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At least 181 records · Page 10Linked to original sources

USGS2014

A Global Lake Ecological Observatory Network (GLEON) for synthesising high-frequency sensor data for validation of deterministic ecological models

A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process- based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

Inland Waters↗

USGS2021

Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19

Streambank erosion and reservoir sedimentation are primary concerns of resource managers in Kansas and throughout many regions of the United States and negatively affect flood control, water supply, and recreation. The Cottonwood and upper Neosho Rivers drain into John Redmond Reservoir, and since reservoir completion in 1964, there has been substantial conservation-pool sedimentation and storage loss in John Redmond Reservoir, causing storage capacity losses more rapidly than most other Federal reservoirs in Kansas. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office, has monitored water quality (temperature, specific conductance, and turbidity) on the Cottonwood River (upstream from the reservoir) and Neosho River (upstream and downstream from the reservoir) since 2007 with additional sites added in 2009. The purpose of this report is to quantify suspended-sediment concentrations, loads, and yields entering and exiting John Redmond Reservoir during January 1, 2010, through December 31, 2019. Three water-quality monitoring sites were upstream from the reservoir (Cottonwood River near Plymouth, Kansas [USGS site 07182250; hereinafter referred to as “Cottonwood”]; Neosho River at Burlingame Road near Emporia, Kans. [USGS site 07179750; hereinafter referred to as “Burlingame”]; and Neosho River at Neosho Rapids, Kans. [USGS site 07182390; hereinafter referred to as “Neosho Rapids”]), and one water-quality monitoring site was downstream from the reservoir (Neosho River at Burlington, Kans. [USGS site 07182510; hereinafter referred to as “Burlington”]). The Neosho Rapids streamgage is downstream from the confluence of the Cottonwood and upper Neosho Rivers and has a contributing drainage area accounting for 91 percent of the total contributing drainage area to John Redmond Reservoir. Continuously measured streamflow, water quality, and discrete water-quality data were used to develop updated regression models to compute suspended-sediment concentrations, loads, and yields upstream and downstream from John Redmond Reservoir in east-central Kansas. Several turbidity sensors were deployed during the analysis period, and there are no established relations between the sensors; therefore, individual models for each sensor were developed. Model statistics for the turbidity and suspended-sediment concentration linear regression models were better (based on the coefficient of determination, root mean square error, and model standard percentage error) than the streamflow and suspended-sediment concentration linear regression models, indicating better model performance. Computed concentrations, loads, and yields do not account for the ungaged 9 percent of the drainage basin downstream from the Neosho Rapids streamgage. Mean daily suspended-sediment loads upstream from the reservoir were largest at Neosho Rapids (2,250 tons), second largest at Cottonwood (2,180 tons), and smallest at Burlingame (624 tons). Streamflow at Burlington was predominately regulated by reservoir releases, and mean daily suspended-sediment loads were smaller (286 tons) than at upstream sites. Among the upstream sites, Cottonwood had the largest mean daily suspended-sediment concentration (179 milligrams per liter [mg/L]), followed by Neosho Rapids (162 mg/L), and Burlingame (108 mg/L). Burlington had the smallest mean daily suspended-sediment concentration of all sites (46 mg/L). Annual reservoir trapping efficiency ranged from 82 to 94 percent, and the largest sediment mass trapped was during 2019 (2,230,000 tons). Reservoir storage decreased an estimated 7,750 acre-feet during 2010 and 2014–19. Using the mean trapping efficiency to estimate suspended-sediment loads during years with missing data (2011–13), the total estimated reservoir storage lost to sedimentation for the analysis period (2010–19) was 8,690 acre-feet, about 17 percent of the remaining storage space reported in 2007. The mean annual sedimentation rate during the analysis period (747 acre-feet per year) was about 85 percent larger than the design sedimentation rate (404 acre-feet per year) originally projected during construction. Different reservoir outflow management strategies, including operating near normal capacity as opposed to higher flood pool levels, could reduce the total reservoir storage lost by 3 percent (about 261 acre-feet), which is equal to 14 percent of the total sediment removed during the dredging operation in 2016. During the study period, about 56 percent of the total suspended-sediment load was transported during streamflows greater than the National Weather Service flood action stage at the upstream sites (0.1–5 percent of the record; Cottonwood mean: 48 percent; Burlingame mean: 40 percent; Neosho Rapids mean: 78 percent). Disproportionately large sediment loads were delivered during short periods of time, and localized efforts of stream erosion protection (streambank stabilization, riparian buffers) were likely to be overwhelmed. Precipitation frequency and intensity are projected to continue to increase in this region; therefore, future sediment reduction strategies that account for extreme episodic events may be beneficial. Changes to reservoir outflow management could also minimize sediment accumulation while still preserving flood control. Continued investigation of sediment reduction measures is necessary for future mitigation with the understanding that sedimentation rate is largely driven by high flows. Results from this study can be used to calibrate sediment models, explore sediment reduction strategies, highlight the importance of continued water-quality monitoring to determine effectiveness and changes in sediment transport, and assess the ability of John Redmond Reservoir to support designated uses into the future.

