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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber

Abstract Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.

58 GEOSCIENCES↗
DOE OSTI2021

Climate Change and Changes in Compound Coastal-Riverine Flooding Hazard Along the U.S. Coasts

The cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low-lying coastal areas. Climate change could increase the level of compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal-riverine frequency under current and future climate conditions. A copula-based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea-level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal-riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal-riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal-riverine stations along the Contiguous United States coast with long-term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal-riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using Ensemble Data Assimilation to Estimate Transient Hydrologic Exchange Flow Under Highly Dynamic Flow Conditions

Abstract Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high‐frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady‐state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub‐daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation‐based approach to estimate the sub‐daily flux under highly dynamic flow conditions using multi‐depth temperature observations at a 5‐min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi‐depth temperature data at 1‐ or 2‐hr time intervals assuming one‐dimensional flow and heat transport governing equation. By comparing estimated fluxes with model‐generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation‐based flux estimation method was able to capture the vertical sub‐daily fluxes using multi‐depth high‐resolution temperature data alone, even in the presence of multi‐dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1‐D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Linking Stream Chemistry to Subsurface Redox Architecture

As drinking-water scarcity grows worldwide, we need to improve predictions of the quantity and quality of our water resources. An overarching problem for model improvement is that we do not know the geological structure of aquifers in sufficient detail. In this work, we demonstrate that mineral-water reactions imprint structure in the subsurface that impacts the flow and transport of some chemical species. Specifically, pyrite, a ubiquitous mineral, commonly oxidizes and depletes in the upper layers of the weathering profile in most humid watersheds, only remaining at depths of meters. We hypothesize that variations in concentrations (C) of pyrite-derived sulfate released into rivers as a function of discharge (q) reflect the rate-limiting step and depth of pyrite-oxidizing layers. We found that log C - log q behaviors thus differ in small and large watersheds in the Susquehanna River Basin as well as in selected watersheds in the Western United States. Although coal mining changes pyrite oxidation from closed to open system with respect to O 2 , patterns in stream chemistry as a function of discharge are consistent with deep and shallow pyrite oxidation zones in small and large watersheds respectively. Therefore, understanding the subsurface patterns of mineral reactions and how they affect the architecture of aquifers will elucidate patterns of changing river chemistry and our ability to manage water resources in the future under accelerated land use and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.

Sadayappan, Kayalvizhi↗
DOE OSTI2025

Opportunistic Short‐Term Water Uptake Dynamics by Subalpine Trees Observed via In Situ Water Isotope Measurements

Abstract Variations in tree water sources are important to understand in semi‐arid ecosystems because climatic shifts towards lower snowpack and increased drought affect water availability in subalpine forests of the western US. Here, we use daily in situ measurements of stable isotopes ( 2 H & 18 O) in soil and tree stem water, soil matric potential and sap flow to study tree water uptake dynamics. We instrumented three soil profiles down to 90 cm, as well as three aspen and engelmann spruce trees near Gothic, Colorado, in the East River watershed. We observed the fate of natural isotopic variations in rainfall, soil, and plants from June to October 2022, and in August 2023 we conducted a 2 H labeled irrigation experiment. Our observations showed that all studied aspen trees compensated for water scarcity in the shallow soil by shifting the dominant water source at 60(±20) cm to ⅔ of uptake from 90 cm within a few days of a dry period. Both species relied on snowmelt stored in the subsoil to sustain transpiration. Intense rainfall caused the plant water uptake to shift partially to top soil layers within 2 days. Spruce transpiration was lower and relied more on snowmelt, because rainfall infiltration was low in the spruce stand due to high canopy interception. Our findings highlight the important role of snowmelt stored in the deep soil layers for subalpine forest drought response and the dominant fate of monsoonal rainfall to become transpiration rather than recharging groundwater and streams in the Upper Colorado River. Plain Language Summary There is a need to understand how trees in mountainous regions respond to dry conditions that lead to water scarcity, because climate projections suggest that such conditions will become more frequent in the future. Here we present a novel data set of measurements of daily stable isotopes of water across soil profiles and in tree stems of aspen and spruce. Our data show that when the upper soil dried out, aspen trees shifted to using water from deeper layers (beneath 60 cm) to keep transpiring. For spruce trees the uptake pattern is less clear, but both types of trees mainly used snowmelt stored in the deeper soil layers to survive the dry summer. After heavy rain, aspen and spruce trees switched to using water from the top 20 cm of soil. However, for spruce, only some rain reached the soil because the dense tree canopy intercepted it, so spruce trees stayed more dependent on snowmelt and used less water overall. This study shows how important deep snowmelt water is for helping forests survive dry periods and suggests that most summer rain is quickly used by trees rather than replenishing streams and groundwater in the headwaters of the Colorado River. Key Points Tree water resources changed within a few days from snow dominated to higher share of rainfall as soils wetted up after a dry period Compensatory plant water uptake by aspen from the deep layer (90 cm), while uptake from soil depths that became drier (60 cm) declined Strong differences between water sources and availability beneath aspen and spruce, respectively

Sprenger, Matthias↗
DOE OSTI2025

An Integrated Hydroclimatic Assessment of Future Reservoir and Hydropower Operations in the U.S.

