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At least 1,405 records · Page 78Linked to original sources

USGS2015

Forecasting and evaluating patterns of energy development in southwestern Wyoming

The effects of future oil and natural gas development in southwestern Wyoming on wildlife populations are topical to conservation of the sagebrush steppe ecosystem. To aid in understanding these potential effects, the U.S. Geological Survey developed an Energy Footprint simulation model that forecasts the amount and pattern of energy development under different assumptions of development rates and well-drilling methods. The simulated disturbance patterns produced by the footprint model are used to assess the potential effects on wildlife habitat and populations. A goal of this modeling effort is to use measures of energy production (number of simulated wells), well-pad and road-surface disturbance, and potential effects on wildlife to identify build-out designs that minimize the physical and ecological footprint of energy development for different levels of energy production and development costs.

Wyoming↗

USGS2017

Mineralogical characterization of weathered outcrops as a tool for constraining water chemistry predictions during project planning

Weathered samples from naturally exposed outcrops of troctolite associated with a magmatic Ni-Cu sulphide deposit were characterized by synchrotron-based micro-X-ray fluorescence mapping (µ-XRF) and X-ray absorption spectroscopy (XAS), as well as by lab-based X-ray diffraction, electron microscopy, Raman spectroscopy and wet chemical methods. Metal mobility in weathered samples was assessed using a sequential leach procedure. Results are interpreted in the context of predictions for future mine water chemistry and used to refine the conceptual model for metal mobility following weathering of waste rock at a potential future mine site.

Conference Paper↗

USGS1986

Morphology and age of fault scarps in the Rio Grande Rift, south-central Colorado

Fault scarps in the Rio Grande rift of Colorado provide most of the evidence of paleoseismicity in the state, and are thus a major focus of assessments of earthquake hazards. Critical components of such assessments are the ages of past faulting events; age control is scarce and generally coarse for the Rio Grande rift in Colorado. Ages estimated from fault-scarp morphology are thus valuable, partly because they are directly related to the fault eVents, and partly for want of alternative methods. The processes responsible for scarp degradation are poorly understood and the many variables that affect the rates and relative importance of those processes limits the precision and accuracy of age estimates derived from scarp morphology. Both analytical and empirical methods are available for relating scarp degradation processes to scarp morphology and age. Diffusion-equation models that have been derived for scarp degradation are useful for their predictive value and for the insight they provide about the degradation processes. However, because of the limitations mentioned above and because of the multiple-event nature of the scarps in the Rio Grande rift, the simpler empirical approach involving the relation between scarp angle and the logarithm of scarp height is used here. The scarp-morphology data from the Rio Grande rift suggest that the youngest movements on all of the scarps examined occurred less than 15,000 years ago, with the exception of two scarps that are formed on lithologically dissimilar deposits. This age estimate is consistent with the observation that all of the scarps occur at least in part on deposits of Pinedale age. The scarp-morphology data suggest that some of the scarps are closer to 5,000 years than to 15,000 years in age; several of these scarps occur on deposits of early Holocene age and are associated with early Holocene radiocarbon dates. One scarp occurs on deposits with radiocarbon dates of only a few thousand years, although the morphology of this scarp is unusual for its age. Three scarps have morphologies that suggest that they may represent fault events younger than 5,000 years old. Although no corroboration is available, these scarps may represent some of the youngest fault movements in Colorado.

Colorado↗

USGS2016

Participatory modeling and structured decision making

Structured decision making (SDM) provides a framework for making sound decisions even when faced with uncertainty, and is a transparent, defensible, and replicable method used to understand complex problems. A hallmark of SDM is the explicit incorporation of values and science, which often includes participation from multiple stakeholders, helping to garner trust and ultimately result in a decision that is more likely to be implemented. The core steps in the SDM process are used to structure thinking about natural resources management choices, and include: (1) properly defining the problem and the decision context, (2) determining the objectives that help describe the aspirations of the decision maker, (3) devising management actions or alternatives that can achieve those objectives, (4) evaluating the outcomes or consequences of each alternative on each of the objectives, (5) evaluating trade-offs, and (6) implementing the decision. Participatory modeling for SDM includes engaging stakeholders in some or all of the steps of the SDM process listed above. In addition, participatory modeling often is crucial for creating qualitative and quantitative models of how the system works, providing data for these models, and eliciting expert opinion when data are unavailable. In these ways, SDM provides a framework for decision making in natural resources management that includes participation from stakeholder groups throughout the process, including the modeling phase.