Kansas↗

USGS2005

Supergene destruction of a hydrothermal replacement alunite deposit at Big Rock Candy Mountain, Utah: Mineralogy, spectroscopic remote sensing, stable-isotope, and argon-age evidences

Big Rock Candy Mountain is a prominent center of variegated altered volcanic rocks in west-central Utah. It consists of the eroded remnants of a hypogene alunite deposit that, at ∼21 Ma, replaced intermediate-composition lava flows. The alunite formed in steam-heated conditions above the upwelling limb of a convection cell that was one of at least six spaced at 3- to 4-km intervals around the margin of a monzonite stock. Big Rock Candy Mountain is horizontally zoned outward from an alunite core to respective kaolinite, dickite, and propylite envelopes. The altered rocks are also vertically zoned from a lower pyrite–propylite assemblage upward through assemblages successively dominated by hypogene alunite, jarosite, and hematite, to a flooded silica cap. This hydrothermal assemblage is undergoing natural destruction in a steep canyon downcut by the Sevier River in Marysvale Canyon. Integrated geological, mineralogical, spectroscopic remote sensing using AVIRIS data, Ar radiometric, and stable isotopic studies trace the hypogene origin and supergene destruction of the deposit and permit distinction of primary (hydrothermal) and secondary (weathering) processes. This destruction has led to the formation of widespread supergene gypsum in cross-cutting fractures and as surficial crusts, and to natrojarosite, that gives the mountain its buff coloration along ridges facing the canyon. A small spring, Lemonade Spring, with a pH of 2.6 and containing Ca, Mg, Si, Al, Fe, Mn, Cl, and SO 4 , also occurs near the bottom of the canyon. The 40 Ar/ 39 Ar age (21.32±0.07 Ma) of the alunite is similar to that for other replacement alunites at Marysvale. However, the age spectrum contains evidence of a 6.6-Ma thermal event that can be related to the tectonic activity responsible for the uplift that led to the downcutting of Big Rock Candy Mountain by the Sevier River. This ∼6.6 Ma event also is present in the age spectrum of supergene natrojarosite forming today, and probably dates the beginning of supergene alteration at Big Rock Candy Mountain. The δ 34 S value (11.9‰) of alunite is similar to those for replacement alunite from other deposits in the Marysvale volcanic field. The δ 34 S values of natrojarosite (0.7‰ to −1.2‰) are similar to those for aqueous sulfate in Lemonade Spring, but are larger than those in pyrite (0.4‰ to −4.7‰). The δ 34 S and δ 18 O SO 4 values of gypsum show an excellent correlation, with values ranging from 15.2‰ to −5.2‰ and 7‰ to −8.2‰, respectively. The stable-isotope data indicate that the aqueous sulfate for gypsum is a mixture derived from the dissolution of hypogene gypsum and alunite, and from the supergene oxidation of pyrite. The aqueous sulfate for the natrojarosite, however, is derived largely from the supergene oxidation of pyrite, with a minor contribution from the dissolution of alunite and gypsum. The exceptional detailed spectral mapping capabilities of AVIRIS led to the recognition of a small amount of jarosite that is probably the top of the steam-heated system that produced the primary hypogene alteration at Big Rock Candy Mountain.

