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412 records · Page 19Linked to original sources
USGS2026

A three-dimensional geologic framework model of the northern Great Plains region of Montana, North Dakota, South Dakota, and Wyoming, USA

This report presents a new three-dimensional geologic framework model (GFM) of the northern Great Plains region, encompassing parts of Montana, North Dakota, South Dakota, and Wyoming. The model provides a regionally consistent, geographic information system (GIS)-ready representation of Phanerozoic sedimentary strata, major fault systems, and Precambrian basement geometry across two sedimentary basins and adjacent uplifts. More than 300,000 geologic and geophysical data inputs were synthesized to model 41 stratigraphic horizons and 47 faults, yielding an internally coherent, sealed-volume interpretation of the subsurface. The modeling workflow developed for this study demonstrates an efficient and scalable approach for constructing basin-to regional-scale GFMs in geologically complex and data-variable settings. Although model fidelity varies with data density and quality, the resulting geometry is broadly consistent with 1:500,000-scale geologic mapping and highlights areas where additional geologic study is most needed. The three-dimensional GFM provides a foundational framework to support groundwater, energy, and mineral resource assessments, and offers a transferable methodology for potential future U.S. Geological Survey efforts to build large-area subsurface models in underexplored regions of the United States.

Montana, North Dakota, South Dakota, Wyoming↗
USGS2026

Shallow hydrogeologic framework of the Tully Valley mudboil area, Onondaga County, New York

Mudboils have been documented in the Tully Valley in southern Onondaga County, New York, since the late 1890s. Sediment-laden water from the mudboils flows into Onondaga Creek, which empties into Onondaga Lake at Syracuse 15 miles to the north. Turbidity from the mudboils has degraded the water quality of Onondaga Creek despite a series of mitigation efforts that began in the early 1990s. Turbidity mitigation actions presently (2025) being considered include creek relocation and offline sediment settling. In support of these proposed actions during 2021–23, the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, U.S. Environmental Protection Agency, Onondaga Nation, Onondaga Environmental Institute, and Central New York Regional Planning and Development Board, collected and analyzed geologic, hydrologic, geophysical, and geotechnical data to characterize the shallow hydrogeology along four proposed creek-relocation paths and in the proposed offline settling basin area. The investigation indicated that the four proposed creek-relocation paths, two east of Onondaga Creek and two west of Onondaga Creek, are underlain by sediments including muck, alluvium, mudboil deposits, alluvial-fan sand and gravel, and lacustrine fines. The proposed excavations would penetrate partially to fully saturated conditions: generally, the water table is shallow near the creek and deep on the alluvial fans. The shallowest excavation, about 5 feet below land surface, would be near the creek and primarily in alluvium, and the deepest excavation, as much as 30 feet below land surface, would be in the alluvial-fan deposits. Brackish waters would be penetrated by proposed channel excavations on the eastern side of Onondaga Creek in an area downgradient from a potentially leaking historical salt-exploration borehole and near the main mudboil area. Excavation in these areas likely would provide a continuous source of brackish groundwater to the relocated creek. Proposed channel excavations of muck, soft to very soft lacustrine fines, and mudboil-type sediments in mudboil and suspected mudboil areas would pose an excavation and slope stability challenge and would have the greatest potential to create new mudboils. Proposed channel excavations below the water table on the Rattlesnake Gulf and Rainbow Creek alluvial fans would intercept groundwater and make the constructed streambank susceptible to seepage-induced slope instability. The substantial water-level fluctuation in the sediments of both alluvial fans would aggravate the stability condition. In addition, excavation on the Rattlesnake Gulf alluvial fan would have the potential to affect water-supply springs at the toe of the fan. The proposed offline settling basin area is in the northern part of the Rattlesnake Gulf alluvial fan. Natural and man-made diversions of Rattlesnake Gulf have resulted in saturated conditions in the general area of the proposed basin. The proposed offline settling basin would be excavated in, and berms would be constructed on, alluvial-fan deposits and lacustrine fines. In the proposed basin area, the alluvial deposits overlying the lacustrine fines are less than 10 feet thick. Excavation, berm construction, and loading of the saturated, soft to very soft lacustrine fines may be problematic and require soil strengthening.

