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USGS2025

Peak streamflow trends in Montana and northern Wyoming and their relation to changes in climate, water years 1921–2020

Frequency analysis on annual peak streamflow (hereinafter, peak flow) is essential to water-resources management applications, including critical structure design (for example, bridges and culverts) and floodplain mapping. Nonstationarity is a statistical property of a peak-flow series such that the distributional properties (the mean, variance, or skew) change either gradually (monotonic trend) or abruptly (shift, step change or change point) through time. Not incorporating or accounting for observed nonstationarity into peak-flow frequency analysis might result in a poor representation of the true probability of large floods and thus misrepresent the actual flood risks to life and property. This report summarizes how hydroclimatic variability might affect the temporal and spatial distributions of peak-flow data in the State of Montana (and northern Wyoming) and is part of a larger study to document peak-flow nonstationarity and hydroclimatic changes across a nine-State region consisting of Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flows. This study was completed in cooperation with the Montana Department of Natural Resources and Conservation. The purpose of this report is to characterize temporal and spatial patterns of nonstationarity in peak flows and hydroclimatology in Montana and northern Wyoming. In this evaluation, peak-flow, daily streamflow, and model-simulated gridded climatic data were examined for monotonic trends, change points, and other statistical properties that might indicate changing climatic and environmental conditions. This report includes background information on the study area, the history of U.S. Geological Survey peak-flow data collection and frequency analysis in Montana, and the review of research relating to hydroclimatic variability and change in Montana. This study might help provide a framework for addressing potential nonstationarity issues in peak-flow frequency updates that commonly are completed by the U.S. Geological Survey in cooperation with other agencies throughout the Nation. The analytical structure of this study includes analyses of monotonic trends and change points in numerous hydroclimatic variables in assigned 30-, 50-, 75-, and 100-year analysis periods. For Montana and part of Wyoming, the 30-, 50-, 75, and 100-year analyses included 157, 70, 48, and 12 streamgages, respectively. For those streamgages, nonstationarities were analyzed in the following variables: (1) climatic variables, including annual and seasonal (winter, spring, summer, and fall) temperature and precipitation; (2) daily streamflow variables, including the annual center of volume duration, annual center of volume median, and peaks over threshold with a mean of four events per year; and (3) annual peak-flow variables, including peak-flow timing and magnitude. A likelihood approach was used to express statistical confidence and assign the nonstationarity results as likely upward or downward (highest statistical confidence), somewhat likely upward or downward (less statistical confidence), or about as likely as not (little statistical confidence; hereinafter, neutral). For the nonstationarity analyses of the climatic, daily streamflow, and peak-flow variables, the results are presented in detail and discussed with respect to statewide patterns and geographic variability. For each of the 30-, 50-, and 75-year analyses, peak-flow change-point and monotonic trend analyses were compiled for streamgages classified with likely downward or likely upward trends. For those streamgages, the associated basin characteristics and nonstationarity results for peak-flow timing, daily streamflow, and climatic variables were investigated and statistically compared to discern associations among other variables that might contribute to the peak-flow nonstationarity results. The 50- and 75-year peak-flow nonstationarities identified in this study are mostly downward, in association with mostly upward temperature and potential evapotranspiration:precipitation monotonic trends. For the 50-, 75-, and 100-year analyses, the peak-flow change points are predominantly downward and are concentrated in the 1970s and 1980s, which indicates general consistency among the longer trend periods. These findings are in association with substantial research documenting globally rising temperature and atmospheric greenhouse gas concentrations that might be largely attributed to anthropogenic activities. Anthropogenic effects might represent long-term (on the order of several decades to more than a century) climate changes that might happen within highly variable natural climate fluctuations. Several paleo studies in the north-central United States have indicated that hydroclimatic extremes (that is, low- and high-streamflow conditions) before European settlement have been outside of extremes since the 1900s. Depending on the interactions of anthropogenic effects and natural climate variability, extreme high-streamflow conditions might occur in the future, even in the presence of long-term downward peak-flow trends.