The engineering of rivers by dams is a formative feature of human-nature systems and the interconnectivity of water, energy, and the climate. Sufficient and broad-based representations of dams in large-scale hydrological models prove essential to mapping their extensive regulation of river flow and biogeochemistry and gauging climate-linked provisions, including freshwater supply and hydropower. We present an integrated modeling framework to investigate future streamflow and hydropower generation in the Contiguous U.S. (1990–2075), leveraging an ensemble of six downscaled and bias-corrected General Circulation Models (GCMs) from the high-end SSP585 scenario of the CMIP6. To achieve this, we develop a reservoir operations and parameterization scheme for 1,384 dams in a high-resolution river network, including simulated hydropower generation for 326 dams. For the GCM ensemble mean, we simulate a widespread increase in regulated streamflow into the late-century (11% annual and 17% in winter for the dam median) with region-specific changes in summer streamflow that feature prominent declines in the Northwest (−7%). Mediation by reservoirs is shown to dampen intra-annual streamflow changes, delivering additional summer releases that partially mitigate declining flows. Total hydropower generation is projected to increase modestly (+3%), with boosted generation in the winter (+9%) and spring (+5%) offsetting declined summer generation (−3.4%), suggesting strong adaptation potential for hydropower in the future energy portfolio. Further analysis reveals that the choice of GCM, particularly in western regions, has significant bearing on projected streamflow and hydropower changes.

13 HYDRO ENERGY↗
DOE OSTI2026

Small Reservoirs Offer a New Perspective on Flood Reduction in Large Basins

The flood reduction potential of individual reservoirs within a large river network continuum remains poorly understood due to the complex interplay between reservoir characteristics and network properties. Here we investigate whether a collection of relatively small reservoirs can play a significant role in mediating downstream floods and assess how that role may be influenced by reservoir network properties compared to traditionally known reservoir characteristics. Our unique contribution was the simulation of downstream flood inundation maps alongside peak flows for each of the 81 major reservoirs (6 × 104 to 8 × 109 m3) across 15,000 river reach segments, integrated into a process-based hydrologic model covering a 415,000 km2 region in the Texas Gulf Coast, United States. The three key takeaways from our study are as follows. (a) Smaller reservoirs can substantially reduce downstream flooding, suggesting that inclusion of large reservoirs—the traditional approach in flood risk management studies—may present only a partial picture. (b) Flood reduction by smaller reservoirs is more effective upstream, although this phenomenon may be linked with aridity and overall water availability. (c) While reservoir size matters, it is not the primary factor determining its downstream flood reduction potential; the influence of network properties, such as catchment area, the count of upstream reservoirs, the cumulative maximum storage capacity of upstream reservoirs, and Stream Order (i.e., location), is equally and often more important. The broader impact of our findings goes beyond just floods, providing foundational insights for addressing emerging challenges such as aging dams and river connectivity.

Patel, Krutikkumar [University of Texas at Arlingt↗
DOE OSTI2026

ELM‐MOSART‐DOC: A Large‐Scale Riverine Dissolved Organic Carbon Model and Its Application Over the United States

Riverine dissolved organic carbon (DOC), primarily sourced from soil organic carbon (SOC), plays a crucial role in regional and global carbon cycles. However, the complexities of the underlying mechanisms and limited observations present significant challenges for predictive understanding of DOC at regional or larger scales. Recently, we developed a machine learning‐based (ML) map of DOC transformation rates, bridging the gap between SOC and DOC leaching flux and simplifying terrestrial DOC representation. Building on this advancement, we introduce ELM‐MOSART‐DOC, a DOC module integrated into the riverine component of the Energy Exascale Earth System Model (E3SM)—the Model for Scale Adaptive River Transport (MOSART). ELM‐MOSART‐DOC simulates DOC transport and transformation across both headwater streams and river networks, including those managed. Model validation demonstrates the ability of ELM‐MOSART‐DOC to accurately capture long‐term average DOC concentrations, with Kling‐Gupta Efficiency (KGE) scores of 0.58 and 0.76 at large and local stations, respectively. We further assess the impact of reservoirs through different simulation schemes, revealing that reservoirs significantly alter DOC fluxes by regulating streamflow patterns and promoting DOC mineralization. Model simulations indicate that reservoirs reduce total DOC flux from the Mississippi River into the ocean by 7.5%, with the long‐term average annual export decreasing from 3.34 to 3.14 teragrams (Tg) per year. ELM‐MOSART‐DOC integrates process‐based modeling with ML parameterization to enhance the predictive understanding of riverine biogeochemical processes. This approach reduces uncertainties in modeling regional and global carbon cycle ESMs and provides new insights into carbon cycling and its implications for global environmental change.

