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At least 469 records · Page 26Linked to original sources
USGS1987

Inelastic properties of ice Ih at low temperatures and high pressures

The aim of our research programme is to explore the rheological behavior of H 2 O ices under conditions appropriate to the interiors of the icy satellites of the outer planets in order to give insight into their deformation. To this end, we have performed over 100 constant-strain-rate compression tests at pressures to 500 MPa and temperatures as low as 77 K. At P > 30 MPa, ice I h fails by a shear instability producing faults in the maximum shear stress orientation and failure strength typically is independent of pressure. This unusual faulting behavior is thought to be connected with phase transformations localized in the shear zones. The steady-state strength follows rheological laws of the thermally-activated power-law type, with different flow law parameters depending on the range of test temperatures. The flow laws will be discussed with reference to the operating deformation mechanisms as deduced from optical-scale microstructures and comparison with other work.

Journal de Physique Colloques↗
USGS2020

Latitudinal variation in snowshoe hare (Lepus americanus) body mass: A test of Bergmann’s Rule

The relationship between body size and latitude have been the focus of dozens of studies across many species. However, results of testing Bergmann’s Rule – that organisms in colder climates or at higher latitudes possess larger body sizes – have been inconsistent across studies. We investigated whether snowshoe hares (Lepus americanus) follow the Rule by investigating differences in body mass using data from six published studies and from data of 755 individual hares captured from ten populations across North America covering 26° of latitude. We also explored alternative hypotheses related to variation in hare body mass, including winter severity, length of growing season, elevation, and snow depth. We found body mass of hares varied throughout their range, but the drivers of body mass differed based on geographic location. Females in northern populations followed Bergmann’s rule, whereas males did not. In northern populations male mass was related to average snow depth. In contrast, in southern populations body mass of both sexes was related to length of the growing season. These differences likely represent variation in the drivers of selection. Specifically, in the north, a large body size is beneficial to conserve heat because of low winter temperatures, whereas in the south, it is likely due to increased food supply associated with longer growing seasons.

Canadian Journal of Zoology↗
USGS2014

Daytime avoidance of chemosensory alarm cues by adult sea lamprey ( Petromyzon marinus )

Sea lamprey ( Petromyzon marinus ) avoid damage-released and predator chemosensory cues at night, but their response to these cues during the day is unknown. Here, we explored (i) whether sea lamprey avoid these cues during the day and (ii) the effect of water temperature on the avoidance of chemosensory alarm cues in two diurnal laboratory experiments. We hypothesized that daytime activity would be temperature-dependent and that only sea lamprey vulnerable to predation (i.e., not hiding) would behaviourally respond to chemosensory alarm cues. Ten groups of ten sea lamprey were exposed to one of a variety of potential chemosensory cues. The experiments were conducted over a range of temperatures to quantify the effect of temperature on avoidance behaviour. Consistent with our hypothesis, a higher proportion of animals were active during daytime as water temperature increased. Moving sea lamprey showed an avoidance response to 2-phenylethylamine (a compound found in mammalian urine) and human saliva once water temperatures had risen to mean (±SD) = 13.7 (±1.4) °C. Resting and hiding sea lamprey did not show an avoidance response to any of the experimental stimuli.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗
USGS2008

Short-term response of methane fluxes and methanogen activity to water table and soil warming manipulations in an Alaskan peatland

Growing season CH 4 fluxes were monitored over a two year period following the start of ecosystem-scale manipulations of water table position and surface soil temperatures in a moderate rich fen in interior Alaska. The largest CH 4 fluxes occurred in plots that received both flooding (raised water table position) and soil warming, while the lowest fluxes occurred in unwarmed plots in the lowered water table treatment. A combination of treatment and soil hydroclimate variables explained more than 70% of the variation in ln-transformed CH 4 fluxes, with mean daily water table position representing the strongest predictor. We used quantitative PCR of the α -subunit of mcr operon to explore the influence of soil climate manipulations on methanogen abundances. Methanogen abundances were greatest in warmed plots, and showed a positive relationship with mean daily CH 4 fluxes. Our results show that water table manipulations that led to soil inundation (flooding) had a stronger effect on CH 4 fluxes than water table drawdown. Seasonal CH 4 fluxes increased by 80–300% under the combined wetter and warmer soil climate treatments. Thus, while warming is expected to increase CH 4 emissions from Alaskan wetlands, higher water table positions caused by increases in precipitation or disturbances such as permafrost thaw that lead to thermokarst and flooding in wetlands will stimulate CH 4 emissions beyond the effects of soil warming alone. Consequently, we argue that modeling the effects of climate change on Alaskan wetland CH 4 emissions needs to consider the interactive effects of soil warming and water table position on CH 4 production and transport.

