Geology Reports⌕ Search

Geology topics

Research about Rocky Mountains

Source-linked reports with geographic coverage including Rocky Mountains.

At least 19 recordsLinked to original sources
USGS2026

Fine-scale factors affecting the abundance and thermal sensitivity of nonnative Brook Trout in coldwater Rocky Mountain streams

The Brook Trout ( Salvelinus fontinalis ) is a globally distributed nonnative species that threatens native salmonids in coldwater streams. Understanding the factors regulating Brook Trout densities in coldwater refugia is critical to effective management, so we investigated (a) fine-scale drivers of Brook Trout abundance and (b) factors affecting their thermal sensitivity in 49 coldwater streams in Idaho. Among the 14 candidate variables evaluated, Brook Trout density was most closely associated with mean August water temperature (dome-shaped response peaking at 11.0°C–11.1°C), wetted width (negative association), gradient (negative association), run habitat (positive association), and substrate size (negative association). Simulations indicated that densities were most sensitive to climate warming in low-velocity habitats, with the largest increases occurring in areas with baseline temperatures of 8.9°C and largest decreases in areas with temperatures of 12.2°C. We discuss our results in the context of Brook Trout behavior, effects on native salmonids, climate warming, and habitat restoration.

Idaho↗
USGS2026

Millennial-scale climatic and cultural impacts on vegetation and fire at the southern edge of the Rocky Mountains, USA

Mountain forests and woodlands in semiarid regions of the world are threatened by climatic change and other human impacts. In the southwestern USA, climate and culturally driven changes to the structure and fire regimes of dry coniferous forests over recent centuries are well documented by tree-ring archives. However, the roles of climate and people as drivers of millennial-scale changes are less understood. We present a new record of vegetation dynamics and regional fire activity inferred from pollen, microscopic charcoal, and sediment geochemistry from Santa Fe Lake, NM (3532 m a.s.l.), the southernmost natural lake in the Rocky Mountains. Declining elemental intensities (e.g., Ti, Fe, Si) record local deglaciation after 14,000 cal yr BP followed by upslope expansion of trees indicated by increasing Pinus and Picea pollen percentages as the climate warmed during the Late Glacial. Cool, dry growing seasons probably limited the establishment of dense forests until after 12,200 cal yr BP when we hypothesize that Pinus ponderosa (ponderosa pine) expanded regionally (i.e., within 10–100 km) due to continued warming and a possible increase in monsoonal precipitation. Subalpine forests established near Santa Fe Lake by 10,300 cal yr BP as indicated by abundant conifer stomates and increasing Picea and Pinus aristata pollen percentages, which are highest after 5100 cal yr BP. Increasing Juniperus -type, Quercus , and Pinus edulis -type pollen record changes in vegetation belts at lower elevations after 10,300 cal yr BP. Maize pollen, an unambiguous indicator of Puebloan agriculture, first appears at 800 cal yr BP (1150 cal yr CE) and is present through 1600 cal yr CE when Spanish colonization brought cultural upheaval and population loss to local indigenous communities. Regional fire activity, inferred from microscopic charcoal influx, remained relatively constant for most of our record. However, average microscopic charcoal influx more than doubled relative to the rest of the Holocene during the last 2000 years, with the highest influx after 1550 cal yr BP (400 cal yr CE). The increased influx of microscopic charcoal coincides with archaeological evidence for dramatic regional population growth in the northern Rio Grande region and probably reflects extensive cultural burning associated with the development of an agricultural economy. Although climate was an important driver of vegetation change and fire regimes in the mountains of the southwestern USA during the Holocene, our results suggest that human impacts on regional burning during the last 2000 years far exceeded earlier climate-driven variation.

Rocky Mountains↗
USGS2025

Movements and habitat use vary across the Rocky Mountain Population of trumpeter swans

