relative importance of periodicities over time. Our analysis demonstrates the pervasiveness of human signatures now characterizing the U.S. rivers' flow regimes, and may inform the restoration of environmental periodicity downstream of reservoirs via controlled flow releases—a critical need in light of new damming and dam retrofitting for hydropower globally. 

Abstract Groundwater is a vital ecosystem of the global water cycle, hosting unique biodiversity and providing essential services to societies. Despite being the largest unfrozen freshwater resource, in a period of depletion by extraction and pollution, groundwater environments have been repeatedly overlooked in global biodiversity conservation agendas. Disregarding the importance of groundwater as an ecosystem ignores its critical role in preserving surface biomes. To foster timely global conservation of groundwater, we propose elevating the concept of keystone species into the realm of ecosystems, claiming groundwater as a keystone ecosystem that influences the integrity of many dependent ecosystems. Our global analysis shows that over half of land surface areas (52.6%) has a medium‐to‐high interaction with groundwater, reaching up to 74.9% when deserts and high mountains are excluded. We postulate that the intrinsic transboundary features of groundwater are critical for shifting perspectives towards more holistic approaches in aquatic ecology and beyond. Furthermore, we propose eight key themes to develop a science‐policy integrated groundwater conservation agenda. Given ecosystems above and below the ground intersect at many levels, considering groundwater as an essential component of planetary health is pivotal to reduce biodiversity loss and buffer against climate change. 

Abstract As climate change continues to increase air temperature in high‐altitude ecosystems, it has become critical to understand the controls and scales of aquatic habitat vulnerability to warming. Here, we used a nested array of high‐frequency sensors, and advances in time‐series models, to examine spatiotemporal variation in thermal vulnerability in a model Sierra Nevada watershed. Stream thermal sensitivity to atmospheric warming fluctuated strongly over the year and peaked in spring and summer—when hot days threaten invertebrate communities most. The reach scale (~ 50 m) best captured variation in summer thermal regimes. Elevation, discharge, and conductivity were important correlates of summer water temperature across reaches, but upstream water temperature was the paramount driver—supporting that cascading warming occurs downstream in the network. Finally, we used our estimated summer thermal sensitivity and downscaled projections of summer air temperature to forecast end‐of‐the‐century stream warming, when extreme drought years like 2020–2021 become the norm. We found that 25.5% of cold‐water habitat may be lost under high‐emissions scenario representative concentration pathway (RCP) 8.5 (or 7.9% under mitigated RCP 4.5). This estimated reduction suggests that 27.2% of stream macroinvertebrate biodiversity (11.9% under the mitigated scenario) will be stressed or threatened in what was previously cold‐water habitat. Our quantitative approach is transferrable to other watersheds with spatially replicated time series and illustrates the importance of considering variation in the vulnerability of mountain streams to warming over both space and time. This approach may inform watershed conservation efforts by helping identify, and potentially mitigate, sites and time windows of peak vulnerability. 

Williams et al . claim that the data used in Sabo et al . were improperly scaled to account for fishing effort, thereby invalidating the analysis. Here, we reanalyze the data rescaled per Williams et al . and following the methods in Sabo et al . Our original conclusions are robust to rescaling, thereby invalidating the assertion that our original analysis is invalid.