Alaska↗
USGS2020

Why let the dogs out? Exploring variables associated with dog confinement and general characteristics of the free-ranging owned-dog population in a peri-urban area

Free-ranging dogs (FRDs), are a problem in several countries, with impacts on humans, domestic animals, and wildlife, although increasing evidence suggests that most FRDs are owned. Therefore, understanding dog ownership on a fine scale is critical. The main objectives of this study were to explore dog management in rural localities from central Chile focusing on modeling owner-related variables associated with dog confinement and characterize confined and FRDs populations. Interviews (170) were carried out in Paine municipality, reporting a human:dog ratio of 1.5:1, and dogs in most households (85.9%, 146/170). Thirty-seven percent (54/146) of those households did not confine their dog(s) to some degree, and 41% (196/472) of surveyed dogs were FRD. Based on multivariable logistic regression models, non-confinement was decreased by (i) negative opinion of owners toward roaming behavior of their dogs, (ii) negative opinion toward FRDs, among others. Dog confinement increased along with owners' concerns about the impacts of their dogs on others. Owned-FRDs tended to have poorer general care than confined dogs. Our findings represent a contribution to the understanding of the human dimensions behind FRDs and provide critical quantitative elements to consider when planning effective control strategies.

Journal of Applied Animal Welfare Science↗
USGS2003

Windows of opportunity: white-tailed deer and the dynamics of northern hardwood forests of the northeastern US

Herbivory, lighting regimes, and site conditions are among the most important determinants of forest regeneration success, but these are affected by a host of other factors such as weather, predation, human exploitation, pathogens, wind and fire. We draw together > 50 years of research on the Huntington Wildlife Forest in the central Adirondack Mountains of New York to explore regeneration of northern hardwoods. A series of studies each of which focused on a single factor failed to identify the cause of regeneration failure. However, integration of these studies led to broader understanding of the process of forest stand development and identified at least three interacting factors: lighting regime, competing vegetation and selective browsing by white-tailed deer (Odocoileus virginianus). The diverse 100-200 year-old hardwood stands present today probably reflect regeneration during periods of low deer density (< 2.0 deer/km super(2)) and significant forest disturbance. If this hypothesis is correct, forest managers can mimic these 'natural windows of opportunity' through manipulation of a few sensitive variables in the system. Further, these manipulations can be conducted on a relatively small geographic scale. Control of deer densities on a scale of 500 ha and understory American beech (Fagus grandifolia) on a scale of < 100 ha in conjunction with an even-aged regeneration system consistently resulted in successful establishment of desirable hardwood regeneration.

Journal for Nature Conservation↗
USGS2016

Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region

Viral haemorrhagic septicaemia virus (VHSV) genotype IVb has been responsible for large-scale fish mortality events in the Great Lakes of North America. Anticipating the areas of potential VHSV occurrence is key to designing epidemiological surveillance and disease prevention strategies in the Great Lakes basin. We explored the environmental features that could shape the distribution of VHSV, based on remote sensing and climate data via ecological niche modelling. Variables included temperature measured during the day and night, precipitation, vegetation, bathymetry, solar radiation and topographic wetness. VHSV occurrences were obtained from available reports of virus confirmation in laboratory facilities. We fit a Maxent model using VHSV-IVb reports and environmental variables under different parameterizations to identify the best model to determine potential VHSV occurrence based on environmental suitability. VHSV reports were generated from both passive and active surveillance. VHSV occurrences were most abundant near shore sites. We were, however, able to capture the environmental signature of VHSV based on the environmental variables employed in our model, allowing us to identify patterns of VHSV potential occurrence. Our findings suggest that VHSV is not at an ecological equilibrium and more areas could be affected, including areas not in close geographic proximity to past VHSV reports.