Montana, Wyoming↗
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

PEST++IES how many iterations & realizations, finding the point of diminishing returns

PEST++IES (White 2018; White et al. 2020) is widely used in the groundwater modeling community for its ability to perform computationally efficient history matching and uncertainty analysis in a highly parameterized context. One primary advantage of using an iterative ensemble smoother is that the number of model runs required per iteration depends on the number of realizations in an ensemble, not the number of parameters in each realization. However, this raises the question: what is the optimal number of realizations and iterations to use for any one model before the point of diminishing returns? Using a modified version of the Freyberg model (Freyberg 1988; Hunt et al. 2020), different parameter and observation scenarios were evaluated for four iterations and ensembles of 10, 25, 50, 100, 250, 500, 1000, and 2000 realizations. To match observations, PEST++IES altered hydraulic conductivity ( k ), both globally across the model and locally at three different pilot point densities, as well as global recharge (via a single multiplier), global river conductance, and individual well flow rates. Risk-based well capture zone results (Fienen et al. 2022a) and estimated hydraulic conductivity fields from each scenario were quantitatively and qualitatively compared against the “truth” model and its outputs. Across the cases examined, ensemble sizes of 100 to 250 realizations and two PEST++IES iterations were generally sufficient to achieve good results.

Groundwater↗
USGS2025

Evidence for nonlocal sediment transport on hillslopes from fault scarp morphology

Hillslope sediment transport processes such as bioturbation, rainsplash, and granular mechanics occur across the entire planet. Yet, it remains uncertain how these small-scale processes act together to shape landscapes. Longstanding hillslope diffusion theory posits that hillslope processes are spatially limited, whereas new concepts of nonlocal sediment transport argue otherwise. However, each theory produces subtly different, but distinct, predictions for the evolution of fault scarps. We use the topographic change of fault scarps to demonstrate that hillslope processes produce nonlocal sediment transport. Analysis of a global compilation of 340 dated single-earthquake scarp profiles reveals a statistically significant ( p < 0.05 ) relationship between scarp age and scarp asymmetry, here defined as the ratio of imaginary to real components of the Fourier transform of absolute slope. Numerical simulations show that nonlocal models predict this relationship, whereas hillslope diffusion models do not. To further investigate this result, we examined the depositional geometry of a well-exposed colluvial wedge along the Wasatch fault in central Utah, United States. Our quantitative comparison between the exposure and numerical simulations reveals better agreement with the nonlocal model. Nonlocal sediment transport theory appears to best capture the physics of how hillslope processes shape fault scarps, yet hillslope diffusion provides a useful approximation in many cases. As the processes that act on fault scarps are nearly identical to those acting on hillslopes, our results provide evidence supporting nonlocality as a generalized model of hillslope sediment transport.

Utah↗
USGS2025

Footprints of past mining in Alaska (USA) derived from high-resolution satellite imagery

Mapping the land area used for mining in the past is essential for guiding the remediation of affected landscapes and assessing the resource potential of related waste products. Despite significant recent progress delineating footprints of active and inactive mining globally, the known inventory of such mine lands remains incomplete. Here, I describe a new map dataset of footprints of land surface disturbance and waste at sites of past mining in Alaska (USA) based on visual interpretation of satellite imagery. This dataset maps 6–14 times the area of previous regional and global mine footprint maps in Alaska and is the first in the region to explicitly delineate mine waste landforms (e.g., tailings piles). The data are publicly available from the U.S. Geological Survey under a “no rights reserved” Creative Commons (CC0) license agreement.

Alaska↗
USGS2026

Thermal detectability of subsurface water ice on Mars: A comparative analysis for the Subsurface Water Ice Mapping (SWIM) Project

We have developed a new global map of shallow ground ice distribution, SWIM23, based on Mars Global Surveyor Thermal Emission Spectrometer data and made systematic comparisons between this new map and two similar, previously developed data products. We have explored the origin of differences between the three ice maps by detailing technical and procedural differences in their development, by making global pixel-by-pixel comparisons, and by carrying out a series of one-dimensional thermal simulations to explore fundamental physical limitations of thermal ice-detection techniques. These efforts and the production of a composite thermal ice-consistency map supported integration of multiple geophysical data products relevant to ice detection in the upper meter of the Martian regolith into the larger Mars Subsurface Water Ice Mapping project. Our work also highlights fundamental physical limitations to thermal ice detection as a technique, particularly the rapid fall-off in ice detection sensitivity at depths >30 cm, which produces maximum uncertainty in the presence and depth of ice within regions preferred for potential human landing sites. A future Mars orbiter mission designed to detect ice and support crewed landing site selection in the midlatitude region should give payload priority to an instrument capable of probing the 1–5 m depth range (i.e., a high-frequency radar), over a next-generation thermal spectrometer, which is unlikely to offer clarity on ice table depths or lateral continuity of the ice table in the locations of highest interest.

