Search USGS⌕ Search

Geology topics

Research about Montana

Source-linked reports with geographic coverage including Montana.

At least 73 records · Page 4Linked to original sources

Characterizing vegetation and return periods in avalanche paths using lidar and aerial imagery

Snow avalanches are a hazard and ecological disturbance across mountain landscapes worldwide. Understanding how avalanche frequency affects forests and vegetation improves infrastructure planning, risk management, and avalanche forecasting. We implemented a novel approach using lidar, aerial imagery, and a random forest model to classify imagery-observed vegetation within avalanche paths in southern Glacier National Park, Montana, USA. We calculated spatially explicit avalanche return periods using a physically based spatial interpolation method and characterized the vegetation within those return period zones. The automated vegetation classification model differed slightly between avalanche paths, but the combination of lidar and spectral signature metrics provided the best accuracy (88–92 percent) for predicting vegetation classes within complex avalanche terrain rather than lidar or spectral signature metrics alone. The highest frequency avalanche return periods were broadly characterized by grassland and shrubland, but the influence of topography greatly influences the vegetation classes as well as the return periods. Furthermore, statistically significant differences in lidar-derived vegetation canopy height exist between categorical return periods. The ability to characterize vegetation within various avalanche return periods using remote sensing data provides land use planners and avalanche forecasters a tool for assessing the spatial extent of large-magnitude avalanches in individual avalanche paths.

Montana↗

Glacier National Park bumble bee survey report 2023

Glacier National Park's grasslands provide important contributions to the character and ecology of the park. In 1999-2001, Glacier National Park (hereafter, the park) established 155 permanent vegetation monitoring plots to inventory grassland vegetation communities east of the Continental Divide. In June of 2023, the Blackfeet Nation (Amskapi Piikuni) re-introduced a herd of free roaming bison on adjacent tribal land (the linnii Initiative), and those bison may enter the park. Because grasslands are important areas for bison grazing, and because biological communities have likely changed since the initial inventories, the park’s vegetation program began revisiting grassland monitoring plots in 2018. New data will provide insights into how these grasslands, and the wildlife that depend on them, have changed over the past two decades. Data on pollinators in these grasslands, however, are limited. Bison have been shown to influence plant communities, for example, by increasing herbaceous forb diversity and drought resilience (Elson and Hartnett 2017; Ratajczak et al. 2022). These changes directly influence resources available to foraging pollinators. To provide understanding of pollinators prior to bison reintroduction, bumble bee surveying at these grassland plots began in 2020 and has continued through 2023. Target sites for 2020-2022 focused on collecting data at plots where new vegetation surveys were recently completed to match current vegetation data with the bumble bee data.

Montana↗

Detecting avalanche path ground cover and vegetation change across multiple scales through time using remote sensing tools

Large-magnitude avalanches often alter vegetation composition, avalanche path dimensions, and subsequent avalanche return periods. Understanding temporal changes in individual avalanche path trimlines, runout zones, and geomorphic characteristics helps forecasters, planners, and engineers estimate potential avalanche destructive size and impact on infrastructure or settlements in the runout zone. Understanding these changes on a large scale also provides information on post-cycle avalanche distribution. Here, we use remote sensing platforms and change detection techniques to examine vegetation change in avalanche paths in Montana and Colorado. In northwest Montana, we implemented a novel approach using lidar, aerial imagery, and a random forest model to classify imagery-observed vegetation within avalanche paths. We calculated spatially explicit avalanche return periods using a physically based spatial interpolation method and characterized the vegetation within those return period zones. In Colorado, we investigated changes in avalanche path vegetation characteristics prior to and after a widespread large-magnitude avalanche cycle. The highest frequency of avalanche return periods was broadly characterized by grassland and shrubland, but topography greatly influences vegetation classes and return periods. Furthermore, statistically significant differences in lidar-derived vegetation canopy height exist between categorical return periods. We used optical sensors from satellite imagery to analyze changes in Normalized Difference Vegetation Index (NDVI) to calculate ground cover change over time. NDVI, a measure of near-infrared and red bands within the imagery, allowed us to distinguish between green vegetation (e.g., trees and shrubs) and non-vegetated ground cover (e.g., dead and downed trees, rocks, and dirt) within avalanche paths. For this study, we calculated changes in NDVI values by comparing imagery from 2018 to imagery from 2019 after a widespread large magnitude avalanche cycle occurred in March 2019 in Colorado, United States. We applied a filtering process to reduce error, classified NDVI change based on the value distribution, and then calculated area change of all areas within each avalanche path. We completed this process for 1633 avalanche paths throughout Colorado. We found that using NDVI difference values pre- and post-avalanche cycle allowed us to identify ground cover change in avalanche paths throughout Colorado. These changes span from a slight expansion of existing avalanche paths to substantial landscape disturbance. For example, a size D5 avalanche caused severe ground cover change in 18% of one single path near Aspen, Colorado. This suggests that large magnitude avalanches can redefine avalanche path dimensions and could impact subsequent avalanche size and frequency. Using NDVI from satellite imagery is a simple way to detect ground cover changes in avalanche paths on a large scale or in remote areas. In general, remote sensing products to detect and examine vegetation and ground cover change in avalanche paths can help inform avalanche distribution and benefit planning efforts.