Li, Lingbo [Univ. of Houston, TX (United States); ↗
DOE OSTI2021

Wildfires increasingly impact western US fluvial networks

Wildfires are increasing globally in frequency, severity, and extent, but their impact on fluvial networks, and the resources they provide, remains unclear. We combine remote sensing of burn perimeter and severity, in-situ water quality monitoring, and longitudinal modeling to create the first large-scale, long-term estimates of stream+river length impacted by wildfire for the western US. We find that wildfires directly impact ~6% of the total stream+river length between 1984 and 2014, increasing at a rate of 342 km/year. When longitudinal propagation of water quality impacts is included, we estimate that wildfires affect ~11% of the total stream+river length. Our results indicate that wildfire activity is one of the largest drivers of aquatic impairment, though it is not routinely reported by regulatory agencies, as wildfire impacts on fluvial networks remain unconstrained. We identify key actions to address this knowledge gap and better understand the growing threat to fluvial networks, water security, and public health risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Spatial ecology of translocated raccoons

Raccoons (Procyon lotor) are routinely translocated both legally and illegally to mitigate conflicts with humans, which has contributed to the spread of rabies virus across eastern North America. The movement behavior of translocated raccoons has important ramifications for disease transmission yet remains understudied and poorly quantified. To examine the spatial ecology of raccoons following experimental translocation, we performed reciprocal 16 km-distance translocations of 30 raccoons between habitats of high and low raccoon density (bottomland hardwood and upland pine, respectively) across the Savannah River Site (SRS) in Aiken, South Carolina, USA (2018–2019). Translocation influenced patterns of raccoon space use, with translocated animals exhibiting a 13-fold increase in 95% utilization distributions (UDs) post- compared to pre-translocation (mean 95% UD 35.8 ± 36.1 km 2 vs 1.96 ± 1.17 km 2 ). Raccoons originating from upland pine habitats consistently had greater space use and larger nightly movement distances post-translocation compared to raccoons moved from bottomland hardwood habitats, whereas these differences were generally not observed prior to translocation. Estimated home ranges of male raccoons were twice the area as estimated for female raccoons, on average, and this pattern was not affected by translocation. After a transient period lasting on average 36.5 days (SD = 30.0, range = 3.25–92.8), raccoons often resumed pre-experiment movement behavior, with 95% UD sizes not different from those prior to translocation (mean = 2.27 ± 1.63km 2 ). Most animals established new home ranges after translocation, whereas three raccoons moved > 16 km from their release point back to the original capture location. Four animals crossed a 100-m wide river within the SRS post-translocation, but this behavior was not documented among collared raccoons prior to translocation. Large increases in space use combined with the crossing of geographic barriers such as rivers may lead to elevated contact rates with conspecifics, which can heighten disease transmission risks following translocation. These results provide additional insights regarding the potential impacts of raccoon translocation towards population level risks of rabies outbreaks and underscore the need to discourage mesocarnivore translocations to prevent further spread of wildlife rabies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Bayesian-Motivated Probabilistic Model of Hurricane-Induced Multimechanism Flood Hazards

Multimechanism floods (MMFs) are caused by the simultaneous occurrence of more than one flood mechanism such as storm surge, precipitation, tides, and waves. MMFs can lead to more severe or differing impacts than single-mechanism floods. As a result, comprehensive risk assessments require the ability to assess the multivariate probabilistic behaviors of hazards from MMFs. Here this study introduces a novel Bayesian-motivated approach for the probabilistic assessment of hurricane-induced hazards from the combination of the surge, precipitation, tides, and river antecedent flow. A Bayesian network (BN) is developed to capture the physical (conditional) relationship between variables and facilitate the generation of a hazard curve for river discharge that captures the contributions from multiple flood drivers. A case study located along the Delaware River is used to illustrate the proposed approach. Five computationally efficient representative predictive models are developed to estimate the conditional distributions required for the BN as a means of demonstrating the overall framework. The predictive models used in this study act as placeholders and can be replaced with more sophisticated and high-fidelity models depending on the desired accuracy level. While the predictive models are intended to be representative and illustrative, the model performance is evaluated using three historical storms that affected the area. Overall, the proposed framework is shown to be transparent, effective, and adaptable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Continental-Scale Controls on Hyporheic Respiration Revealed by Knowledge-Guided Machine Learning