Planetary Science Journal↗
USGS2025

Reconstruction of Holocene and Last Interglacial vegetation dynamics and wildfire activity in Southern Siberia

Wildfires are a rapidly increasing threat to boreal forests. While our understanding of the drivers behind wildfires and their environmental impact is growing, it is mostly limited to the observational period. Here we focus on the boreal forests of southern Siberia and exploit a U–Th-dated stalagmite from Botovskaya Cave, located in the upper Lena region of southern Siberia, to document wildfire activity and vegetation dynamics during parts of two warm periods: the Last Interglacial (LIG; specifically part of the Last Interglacial maximum between 124.1 and 118.8 ka) and the Holocene (10–0 ka). Our record is based on levoglucosan (Lev), a biomarker sensitive to biomass burning, and on lignin oxidation products (LOPs) that discriminate between open and closed forest and hard- or softwood vegetation. In addition, we used carbonate carbon stable isotope ratios ( δ 13 C ), which reflect a dominant control of the host rock, to evaluate soil respiration and local infiltration changes. Our LOP data suggest that, during the Last Interglacial, the region around Botovskaya Cave was characterised by open forest, which by ca. 121.5 ka underwent a transition from fire-resistant hardwood to fire-prone softwood. The Lev record indicates that fire activity was high and increased towards the end of Last Interglacial just before 119 ka. In contrast, the Holocene was characterised by a closed-forest environment with mixed hard- and softwood vegetation. Holocene fire activity varied but at a much lower level than during the Last Interglacial. We attribute the changes in wildfire activity during the intervals of interest to the interplay between vegetation and climate. The open forests of the Last Interglacial were more likely to ignite than their closed Holocene equivalents, and their flammability was aided by warmer and drier summers and a stronger seasonal temperature contrast due to the increase in seasonal insolation difference compared to the Holocene. Our comparison of the last two interglacial intervals suggests that, with increasing global temperatures, the boreal forest of southern Siberia may become progressively more vulnerable to higher wildfire activity.

Botovskaya Cave, Siberia↗
USGS2025

Analysis of the potential effects of Uzbekistan’s mineral endowment on the critical mineral supply of tungsten

Tungsten appears on the 2018 and 2022 U.S. Geological Survey critical mineral lists in part because of a very high global production concentration in China, which produces almost 83 percent of the world’s mined tungsten. Using known parameters and values from other tungsten mining operations, we created hypothetical scenarios in which three tungsten deposits in Uzbekistan are considered for development. Our results show that all three deposits are likely to be economically viable to develop under 2024 market conditions. If the three studied tungsten deposits were put into production, Uzbekistan could become the third-leading tungsten-producing country in the world and increase world output of tungsten by 2.7 percent. Putting these tungsten deposits in Uzbekistan into production could slightly reduce the tungsten global market concentration, therefore reducing the supply disruption potential for tungsten.

Open-File Report↗
USGS2024

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research↗
USGS2026

Surface variable‐based machine learning for scalable arsenic prediction in undersampled areas