Montana↗

Wolf harvest management strategy evaluation: Annual Report, 2024

Wolf harvest season setting is complicated and controversial. State law requires Montana Fish, Wildlife and Parks (MFWP) to both reduce the wolf population and avoid federal relisting under the Endangered Species Act (Montana Fish, Wildlife and Parks, 2002). Disparate stakeholder groups each have different objectives for wolf management. For instance, big game advocates want to see improved big game populations and hunting opportunities in northwest Montana, while wolf advocates want to see regulations that minimize wolf mortality. Decision making about season setting tries to balance these objectives. Wolf hunting and trapping season decisions are made by the Montana Fish and Wildlife Commission and are informed by annual wolf abundance estimates from an integrated patch occupancy model (iPOM, Sells et al., 2022c) as well as the predictions of wolf abundance into the future under potential constant harvest levels. Parametric uncertainty (uncertainty surrounding the value of a parameter) from the iPOM estimates is propagated through to future projections, providing the Commission with plausible and worst-case outcomes of different levels of public harvest over the short term, i.e., five years into the future, on the wolf population in Montana (Parks et al., 2024). An alternative approach to inform wolf management and harvest decisions is through adaptive management. Adaptative management is appropriate for decisions that are made iteratively and when monitoring data are collected to learn about the outcomes from decisions, where monitoring data help to reduce critical uncertainties regarding ecosystem function or management outcomes (Walters, 1986; Williams, 2011). Management strategy evaluation (MSE) is one way to develop an adaptive management framework. MSE was developed by fisheries managers and scientists to more accurately and fully incorporate various forms of uncertainty, consider long-term time horizons, and add more transparency in a fisheries context (Punt et al., 2016). It has been used routinely and has become a standard approach for complicated and contentious marine fisheries management situations, yet it has been underutilized in wildlife management (but see Bunnefeld et al., 2013, 2011). MSE is a forward simulation approach for testing prospective management options or strategies over a wide range of possible states (Punt et al., 2016). A MSE framework captures the ‘truth’ or what is happening in the system (termed the ‘the operating model’) and the information available to the decision makers (termed ‘the estimation model’ or ‘management strategy’). More precisely, there are four main processes modeled. First, models are constructed based on current understanding and data to represent ‘truth’. Second, the collection of monitoring data is simulated from the ‘truth’ model. Third, the simulated monitoring data are fit to an estimation model and the next time step’s population metrics are predicted from the estimated parameters. Fourth, based on the estimation model results and the predictions, the decision-making process is simulated following a management strategy, whereby a decision is made and the implementation of this decision feeds back into the ‘truth’ model (Figure 1). This process continues through time. Additionally, each simulation through time is repeated to capture the full range of stochasticity and uncertainty.

Montana↗

The 3D Elevation Program—Supporting Montana’s economy

Introduction Montana, America’s fourth largest State with an area of 147,040 square miles, is defined by its diverse terrain. The western two-fifths of the State falls within the Rocky Mountains and the eastern three-fifths is in the Great Plains. Because of its location along the Continental Divide, the rivers in Montana drain into either the Pacific Ocean or the Gulf of Mexico. Montana is often called the Treasure State due to its mineral wealth, which includes oil, gas, and coal, but the State’s primary economic activity is agriculture. Other economic activities include natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, and geologic resource assessment and hazard mitigation. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.