Hyporheic zone sediments regulate organic matter turnover and in-stream respiration, yet controls on sediment respiration remain poorly constrained across heterogeneous river networks, limiting prediction of stream metabolism and carbon processing at continental scales. Here, we integrate observations from ~90 river corridors across the United States in the WHONDRS consortium with a knowledge-guided machine learning (KGML) framework that couples thermodynamic rate theory with machine learning to identify dominant controls on hyporheic respiration. Diagnostic analyses show that organic matter concentration and thermodynamic favorability define an upper bound on respiration potential, whereas biological catalytic capacity and physical accessibility jointly govern realized respiration rates through interaction effects. To represent unmeasurable accessibility constraints, we use the mechanistic model as a scaffold for KGML, allowing machine learning to target residual structure not explained by process theory. This hybrid framework improves predictive skill relative to both the mechanistic model alone and fully data-driven models while preserving interpretability. These results indicate that variability in hyporheic respiration is largely mechanistically structured and demonstrate how integrating process theory with explainable AI enhances predictive performance while enabling scalable synthesis of river corridor observations.

Zheng, Jianqiu↗
DOE OSTI2022

A Novel Framework for Parametric Analysis of Coastal Transition Zone Modeling

Abstract Vulnerability of coastal regions to extreme events motivates an operational coupled inland‐coastal modeling strategy focusing on the coastal transition zone (CTZ), an area between the coast and upland river. To tackle this challenge, we propose a top‐down framework for investigating the contribution of different processes to the hydrodynamics of CTZs with various geometrical shapes, different physical properties, and under several forcing conditions. We further propose a novel method, called tidal vanishing point (TVP), for delineating the extent of CTZs through the upland. We demonstrate the applicability of our framework over the United States East and Gulf coasts. We categorize CTZs in the region into three classes, namely, without estuary (direct river–coast connection), triangular‐, and trapezoidal‐shaped estuary. The results show that although semidiurnal tidal constituents are dominant in most cases, diurnal tidal constituents become more prevalent in the river segment as the discharge increases. Also, decreasing the bed roughness value promotes more significant changes in the results than increasing it by the same value. Additionally, the estuary promotes tidal energy attenuation and consequently decreases the reach of tidal signals through the upland. The proposed framework is generic and extensible to any coastal region.

Chegini, Taher↗
DOE OSTI2021

Genomic region associated with run timing has similar haplotypes and phenotypic effects across three lineages of Chinook salmon

Abstract Conserving life‐history variation is a stated goal of many management programs, but the most effective means by which to accomplish this are often far from clear. Early‐ and late‐migrating forms of Chinook salmon ( Oncorhynchus tshawytscha ) face unequal pressure from natural and anthropogenic forces that may alter the impacts of genetic variation underlying heritable migration timing. Genomic regions of chromosome 28 are known to be strongly associated with migration variation in adult Chinook salmon, but it remains unclear whether there is consistent association among diverse lineages and populations in large basins such as the Columbia River. With high‐throughput genotyping (GT‐seq) and phenotyping methods, we examined the association of genetic variation in 28 markers (spanning GREB1L to ROCK1 of chromosome 28) with individual adult migration timing characteristics gleaned from passive integrated transponder recordings of over 5000 Chinook salmon from the three major phylogeographic lineages that inhabit the Columbia River Basin. Despite the strong genetic differences among them in putatively neutral genomic regions, each of the three lineages exhibited very similar genetic variants in the chromosome 28 region that were significantly associated with adult migration timing phenotypes. This is particularly notable for the interior stream‐type lineage, which exhibits an earlier and more constrained freshwater entry than the other lineages. In both interior stream‐type and interior ocean‐type lineages of Chinook salmon, heterozygotes of the most strongly associated linkage groups had largely intermediate migration timing relative to homozygotes, and results indicate codominance or possibly marginal partial dominance of the allele associated with early migration. Our results lend support to utilization of chromosome 28 variation in tracking and predicting run timing in these lineages of Chinook salmon in the Columbia River.