Great Lakes↗
USGS1990

Search path of a fossorial herbivore, Geomys bursarius , foraging in structurally complex plant communities

The influence of habitat patchiness and unpalatable plants on the search path of the plains pocket gopher ( Geomys bursarius ) was examined in outdoor enclosures. Separate experiments were used to evaluate how individual animals explored (by tunnel excavation) enclosures free of plants except for one or more dense patches of a palatable plant ( Daucus carota ), a dense patch of an unpalatable species ( Pastinaca sativa ) containing a few palatable plants ( D. carota ), or a relatively sparse mixture of palatable ( D. carota ) and unpalatable ( Raphanus sativus ) species. Only two of eight individuals tested showed the predicted pattern of concentrating search effort in patches of palatable plants. The maintenance of relatively high levels of effort in less profitable sites may reflect the security afforded food resources by the solitary social system and fossorial lifestyle of G. bursarius . Unpalatable plants repelled animals under some conditions, but search paths in the sparsely planted mixed-species treatment suggest animals can use visual or other cues to orient excavations. Evidence supporting area-restricted search was weak. More information about the use of visual cues by G. bursarius and the influence of experience on individual search mode is needed for refining current models of foraging behavior in this species.

Journal of Mammalogy↗
USGS2014

Vegetation dynamics after spring and summer fires in red and white pine stands at Voyageurs National Park

Conducting dormant season or springtime prescribed fire treatments has become a common practice in many regions of the United States to restore ecosystems to their natural state. Despite the knowledge that historically, fires often occurred during the summer, the application of summer burns has been deterred, in part, by a lack of understanding of fire season effects on vegetation. We explored the differences in fire effects between spring and summer burns at Voyageurs National Park, Minnesota. The fire season effects on the ground layer vegetation were clearly different among the treatments: pre-burn, spring, and summer. Vegetation composition of pre-burn and after spring fires was similar, but differed significantly from the summer fires. Spring fires propagated the same species that were present prior to the fire, whereas summer fires promoted a new suite of species through the germination of seedbank and high seed dispersal species. Cover and richness of seed bank and intolerant species were greatest after the summer fires, which contributed to the peak in richness found across all reproductive and tolerance attributes five years after these fires. Post summer fire composition showed shifts in composition through time. Substantial differences in the effects of burn seasonality on ground layer vegetation should be considered in long term restoration efforts to help maintain species diversity in red and white pine forest ecosystems.

Minnesota↗
USGS2010

Exploring the limits of identifying sub-pixel thermal features using ASTER TIR data

Understanding the characteristics of volcanic thermal emissions and how they change with time is important for forecasting and monitoring volcanic activity and potential hazards. Satellite instruments view volcanic thermal features across the globe at various temporal and spatial resolutions. Thermal features that may be a precursor to a major eruption, or indicative of important changes in an on-going eruption can be subtle, making them challenging to reliably identify with satellite instruments. The goal of this study was to explore the limits of the types and magnitudes of thermal anomalies that could be detected using satellite thermal infrared (TIR) data. Specifically, the characterization of sub-pixel thermal features with a wide range of temperatures is considered using ASTER multispectral TIR data. First, theoretical calculations were made to define a “thermal mixing detection threshold” for ASTER, which quantifies the limits of ASTER's ability to resolve sub-pixel thermal mixing over a range of hot target temperatures and % pixel areas. Then, ASTER TIR data were used to model sub-pixel thermal features at the Yellowstone National Park geothermal area (hot spring pools with temperatures from 40 to 90 °C) and at Mount Erebus Volcano, Antarctica (an active lava lake with temperatures from 200 to 800 °C). Finally, various sources of uncertainty in sub-pixel thermal calculations were quantified for these empirical measurements, including pixel resampling, atmospheric correction, and background temperature and emissivity assumptions.