Utah↗

USGS2016

Detection rates of geckos in visual surveys: Turning confounding variables into useful knowledge

Transect surveys without some means of estimating detection probabilities generate population size indices prone to bias because survey conditions differ in time and space. Knowing what causes such bias can help guide the collection of relevant survey covariates, correct the survey data, anticipate situations where bias might be unacceptably large, and elucidate the ecology of target species. We used negative binomial regression to evaluate confounding variables for gecko (primarily Hemidactylus frenatus and Lepidodactylus lugubris) counts on 220-m-long transects surveyed at night, primarily for snakes, on 9,475 occasions. Searchers differed in gecko detection rates by up to a factor of six. The worst and best headlamps differed by a factor of at least two. Strong winds had a negative effect potentially as large as those of searchers or headlamps. More geckos were seen during wet weather conditions, but the effect size was small. Compared with a detection nadir during waxing gibbous (nearly full) moons above the horizon, we saw 28% more geckos during waning crescent moons below the horizon. A sine function suggested that we saw 24% more geckos at the end of the wet season than at the end of the dry season. Fluctuations on a longer timescale also were verified. Disturbingly, corrected data exhibited strong short-term fluctuations that covariates apparently failed to capture. Although some biases can be addressed with measured covariates, others will be difficult to eliminate as a significant source of error in longterm monitoring programs.

Andersen Air Force Base↗

USGS2025

Flood-inundation maps for 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, 2023

Digital flood-inundation map libraries for two reaches that constitute 14.8 miles of Little and Big Papillion Creeks in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resource District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at Little Papillion Creek at Irvington, Nebr. (USGS station 06610750), Little Papillion Creek at Ak-Sar-Ben at Omaha, Nebr. (USGS station 06610765), and Big Papillion Creek at Q Street at Omaha, Nebr. (USGS station 06610770) streamgages. Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System database at https://doi.org/10.5066/F7P55KJN or from the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/ . Flood profiles were computed for two different reaches that constitute 14.8 miles of stream length in the study area by using hydraulic models. The models were calibrated by adjusting roughness coefficients to best represent the current (2022) stage-streamflow relation at the streamgages within the study reach. The hydraulic models were then used to compute water-surface profiles at 1-foot stage intervals for selected stage ranges to represent various flooding scenarios at the streamgages in each reach. The simulated water-surface profiles then were combined with a digital elevation model using a geographic information system, which had a 10-foot grid spacing to delineate the flooding extents and water depths for each stage. The availability of these flood-inundation maps, along with information regarding current stage from the USGS streamgages, can provide emergency management personnel and residents with information that is critical for flood response activities and post flood recovery efforts.

Nebraska↗

USGS2009

Continental-scale patterns in soil geochemistry and mineralogy: results from two transects across the United States and Canada

In 2004, the US Geological Survey (USGS) and the Geological Survey of Canada (GSC) initiated a pilot study that involved collection of more than 1500 soil samples from 221 sites along two continental transects across Canada and the United States. The pilot study was designed to test and refine protocols for a soil geochemical survey of North America. The two transects crossed a wide array of soil parent materials, soil ages, climatic conditions, landforms, land covers and land uses. Sample sites were selected randomly at approximately 40-km intervals from a population defined as all soils of the continent. At each site, soils representing 0 to 5 cm depth, and the O, A, and C horizons, if present, were collected and analyzed for their near-total content of over 40 major and trace elements. Soils from 0–5 cm depth were also collected for analysis of organic compounds. Results from the transects confirm that soil samples collected at a 40-km spacing reveal coherent, continental- to subcontinental-scale geochemical and mineralogical patterns that can be correlated to aspects of underlying soil parent material, soil age and climate influence. The geochemical data also demonstrate that at the continental-scale the dominance of any of these major factors that control soil geochemistry can change across the landscape. Along both transects, soil mineralogy and geochemistry change abruptly with changes in soil parent materials. However, the chemical influence of a soil’s parent material can be obscured by changing climatic conditions. For the transects, increasing precipitation from west to east and increasing temperature from north to south affect both soil mineralogy and geochemistry because of climate effects on soil weathering and leaching, and plant productivity. Regional anomalous metal concentrations can be linked to natural variations in soil parent materials, such as high Ni and Cr in soils developed on ultramafic rocks in California or high P in soils formed on weathered Ordovician limestones in central Kentucky. On local scales, anomalous metal concentrations recognized in soil profiles, such as high P in soils from animal confinement sites, are consistent with local anthropogenic disturbances. At a larger scale, the distribution of Hg across the west to east transect demonstrates that it can be difficult to distinguish between natural or anthropogenic contributions and that many factors can contribute to an element’s spatial distribution. Only three samples in a subset of seventy-three 0–5 cm depth soil samples from the north to south transect had organochlorine pesticides values above the method detection limit, apparently related to historic usage of the pesticides DDT and dieldrin.