Montana↗

Mountain glaciers influence biogeochemical and ecological characteristics of high-elevation lakes across the northern Rocky Mountains, USA

Mountain glaciers are retreating rapidly due to climate change, leading to the formation of downstream lakes. However, little is known about the physical and biogeochemical conditions in these lakes across a range of glacial influence. We surveyed alpine lakes fed by both glacial and snowpack meltwaters and those fed by snowpack alone to compare nutrient concentrations, stoichiometry, water clarity, chlorophyll, and zooplankton communities. Total phosphorus (TP) and soluble reactive phosphorus were two times higher in glacial lakes than in non-glacial lakes, while nitrate concentrations were three times higher. However, organic carbon concentrations in glacial lakes were two times lower than in non-glacial lakes. The carbon-to-phosphorus ratio and the nitrogen-to-phosphorus ratio of lake seston increased with water clarity in glacial lakes, suggesting that turbidity from glacial flour increases light limitation and increases stoichiometric food quality for zooplankton in newly formed lakes. However, chlorophyll a concentrations did not differ between lake types. Through structural equation modeling, we found that glaciers exhibit a bidirectional association with nitrate and TP concentrations, perhaps mediated through landscape vegetation and lake clarity. Zooplankton communities in high-turbidity glacial lakes were largely composed of cyclopoid copepods and rotifers (i.e., non-filter feeders), while non-glacial lakes tended to be dominated by calanoid copepods and cladocerans (i.e., filter feeders). Our results show that glacier-influenced lakes have biogeochemical and ecological characteristics distinct from snow-fed mountain lakes. Sustained studies are needed to assess the dynamics of these unique features as the influence of the alpine cryosphere fades under ongoing climate change.

Montana↗

The patchwork governance of ecologically available water: A case study in the Upper Missouri Headwaters, Montana, United States

Institutional authority and responsibility for allocating water to ecosystems (“ecologically available water” [EAW]) is spread across local, state, and federal agencies, which operate under a range of statutes, mandates, and planning processes. We use a case study of the Upper Missouri Headwaters Basin in southwestern Montana, United States, to illustrate this fragmented institutional landscape. Our goals are to (a) describe the patchwork of agencies and institutional actors whose intersecting authorities and actions influence the EAW in the study basin; (b) describe the range of governance mechanisms these agencies use, including laws, policies, administrative programs, and planning processes; and (c) assess the extent to which the collective governance regime creates gaps in responsibility. We find the water governance regime includes a range of nested mechanisms that in various ways facilitate or hinder the governance of EAW. We conclude the current multilevel governance regime leaves certain aspects of EAW unaddressed and does not adequately account for the interconnections between water in different parts of the ecosystem, creating integrative gaps. We suggest that more intentional and robust coordination could provide a means to address these gaps.

Montana↗

Predicting water quality in the Clark Fork near Grant-Kohrs Ranch National Historic Site, southwestern Montana

The U.S. Geological Survey (USGS) provides a wide range of streamflow, groundwater, and water-quality data to Government, commercial, academic, and public users. The USGS has a record of success with using optical turbidity sensors to predict suspended-sediment concentrations in rivers and streams. Turbidity sensors collect backscatter signals from suspended particles in water, which can be accurately measured and linked closely to hazardous contaminants that travel on the surfaces of suspended particles. Contaminant concentrations derived from the statistical relations between turbidity and contaminants like copper and lead can then be measured in real-time.