The Rocky Mountain Population (RMP) of trumpeter swans Cygnus buccinator (hereafter, swans) in North America includes breeders in the Greater Yellowstone Area (GYA) and other western states (together, United States segment) and western provinces of Canada (Canada segment). Conservation concern for the United States segment stems from its slow population growth and the resident nature of GYA swans, which intermingle with migrating Canada segment swans in wintering habitats. Thus, understanding variation in migratory behavior and habitat use by swans in the two population segments can inform how management actions may affect the RMP. We used telemetry data from 55 RMP swans captured in the western United States to understand their movements and habitat use. For 45 swans (60 swan-years) that spent the summer in the United States, distance traveled between breeding and wintering areas ranged from 0 km (i.e., no migration in 22% of swan-years) to 473 km, with an average of nonzero movements of 118 ± 95 km (SD). Swans traveled farther distances when maximum temperatures were lower. For 10 swans (16 swan-years) that spent the summer in Canada, five appeared to molt but not to nest, and four appeared to nest in one or more years. Migration timing was similar for molting and nesting swans. All five molting swans and one nesting swan spent at least one previous summer in the GYA. Migratory connectivity of all birds was weaker in years when more swans migrated to Canada for the summer. During the breeding season, Canada swans used low-elevation lakes, but United States swans used high-elevation lakes. Both groups of swans increased use of crop fields outside of the breeding season. Our study shows interchange between the United States and Canada segments, a finding that challenges the efficacy of existing population designations. Furthermore, variation in movement behavior of GYA swans suggests possible actions, such as restoring winter habitats to increase swan distribution and migration, to support swan conservation.

Rocky Mountains↗
USGS2025

Climate-driven sulfate export in alpine watersheds may stimulate methylmercury production

Climate change is increasing sulfate export and changing wetland extent in mountain regions. These changes may increase microbially mediated production of the neurotoxic substance methylmercury due to enhanced sulfate metabolism in mountain environments. Here, we assess methylmercury concentrations and formation rates across high-elevation wetlands in the Colorado Rocky Mountains. We also investigate sulfate controls on methylmercury production within subalpine peatlands by amending soils with sulfate to mimic increased stream export of sulfate from the alpine zone and measuring methylmercury formation rates for different sulfate treatments. We found that subalpine peatlands have statistically significant higher methylmercury concentrations and formation rates compared to alpine, mineral-soil wetlands. Methylmercury production in subalpine peatlands also increased significantly ( p < 0.05) following sulfate additions; the highest rates occurred in sediments with intermediate extractable sulfate concentrations (∼0.60–1.4 mg sulfate g −1 dry soil). Our study is the first to identify soil sulfate-related thresholds for methylmercury production and sulfate-limitation of methylmercury production in subalpine peatlands. These findings highlight important linkages between climate-driven mineral weathering and mercury cycling in mountain regions globally.

Colorado↗
USGS2025

Fine-resolution satellite remote sensing improves spatially distributed snow modeling to near real time

Given the highly variable distribution of seasonal snowpacks in complex mountainous environments, the accurate snow modeling of basin-wide snow water equivalent (SWE) requires a spatially distributed approach at a sufficiently fine grid resolution (<500 m) to account for the important processes in the seasonal evolution of a snowpack (e.g., wind redistribution of snow to resolve patchy snow cover in an alpine zone). However, even well-validated snow evolution models, such as SnowModel, are prone to errors when key model inputs, such as the precipitation and wind speed and direction, are inaccurate or only available at coarse spatial resolutions. Incorporating fine-spatial-resolution remotely sensed snow-covered area (SCA) information into spatially distributed snow modeling has the potential to refine and improve fine-resolution snow water equivalent (SWE) estimates. This study developed 30 m resolution SnowModel simulations across the Big Thompson River, Fraser River, Three Lakes, and Willow Creek Basins, a total area of 4212 km 2 in Colorado, for the water years 2000–2023, and evaluated the incorporation of a Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat SCA datasets into the model’s development and calibration. The SnowModel was calibrated spatially to the Landsat mean annual snow persistence (SP) and temporally to the MODIS mean basin SCA using a multi-objective calibration procedure executed using Latin hypercube sampling and a stepwise calibration process. The Landsat mean annual SP was also used to further optimize the SnowModel simulations through the development of a spatially variable precipitation correction field. The evaluations of the SnowModel simulations using the Airborne Snow Observatories’ (ASO’s) light detection and ranging (lidar)-derived SWE estimates show that the versions of the SnowModel calibrated to the remotely sensed SCA had an improved performance (mean error ranging from −28 mm to −6 mm) compared with the baseline simulations (mean error ranging from 69 mm to 86 mm), and comparable spatial patterns to those of the ASO, especially at the highest elevations. Furthermore, this study’s results highlight how a regularly updated 30 m resolution SCA could be used to further improve the calibrated SnowModel simulations to near real time (latency of 5 days or less).