Applied Geochemistry↗

USGS2010

The thermal signature of volcanic eruptions on Io and Earth,

We investigate a spectrum-based technique to identify the style of active volcanic eruptions on Jupiter's moon Io. Thermal remote sensing of Io has had to rely primarily on low-spatial-resolution data, similar to low-spatial-resolution satellite data applied to detecting and charting the temporal evolution of terrestrial hot spots. These terrestrial analyses use data from sensors designed to monitor the weather and sea surface temperature. On Io, such low-spatial-resolution data are used to classify eruption styles (modes of emplacement) by means of several criteria related to the temporal evolution of the infrared spectrum associated with the eruptive activity at each hot spot, which we term “thermal signature.” We find that the ratio of the emission at 2 and 5 µm, and how this ratio changes with time, is often diagnostic of eruption style, even in low-spatial-resolution data. Tests using thermal data for terrestrial “ground truth” cases show that our classification system is valid on Earth. The results of our analysis can be used to aid in the design of future space-based instruments that can be used for volcano monitoring on Io, as well as Earth.

Journal of Volcanology and Geothermal Research↗

USGS2024

Predictive understanding of stream salinization in a developed watershed using machine learning

Stream salinization is a global issue, yet few models can provide reliable salinity estimates for unmonitored locations at the time scales required for ecological exposure assessments. Machine learning approaches are presented that use spatially limited high-frequency monitoring and spatially distributed discrete samples to estimate the daily stream-specific conductance across a watershed. We compare the predictive performance of space- and time-unaware Random Forest models and space- and time-aware Recurrent Graph Convolution Neural Network models (KGE: 0.67 and 0.64, respectively) and use explainable artificial intelligence methods to interpret model predictions and understand salinization drivers. These models are applied to the Delaware River Basin, a developed watershed with diverse land uses that experiences anthropogenic salinization from winter deicer applications. These models capture seasonality for the winter first flush of deicers, and the streams with elevated predictions correspond well with indicators of deicer application. This result suggests that these models can be used to identify potential salinity-impaired streams for winter best management practices. Daily salinity predictions are driven primarily by land cover (urbanization) trends that may represent anthropogenic salinization processes and weather at time scales up to three months. Such modeling approaches are likely transferable to other watersheds and can be applied to further understand salinization risks and drivers.

Environmental Science and Technology↗

USGS2022

Towards real-time probabilistic ash deposition forecasting for New Zealand

Volcanic ashfall forecasts are highly dependent on eruption source parameters (ESPs) and synoptic weather conditions at the time and location of the eruption. In New Zealand, MetService and GNS Science have been jointly developing an ashfall forecast system that incorporates four-dimensional high-resolution numerical weather prediction (NWP) and ESPs into the HYSPLIT model, a state-of-the art hybrid Eulerian and Lagrangian dispersion model widely used for volcanic ash. However, these forecasts are based on discrete ESPs combined with a deterministic weather forecast and thus provide no information on output uncertainty. This shortcoming hinders stakeholder decision making, particularly near the geographical margin of forecasted ashfall and in areas with large gradients in forecasted ash deposition. Our study presents a new approach that incorporates uncertainty from both eruptive and meteorological inputs to deliver uncertainty in the model output. To this end, we developed probability density functions (PDFs) for three key ESPs (plume height, mass eruption rate, eruption duration) tailored to New Zealand’s volcanoes and combine them with NWP ensemble datasets to generate probabilistic ashfall forecasts using the HYSPLIT model. We show that the Latin Hypercube Sampling (LHS) technique can be used to representatively span this four-dimensional parameter space and allow us to add uncertainty quantification to rapid response forecast systems. For a case study of a hypothetical eruption at Tongariro, New Zealand we suggest that large parts of New Zealand’s North Island would not receive adequate warning for potential ashfall if uncertainties were not included in the forecasts. We also propose new probabilistic summary products to support public information and emergency responders decision making.