Book chapter↗

USGS1989

Determination of sensible heat flux over sparse canopy using thermal infrared data

Surface temperatures, T s , were estimated for a natural vegetative surface in Owens Valley, California, with infrared thermometric observations collected from an aircraft. The region is quite arid and is composed primarily of bushes (∼30%) and bare soil (∼70%). Application of the bulk transfer equation for the estimation of sensible heat, H , gave unsatisfactory values when compared to Bowen ratio and eddy correlation methods over a particular site. This was attributed to the inability with existing data to properly evaluate the resistance to heat transfer, r ah . To obtain appropriate r ah -values the added resistance to heat transfer, kB −1 , was allowed to vary although there is both theoretical and experimental evidence that kB −1 for vegetative surfaces can be treated as constant. The present data indicate that for partial canopy cover under arid conditions kB −1 may be a function of T s measured radiometrically. The equation determining kB −1 was simplified and tested over another arid site with good results; however, this had a limited data set (i.e., 6 data points). The dimensionless kB −1 equation is simplified for use over full canopy cover and is shown to give satisfactory estimates of H over a fully-grown wheat crop.

Agricultural and Forest Meteorology↗

USGS1998

Fundamentals of isotope geochemistry

The dominant use of isotopes in catchment research in the last few decades has been to trace sources of waters and solutes. Generally, such data were evaluated with simple mixing models to determine how much was derived from either of the two (sometimes three) constant-composition sources. This chapter illustrates the environmental isotopes that are natural and anthropogenic isotopes whose wide distribution in the hydrosphere can assist in the solution of hydrogeochemical problems. Water isotopes often provide unambiguous information about residence times and relative contributions from different water sources, and these data can then be used to make hypotheses about water flowpaths. Solute isotopes can provide an alternative, independent isotopic method for determining the relative amounts of water flowing along various subsurface flowpaths. The isotopic and chemical compositions provides very detailed information about sources and reactions in shallow systems This integration of chemical and isotopic data with complex hydrologic models constitutes an important frontier of catchment research.

Book chapter↗

USGS2026

The influence of tree canopy cover data choices on urban ecosystem accounting

Because urban landscapes are heterogeneous, the methods and spatial resolution used to depict the land surface greatly influence the representation of urban features. Land cover products such as tree canopy cover (TCC) are particularly sensitive to the methodology and resolution used in their creation. Differences in TCC mapping have implications on the outcomes of ecosystem service (ES) models, including those underlying natural capital accounting. Here, we quantify the sensitivity of physical rainfall interception and local climate regulation ES models for 189 U.S. cities to TCC inputs from four TCC products: a) National Land Cover Database (NLCD), b) Enhanced NLCD TCC, c) aggregated city-specific composite, and d) global tree canopy height dataset. We find both city-level and aggregate differences in TCC estimates, from a 38% decrease to a 3% increase relative to an aggregated high-resolution product. These differences result in up to 3% overestimations and 27% underestimation of rainfall interception and 2–56% underestimation of local climate regulation ES. City size, population, and greenness in addition to climatic variation drove differences between TCC products, and this variation requires users to carefully consider the choice of input data for any planned analysis. Though high-resolution data can offer greater nuance and accuracy, more limited spatiotemporal availability can hinder their usefulness for long-term monitoring applications such as natural capital accounting. The differences found in this study provide valuable insights for making informed decisions on data inputs for use in urban ecosystem research and for contextualizing model outcomes.

Contiguous United States↗

USGS2003

Effects of spectrometer band pass, sampling, and signal‐to‐noise ratio on spectral identification using the Tetracorder algorithm