In the United States, private wells are not federally regulated, and many households do not test for Arsenic (As). Chronic exposure is linked with multiple health outcomes, and risk can change sharply over short distances and with well depth. Coarse maps or sparse sampling often miss exceedances. Most existing models operate at ∼1 km resolution and use groundwater chemistry or detailed geologic logs, which limits their use in undersampled areas where improved guidance is most needed. We overcome these limitations by developing a machine learning model for Minnesota, USA, that predicts As exposure risk using only surficial variables from remote sensing and global data sets. Variables related to surface water hydrology and geomorphology are selected based on mechanistic links that control redox conditions and As mobilization. Local training was essential, and surficial geology variables that are more sensitive to local conditions were needed to maximize model accuracy. The resulting complete model was sufficiently sensitive to generate accurate and detailed risk maps and depth profiles of As concentrations above the 10 μg/L maximum contaminant level. Accuracy depended on local training data density. We identified a training data density of 0.07 wells/km 2 as a practical target for stable county-level performance. Maps of exceedance probabilities highlight priority areas for testing that are particularly important in rural communities that have received less sampling. These results support public health action by guiding where to install wells and where to test them, how much new sampling is needed, and where treatment outreach is most urgent.

Minnesota↗
USGS2025

Zircon as a pathfinder to REE mineralization

Carbonatites and alkaline silicate rocks are major primary sources of the rare earth elements (REE) and other critical metals, such as Nb. Despite the economic significance of these rocks, their formation and the processes of REE enrichment are poorly understood. Here, statistical analysis of a global dataset demonstrates that zircon geochemistry is a powerful recorder of REE metallogenesis and a potential pathfinder for REE deposits. Zircons from REE and Nb fertile intrusions lack Eu anomalies and have elevated Gd/Yb and Th/Yb, indicating they crystallised from magmas that originated from deep, oxidised and enriched mantle sources. Complexes with Nb enrichment have low U/Nb, reflecting an enriched mantle source, whereas high U/Nb in REE-only fertile intrusions suggest a subduction-metasomatised mantle source. Machine learning models demonstrate high accuracy in classifying zircon from barren and fertile deposits. Classification of detrital zircons shows that REE-enriched deposits correlate with supercontinent assembly, whereas Nb fertile complexes are associated with supercontinent breakup. This approach offers a new, mineral to global scale, petrologic and exploration tool that enhances understanding of REE metallogenesis.

Geochemical Perspectives Letters↗
USGS2025

Gas emissions from the Sulphur Bank Mercury Mine hydrothermal system, Clear Lake volcanic field, California

The Sulphur Bank Mercury Mine (SBMM) hydrothermal system offers insights into active degassing processes in the Clear Lake volcanic field (CLVF), a high-threat region based on its record of Holocene eruptions and proximity to populated areas. Here we present chemical and isotopic analyses of gas samples collected between 2015 and 2023, along with the first comprehensive CO 2 flux survey of the SBMM area conducted in 2023. Sampled gases are CO 2 - and CH 4 -rich (≥84 and 6 mol% in dry gas, respectively) with high mantle-derived helium contributions ( 3 He/ 4 He = 6.54–7.86 R C /R A ). Carbon isotopic compositions of CO 2 (δ 13 C = −10.0 to −9.5 ‰) and CH 4 (δ 13 C = −35.8 ‰) indicate mixed sources, with significant contributions from metamorphism of organic-rich Franciscan Complex rocks hosting the hydrothermal system. Modeling of gas compositions shows that scrubbing by interaction with air-saturated groundwater strongly influences observed compositional variability. From our CO₂ flux measurements, we estimate the deeply derived CO 2 emission rate from the SBMM hydrothermal area (0.2 km 2 ) at 240 t d −1 , comparable to many quiescently degassing volcanoes worldwide. We also provide a first-order estimate of CH 4 emissions at approximately 0.5 t d −1 . Our findings establish crucial baseline data for future volcanic monitoring efforts, enhancing detection capabilities for potential changes in this active hydrothermal system. This work contributes to the broader understanding of volatile contributions from volcanic and metamorphic sources to the global carbon budget, while highlighting the strong influence of bedrock geology on gas compositions in the CLVF.