New York↗
USGS2025

Disturbance is the primary determinant of food chain length when the top predator is constant

Food chain length (FCL) is a primary determinant of food web structure and is hypothesized to be influenced by habitat size, productivity, and disturbance. Understanding the environmental characteristics that determine food chain length can assist in understanding how food webs may be impacted due to changes in habitats and environmental characteristics. This study examines the impact of hydrologic disturbance on stream food webs when the top predator is constant. We analyzed FCL in less disturbed groundwater flashy streams and more disturbed runoff flashy streams using stable isotopes. Despite no difference in species richness or fish density, food chains in more disturbed streams had a lower FCL compared to food chains in more stable streams. Assemblage analysis showed that flow regime and drainage area significantly impacted individual species abundances. The more disturbed runoff flashy streams had higher proportions of primary consumer fish, such as the algivorous Campostoma sp. (Stonerollers), which likely drives the reduced FCL. Drainage area and land cover had non-significant relationships with FCL. Shifting community structure due to hydrologic variability likely leads to differences in diet of Micropterus dolomieu (Smallmouth Bass), and thus a difference in FCL.

Arkansas, Missouri, Oklahoma↗
USGS2025

Paleomagnetic correlation of surface and subsurface basalt flows in the central and southwestern part of the Idaho National Laboratory, Idaho

The U.S. Geological Survey, in cooperation with the U.S. Department of Energy, used paleomagnetic data from 22 coreholes to construct 3 fence diagrams of subsurface basalt flows in the southern part of the Idaho National Laboratory. These diagrams provide comprehensive descriptions of the horizontal and vertical distribution of basalt flows and sediment layers beneath the surface, aiding geological studies and contributing valuable data to numerical models of groundwater flow and contaminant transport. The correlations established though these diagrams include spatial correlations between basalt flows found in multiple coreholes. Correlations were identified by matching average paleomagnetic inclinations and confirming or denying these correlations using petrology, geochemistry and radiometric ages. The fence diagrams aid in identifying potential locations of subsurface vents, volcanic vents that have been buried by more recent volcanic activity, associated to subsurface basalt flows. By tracing the subsurface flows and analyzing where the greatest thickness occurs, the locations of buried vents can be inferred. Some subsurface flows exhibit correlations across several coreholes and may indicate yet unidentified surface or buried vents, thereby enhancing our understanding of the volcanic history and subsurface geology of the region.

Idaho↗
USGS2025

Total uncertainty quantification in inverse solutions with deep learning surrogate models

We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.

Journal of Computational Physics↗
USGS2025

USGS—An Unparalleled Scientific Asset

The U.S. Geological Survey (USGS) delivers information critical to powering our economy, managing our natural resources, and keeping Americans safe and healthy. 1 Mapping the Nation $21B Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B. $25.6B in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS. $13.5B in annual benefits is generated by the USGS's 3D Elevation Program. Securing America’s Energy Independence 44% USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation. 29.4B barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments. Protecting Americans’ Health and Safety $424B in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk. USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption. $4.5B is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property. Supporting National Security $3.1B The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list. Enhancing Our Lands and Waters $21B in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation. USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone. $45B USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy. Fostering American Prosperity $4.1T Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued. 45,000 metric tons Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply. Guarding American Food Security $70.2B USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production. $11.8B USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry. 1 Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.

General Information Product↗
USGS2025

Detection of viral, bacterial, and protozoan pathogens and microbial source tracking markers in paired large- and small-volume water samples

When sampling for waterborne microbes, researchers may need to diverge from recommended sample volumes due to logistical constraints, novel targets, or challenging matrices, with little guidance about the potential impact on results. In field studies, we measured bacteria, viruses, and protozoa (15 quantitative polymerase chain reaction assays) in paired large- and small-volume samples to evaluate method performance and relevant factors. Concordance between methods was low. Large-volume ultrafiltration yielded more detections than small-volume sampling, especially for pathogens in groundwater. Greater microbial concentrations were associated with more frequent detections in small-volume samples and greater concordance between paired samples. Large-volume samples appeared to be more susceptible to diminished sensitivity from complex sample matrices. In laboratory studies, recovery of microbes was poorer for large- than small-volume methods, although large-volume methods more reliably detected low-concentration targets. Large-volume samples were less stable than small-volume samples during storage. Overall, large-volume sampling was superior for detecting pathogens but may underestimate concentrations; small-volume sampling was more prone to false negatives but was adequate when concentrations were relatively high, like we observed for microbial source tracking in surface waters.