Journal of Applied Volcanology↗

USGS2011

Comparing the role of fuel breaks across southern California national forests

Fuel treatment of wildland vegetation is the primary approach advocated for mitigating fire risk at the wildland–urban interface (WUI), but little systematic research has been conducted to understand what role fuel treatments play in controlling large fires, which factors influence this role, or how the role of fuel treatments may vary over space and time. We assembled a spatial database of fuel breaks and fires from the last 30 years in four southern California national forests to better understand which factors are consistently important for fuel breaks in the control of large fires. We also explored which landscape features influence where fires and fuel breaks are most likely to intersect. The relative importance of significant factors explaining fuel break outcome and number of fire and fuel break intersections varied among the forests, which reflects high levels of regional landscape diversity. Nevertheless, several factors were consistently important across all the forests. In general, fuel breaks played an important role in controlling large fires only when they facilitated fire management, primarily by providing access for firefighting activities. Fire weather and fuel break maintenance were also consistently important. Models and maps predicting where fuel breaks and fires are most likely to intersect performed well in the regions where the models were developed, but these models did not extend well to other regions, reflecting how the environmental controls of fire regimes vary even within a single ecoregion. Nevertheless, similar mapping methods could be adopted in different landscapes to help with strategic location of fuel breaks. Strategic location of fuel breaks should also account for access points near communities, where fire protection is most important.

California↗

USGS2022

Alabama and Landsat

Alabama’s warm climate and rich soil bolster its agriculture and timber industries, but they also offer ideal conditions for natural playgrounds, enjoyed by humans and the wildlife that call the open green spaces home. Alabama has 21 State parks and 11 national parks, monuments, and trails across its diverse geography. Cotton is no longer king in the Cotton State, but it remains a part of the fabric of its multibillion-dollar agriculture sector. The State also produces poultry, cattle, calves, corn, lumber, soybeans, and catfish. The State is home to Dauphin Island, the first land mass seen by migratory birds and pollinators upon their return from South America. Dauphin Island acts as a landing zone for hundreds of species, including sandpipers, plovers, and herons, and protects Alabama’s coastline. Since 1961, Dauphin Island has been the home of the Audubon Bird Sanctuary. The varied landscapes of the Cotton State face challenges from climate change, land change, and extreme weather. Satellite imagery from the U.S. Geological Survey Landsat Program can offer insight and understanding in these and other areas. Here are some ways Landsat benefits Alabama.

Alabama↗

USGS2009

GRS evidence and the possibility of paleooceans on Mars

The Gamma Ray Spectrometer (Mars Odyssey spacecraft) has revealed elemental distributions of potassium (K), thorium (Th), and iron (Fe) on Mars that require fractionation of K (and possibly Th and Fe) consistent with aqueous activity. This includes weathering, evolution of soils, and transport, sorting, and deposition, as well as with the location of first-order geomorphological demarcations identified as possible paleoocean boundaries. The element abundances occur in patterns consistent with weathering in situ and possible presence of relict or exhumed paleosols, deposition of weathered materials (salts and clastic minerals), and weathering/transport under neutral to acidic brines. The abundances are explained by hydrogeology consistent with the possibly overlapping alternatives of paleooceans and/or heterogeneous rock compositions from diverse provenances (e.g., differing igneous compositions). ?? 2008 Elsevier Ltd.

Planetary and Space Science↗

USGS2025

Home range, seasonality, and the importance of canopy cover for Texas Tortoises (Gopherus berlandieri)

Texas Tortoises ( Gopherus berlandieri ) are understudied compared to federally protected congeners. Despite important early studies on the basic ecology of G. berlandieri , quantitative identification of habitat associations with specific environmental conditions has been limited. Gopherus berlandieri inhabits Tamaulipan thornscrub across its range, and coastal populations are historically associated with low-relief clay ridges with thick mesquital scrub surrounded by salt prairie grasslands. Our study examined tortoise home range size and association with canopy cover and potential ground moisture at a protected natural area in Cameron County, TX, USA. Twelve tortoises were outfitted with GPS loggers that recorded location once an hour from March 2020 to March 2022. To delineate home ranges, we estimated utilization distributions (UDs) for tortoises as autocorrelated kernel density estimates (AKDEs) at low-use (95%) and core-use (50%) levels for each tortoise. UDs were estimated for the entire study period and during seasons of sustained heat or cold to determine if tortoises used space differently across these seasons over the study period. Applying a use-availability study design, we compared canopy cover and potential mesic ground condition (i.e., precipitation flow accumulation) within each tortoise's UD (“use”) to the area within 1 day's movement around the boundary of the UD (“available”). Tortoise UD sizes were significantly different across seasons for low-use (95%) but not for core-use (50%) AKDE levels. Tortoise UDs had greater canopy cover compared to available-but-unused areas at both AKDE levels. Potential mesic ground condition did not significantly differ between available and used areas. Our study revealed that tortoises vary the size of their home ranges throughout the year, whereas areas of intensive use or occupation tended to remain remarkably stable throughout the year. In seasons of extreme weather (hot or cold), tortoises seem to seek out areas of denser canopy cover that likely serve as thermal refugia. Based on our results, effective habitat identification may best be served by ensuring that canopy cover is at least equivalent to the values reported here to ensure sufficient refugia during extreme seasonal temperatures.