Montana↗

Spatiotemporal variations in copper, arsenic, cadmium, and zinc concentrations in surface water, fine-grained bed sediment, and aquatic macroinvertebrates in the upper Clark Fork Basin, western Montana—A 20-year synthesis, 1996–2016

The legacy of mining-related contamination in the upper Clark Fork Basin created an extensive longitudinal gradient in metal concentrations, extending from Silver Bow Creek to Lake Pend Oreille, Idaho. Downstream metal concentrations continue to decline, but, despite such improvements, the ecological health of much of the river remains uncertain. Understanding the long-term consequences of the Clark Fork River mining legacy may be supported by environmental monitoring techniques that include a holistic assessment of biological health or response to define organism exposure to complex contaminant mixtures and the consequences of such exposures. This report presents the spatiotemporal patterns of mining-related contaminants, copper, arsenic, cadmium, and zinc, in surface water, fine-grained bed sediment, and macroinvertebrate (aquatic insect) tissue in the upper Clark Fork from near Butte to Missoula, Montana. Overall, the patterns in water column sample concentrations observed in this study were consistent with previously observed trends, but bed sediment concentrations and concentrations of copper and arsenic varied more in tissue samples among sites. Trace element concentrations, especially copper, often exceeded the chronic aquatic life criteria and consistently exceeded the sediment probable effects level PEL for copper, particularly in the upper and middle river segments. The 20 years considered here were the wettest period since remediation started, and this increase in precipitation may have affected patterns in contaminant concentrations. Results of this study demonstrated the utility of a continued, comprehensive biomonitoring program to help guide and evaluate future environmental cleanup activities in the Clark Fork. Despite variation in defining complete restoration in these watersheds, using multiple lines of evidence in this study provided quantifiable measures of the timing and completeness of recovery relative to reference conditions. Successful recovery in the Clark Fork may benefit from an adaptive management strategy to continue collecting a comprehensive, multivariate dataset to evaluate whether established goals are being met and for subsequent adjustments and management, as needed.

Montana↗

Application of surrogate technology to predict real-time metallic-contaminant concentrations and loads in the Clark Fork near Grant-Kohrs Ranch National Historic Site, Montana, water years 2019–20

Grant-Kohrs Ranch National Historic Site (GRKO) in southwestern Montana commemorates the frontier cattle era and its formative role in shaping the culture and history of the Western United States. The ranch was designated a national historic landmark in 1960 and a unit of the National Park Service (NPS) by Congress in 1972. The GRKO is unique because of its proximity to large-scale extraction, milling, and smelting of gold, silver, copper, and lead ore from the 1860s to the 1980s in the Butte mining district. During this time, mining and milling wastes were discarded in the upper Clark Fork Basin, resulting in the deposition of large amounts of waste materials (tailings) enriched with metallic contaminants (including cadmium, copper, iron, lead, manganese, zinc, and the metalloid trace element arsenic) in soils and in nearby streams and floodplains. Denuded vegetation and fish kills attributed to large concentrations of heavy metals caused the U.S. Environmental Protection Agency to designate a 120-mile section of the Clark Fork River (hereafter referred to as the “Clark Fork”), including GRKO, to be included on the National Priority List for Superfund cleanup in 1989. In 2018, with oversight from the Montana Department of Environmental Quality, the NPS began remediation of 2.6 miles of the Clark Fork as it flows through GRKO property. In 2019, the U.S. Geological Survey (USGS), in collaboration with the NPS, conducted a study using time-series data from backscatter signals from fixed-point turbidity and acoustic sensors with the intent to provide a high-resolution monitoring tool to estimate metallic-contaminant concentrations (MCCs) and loads during NPS remediation of the Clark Fork. Two monitoring sites at USGS streamgages on the Clark Fork on either side of GRKO property were instrumented with turbidity and acoustic sensors and surrogate relations were developed among time-series data and MCCs. The application of high-resolution surrogate data was used to infer contaminant source and fate and evaluate MCC values relative to aquatic-life standards. Using high-resolution surrogate data, it was determined that during spring runoff and storm-related runoff events, MCCs peaked at their highest values at streamflows markedly lower and prior to peak streamflow. Because MCCs peaked prior to streamflow peaks, it could be inferred that the source of MCCs originated from channel bed sediments in close spatial proximity to the monitoring site or from nearby streambanks and floodplains. High-resolution surrogate data revealed that copper concentrations in the Clark Fork exceeded chronic aquatic-life standards 90 percent of the time when streamflow exceeded 200 cubic feet per second (ft 3 /s) and exceeded acute aquatic-life standards 85 percent of the time when streamflow exceeded 260 ft 3 /s. These data helped support NPS management goals for evaluating variation in water quality during remediation of GRKO property, evaluating MCC values relative to aquatic-life standards, and quantifying benefits from Superfund remediation activities.