Colorado↗
USGS2025

Latitudinal gradients of snow contamination in the Rocky Mountains associated with anthropogenic sources

Seasonal snow is an important source of drinking water and recreation, and for agriculture in the Rocky Mountain region. Monitoring snow-water quality can inform on the effects to the albedo and energy balance of the snowpack, and the sources of natural and anthropogenic aerosol and gases. This study analyzed metals in the seasonal snowpack from water year (WY) 2018 for 49 sites. Calcium, lanthanum, and cerium concentrations support the importance of mineral dust to the southern Rocky Mountains. Mercury (Hg), zinc (Zn), and cadmium (Cd) concentrations showed a similar spatial pattern to mineral dust, whereas antimony (Sb) concentrations were highest in the northern Rocky Mountains. To assess the relative contributions from dust versus anthropogenic contaminant sources, enrichment factors (EF) were calculated, with values above 10 indicating anthropogenic contamination. For Cd, Hg, Sb, and Zn, EF values exceeded 10 at northern sites. These observations were compared to spatial trends of EF values of Hg from WY2009 to WY2018, regional monitoring networks, and back trajectory analyses. The agreement between these datasets revealed temporally consistent contaminant sources and/or transport processes to the northern Rocky Mountains snowpack. Sources include current and historical mining and smelting in the region. Strategies to limit the emissions of these metals to the Northern Rockies could benefit from focusing on remediation of contaminated sites, and continued monitoring and mitigation of active mining and smelting.

Colorado , Idaho, Montana, New Mexico, Utah, Wyomi↗
USGS2024

Leveraging local wildlife surveys for robust occupancy trend estimation

Natural resource agencies are frequently tasked with monitoring populations of at-risk species to ensure management activities do not negatively affect the viability of wildlife populations. Typically, these monitoring efforts evaluate trends in a population’s abundance, occupancy, or geographic distribution. Often, surveys provide local information, but results are generally not incorporated into broad-scale monitoring efforts that focus on range-wide population changes due to their variable nature in both spatial extent and effort. We investigated whether aggregating these local (hereafter “variable”) surveys can generate enough statistical power to estimate broad-scale population trends using simulations of declining populations of fishers ( Pekania pennati ) over a 10-year time horizon. Our simulations included three population sizes which we refer to as abundant, common, and rare ( N 0 = 700, 350, and 100 individuals, respectively) with each declining at a rapid and moderate pace ( λ = 0.933, and 0.977, respectively). For each population, we simulated variable surveys using an occupancy framework to subsample the population with parameters that mimic combining multiple independent monitoring efforts which vary annually in location, and effort. Regardless of spatial consistency of annual sampling, there was minimal variation in statistical power under both high and low detection probability simulations. However, when sampling effort varied each year, statistical power was lower for most populations and sampling scenarios when compared to consistent sampling effort unless some baseline level of sampling effort was reliably achieved in all years. In many cases, adding low-level consistent baseline sampling to variable surveys resulted in statistical power close to that of consistent sampling efforts. Our results suggest statistical power is driven by annual consistency in the proportion of landscape sampled rather than spatial consistency in sampling locations. This result indicates that current variable surveys could be leveraged and combined to detect population declines for at-risk species at broad-scales if a baseline proportion of landscape is robustly sampled. The level of baseline sampling is highly dependent on population size and magnitudes of population change. In simulations with a common or abundant population experiencing a rapid decline, a baseline survey effort of at least 5% of the landscape in combination with variable surveys resulted in statistical power consistently above the standard threshold of 0.80 for occupancy monitoring. Leveraging existing local efforts to achieve high detection probability and baseline sampling would reduce financial and logistical burdens of broad-scale wildlife monitoring efforts.

Idaho, Montana↗
USGS2024

Climate-driven increases in stream metal concentrations in mineralized watersheds throughout the Colorado Rocky Mountains, USA

