Erin R. Hotchkiss

Dissolved oxygen (DO) has been extensively studied in streams and rivers. Despite this breadth of research, the processes governing DO are rarely quantified concurrently with whole-ecosystem measurements. To address this gap, we synthesize 230 empirical studies (1964-2024) to evaluate how, where, and with what methods oxygen exchanges—the processes by which oxygen enters and leaves streams—have been measured. We organize oxygen exchanges into five groupings, treating whole-stream metabolism as an integrative category of four underlying process domains: (1) water column, (2) benthic, (3) the hyporheic zone and sediments, and (4) surface-atmosphere exchange. Across the literature, estimates of whole-stream metabolism and gas exchange dominate, reported in 66% and 18% of studies, respectively, while underlying process domains were collectively reported in fewer than 16% of studies and jointly quantified in less than 7%. Where units permitted comparison, estimates of respiration in benthic, hyporheic, and underlying sediments were among the most variable exchanges yet least frequently measured. Together, these patterns indicate that our current understanding of stream oxygen dynamics relies heavily on integrative, reach-scale metabolism estimates, while the processes that generate these signals remain poorly resolved due to methodological and disciplinary silos. We identify key challenges and opportunities for synthesizing oxygen exchanges, emphasizing standardized reporting, concurrent measurements, and cross-site comparisons to advance integrated assessments of DO exchanges across streams and rivers.

Dynamics of respired dissolved organic carbon in a stream data

Transformation and removal of dissolved nutrients and pollutants in streams strongly depends on microbial processes in streambed sediments. The contact between these solutes and microbial communities is mediated by the physical transport from the bulk stream to, and through, the streambed, a process broadly referred to as hyporheic exchange. Even though multiple physical and biological processes influence the rate of hyporheic exchange, we here show that many hyporheic exchange mechanisms can be represented simply as a one‐dimensional diffusion process, where the diffusion coefficient decays exponentially with depth into the streambed. This framework is applied to a classic study of nitrate removal in 72 headwater streams across the United States, showing how the interplay among land‐use, stream physics, and stream biology collectively influence nutrient transformation in streambeds. The proposed modeling framework can help the upscaling of hyporheic exchange and promote better understanding of its role for processing and removal of contaminants in streams.

Quantifying headwater stream carbon emissions is important for our understanding of the global carbon cycle because these emissions (an estimated 0.93-1.15 Pg C year) can be substantial compared to the terrestrial flux. Headwater stream networks can have high emissions due to their coupling with the terrestrial environment and high turbulence with some estimates predicting headwater stream networks can contribute 70% of the global riverine stream emissions. These carbon emissions are challenging to predict, especially with regards to headwater stream network spatiotemporal heterogeneity. The majority of headwater streams exhibit changes in stream network area on a seasonal basis, and these locations and extents are not often well documented because they are based on topographic maps with limited spatial accuracy. Research suggests 50-80% of river networks are comprised of non-perennial stream segments. Physically based models are a potential solution to both mapping streamflow permanence and carbon dioxide emissions by accounting for the spatiotemporal heterogeneity that can occur in stream networks.In this study, we modeled stream permanence at three streams across the United States in different ecosystems using the Watershed Erosion Prediction Project (WEPP) hydrological model to simulate changes in stream network area over the year. We then used these results to inform a process-based stream network model to predict carbon emission from these networks throughout the year. We calibrated these network model with longitudinal data collected at the three sites during both low and high flow. Our results show the importance of considering stream permanence when predicting stream network carbon emissions, and how some ecosystems may emerge as hotspots for these emissions during high flow periods.

In this paper we demonstrate that several ubiquitous hyporheic exchange mechanisms can be represented simply as a one‐dimensional diffusion process, where the diffusivity decays exponentially with depth into the streambed. Based on a meta‐analysis of 106 previously published laboratory measurements of hyporheic exchange (capturing a range of bed morphologies, hydraulic conditions, streambed properties, and experimental approaches) we find that the reference diffusivity and mixing length‐scale are functions of the permeability Reynolds Number and Schmidt Number. These dimensionless numbers, in turn, can be estimated for a particular stream from the median grain size of the streambed and the stream's depth, slope, and temperature. Application of these results to a seminal study of nitrate removal in 72 headwater streams across the United States, reveals: (a) streams draining urban and agricultural landscapes have a diminished capacity for in‐stream and in‐bed mixing along with smaller subsurface storage zones compared to streams draining reference landscapes; (b) under steady‐state conditions nitrate uptake in the streambed is primarily biologically controlled; and (c) median reaction timescales for nitrate removal in the hyporheic zone are 0.5 and 20 hr for uptake by assimilation and denitrification, respectively. While further research is needed, the simplicity and extensibility of the framework described here should facilitate cross‐disciplinary discussions and inform reach‐scale studies of pollutant fate and transport and their scale‐up to watersheds and beyond.