Willis, Stuart C.↗
DOE OSTI2024

Efficient species identification for Pacific salmon genetic monitoring programs

Abstract Genetic monitoring of Pacific salmon in the Columbia River basin provides crucial information to fisheries managers that is otherwise challenging to obtain using traditional methods. Monitoring programs such as genetic stock identification (GSI) and parentage‐based tagging (PBT) involve genotyping tens of thousands of individuals annually. Although rare, these large sample collections inevitably include misidentified species, which exhibit low genotyping success on species‐specific Genotyping‐in‐Thousands by sequencing (GT‐seq) panels. For laboratories involved in large‐scale genotyping efforts, diagnosing non‐target species and reassigning them to the appropriate monitoring program can be costly and time‐consuming. To address this problem, we identified 19 primer pairs that exhibit consistent cross‐species amplification among salmonids and contain 51 species informative variants. These genetic markers reliably discriminate among 11 salmonid species and two subspecies of Cutthroat Trout and have been included in species‐specific GT‐seq panels for Chinook Salmon, Coho Salmon, Sockeye Salmon, and Rainbow Trout commonly used for Pacific salmon genetic monitoring. The majority of species‐informative amplicons (16) were newly identified from the four existing GT‐seq panels, thus demonstrating a low‐cost approach to species identification when using targeted sequencing methods. A species‐calling script was developed that is tailored for routine GT‐seq genotyping pipelines and automates the identification of non‐target species. Following extensive testing with empirical and simulated data, we demonstrated that the genetic markers and accompanying script accurately identified species and are robust to missing genotypic data and low‐frequency, shared polymorphisms among species. Finally, we used these tools to identify Coho Salmon incidentally caught in the Columbia River Chinook Salmon sport fishery and used PBT to determine their hatchery of origin. These molecular and computing resources provide a valuable tool for Pacific salmon conservation in the Columbia River basin and demonstrate a cost‐effective approach to species identification for genetic monitoring programs.

Robinson, Zachary L.↗
DOE OSTI2022

Resource selection and species interactions between native and non‐native fishes in a simulated stream system

Abstract Effective fishery management necessitates understanding of resource partitioning by fishes that inhabit complex systems composed of biotic and abiotic features. Evaluations of non‐native species introductions have continually demonstrated adverse effects associated with abundance and distribution of native fishes. Therefore, understanding resource selection and interactions between native and non‐native species is important for recovery efforts. Habitat use by two native fish species (largescale sucker Catostomus macrocheilus [Girard] and mountain whitefish Prosopium williamsoni [Girard]) and one non‐native fish species (pumpkinseed Lepomis gibbosus [Linnaeus]) of the Kootenai River, Idaho, were evaluated in a laboratory stream system. Trials were conducted in allopatry and in sympatry with and without the presence of wood to describe habitat selection in the context of on‐going habitat rehabilitation efforts. Interactions were evident between native largescale sucker and non‐native pumpkinseed concerning use of a woody structure and current velocity. Mountain whitefish used low‐velocity habitats and selected locations that were further from wood when in sympatry with pumpkinseed. Our research suggests that habitat use of native, large‐river fishes may be influenced by the presence of a non‐native species, and that considering such interactions is critical when designing and implementing habitat rehabilitation efforts in river ecosystems.

Branigan, Philip R.↗
DOE OSTI2022

Riparian vegetation shade restoration and loss effects on recent and future stream temperatures

River temperatures are expected to increase this century harming species requiring cold-water habitat unless restoration activities protect or improve habitat availability. Local shading by riparian vegetation can cool water temperatures, but uncertainty exists over the scaling of this local effect to larger spatial extents. Here, we evaluate this issue using a regional spatial stream network temperature model with covariates representing shade effects to predict mean August stream temperatures across 78,195 km of tributaries flowing into the Columbia River in the northwestern United States. We evaluate nine scenarios predicting stream temperatures for three riparian shade conditions (current, restored, and no riparian vegetation) within three different climate periods (2000s, 2040s, and 2080s). Results suggest riparian shade restoration (2000s climate) could decrease mean August stream temperatures by 0.62°C across the study network. Under the same restored shade conditions, temperature predictions for tributaries at their confluence with the Columbia River range from 0.02 to 2.08°C cooler than under current shade conditions. The climate warming effect predicted for the 2040s and 2080s, however, is greater than the cooling effect from restoring riparian shade. Streams less than 10-m bankfull width cooled more frequently with riparian shade restoration. In Oregon, the proportion of fish habitat for salmon and trout rearing and migration that meet temperature numeric water quality criteria could be increased by 20% under restored shade conditions although net habitat declines may still occur in the future. We conclude riparian vegetation restoration could partially mitigate future warming and help maintain cold-water habitats that function as thermal refuges if implemented strategically.

54 ENVIRONMENTAL SCIENCES↗