California↗
USGS2024

Comparing subduction ground-motion models to observations for Cascadia

We evaluate Cascadia subduction ground-motion models (GMMs), considered for the 2023 US National Seismic Hazard Model (NSHM) update, by comparing observations to model predictions. The observations comprise regional recordings from intraslab earthquakes, including contributions from 2021 and 2022 events in southern Cascadia and global records from interface earthquakes. Since the 2018 NSHM update, new GMMs for Cascadia have been published by the Next Generation Attenuation (NGA)-Subduction Project that require independent evaluation. In the regional intraslab comparisons, we highlight a characteristic frequency dependence for Cascadia data, with short periods having lower ground motions and longer periods being comparable to other subduction zones. We evaluate differences in northern and southern Cascadia and find that the NGA-Subduction GMMs developed using southern Cascadia data perform better in this region than the model that did not consider these data. We compare ground-motion variability in Cascadia with the NGA-Subduction model predictions and find differences at short periods ( T = 0.1 s) due to the use of global versus regional data in the development of these models. Moreover, the within-event component of aleatory variability from the GMMs overpredicts the standard deviation of Cascadia recordings at very short periods ( T < 0.05 s). Using global interface earthquakes as a proxy to evaluate the Cascadia GMMs, we find long-period overprediction from a simulation-based GMM and some of the empirical GMMs. When comparing recent observations, we find a similar misfit to GMMs and the 2010 and 2022 Ferndale earthquakes. Finally, we observe different basin amplification factors arising in different subsets of the data, which indicate that differences in basin factors between empirical GMMs could arise from the data selection choices by the developers. As part of evaluating the regional basin terms, we apply basin amplification factors from the magnitude 9 Cascadia earthquake simulations to the empirical GMMs for interface earthquakes. The comparisons presented in this study indicate that the NGA-Subduction GMMs for Cascadia perform well relative to observations and older subduction GMMs.

British Columbia, California, Oregon, Washington↗
USGS2026

Riverscape heterogeneity shapes population diversity for a migratory fish

Habitat patch dynamics can scale up to influence population demography and diversity with implications for resilience to environmental stochasticity. But how the spatial arrangement and size of habitat patches interact with other components of habitat heterogeneity to shape population diversity at larger spatial scales is not well understood. For riverine fishes, there is increasing evidence that tributary streams provide critical demographic support to main stem rivers. However, the extent to which main stem rivers rely on demographic contributions from tributaries, and the factors underlying this dependence, have not been assessed. Here, we used genetic stock identification to evaluate the effect of tributaries on population diversity of Yellowstone cutthroat trout ( Oncorhynchus virginalis bouvieri ) occupying the main stem Snake River, Wyoming, USA. We found that the main stem relied almost entirely on tributaries for demographic support, but main stem composition varied spatially among river sections. Distance between habitat patches, catchment area, and groundwater availability acted in concert to determine the contribution of specific tributaries to the main stem, but contributions were ultimately modulated by habitat connectivity. We also found evidence for multi-scale spatial structure in tributary contributions, providing insight into untested drivers of main stem river population diversity. Our results demonstrate how spatially discrete and distributed riverscape attributes influence population diversity at broader spatial scales, illustrating how ecosystem resilience emerges from the dynamic, two-way exchange of individuals and energy across habitat networks. Management plans for large rivers that address the ecological contributions of tributaries may be needed to achieve optimal outcomes. Similarly, conservation strategies that exclusively focus on headwater streams may fail to capture the broader habitat requirements necessary to maintain robust cold-water fish populations and associated recreational fisheries, particularly under global environmental change.

Wyoming↗
USGS2025

Arctic speleothems reveal nearly permafrost-free Northern Hemisphere in the Late Miocene

Arctic warming is happening at nearly four times the global average rate. Long-term trends of permafrost dynamics cannot be estimated directly from monitoring of present-day thaw processes, requiring paleoclimate-proxy information. Here we use cave carbonates (speleothems) from a northern Siberian cave to determine when the Northern Hemisphere was mostly permafrost-free. At present, thick continuous permafrost in this region prevents speleothem growth. In a series of partially eroded caves, speleothems grew during the late Tortonian stage (8.68 ± 0.09 Ma), a time when the geographic position of this site was already similar to today. Paleotemperatures reconstructed from speleothems show that mean annual air temperatures (MAAT) in the region were + 6.6°C to + 11.1°C, when contemporary global MAAT were ~ 4.5 °C higher than modern. Our findings provide direct evidence that warming to Tortonian-like temperatures would leave most of the Northern Hemisphere permafrost-free. This may release up to ~ 130 petagrams of carbon, enhancing further warming.