Texas↗

USGS1979

Sand dunes on the central Delmarva Peninsula, Maryland and Delaware

Inconspicuous ancient sand dunes are present in parts of the central Delmarva Peninsula, Maryland and Delaware. Many dunes are roughly V-shaped, built by northwest winds, especially on the east sides of some of the large rivers. On the uplands, the form and spacing of the dunes are variable. A surficial blanket composed mainly of medium and fine-grained sand-the Parsonsburg Sand-forms both the ancient dunes and the broad plains between the dunes. The sand that forms the dunes is massive and intensely burrowed in the upper part; traces of horizontal or slightly inclined bedding appear near the base. Quartz is the dominant mineral constituent of the sand. Microline is abundant in the very fine to fine sand fraction. The heavy-mineral assemblages (high zircon, tourmaline, rutile) are more mature than in most of the possible source rocks. The most abundant minerals in the clay-sized fraction are dioctahedral vermiculite, kaolinite, illite, montmorillonite, and gibbsite. The first four minerals are common in deposits of late Wisconsin and Holocene age. The gibbsite may be detrital, coming from weathered rocks of Tertiary age. The soil profile in the dune sand is weakly to moderately developed. At or near the base of the Parsonsburg Sand are peaty beds that range in age from about 30,000 to about 13,000 radiocarbon years B.P. Microfloral assemblages in the peaty beds suggest that the dunes on the uplands formed in a spruce parkland during the late Wisconsin glacial maximum. The river dunes may also be of late Wisconsin age, but could be Holocene.

Professional Paper↗

USGS2020

Investigation of suitable habitat for the endangered plant Ptilimnium nodosum (Rose) Mathias (harperella) using remote sensing and field analysis—Documentation of methods and results

Ptilimnium nodosum (Rose) Mathias (harperella) is an endangered plant species found in Maryland, Virginia, and West Virginia, as well as in other locations throughout the southeastern United States. The narrow range of habitat characteristics for areas in which harperella has been found makes locating potential occurrence sites difficult and attempts at reintroduction of the plant relatively unsuccessful. Sightings of harperella have been made along the banks and in-channel bars of the Potomac River, along the Chesapeake and Ohio Canal National Historic Park, and within the Sideling Hill Wildlife Refuge near Hancock, Md. The large area covered by these sightings presents logistical challenges for repeat studies of harperella growth within the Park and in nearby areas. This study developed a geospatial method for characterizing harperella habitat through remote sensing, geospatial analysis, and field investigation. A geospatial prediction model was developed to model the habitat characteristics discussed in literature and found at harperella field observation sites in order to narrow the potential area for observation of the plant and its habitat. Analysis of historical aerial imagery was conducted within the space of the Potomac River to observe the persistence and flooding conditions of in-channel bars. The products of the geospatial prediction model and the historical aerial image analysis are a geospatial description of where harperella habitat is most likely to be found, as well as a map of in-channel bar locations and their persistence through time. From these two analyses, areas were identified that merited detailed observation. Very high resolution, unmanned aerial systems imagery was collected for 10 sites within this area in the Potomac River in June 2019. Unmanned aerial systems imagery has the potential to greatly improve detailed study of the harperella plant, as it provides the spatial resolution necessary to catalog detailed vegetation conditions (and potentially species identification). More importantly, the timing of imagery collection can be aligned carefully with the plant’s phenological patterns and local weather conditions to maximize cost-effectiveness of repeated imaging for specific areas.