Journal of Volcanology and Geothermal Research↗
USGS2012

Modeling thermal dynamics of active layer soils and near-surface permafrost using a fully coupled water and heat transport model

Thawing and freezing processes are key components in permafrost dynamics, and these processes play an important role in regulating the hydrological and carbon cycles in the northern high latitudes. In the present study, we apply a well-developed soil thermal model that fully couples heat and water transport, to simulate the thawing and freezing processes at daily time steps across multiple sites that vary with vegetation cover, disturbance history, and climate. The model performance was evaluated by comparing modeled and measured soil temperatures at different depths. We use the model to explore the influence of climate, fire disturbance, and topography (north- and south-facing slopes) on soil thermal dynamics. Modeled soil temperatures agree well with measured values for both boreal forest and tundra ecosystems at the site level. Combustion of organic-soil horizons during wildfire alters the surface energy balance and increases the downward heat flux through the soil profile, resulting in the warming and thawing of near-surface permafrost. A projection of 21st century permafrost dynamics indicates that as the climate warms, active layer thickness will likely increase to more than 3 meters in the boreal forest site and deeper than one meter in the tundra site. Results from this coupled heat-water modeling approach represent faster thaw rates than previously simulated in other studies. We conclude that the discussed soil thermal model is able to well simulate the permafrost dynamics and could be used as a tool to analyze the influence of climate change and wildfire disturbance on permafrost thawing.

Journal of Geophysical Research D: Atmospheres↗
USGS1998

Survey of vesicular-arbuscular mycorrhizae in lettuce production in relation to management and soil factors

The occurrence of vesicular-arbuscular mycorrhizae (VAM) root colonization and spore number in soil was assessed for 18 fields under intensive lettuce (Lactuca sativa L.) production in California during July and August of 1995. Data on management practices and soil characteristics were compiled for each field, and included a wide range of conditions. The relationship between these factors and the occurrence of VAM in these fields was explored with multivariate statistical analysis. VAM colonization of lettuce tended to decrease with the use of chemical inputs, such as pesticides and high amounts of P and N fertilizers. Addition of soil organic matter amendments, the occurrence of other host crops in the rotation, and soil carbon:phosphorus and carbon:nitrogen ratios, were positively associated with VAM colonization of lettuce roots. The number of VAM spores in soil was strongly correlated with the number of other host crops in the rotation, the occurrence of weed hosts and sampling date, but was more affected by general soil conditions than by management inputs. Higher total soil N, C and P, as well as CEC, were inversely related to soil spore number. A glasshouse study of the two primary lettuce types sampled in the field showed no significant differences in the extent of root colonization under similar growing conditions. The results of this study are compared with other studies on the effects of management and soil conditions on mycorrhizal occurrence in agriculture.

Journal of Agricultural Science↗
USGS2015

Coevolution of bed surface patchiness and channel morphology: 2. Numerical experiments

In gravel bed rivers, bed topography and the bed surface grain size distribution evolve simultaneously, but it is not clear how feedbacks between topography and grain sorting affect channel morphology. In this, the second of a pair of papers examining interactions between bed topography and bed surface sorting in gravel bed rivers, we use a two-dimensional morphodynamic model to perform numerical experiments designed to explore the coevolution of both free and forced bars and bed surface patches. Model runs were carried out on a computational grid simulating a 200 m long, 2.75 m wide, straight, rectangular channel, with an initially flat bed at a slope of 0.0137. Over five numerical experiments, we varied (a) whether an obstruction was present, (b) whether the sediment was a gravel mixture or a single size, and (c) whether the bed surface grain size feeds back on the hydraulic roughness field. Experiments with channel obstructions developed a train of alternate bars that became stationary and were connected to the obstruction. Freely migrating alternate bars formed in the experiments without channel obstructions. Simulations incorporating roughness feedbacks between the bed surface and flow field produced flatter, broader, and longer bars than simulations using constant roughness or uniform sediment. Our findings suggest that patches are not simply a by-product of bed topography, but they interact with the evolving bed and influence morphologic evolution.