Siberia↗
USGS2024

Unscrambling the Proterozoic supercontinent record of northeastern Washington State, USA

The time interval from Supercontinent Nuna assembly in the late Paleoproterozoic to Supercontinent Rodinia breakup in the Neoproterozoic is considered by some geologists to comprise the “Boring Billion,” an interval possibly marked by a slowdown in plate tectonic processes. In northeastern Washington State, USA, similar to much of western Laurentia, early workers generally thought the tectonostratigraphic framework of this interval of geologic time consisted of two major sequences, the (ca. 1480–1380 Ma) Mesoproterozoic Belt Supergroup and unconformably overlying (<720 Ma) Neoproterozoic Windermere Supergroup. However, recent research indicates that strata considered by early workers as Belt Supergroup equivalents are actually younger, and a post-Belt, pre-Windermere record is present within the <1360 Ma Deer Trail Group and <760 Ma Buffalo Hump Formation. Thus, the northeastern Washington region perhaps comprises the most complete stratigraphic record of the “Boring Billion” time interval in the northwestern United States and holds important insights into global Proterozoic supercontinent tectonic processes. In light of these exciting developments, this field guide will address the early historic economic geology and original mapping of these Proterozoic sequences in the northeastern Washington region, and from that foundation explore more recent isotopic provenance data and their regional to global context. Finally, the guide will end with a discussion of remaining questions with a goal of stimulating interest in these relatively understudied, yet important, rocks.

Washington↗
USGS2026

Tringa flavipes (Lesser Yellowlegs) from separate breeding sites subdivides the Prairie Pothole Region in space and time during southbound migration

Some staging regions support multiple groups of the same migratory species, each of which may use the region differently. Characterizing the ways, in which separate groups use such regions can therefore help to identify vulnerabilities during this sensitive period of the annual cycle. The Prairie Pothole Region (PPR) is a massive wetland complex in the northern Great Plains of North America used by ∼11 million shorebirds during migration. The PPR has been heavily modified by agriculture and is experiencing varied effects of global climate change, threatening the health of the shorebirds that rely on it. Here, we used 6 seasons of southbound tracking data of Tringa flavipes (Lesser Yellowlegs)—a long-distance migratory shorebird species with an estimated population decline of 63% over the last 4 decades—from 9 sites across their breeding range to explore differences in migratory behavior within this important staging region. We found that 75% of tracked individuals used the region during southbound migration, and T. flavipes from different breeding sites detoured 110–875 km from their most direct migratory route to access the PPR. Individuals that arrived later stayed longer and made more stops within the region than those that arrived early. Individuals originating from different breeding sites also displayed spatial and temporal segregation within the region: T. flavipes from southwest and central Alaska relied heavily on the northwestern PPR, while those from Canada used the central and southeastern portions of the PPR. Finally, timing of use varied among groups, but the southeastern PPR became increasingly important over the course of the southbound migratory window, as other wetlands likely dried out. Our study highlights the portions of the PPR of critical importance to migrating T. flavipes and the diversity of ways, in which different groups from within the same species can use a single staging region.