Increasing stream metal concentrations apparently caused by climate warming have been reported for a small number of mountain watersheds containing hydrothermally altered bedrock with abundant sulfide minerals (mineralized watersheds). Such increases are concerning and could negatively impact downstream ecosystem health, water resources, and mine-site remediation efforts. However, the pervasiveness and typical magnitude of these trends remain uncertain. We aggregated available streamwater chemistry data collected from late summer and fall over the past 40 years for 22 mineralized watersheds throughout the Colorado Rocky Mountains. Temporal trend analysis performed using the Regional Kendall Test indicates significant regional upward trends of ∼2% of the site median per year for sulfate, zinc, and copper concentrations in the 17 streams affected by acid rock drainage (ARD; median pH ≤ 5.5), equivalent to concentrations roughly doubling over the past 30 years. An examination of potential load trends utilizing streamflow data from eight “index gages” located near the sample sites provides strong support for regionally increasing sulfate and metal loads in ARD-affected streams, particularly at higher elevations. Declining streamflows are likely contributing to regionally increasing concentrations, but increasing loads appear to be on average an equal or greater contributor. Comparison of selected site characteristics with site concentration trend magnitudes shows the highest correlation for mean annual air temperature and mean elevation (R 2 of 0.42 and 0.35, respectively, with all others being ≤0.14). Future research on climate-driven controlling mechanisms should therefore focus on processes such as melting of frozen ground directly linked to site mean temperature and elevation.

Colorado↗
USGS2023

Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA

Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the predicted burn probabilities with decadal housing density. We then compared the predicted burn probabilities and risk across the study area with observed values and quantified trends. Finally, we evaluated how housing growth and changes in burn probability influenced risk individually and combined. Fires burned 9055 km 2 and exposed more than 8500 homes from 1990 to 2019. Observed burned area increased 632% from the 1990s to the 2000s, which combined with housing growth, resulted in a 1342% increase in homes exposed. Increases continued in the 2010s but at lower rates; burned area by 65% and exposure by 32%. The random forests model had excellent fit and high correlation with observations (AUC = 0.88 and r = 0.9). Observed values were within the 95% uncertainty interval for all years except 2016 (burned area) and 2000 (exposure). However, our model overpredicted in years with low observed burned area and underpredicted in years with high observed burned area. Overpredictions in risk resulted in lower rates of change in predicted risk compared with change in observed exposure. Increases in risk between the 1990s and 2000s were primarily due to warmer and drier weather conditions and secondarily because of housing growth. However, increases between the 2000s and 2010s were primarily due to housing growth. Our modeling approach identifies spatial and temporal patterns of wildfire potential and risk, which is critical information to guide decision-making. Because the drivers behind risk shift over time, strategies to mitigate risk may need to account for multiple drivers simultaneously.

Colorado, New Mexico, Wyoming↗
USGS2022

Black carbon dominated dust in recent radiative forcing on Rocky Mountain snowpacks

The vast majority of surface water resources in the semi-arid western United States start as winter snowpack. Solar radiation is a primary driver of snowmelt, making snowpack water resources especially sensitive to even small increases in concentrations of light absorbing particles such as mineral dust and combustion-related black carbon (BC). Here we show, using fresh snow measurements and snowpack modeling at 51 widely distributed sites in the Rocky Mountain region, that BC dominated impurity-driven radiative forcing in 2018. BC contributed three times more radiative forcing on average than dust, and up to 17 times more at individual locations. Evaluation of 2015 to 2018 archived samples from most of the same sites yielded similar results. These findings, together with long-term observations of atmospheric concentrations and atmospheric model studies, indicate that BC rather than dust has dominated radiative forcing by light absorbing impurities on snow for decades, indicating that mitigation strategies to reduce radiative forcing on headwater snow-water resources would need to focus on reducing winter and spring BC emissions.

Colorado, Idaho, Montana, New Mexico, Utah, Wyomin↗
USGS2021

Evidence of glacial activity during MIS 4 in the Rocky Mountains, Colorado, USA

The Ziegler Reservoir fossil site near Snowmass Village, Colorado, provides a rare opportunity to examine environmental conditions in the Rocky Mountains during marine isotope stage (MIS) 4 (71–57 ka). Although recognized as a global-scale cold event, MIS 4 is typically absent from Rocky Mountain glacial chronologies because the geologic evidence was covered or destroyed during the subsequent, and more extensive, MIS 2 (Pinedale; 29–14 ka) glaciation. Ziegler Reservoir lies beyond the Pinedale glacial extent, which allowed for the preservation of a long-lived sequence of eolian sediments deposited in a lacustrine environment that spans from late MIS 6 (ca. 140 ka) through early MIS 3 (ca. 55 ka). Sediments dating to MIS 4 exhibit a significant increase in clay-sized particles, suggesting that the source areas, most likely nearby glacio-fluvial deposits, were enriched with fine-grained material at that time. We hypothesize that the elevated clay content was the result of rock flour production by nearby valley glaciers that were active in the Rocky Mountains during MIS 4. The results of our study illustrate how recognizing indirect evidence of glacial activity can result in a more complete record of past climate conditions than what could be achieved by the study of moraines alone.