Montana↗

Multi-scale relationships in thermal limits within and between two cold-water frog species uncover different trends in physiological vulnerability

1. Critical thermal limits represent an important component of an organism's capacity to cope with future temperature changes. Understanding the drivers of variation in these traits may uncover patterns in physiological vulnerability to climate change. Local temperature extremes have emerged as a major driver of thermal limits, although their effects can be mediated by the exploitation of fine-scale spatial variation in temperature through behavioural thermoregulation. 2. Here, we investigated thermal limits along elevation gradients within and between two cold-water frog species ( Ascaphus spp.), one with a coastal distribution ( A. truei ) and the other with a continental range ( A. montanus ). We quantified thermal limits for over 700 tadpoles, representing multiple populations from each species. We combined local temporal and fine-scale spatial temperature data to quantify local thermal landscapes (i.e., thermalscapes), including the opportunity for behavioural thermoregulation. 3. Lower thermal limits for either species could not be reached experimentally without the water freezing, suggesting that cold tolerance is <0.3°C. By contrast, upper thermal limits varied among populations, but this variation only reflected local temperature extremes in A . montanus , perhaps as a consequence of the greater variation in stream temperatures across its range. Lastly, we found minimal fine-scale spatial variability in temperature, suggesting limited opportunity for behavioural thermoregulation and thus increased vulnerability to warming for all populations. 4. By quantifying local thermalscapes, we uncovered different trends in the relative vulnerability of populations across elevation for each species. In A . truei , physiological vulnerability decreased with elevation, whereas in A . montanus , all populations were equally physiologically vulnerable. These results highlight how similar environments can differentially shape physiological tolerance and patterns of vulnerability of species, and in turn impact their vulnerability to future warming.

Montana↗

Electromagnetic and magnetic imaging of the Stillwater Complex, Montana, USA

Modelling and analysis of helicopter electromagnetic data result in resistivity and susceptibility models and derivatives of magnetic data that characterise shallow parts of the Stillwater Complex, critical for aiding exploration and expansion of globally scarce critical and battery mineral resources that include platinum group elements, nickel, copper and chromium. The magnetic susceptibly models derived from the electromagnetic data and the tilt derivative of the magnetic data image layering, mafic dikes, banded iron formation, and serpentinised peridotite. Known areas with contact-type mineralisation are generally characterised by low resistivities and susceptibilities where the volume of mineralised rock is large and/or the depth is shallow. We use iso-cluster and edge detection analysis of both resistivities and susceptibilities to identify potential mineralisation in poorly characterised regions as well as faults. Low resistivity layers beneath large landslides reflect water saturated porous slip surfaces which can interfere with drilling. This uncommon approach of tightly linking the resistivity and susceptibility models and magnetic anomaly data to rock property, surficial geologic, drill hole and soil geochemistry data to image the geology in the upper ∼100 m, aids identification of prospective mineralised regions as well landslides and faults that can impact mineral exploration and local hazards.

Montana↗

Ecogeomorphic interactions of Russian olives (Elaeagnus angustifolia) and point-bar morphology along Powder River, Montana, USA

Point bars are crucial alluvial features that help sustain meandering river ecosystems. They are influenced by interactions among physical processes and biological components, such as riparian vegetation. Understanding the mechanisms underlying these interactions can inform management decisions. The meandering Powder River in southeastern Montana, USA, provides a valuable study system for fluvial interactions because it has no major human alterations. Riparian stands of non-native Russian olive trees ( Elaeagnus angustifolia ) became noticeable after ~50-year flood in 1978. Fortuitously, 20 channel cross-sections had been established in 1975 and 1977 and have been surveyed periodically ever since. This temporally extensive dataset was coupled with a spatially extensive dataset of 85 point-bar cross-sections derived from high-resolution LiDAR that enabled evaluation of interactions between Russian olives and point-bar morphology through time and space. Based on published literature and field observations, we hypothesised that an increase in the width of Russian olive stands would result in (1) a decrease in the overall point-bar slope, (2) an increase in point-bar heights and (3) in point-bar toe-slopes. The results indicated that point-bar slopes did decrease with an increase in stand width, supporting the first hypothesis ( R 2 = 0.87). However, point-bar heights decreased with an increase in stand width ( R 2 = 0.63), contradicting the second hypothesis and there was no relation between point-bar toe-slopes and stand width ( R 2 < 0.1). The reverse hypothesis that point-bar morphology controls Russian olive stand widths makes more biophysical sense. Thus, Russian olive stand width increases as the point-bar slope and height decrease ( R 2 = 0.79 and 0.50), which provide a greater area of inundation for colonisation. This study demonstrates that geomorphology is controlling non-native vegetation colonisation along Powder River, but that the subsequent stabilisation associated with Russian oliveexpansion may in turn upset the critical geomorphic balance between bank erosion and point-bar aggradation necessary for a stable meandering system.

