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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.

 

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.

 

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.

 

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.

 

Production of animal biomass and the number of trophic levels supported by an ecosystem depend in part on rates of primary production, disturbance, predator–prey interactions, and the efficiency of energy flow through food webs. Of these factors, food web efficiency has been among the most difficult to quantify empirically. Thus, both the drivers and consequences of variation in food web efficiency remain largely unstudied in field settings. We estimated food web efficiency in nine desert streams spanning gradients of flash flood recurrence, resource availability, and trophic structure. Food web efficiency was estimated as fish community production relative to gross primary production at an annual timescale, based on quarterly observations of fish biomass and stream metabolism. Gross primary production was greatest in streams characterized by flashier flow regimes and greater relative light, temperature, and nitrogen availability. Fish production ranged from 0.02 to 0.50 g C m⁻² yr⁻¹, food web efficiency ranged from 9.5 × 10⁻⁵to 1.8 × 10⁻², and both properties decreased with flashier flow regime, light, temperature, and nitrogen availability, but were not associated with food chain length. These results, combined with opposite effects of environmental variation on primary vs. fish production, indicated that the effects of disturbance regime (i.e., scouring floods), light, and temperature on fish production were not strongly mediated by bottom‐up controls. Estimates of food web efficiency under ambient disturbance and resource regimes suggest that a decoupling of energy flow from primary producers to upper trophic levels may prevail in hydrologically dynamic desert stream ecosystems.

 

Environmental regimes, which encompass decadal‐scale or longer variation in climate and disturbance, shape communities by selecting for adaptive life histories, behaviors, and morphologies. In turn, at ecological timescales, extreme events may cause short‐term changes in composition and structure via mortality and recolonization of the species pool. Here, we illustrate how short‐term variation in desert stream fish communities following floods and droughts depends on the context of the long‐term flow regime through ecological filtering of life history strategies. Using quarterly measures of fish populations in streams spanning a 10‐fold gradient in flow variation in Arizona, USA, we quantified temporal change in community composition and life history strategies. In streams with highly variable flow regimes, fish communities were less diverse, fluctuation in species richness was the principle mechanism of temporal change in diversity, and communities were dominated by opportunistic life history strategies. Conversely, relatively stable flow regimes resulted in more diverse communities with greater species replacement and dominance of periodic and equilibrium strategies. Importantly, the effects of anomalous high‐ and low‐flow events depended on flow regime. Under more stable flow regimes, fish diversity was lower following large floods than after seasons without floods, whereas diversity was independent of high‐flow events in streams with flashier flow regimes. Likewise, community life history composition was more dependent on antecedent anomalous events in stable compared to more temporally variable regimes. These findings indicate that extreme events may be a second‐level filter on community composition, with effects contingent on the long‐term properties of the disturbance regime (e.g., overall degree of variation) in which extremes take place. Ongoing changes to global environmental regimes will likely drive new patterns of community response to extreme events.

 

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. 

Storing and managing river flows through reservoirs could dampen or increase climate‐induced fluctuations in streamflow, but interactions between the effects of dams and climate are poorly understood. Here, we examined how dam properties control different facets of flow alteration across the coterminous United States (CONUS), and compared alteration trends between dam‐affected and reference stream gages. We quantified departures from the natural flow regime using 730 stations with long‐term daily discharge data. Dam size and purpose explained high variation in flow alteration, and alteration was particularly severe in water‐stressed regions. Importantly, regulation of river flows by dams often dampened climate‐driven alteration (48% of the flow metrics), particularly in watersheds with positive flow trends; while worsening climatic impacts in other cases (44%), or even having dual effects (8%). Our results show that dam and climate impacts on streamflow need to be assessed jointly, and based on a diverse range of flow regime facets (e.g., event magnitude and duration, frequency, and timing) instead of mean annual flows only. By pairing the USGS streamflow records available from upstream and downstream of 209 dams across the CONUS, we advance the notion that dams amplify flow alteration, but also ameliorate some flow alteration metrics. Understanding such potential and limitations is important in light of climate non‐stationarity and a new wave of damming in developing economies, and will be key to further advancing environmental flow science into the future.

 

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.