Maryland, Virginia↗

USGS2013

The stability of sulfate and hydrated sulfate minerals near ambient conditions and their significance in environmental and planetary sciences

Sulfate and hydrated sulfate minerals are abundant and ubiquitous on the surface of the Earth and also on other planets and their satellites. The humidity-buffer technique has been applied to study the stability of some of these minerals at 0.1 MPa in terms of temperature-relative humidity space on the basis of hydration-dehydration reversal experiments. Updated phase relations in the binary system MgSO 4 -H 2 O are presented, as an example, to show how reliable thermodynamic data for these minerals could be obtained based on these experimental results and thermodynamic principles. This approach has been applied to sulfate and hydrated sulfate minerals of other metals, including Fe (both ferrous and ferric), Zn, Ni, Co, Cd, and Cu. Metal-sulfate salts play important roles in the cycling of metals and sulfate in terrestrial systems, and the number of phases extends well beyond the simple sulfate salts that have thus far been investigated experimentally. The oxidation of sulfide minerals, particularly pyrite, is a common process that initiates the formation of efflorescent metal-sulfate minerals. Also, the overall abundance of iron-bearing sulfate salts in nature reflects the fact that the weathering of pyrite or pyrrhotite is the ultimate source for many of these phases. Many aspects of their environmental significance are reviewed, particularly in acute effects to aquatic ecosystems related to the dissolution of sulfate salts during rain storms or snow-melt events. Hydrous Mg, Ca, and Fe sulfates were identified on Mars, with wide distribution and very large quantities at many locations, on the basis of spectroscopic observations from orbital remote sensing and surface explorations by rovers. However, many of these findings do not reveal the detailed information on the degree of hydration that is essential for rigorous interpretation of the hydrologic history of Mars. Laboratory experiments on stability fields, reactions pathways, and reaction rates of hydrous sulfates likely to be found on Mars enhance our understanding of the degrees of hydration of various sulfates that should currently exist on Mars at various seasons and locations and during various atmospheric pressure and obliquity periods. Two sets of systematic experiments were described; one on hydrous Mg sulfates and the other on hydrous Fe 3+ sulfates. Also, their implications to Mars sulfates mineralogy were discussed.

Journal of Asian Earth Sciences↗

USGS2021

Integrating ecological impacts: Perspectives on drought in the Upper Missouri Headwaters, Montana, United States

Drought is a complex challenge experienced in specific locations through diverse impacts, including ecological impacts. Different professionals involved in drought preparedness and response approach the problem from different points of view, which means they may or may not recognize ecological impacts. This study examines the extent to which interviewees perceive ecological drought in the Upper Missouri Headwaters basin in southwestern Montana. Through semistructured interviews, this research investigates individuals’ perceptions of drought by analyzing how they define drought, how they describe their roles related to drought, and the extent to which they emphasize ecological impacts of drought. Results suggest that while most interviewees have an integrated understanding of drought, they tend to emphasize either ecological or nonecological impacts of drought. This focus was termed their drought orientation. Next, the analysis considers how participants understand exposure to drought. Results indicate that participants view drought as a complex problem driven by both human and natural factors. Last, the paper explores understandings of the available solution space by examining interviewees’ views on adaptive capacity, particularly factors that facilitate or hinder the ability of the Upper Missouri Headwaters region to cope with drought. Participants emphasized that adaptive capacity is both helped and hindered by institutional, cultural, and economic factors, as well as by available information and past resource management practices. Understanding how interviewees perceive the challenges of drought can shape drought preparedness and response, allowing those designing programs to better align their efforts to the perceptions of their target audience.

Montana↗

USGS2023

Assessing snowpack stratigraphy accuracy based on different input data: Insights for operations avalanche forecasting

Avalanche forecasters and snow scientists use physically based snow stratigraphy models to fill spatial and temporal gaps in field-based snow profile observations. These models generate stratigraphy predictions using meteorological input from automated weather stations (AWS) or numerical weather prediction (NWP) models. The choice of input data is often determined by data availability or convenience instead of giving full consideration to the most appropriate source for a particular application. For example, while AWS may provide weather observations that better represent a particular site, they have large up-front costs and require specialized personnel to service and maintain. The goal of this study is to quantify the accuracy of snow stratigraphy produced by the SNOWPACK model driven by different input data, with a particular focus on cost-benefit analysis for operational avalanche forecasting. We generate modeled snow profiles at a field site in the Bridger Range of southwestern Montana, USA, using a) observations from an AWS at the field site and b) NWP output from the NOAA High-Resolution Rapid Refresh (HRRR) model. Validation data consist of a season-long time series of 10 manual snow profiles. We use dynamic time-warping (DTW) to quantify the overall and grain-type categorized similarities between modeled and in-situ observed profiles that are collocated in time and in space. Based on the similarity results, we present a cost-benefit analysis that considers the cost of installing and maintaining an AWS alongside the improved representation of snow depth, grain size, and weak layer types.

Montana↗