Colorado↗
USGS2021

Integrating observations and models to determine the effect of seasonally frozen ground on hydrologic partitioning in alpine hillslopes in the Colorado Rocky Mountains, USA

This study integrated spatially distributed field observations and soil thermal models to constrain the impact of frozen ground on snowmelt partitioning and streamflow generation in an alpine catchment within the Niwot Ridge Long-Term Ecological Research site, Colorado, USA. The study area was comprised of two contrasting hillslopes with notable differences in topography, snow depth and plant community composition. Time-lapse electrical resistivity surveys and soil thermal models enabled extension of discrete soil moisture and temperature measurements to incorporate landscape variability at scales and depths not possible with point measurements alone. Specifically, heterogenous snowpack thickness (~0–4 m) and soil volumetric water content between hillslopes (~0.1–0.45) strongly influenced the depths of seasonal frost, and the antecedent soil moisture available to form pore ice prior to freezing. Variable frost depths and antecedent soil moisture conditions were expected to create a patchwork of differing snowmelt infiltration rates and flowpaths. However, spikes in soil temperature and volumetric water content, as well as decreases in subsurface electrical resistivity revealed snowmelt infiltration across both hillslopes that coincided with initial decreases in snow water equivalent and early increases in streamflow. Soil temperature, soil moisture and electrical resistivity data from both wet and dry hillslopes showed that initial increases in streamflow occurred prior to deep soil water flux. Temporal lags between snowmelt infiltration and deeper percolation suggested that the lateral movement of water through the unsaturated zone was an important driver of early streamflow generation. These findings provide the type of process-based information needed to bridge gaps in scale and populate physically based cryohydrologic models to investigate subsurface hydrology and biogeochemical transport in soils that freeze seasonally.

Colorado↗
USGS2018

A landscape-level assessment of whitebark pine regeneration in the Rocky Mountains, USA

Whitebark pine (Pinus albicaulis Engelm.) has recently experienced high mortality due to multiple stressors, and future population viability may rely on natural regeneration. We assessed whitebark pine seedling densities throughout the US Rocky Mountains and identified stand, site, and climatic variables related to seedling presence based on data from 1,217 USDA Forest Service Forest Inventory and Analysis plots. Although mean densities were highest in the whitebark pine forest type, 83% of sites with seedlings present occurred in non-whitebark pine forest types, and the highest densities occurred in the lodgepole pine forest type. To identify factors related to whitebark pine seedling presence, we compared the results generated from three statistical models: logistic regression, classification tree, and random forests. All three models identified cover of grouse whortleberry (Vaccinium scoparium Leiberg ex Coville) as an important predictor, two models distinguished live and dead whitebark pine basal area and elevation, and one model recognized seasonal temperature. None of the models identified forest type as an important predictor. Understanding these factors may help managers identify areas where natural regeneration of whitebark pine is likely to occur, including sites in non-whitebark pine forest types.

Rocky Mountains↗
USGS2018

Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using nitrogen isotopes

Variation in source areas and source types of atmospheric nitrogen (N) deposition to high-elevation ecosystems in the Rocky Mountains were evaluated using spatially and temporally distributed N isotope data from atmospheric deposition networks for 1995-2016. This unique dataset links N in wet deposition and snowpack to mobile and stationary emissions sources, and enhances understanding of the impacts of anthropogenic activities and environmental policies that mitigate effects of accelerated N cycling across the Rocky Mountain region. δ 15 N−NO 3 − at 50 U.S. Geological Survey Rocky Mountain Snowpack (Snowpack) sites ranged from −3.3‰ to +6.5‰, with a mean value of +1.4‰. At 15 National Atmospheric Deposition Program (NADP)/National Trends Network wet deposition (NADP Wetfall) sites, summer δ 15 N−NO 3 − is significantly lower ranging from −7.6‰ to −1.3‰ while winter δ 15 N−NO 3 − ranges from −2.6‰ to +5.5‰, with a mean value of +0.7‰ during the cool season. The strong seasonal difference in NADP Wetfall δ 15 N−NO 3 − is due in part to variation in the proportion of N originating from source regions at different times of the year due to seasonal changes in weather patterns. Snowpack NO 3 − and δ 15 N−NO 3 − are significantly related to NADP Wetfall (fall and winter) suggesting that bulk snowpack samples provide a reliable estimate at high elevations. Spatial trends show higher NO 3 − concentrations and δ 15 N−NO 3 − in the Southern Rocky Mountains located near larger anthropogenic N emission sources compared to the Northern Rocky Mountains. NADP Wetfall δ 15 N−NH 4 + ranged from −10‰ to 0‰, with no observed spatial pattern. However, the lowest δ 15 N−NH 4 + (−9‰), and the highest NH 4 + concentration (35 μeq/L) were observed at a Utah site dominated by local agricultural activities, whereas the higher δ 15 N−NH 4 + observed in Colorado and Wyoming are likely due to mixed sources, including fossil fuel combustion and agricultural sources. These findings show spatial and seasonal variation in N isotope data that reflect differences in sources of anthropogenic N deposition to high-elevation ecosystems and have important implications for environmental policy across the Rocky Mountain region.