Wisconsin↗
USGS2024

Aboveground carbon stocks across a hydrological gradient: Ghost forests to non-tidal freshwater forested wetlands

Upper estuarine forested wetlands (UEFWs) play an important role in the sequestration of atmospheric carbon (C), which is facilitated by their position at the boundary of terrestrial and maritime environments but threatened by sea level rise. This study assessed the change in aboveground C stocks along the estuarine–riverine hydrogeomorphic gradient spanning salt-impacted freshwater tidal forested wetlands to freshwater forested wetlands in seasonally tidal and nontidal landscape positions. Standing stocks of C in forested wetlands were measured along two major coastal river systems, the Winyah Bay in South Carolina and the Savannah River in Georgia (USA), replicating and expanding a previous study to allow the assessment of change over time. Aboveground C stocks on these systems averaged 172.9 Mg C ha −1 , comparable to those found in UEFWs across the globe and distinct from the terrestrial forested ecosystems they are often considered to be a part of during large-scale C inventory efforts. Groundwater salinity conditions as low as 1.3 ppt were observed in conjunction with losses of aboveground C. When viewed in context alongside expected sea level rise and corresponding saltwater intrusion estimates, these data suggest a marked decrease in aboveground C stocks in forested wetlands situated in and around tidal estuaries.

Georgia, South Carolina↗
USGS2024

Trends and environmental impacts of virtual water trade

Virtual water describes water embedded in the production of goods and offers meaningful insights about the complex interplay between water, trade and sustainability. In this Review, we examine the trends, major players, traded products and key drivers of virtual water trade (VWT). Roughly 20% of water used in global food production is traded virtually rather than domestically consumed. As such, agriculture dominates VWT, with livestock products, wheat, maize, soybean, oil palm, coffee and cocoa contributing over 70% of total VWT. These products are also driving VWT growth, the volume of which has increased 2.9 times from 1986 to 2022. However, the countries leading VWT contributions (with China, the United States, the Netherlands, Germany and India accounting for 34% of the global VWT in 2022) have remained relatively stable over time, albeit with China becoming an increasingly important importer. VWT can mitigate the effects of water scarcity and food insecurity, although there are concerns about the disconnect between consumers and the environmental impacts of their choices, and unsustainable resource exploitation. Indeed, approximately 16% of unsustainable water use and 11% of global groundwater depletion are virtually traded. Future VWT analyses must consider factors such as water renewability, water quality, climate change impacts and socioeconomic implications.

Nature Reviews Earth & Environment↗
USGS2025

Over, under, and through: Hydrologic connectivity and the future of coastal landscape salinization

Seawater intrusion (SWI) affects coastal landscapes worldwide. Here we describe the hydrologic pathways through which SWI occurs - over land via storm surge or tidal flooding, under land via groundwater transport, and through watersheds via natural and artificial surface water channels—and how human modifications to those pathways alter patterns of SWI. We present an approach to advance understanding of spatiotemporal patterns of salinization that integrates these hydrologic pathways, their interactions, and how humans modify them. We use examples across the East Coast of the United States that exemplify mechanisms of salinization that have been reported around the planet to illustrate how hydrologic connectivity and human modifications alter patterns of SWI. Finally, we suggest a path for advancing SWI science that includes (a) deploying standardized and well-distributed sensor networks at local to global scales that intentionally track SWI fronts, (b) employing remote sensing and geospatial imaging techniques targeted at integrating above and belowground patterns of SWI, and (c) continuing to develop data analysis and model-data fusion techniques to measure the extent, understand the effects, and predict the future of coastal salinization.