Montana↗

U.S. Geological Survey and Blackfeet Water Department Hydrologic Assessment of the Blackfeet Indian Reservation, Montana

The Blackfeet Nation seeks an increased scientific understanding of the water resources within the Blackfeet Indian Reservation of northwestern Montana. Hydrologic information is needed to better inform water-management decisions as the Blackfeet Nation implements the Blackfeet Water Rights Compact, initiates new water-use projects, and improves the Blackfeet Irrigation Project. The U.S. Geological Survey and the Blackfeet Water Department began cooperating in 2019 to design and implement a hydrologic data-collection program. The program is being implemented in phases that include discrete and continuous discharge measurements of streams and canals, installation, operation of streamgages, groundwater-level monitoring, and database management. Data collected will be used to characterize current hydrologic conditions on the reservation and will act as a baseline for comparison as Blackfeet Nation water projects are implemented.

Montana↗

Increased whitebark pine (Pinus albicaulis) growth and defense under a warmer and regionally drier climate

Introduction: Tree defense characteristics play a crucial role in modulating conifer bark beetle interactions, and there is a growing body of literature investigating factors mediating tree growth and resin-based defenses in conifers. A subset of studies have looked at relationships between tree growth, resin duct morphology and climate; however, these studies are almost exclusively from lower-elevation, moisture-limited systems. The relationship between resin ducts and climate in higher-elevation, energy-limited ecosystems is currently poorly understood. Methods: In this study, we: (1) evaluated the relationship between biological trends in tree growth, resin duct anatomy, and climatic variability and (2) determined if tree growth and resin duct morphology of whitebark pine, a high-elevation conifer of management concern, is constrained by climate and/or regional drought conditions. Results: We found that high-elevation whitebark pine trees growing in an energy-limited system experienced increased growth and defense under warmer and regionally drier conditions, with climate variables explaining a substantive proportion of variation (∼20–31%) in tree diameter growth and resin duct anatomy. Discussion: Our results suggest that whitebark pine growth and defense was historically limited by short growing seasons in high-elevation environments; however, this relationship may change in the future with prolonged warming conditions.

Montana↗

Sampling and analysis plan for the Koocanusa Reservoir and upper Kootenai River, Montana, water-quality monitoring program, 2021

In 2021, the U.S. Geological Survey will collect water-quality samples and environmental data from 3 sites in Koocanusa Reservoir and from 1 site in the Kootenai River. The transboundary Koocanusa Reservoir is in southeastern British Columbia, Canada, and northwestern Montana, United States, and was formed with the construction of Libby Dam on the Kootenai River 26 kilometers upstream from Libby, Montana. Two of the reservoir sites and the Kootenai River site, in the Libby Dam tailwater (the outflow of the reservoir flow into the Kootenai River), are equipped with automated, high-frequency ServoSipper water samplers. At the two reservoir sites, these samplers are mounted to pontoon platforms and automatically collect samples from multiple depths; a ServoSipper sampler was deployed at one site in 2019, and another ServoSipper sampler will be deployed at a second site in 2021. Discrete water-quality samples will be collected monthly at two depths at the river site and at two of the reservoir sites. The goal of this project is to collect multidepth, high-frequency vertical and temporal water-quality samples and data to understand the limnological and biological processes that control variations and trends in selenium concentrations and loads throughout Koocanusa Reservoir and in the Libby Dam tailwater at the southern end of the reservoir. This sampling and analysis plan documents the organization, sampling and data-collection scheme and design, pre- and post-collection processes, and quality-assurance and quality-control procedures.

Montana↗