Alaska, Manitoba, Northwest Territories, Ontario, ↗
USGS2024

Ground deformation and gravity for volcano monitoring

Introduction When magma accumulates or migrates, it can cause pressurization and related ground deformation. Characterization of surface deformation provides important constraints on the potential for future volcanic activity, especially in combination with seismic activity, gas emissions, and other indicators. A wide variety of techniques and instrument types have been applied to the study of ground deformation at volcanoes (sidebar, p. 2; Dzurisin, 2000, 2003, 2007). Geodetic instruments include continuously recording Global Navigation Satellite System (GNSS; of which the United States’ Global Positioning System is one example) stations (fig. D1), borehole tiltmeters, and interferometric synthetic aperture radar (InSAR) measurements (from satellites, occupied and unoccupied aircraft systems, and ground-based sensors). Additional geodetic measurements like continuous- and survey-mode gravity (fig. D2) can contribute substantially to interpreting these data. Borehole strainmeters (see chapter K , this volume, by Hurwitz and Lowenstern, 2024) also have outstanding utility for monitoring deformation, although because of cost and permitting challenges, we do not include them as part of standard volcano monitoring networks for U.S. volcanoes. Still other techniques like light detection and ranging (lidar), structure from motion, and optical satellite data can be used to derive gross topographic changes, which can be used to map volcanic deposits, infer eruption rates, and gain insights into the source processes associated with eruptive activity (see chapter G , this volume, on tracking surface changes caused by volcanic activity; Orr and others, 2024). Experience has shown that no single geodetic monitoring technique is adequate to detect and track the entire range of ground-motion patterns that occur at volcanoes, primarily because of the temporal and spatial diversity of volcano deformation (fig. D3). Similarly, the magnitude of surface deformation varies widely. Geodetic monitoring strategies should therefore include multiple techniques and instrument types to cover a wide range of spatial and temporal scales. In identifying recommendations for geodetic instrumentation for volcano monitoring networks, we attempted to maximize the diversity of instrument types to measure the full range of deformation signals and minimize their expense and number; thus, we do not include several well-known deformation-monitoring techniques in our recommendations. Extensometers, for example, measure strains over distances of a few meters and have an excellent record of success in detecting changes in preeruptive localized ground motion across existing cracks, including at Mount St. Helens, Washington (Iwatsubo and others, 1992), and Piton de la Fournaise, Réunion Island (Peltier and others, 2006). Despite being relatively inexpensive, extensometers are best used primarily when localized ground displacements (for example, ground cracks) need to be tracked, and are not necessary at all volcanoes. In considering volcano deformation monitoring strategies, two complicating factors are deserving of special attention. First, not all deformation is driven by subsurface magmatic activity—for example, at many large stratovolcanoes (for example, Mount Rainier), flank collapses and landslides are significant geologic hazards (Reid and others, 2001) that may occur even in the absence of magmatic activity. Monitoring the stability of volcanoes is thus another critical application of geodetic monitoring networks to inform hazard assessment. One of the most famous examples of edifice instability is the large flank collapse that initiated the May 18, 1980, eruption of Mount St. Helens. Deformation monitoring had detected a bulge on the north flank of the mountain in April 1980 that was expanding by several meters per day (Lipman and others, 1981). Given that flank collapses can happen at any time during a period of volcanic unrest (or even outside a period of unrest), the capability to assess edifice stability is critical. Second, although volcanoes are commonly treated as idealized structures that erupt from single points, like centralvent stratovolcanoes, many are characterized by long rift zones from which eruptions may originate, and distributed volcanic fields are characterized by broadly spaced vents. For example, linear dikes are common at Kīlauea, Mauna Loa, and between Mount Shasta and Medicine Lake in California. At Kīlauea, one of these linear dikes emerged more than 40 kilometers (km) away from the summit of the volcano during the lower East Rift Zone eruption in 2018. Other volcanic fields, like Lassen volcanic center, California, or the San Francisco Volcanic Field, Arizona, have many small vents spread over a wide area. Although the instrumentation guidelines presented in this chapter remain phrased for central-vent volcanoes, they should be modified as needed in the context of the eruptive characteristics of each individual volcanic system. Spatial analysis of geodetic network coverage could help to ensure adequate instrumentation in areas where volcanism can occur over a broad area as opposed to a central vent. As an example, consider the adjacent volcanoes Mount Shasta and Medicine Lake. If station locations are chosen based only on the distance from the centers of the volcanoes, then any geodetic anomalies between the two volcanoes—an area of potential volcanism as indicated by the presence of volcanic features—may remain undetected by ground-based instrumentation. The spatial analysis is accomplished via a grid of pressure point sources (Mogi, 1958) evenly distributed across the map area, at a depth of 5 km in this example (fig. D4). Each source is inflated until predicted deformations exceed the GNSS white noise uncertainty estimates at one site (Langbein, 2017; Murray and Svarc, 2017). This volume of detectable magma provides a measure of the quality of the coverage (fig. D4). The results indicate that, as of 2022, there is a large area between Mount Shasta and Medicine Lake volcano with existing mapped dikes in which a substantial amount of magma could intrude without being detected geodetically. Applying this style of analysis to individual volcanic systems can provide a guide for designing network geometry given the expected locations of future eruptions.

Scientific Investigations Report↗