Journal of Geophysical Research F: Earth Surface↗
USGS2016

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4–8. Training data were selected from map products of the U.S. Geological Survey’s Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening ‘‘Function of mask” (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2016

Deriving habitat models for northern long-eared bats from historical detection data: A case study using the Fernow Experimental Forest

The listing of the northern long-eared bat ( Myotis septentrionalis ) as federally threatened under the Endangered Species Act following severe population declines from white-nose syndrome presents considerable challenges to natural resource managers. Because the northern long-eared bat is a forest habitat generalist, development of effective conservation measures will depend on appropriate understanding of its habitat relationships at individual locations. However, severely reduced population sizes make gathering data for such models difficult. As a result, historical data may be essential in development of habitat models. To date, there has been little evaluation of how effective historical bat presence data, such as data derived from mist-net captures, acoustic detection, and day-roost locations, may be in developing habitat models, nor is it clear how models created using different data sources may differ. We explored this issue by creating presence probability models for the northern long-eared bat on the Fernow Experimental Forest in the central Appalachian Mountains of West Virginia using a historical, presence-only data set. Each presence data type produced outputs that were dissimilar but that still corresponded with known traits of the northern long-eared bat or are easily explained in the context of the particular data collection protocol. However, our results also highlight potential limitations of individual data types. For example, models from mist-net capture data only showed high probability of presence along the dendritic network of riparian areas, an obvious artifact of sampling methodology. Development of ecological niche and presence models for northern long-eared bat populations could be highly valuable for resource managers going forward with this species. We caution, however, that efforts to create such models should consider the substantial limitations of models derived from historical data, and address model assumptions.

West Virginia↗
USGS2020

Variations in community evacuation potential related to average return periods in probabilistic tsunami hazard analysis

Tsunami risk management requires strategies that can address multiple sources with different recurrence intervals, wave-arrival times, and inundation extents. Probabilistic tsunami hazard analysis (PTHA) provides a structured way to integrate multiple sources, including the uncertainties due to the natural variability and limited knowledge of sources. PTHA-based products relate to specific average return periods (ARP) and while there has been considerable attention paid to ARP choice for building codes, guidance on ARP choice to support evacuation planning and related land use is lacking. We use the State of California (USA) coastal communities as a case study to explore the use of geospatial analysis and pedestrian-evacuation modeling for comparing the societal implications of tsunamis based on evacuation areas that reflect inundation from 475-year, 975-year, and 2475-year ARPs. Results demonstrate that changes in PTHA ARP had a substantial effect on the number of tax-lot parcels in PTHA evacuation areas, but not on the primary land use of these parcels or which communities had the largest number of exposed parcels. Composite PTHA maps provided high-level insights on hazard exposure and identified dominant sources; however, disaggregated PTHA outputs that reflect single source parameters (e.g., wave-arrival time) were necessary to quantify evacuation potential from local and distant tsunamis. Framing changes in ARP assumption based on changes in the number, land-use type, and potential evacuation challenges of parcels in evacuation areas can provide valuable insight on the real-world implications of which ARP to use in land use or evacuation planning.

California↗
USGS2013

An approach for characterizing the distribution of shrubland ecosystem components as continuous fields as part of NLCD

Characterizing and quantifying distributions of shrubland ecosystem components is one of the major challenges for monitoring shrubland vegetation cover change across the United States. A new approach has been developed to quantify shrubland components as fractional products within National Land Cover Database (NLCD). This approach uses remote sensing data and regression tree models to estimate the fractional cover of shrubland ecosystem components. The approach consists of three major steps: field data collection, high resolution estimates of shrubland ecosystem components using WorldView-2 imagery, and coarse resolution estimates of these components across larger areas using Landsat imagery. This research seeks to explore this method to quantify shrubland ecosystem components as continuous fields in regions that contain wide-ranging shrubland ecosystems. Fractional cover of four shrubland ecosystem components, including bare ground, herbaceous, litter, and shrub, as well as shrub heights, were delineated in three ecological regions in Arizona, Florida, and Texas. Results show that estimates for most components have relatively small normalized root mean square errors and significant correlations with validation data in both Arizona and Texas. The distribution patterns of shrub height also show relatively high accuracies in these two areas. The fractional cover estimates of shrubland components, except for litter, are not well represented in the Florida site. The research results suggest that this method provides good potential to effectively characterize shrubland ecosystem conditions over perennial shrubland although it is less effective in transitional shrubland. The fractional cover of shrub components as continuous elements could offer valuable information to quantify biomass and help improve thematic land cover classification in arid and semiarid areas.

Arizona, Florida, Texas↗