Water Resources Research↗
USGS2024

Revision of ModelMuse to support the use of PEST software with MODFLOW and SUTRA models

Executive Summary ModelMuse is a graphical user interface for several groundwater modeling programs. ModelMuse was updated to generate the input files for the parameter estimation software suite PEST. The software is used with MODFLOW or SUTRA models to run PEST-based parameter estimation and display the updated model inputs after parameter estimation. The PEST input files can also be used with the PEST++ version 5 software suite. Parameter estimation typically requires defining the parameters being adjusted during calibration and observations for assessing calibration quality. After a parameter is defined in ModelMuse, it can be applied to all or part of a model dataset. Pilot points—a parameterization device that facilitates higher levels of parameterization—can be used to assign spatially variable distributions of model inputs. Parameters can be applied to temporally varying features, such as boundary conditions, by either applying them to all the values in a series in one step or by applying separate parameters to individual members of a series. ModelMuse allows the definition of many observation types from various model output files. For MODFLOW 6 and SUTRA models, new options were added to ModelMuse to allow it to display the changed input after parameter estimation is complete. For MODFLOW–2005 and MODFLOW–NWT models, ModelMuse can import an entire model for visualization. An example illustrates the use of PEST with a MODFLOW 6 model in ModelMuse.

Techniques and Methods↗
USGS2025

Borehole geophysical time-series logging to monitor passive ISCO treatment of residual chlorinated-ethenes in a confining bed, NAS Pensacola, Florida

In-situ chemical oxidation (ISCO) is a common method to remediate chlorinated ethene contaminants in groundwater. Monitoring the effectiveness of ISCO can be hindered because of insufficient observations to assess oxidant delivery. Advantageously, potassium permanganate, one type of oxidant, provides the opportunity to use its strong electrical signal as a surrogate to track oxidant delivery using time-series borehole geophysical methods, like electromagnetic (EM) induction logging. Here we report a passive ISCO (P-ISCO) experiment, using potassium permanganate cylinders emplaced in boreholes, at a chlorinated ethene contamination site, Naval Air Station Pensacola, Florida. The contaminants are found primarily at the base of a shallow sandy aquifer in contact with an underlying silty-clay confining bed. We used results of the time-series borehole logging collected between 2017 and 2022 in 4 monitoring wells to track oxidant delivery. The EM-induction logs from the monitoring wells showed an increase in EM response primarily along the contact, likely from pooling of the oxidant, during P-ISCO treatment in 2021. Interestingly, concurrent natural gamma-ray (NGR) logging showed a decrease in NGR response at 3 of the 4 wells possibly from the formation of manganese precipitates coating sediments. The coupling of time-series logging and well-chemistry data allowed for an improved assessment of passive ISCO treatment effectiveness.

Florida↗
USGS2026

Long-term monotonic trends in water budget components in the contiguous United States: Insights from two hydrologic models

Characterizing changes to water availability for domestic, industrial, agricultural, and other uses is essential to support water management. To better quantify these changes, the U.S. Geological Survey and National Science Foundation National Center for Atmospheric Research produced two hydrologic models simulating water budget components from 1980 to 2021 over the contiguous United States (CONUS). Both hydrologic models were driven by a common atmospheric forcing dataset and aggregated to common spatial and temporal scales, which enables a novel evaluation of congruency between the models. We present annual and seasonal trends in six water budget components (precipitation, evapotranspiration, streamflow, groundwater recharge, soil saturation, and snow water equivalent) based on the Mann–Kendall test for monotonic trend and Theil-Sen slope estimate for the water year 1983–2021 period for ~86,000 catchments in CONUS. Additional components and metrics from our analysis pipeline are available in an associated published dataset, which contains more than 46 million trend results. The water budget trends showed broad agreement with prior observational and modeling studies that indicate increasing trends in the northeast and decreasing trends in southwestern CONUS. We found the seasonal variability in water budget trends was greatest in the southern, central, and northwest CONUS. These findings support integrated trend assessments when coupled with trends in water quality and use.

Contiguous United States↗
USGS2024

Biogeochemical and community ecology responses to the wetting of non-perennial streams

Transitions between dry and wet hydrologic states are the defining characteristic of non-perennial rivers and streams, which constitute the majority of the global river network. Although past work has focused on stream drying characteristics, there has been less focus on how hydrology, ecology and biogeochemistry respond and interact during stream wetting. Wetting mechanisms are highly variable and can range from dramatic floods and debris flows to gradual saturation by upwelling groundwater. This variation in wetting affects ecological and biogeochemical functions, including nutrient processing, sediment transport and the assembly of biotic communities. Here we synthesize evidence describing the hydrological mechanisms underpinning different types of wetting regimes, the associated biogeochemical and organismal responses, and the potential scientific and management implications for downstream ecosystems. This combined multidisciplinary understanding of wetting dynamics in non-perennial streams will be key to predicting and managing for the effects of climate change on non-perennial ecosystems.

