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Abstract Evaluating stream water chemistry patterns provides insight into catchment ecosystem and hydrologic processes. Spatially distributed patterns and controls of stream solutes are well‐established for high‐relief catchments where solute flow paths align with surface topography. However, the controls on solute patterns are poorly constrained for low‐relief catchments where hydrogeologic heterogeneities and river corridor features, like wetlands, may influence water and solute transport. Here, we provide a data set of solute patterns from 58 synoptic surveys across 28 sites and over 32 months in a low‐relief wetland‐rich catchment to determine the major surface and subsurface controls along with wetland influence across the catchment. In this low‐relief catchment, the expected wetland storage, processing, and transport of solutes is only apparent in solute patterns of the smallest subcatchments. Meanwhile, downstream seasonal and wetland influence on observed chemistry can be masked by large groundwater contributions to the main stream channel. These findings highlight the importance of incorporating variable groundwater contributions into catchment‐scale studies for low‐relief catchments, and that understanding the overall influence of wetlands on stream chemistry requires sampling across various spatial and temporal scales. Therefore, in low‐relief wetland‐rich catchments, given the mosaic of above and below ground controls on stream solutes, modeling efforts may need to include both surface and subsurface hydrological data and processes. 

Abstract Suspended particulate matter, or seston, represents an understudied flux of carbon (C), nitrogen (N), and phosphorus (P) in river networks. Here, we summarize riverine seston C : N : P stoichiometry data from 27 streams and rivers sampled regularly from 2014 to 2022 across the United States by the National Ecological Observatory Network (NEON). We examine relationships among seston C, N, and P content using standardized major‐axis (SMA) and ordinary least squares slopes to test congruence with a constant‐ratio model (scaling coefficient = 1), and hierarchical models to identify watershed‐level covariates of seston C : nutrient stoichiometric allometry. At the continental scale, C and N were tightly coupled and conformed to the constant‐ratio model, while seston C : P and N : P indicated weaker coupling and inconstant ratios across the range of C vs. P and N vs. P values. At the stream‐site scale, C : N, C : P, and N : P often exhibited slopes < 1, indicating that within individual streams seston becomes more nutrient‐rich as seston concentration increases. Watershed forest cover, season, and discharge helped explain stoichiometric allometry across streams, where forested sites in wetter climates had lower scaling slopes, and slopes decreased with low flows. Our study underscores the importance of suspended particles as a material flux in river networks and highlights the interplay between biotic and abiotic factors that drive the relative consistency of its C : nutrient stoichiometry during transport from local to continental scales. 

Abstract While inland freshwater networks cover less than 4% of the Earth's terrestrial surface, these ecosystems play a disproportionately large role in the global cycles of [C]arbon, [N]itrogen, and [P]hosphorus, making streams and rivers critical regulators of nutrient balance at regional and continental scales. Foundational studies have established the relative importance of the hydrologic regime, land cover, and instream removal processes for controlling the transport and processing of C, N, and P in river networks. However, particulate C, N, and P can make up a large proportion of the total material in large rivers and during high flows. To constrain the patterns of the biogeochemistry of riverine particulates, we characterized and modeled dissolved and particulate concentration variability at the continental scale using open‐access data from 27 National Ecological Observatory Network (NEON) sites across the United States. We analyzed these data using Boosted Regression Trees (BRTs) to statistically identify if land cover characteristics could predict nutrient quantity and quality of stream particulates. The BRT models revealed that land cover does not strongly predict particulate dynamics across NEON sites but indicate that instream processes might be more important than catchment characteristics alone. In addition, our study demonstrates the consistent importance of particulates relative to dissolved forms, highlighting their likely significance for biogeochemical processes along the freshwater continuum. 

ABSTRACT Non‐perennial streams are globally prevalent. These streams are vital components of ecosystems, yet their drying patterns and resulting impacts on hydrologic connectivity remain poorly understood at the watershed scale. Aridity is a dominant driver of stream drying, but its influences on hydrologic connectivity have not been fully explored. In this study, we investigated the role of aridity in shaping streamflow and connectivity patterns in non‐perennial stream networks that span the continental United States aridity gradient. Using hydrologic models, we simulated daily streamflow and stream network connectivity under current and future climate scenarios. Our findings support previous research showing that aridity and streamflow are strongly linked. We also found that connectivity was related to aridity, although this relationship was weaker. Under the future climate scenario, mean runoff increased in most watersheds in the future, while mean connectivity decreased in the majority of watersheds. This difference is an indicator of the complex relationship between streamflow and connectivity. Aridity was a strong predictor of changes in very high and very low connectivity periods that resulted from climate change, but aridity did not predict changes in mean connectivity. Arid watersheds tended to experience more high connectivity days due to climate change while humid networks tended to have more low connectivity days. By modelling climate impacts at the network scale and across a broad hydroclimatic gradient, we highlight the importance of considering context‐dependent changes in network connectivity in river flow management and watershed conservation plans. 