Metabolism in stream ecosystems alters the fate of organic carbon (OC) received from surrounding landscapes, but our understanding of in‐stream metabolic processes in boreal ecosystems remains limited. Determining the factors that regulate OC metabolism will help predict how the C balance of boreal streams may respond to future environmental change. In this study, we addressed the question: what controls OC metabolism in boreal headwater streams draining catchments with discontinuous permafrost? We hypothesized that metabolism is collectively regulated by OC reactivity, phosphorus availability, and temperature, with discharge modulating each of these conditions. We tested these hypotheses using a combination of laboratory experiments and whole‐stream ecosystem metabolism measurements throughout the Caribou‐Poker Creeks Research Watershed (CPCRW) in Interior Alaska, USA. In the laboratory experiments, respiration and dissolved OC (DOC) removal were both co‐limited by the supply of reactive C and phosphorus, but temperature and residence time acted as stronger controls of DOC removal. Ecosystem respiration (ER) was largely predicted by discharge and site, with some variance explained by gross primary production (GPP) and temperature. Both ER and GPP varied inversely with watershed permafrost extent, with an inverse relationship between temperature and permafrost extent providing one plausible explanation. Our results provide some of the first evidence of a functional response to permafrost thaw in stream ecosystems and suggest the role of metabolism in landscape C cycling may increase as climate change progresses.

Contribution: This article discusses a research–practice partnership (RPP) where instructors from six undergraduate courses in three universities developed data science modules tailored to the needs of their respective disciplines, academic levels, and pedagogies. Background: STEM disciplines at universities are incorporating data science topics to meet employer demands for data science-savvy graduates. Integrating these topics into regular course materials can benefit students and instructors. However, instructors encounter challenges in integrating data science instruction into their course schedules. Research Questions: How did instructors from multiple engineering and science disciplines working in an RPP integrate data science into their undergraduate courses? Methodology: A multiple case study approach, with each course as a unit of analysis, was used to identify data science topics and integration approaches. Findings: Instructors designed their modules to meet specific course needs, utilizing them as primary or supplementary learning tools based on their course structure and pedagogy. They selected a subset of discipline-agnostic data science topics, such as generating and interpreting visualizations and conducting basic statistical analyses. Although instructors faced challenges due to varying data science skills of their students, they valued the control they had in integrating data science content into their courses. They were uncertain about whether the modules could be adopted for use by other instructors, specifically by those outside of their discipline, but they all believed the approach for developing and integrating data science could be adapted to student needs in different situations.

In this paper we demonstrate that hyporheic exchange can be represented simply as a one-dimensional diffusion process, where the diffusivity decays exponentially with depth into the sediment bed. Based on a meta-analysis of 106 previously published laboratory measurements of hyporheic exchange (capturing a range of bed morphologies, hydraulic conditions, sediment properties, and experimental approaches) we find that the reference diffusivity and mixing length-scale are functions of the permeability Reynolds Number and Schmidt Number. These dimensionless numbers, in turn, can be estimated for a particular stream from the median grain size of the sediment bed and the stream’s depth, slope, and temperature. Application of these results to a seminal study of nitrate removal in 72 headwater streams across the United States, reveals: (1) streams draining urban and agricultural landscapes have a diminished capacity for in-stream and in-bed mixing along with smaller subsurface storage zones compared to streams draining reference landscapes; (2) under steady-state conditions nitrate uptake in the sediment bed is primarily biologically controlled; and (3) under transient conditions (e.g., spills or storms) physical transport processes are likely to influence nitrate removal rates as well. While further research is needed, the simplicity and extensibility of the framework described here should facilitate cross-disciplinary discussions and inform reach-scale studies of pollutant fate and transport and facilitate their scale-up to watersheds and beyond.