Rocky Mountains↗
USGS2018

It matters when you measure it: Using snow-cover Normalised Difference Vegetation Index (NDVI) to isolate post-fire conifer regeneration

Landsat Normalised Difference Vegetation Index (NDVI) is commonly used to monitor post-fire green-up; however, most studies do not distinguish new growth of conifer from deciduous or herbaceous species, despite potential consequences for local climate, carbon and wildlife. We found that dual season (growing and snow cover) NDVI improved our ability to distinguish conifer tree presence and density. We then examined the post-fire pattern (1984–2017) in Landsat NDVI for fires that occurred a minimum of 20 years ago (1986–1997). Points were classified into four categories depending on whether NDVI, 20 years post-fire, had returned to pre-fire values in only the growing season, only under snow cover, in both seasons or neither. We found that each category of points showed distinct patterns of NDVI change that could be used to characterise the average pre-fire and post-fire vegetation condition Of the points analysed, 43% showed a between-season disagreement if NDVI had returned to pre-fire values, suggesting that using dual-season NDVI can modify our interpretations of post-fire conditions. We also found an improved correlation between 5- and 20-year NDVI change under snow cover, potentially attributable to snow masking fast-growing herbaceous vegetation. This study suggests that snow-cover Landsat imagery can enhance characterisations of forest recovery following fire.

Arizona, Colorado, Idaho, Montana, Utah, Washingto↗
USGS2017

Magnetotelluric imaging of lower crustal melt and lithospheric hydration in the Rocky Mountain Front transition zone, Colorado, USA

We present an electrical resistivity model of the crust and upper mantle from two‐dimensional (2‐D) anisotropic inversion of magnetotelluric data collected along a 450 km transect of the Rio Grande rift, southern Rocky Mountains, and High Plains in Colorado, USA. Our model provides a window into the modern‐day lithosphere beneath the Rocky Mountain Front to depths in excess of 150 km. Two key features of the 2‐D resistivity model are (1) a broad zone (~200 km wide) of enhanced electrical conductivity (<20 Ωm) in the midcrust to lower crust that is centered beneath the highest elevations of the southern Rocky Mountains and (2) hydrated lithospheric mantle beneath the Great Plains with water content in excess of 100 ppm. We interpret the high conductivity region of the lower crust as a zone of partially molten basalt and associated deep‐crustal fluids that is the result of recent (less than 10 Ma) tectonic activity in the region. The recent supply of volatiles and/or heat to the base of the crust in the late Cenozoic implies that modern‐day tectonic activity in the western United States extends to at least the western margin of the Great Plains. The transition from conductive to resistive upper mantle is caused by a gradient in lithospheric modification, likely including hydration of nominally anhydrous minerals, with maximum hydration occurring beneath the Rocky Mountain Front. This lithospheric “hydration front” has implications for the tectonic evolution of the continental interior and the mechanisms by which water infiltrates the lithosphere.

Colorado↗
USGS2017

Effects of climate change on forest vegetation in the northern Rockies

Increasing air temperature, through its influence on soil moisture, is expected to cause gradual changes in the abundance and distribution of tree, shrub, and grass species throughout the Northern Rockies, with drought tolerant species becoming more competitive. The earliest changes will be at ecotones between lifeforms (e.g., upper and lower treelines). Ecological disturbance, including wildfire and insect outbreaks, will be the primary facilitator of vegetation change, and future forest landscapes may be dominated by younger age classes and smaller trees. High-elevation forests will be especially vulnerable if disturbance frequency

Rocky Mountains↗