Abstract Climate change is rapidly altering hydrological processes and consequently the structure and functioning of Arctic ecosystems. Predicting how these alterations will shape biogeochemical responses in rivers remains a major challenge. We measured [C]arbon and [N]itrogen concentrations continuously from two Arctic watersheds capturing a wide range of flow conditions to assess understudied event‐scale C and N concentration‐discharge (C‐Q) behavior and post‐event recovery of stoichiometric conditions. The watersheds represent low‐gradient, tundra landscapes typical of the eastern Brooks Range on the North Slope of Alaska and are part of the Arctic Long‐Term Ecological Research sites: the Kuparuk River and Oksrukuyik Creek. In both watersheds, we deployed high‐frequency optical sensors to measure dissolved organic carbon (DOC), nitrate (), and total dissolved nitrogen (TDN) for five consecutive thaw seasons (2017–2021). Our analyses revealed a lag in DOC: stoichiometric recovery after a hydrologic perturbation: while DOC was consistently elevated after high flows, diluted during rainfall events and consequently, recovery in post‐event concentration was delayed. Conversely, the co‐enrichment of TDN at high flows, even in watersheds with relatively high N‐demand, represents a potential “leak” of hydrologically available organic N to downstream ecosystems. Our use of high‐frequency, long‐term optical sensors provides an improved method to estimate carbon and nutrient budgets and stoichiometric recovery behavior across event and seasonal timescales, enabling new insights and conceptualizations of a changing Arctic, such as assessing ecosystem disturbance and recovery across multiple timescales. 

Abstract The interaction of climate change and increasing anthropogenic water withdrawals is anticipated to alter surface water availability and the transport of carbon (C), nitrogen (N), and phosphorus (P) in river networks. But how changes to river flow will alter the balance, or stoichiometry, of these fluxes is unknown. The Lower Flint River Basin (LFRB) is part of an interstate watershed relied upon by several million people for diverse ecosystem services, including seasonal crop irrigation, municipal drinking water access, and public recreation. Recently, increased water demand compounded with intensified droughts have caused historically perennial streams in the LFRB to cease flowing, increasing ecosystem vulnerability. Our objectives were to quantify how riverine dissolved C:N:P varies spatially and seasonally and determine how monthly stoichiometric fluxes varied with overall water availability in a major tributary of LFRB. We used a long‐term record (21–29 years) of solute water chemistry (dissolved organic carbon, nitrate/nitrite, ammonia, and soluble reactive phosphorus) paired with long‐term stream discharge data across six sites within a single LFRB watershed. We found spatial and seasonal differences in soluble nutrient concentrations and stoichiometry attributable to groundwater connections, the presence of a major floodplain wetland, and flow conditions. Further, we showed that water availability, as indicated by the Palmer Drought Severity Index (PDSI), strongly predicted stoichiometry with generally lower C:N and C:P and higher N:P fluxes during periods of low water availability (PDSI < −4). These patterns suggest there may be long‐term and significant changes to stream ecosystem function as water availability is being dramatically altered by human demand with consequential impacts on solute transport, in‐stream processing, and stoichiometric ratios. 

Abstract Processes that drive variability in catchment solute sourcing, transformation, and transport can be investigated using concentration–discharge (C–Q) relationships. These relationships reflect catchment and in‐stream processes operating across nested temporal scales, incorporating both short and long‐term patterns. Scientists can therefore leverage catchment‐scale C–Q datasets to identify and distinguish among the underlying meteorological, biological, and geological processes that drive solute export patterns from catchments and influence the shape of their respective C–Q relationships. We have synthesized current knowledge regarding the influence of biological, geological, and meteorological processes on C–Q patterns for various solute types across diel to decadal time scales. We identify cross‐scale linkages and tools researchers can use to explore these interactions across time scales. Finally, we identify knowledge gaps in our understanding of C–Q temporal dynamics as reflections of catchment and in‐stream processes. We also lay the foundation for developing an integrated approach to investigate cross‐scale linkages in the temporal dynamics of C–Q relationships, reflecting catchment biogeochemical processes and the effects of environmental change on water quality. This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > Water QualityScience of Water > Water and Environmental Change 

Key Points We re‐evaluate equations proposed by Francis Hall to assess concentration‐discharge ( C ‐ Q ) relationships using newly available long‐term and high‐frequency data sets Across time steps we find that log‐log and log‐linear models perform equally well to describe C ‐ Q relationships Parametrization of storage‐discharge relationships via recession analyses provides additional insight to C ‐ Q relationships 

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.