Nature Water↗
USGS2025

Geochemistry and Soils of the Big Smoky Valley Fens, Nevada

Fens are groundwater-fed wetlands that can provide habitat for plants and animals. Due to anthropogenic activities and climate change, many fens around the world are at risk. This paper presents the results of a study of the hydrology and geochemistry of fens in Big Smoky Valley, central Nevada to support the Bureau of Land Management’s activities in the area. A water sample from the largest fen in the study area was analyzed for its water chemistry and compared to a nearby alluvial aquifer and hot spring. The high SiO 2 concentration of the fen sample implies that the fen water may originate from geothermal water. A soil core was taken to analyze radiocarbon age and soil type. A majority of the core was composed of silt and clay interlayered with water-filled voids. Changes in the character of the clay with depth suggest that there may have been changes in the depositional environment over time. Radiocarbon dating of Ruppia seeds showed longevity of the fen, with the minimum 14 C age of the core as 4,375±40 years. This paper provides reconnaissance-level information on the Big Smoky Valley fens, but further information would be needed to better understand the source of water to the fens or how the fen environment has changed over time with climate.

Nevada↗
USGS2024

Potential climate and human water-use effects on water-quality trends in a semiarid, western U.S. watershed: Fountain Creek, Colorado, USA

Nutrients, total dissolved solids (TDS), and trace elements affect the suitability of water for human and natural needs. Here, trends in such water-quality constituents are analyzed for 1999–2022 for eight nested monitoring sites in the 24,000 km 2 Fountain Creek watershed in Colorado, USA, by using the weighted regressions on time, discharge, and season (WRTDS) methodology. Fountain Creek shares characteristics with other western U.S. watersheds: (1) an expanding but more water-efficient population, (2) a heavy reliance on imported water, (3) a semiarid climate trending towards warmer and drier conditions, and (4) shifts of water from agricultural to municipal uses. The WRTDS analysis found both upward and downward trends in the concentrations of nutrients that reflected possible shifts in effluent management, instream uptake, and water conservation by a watershed population that grew by about 40%. Selenium, other trace elements, and TDS can pose water-quality challenges downstream and their concentrations were found to have a downwards trend. Those trends could be driven by either a warming and drying of the local climate or decreased agricultural irrigation, as both would reduce recharge and subsequent mobilization from natural geologic sources via groundwater discharge. The patterns illustrate how changes in climate and water use may have affected water quality in Fountain Creek and demonstrate the patterns to look for in other western watersheds.

Colorado↗
USGS2025

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water↗
USGS2025

Linking permafrost to the abundance, biomass, and energy density of fish in Arctic headwater streams

Permafrost thaw alters groundwater flow, river hydrology, stream-catchment interactions, and the availability of carbon and nutrients in headwater streams. The impact of permafrost on watershed hydrology and biogeochemistry of headwater streams has been demonstrated, but there is little understanding of how permafrost influences fish in these ecosystems. We examined relations among permafrost characteristics, the resulting changes in water temperature, stream hydrology (e.g., discharge flashiness), and macroinvertebrates, with the abundance, biomass, and energy density of juvenile Dolly Varden ( Salvelinus malma ) and Arctic Grayling ( Thymallus arcticus ) across 10 headwater streams in northwestern Alaska. Macroinvertebrate density was driven by concentrations of dissolved carbon and nutrients supporting stream food webs. Dolly Varden abundance was primarily related to water temperature with fewer fish in warmer streams, whereas Dolly Varden energy density decreased with the flashiness of the headwater streams. Dolly Varden biomass was related to both temperature and bottom-up food web effects. The energy density of Arctic Grayling decreased with warmer temperatures and discharge flashiness. These relations demonstrate the importance of terrestrial–aquatic connections in permafrost landscapes and indicate the complexity of landscape effects on fish. Because permafrost thaw is one of the most impactful changes occurring as the Arctic warms, an improved understanding of how stream temperature, hydrology, and bottom-up food web processes influence fish populations can aid forecasting of future conditions across the Arctic.

Alaska↗