[1] Estimates of spectrometer band pass, sampling interval, and signal‐to‐noise ratio required for identification of pure minerals and plants were derived using reflectance spectra convolved to AVIRIS, HYDICE, MIVIS, VIMS, and other imaging spectrometers. For each spectral simulation, various levels of random noise were added to the reflectance spectra after convolution, and then each was analyzed with the Tetracorder spectral identification algorithm [ Clark et al. , 2003]. The outcome of each identification attempt was tabulated to provide an estimate of the signal‐to‐noise ratio at which a given percentage of the noisy spectra were identified correctly. Results show that spectral identification is most sensitive to the signal‐to‐noise ratio at narrow sampling interval values but is more sensitive to the sampling interval itself at broad sampling interval values because of spectral aliasing, a condition when absorption features of different materials can resemble one another. The band pass is less critical to spectral identification than the sampling interval or signal‐to‐noise ratio because broadening the band pass does not induce spectral aliasing. These conclusions are empirically corroborated by analysis of mineral maps of AVIRIS data collected at Cuprite, Nevada, between 1990 and 1995, a period during which the sensor signal‐to‐noise ratio increased up to sixfold. There are values of spectrometer sampling and band pass beyond which spectral identification of materials will require an abrupt increase in sensor signal‐to‐noise ratio due to the effects of spectral aliasing. Factors that control this threshold are the uniqueness of a material's diagnostic absorptions in terms of shape and wavelength isolation, and the spectral diversity of the materials found in nature and in the spectral library used for comparison. Array spectrometers provide the best data for identification when they critically sample spectra. The sampling interval should not be broadened to increase the signal‐to‐noise ratio in a photon‐noise‐limited system when high levels of accuracy are desired. It is possible, using this simulation method, to select optimum combinations of band‐pass, sampling interval, and signal‐to‐noise ratio values for a particular application that maximize identification accuracy and minimize the volume of imaging data.

Journal of Geophysical Research: Planets↗

USGS2026

Constructed value of information with iterative scoring and parametric uncertainty to identify management-relevant research priorities for a declining raptor species

Constructed value of information (CVoI) is an expert elicitation decision-analytic tool used to prioritize sources of uncertainty based on their potential to improve decision outcomes if resolved. Despite increased application of CVoI, the robustness of CVoI prioritization of sources of uncertainty relative to differences in expert elicitation and scoring methods has not been evaluated. We engaged a group of species experts in a decision-analytic process to elicit uncertainties, framed as alternative hypotheses, about current population declines of the American kestrel ( Falco sparverius ) in the United States. Participants scored 13 hypotheses across 3 CVoI criteria, which are defined as constructed scales. Rather than experts selecting a single score per criterion, we used a likelihood point method to incorporate parametric uncertainty in the scoring process, in which experts were given 100 points to distribute across possible score categories within the criterion-specific constructed scale. Experts provided scores over 2 scoring rounds, with an opportunity to review and discuss initial scores between rounds. We used a Shannon entropy calculation to quantify how evenly participants allotted their points. We used simulation to evaluate the robustness of our prioritization results relative to a scoring method in which participants selected a single score category for each criterion. Participants often spread their points across 2 adjacent scores, reflecting parametric uncertainty. For one third of the hypothesis-scoring round combinations, the prioritization results differed in approximately 50% of simulations. The highest scoring hypotheses related to how the use of artificial versus natural nest cavities affects fecundity or survival, whether winter roosting sites are a limiting factor for population growth, and whether gamebird habitat management may benefit kestrel populations. Our CVoI prioritization framework can be used to develop collaborative research that is directly relevant to a management decision and is an advance in eliciting more representative expert beliefs.

Conservation Biology↗

USGS2023

Connecting research and practice to enhance the evolutionary potential of species under climate change

Resource managers have rarely accounted for evolutionary dynamics in the design or implementation of climate change adaptation strategies. We brought the research and management communities together to identify challenges and opportunities for applying evidence from evolutionary science to support on-the-ground actions intended to enhance species' evolutionary potential. We amalgamated input from natural-resource practitioners and interdisciplinary scientists to identify information needs, current knowledge that can fill those needs, and future avenues for research. Three focal areas that can guide engagement include: (1) recognizing when to act, (2) understanding the feasibility of assessing evolutionary potential, and (3) identifying best management practices. Although researchers commonly propose using molecular methods to estimate genetic diversity and gene flow as key indicators of evolutionary potential, we offer guidance on several additional attributes (and their proxies) that may also guide decision-making, particularly in the absence of genetic data. Finally, we outline existing decision-making frameworks that can help managers compare alternative strategies for supporting evolutionary potential, with the goal of increasing the effective use of evolutionary information, particularly for species of conservation concern. We caution, however, that arguing over nuance can generate confusion; instead, dedicating increased focus on a decision-relevant evidence base may better lend itself to climate adaptation actions.

Conservation Science and Practice↗

USGS1996

Late Holocene alluvial geomorphology of the Virgin River in the Zion National Park area, southwest Utah

This study traces the geomorphic development of the alluvial valley of the Virgin River in the Zion National Park region of southwest Utah. The purpose is to identify, date, and interpret the patterns of erosion and deposition that formed the alluvial valley over the past 1,000 years. This information is a basis for understanding how the geomorphology of the alluvial valley changes under essentially natural flow conditions. Sediment in the alluvial valley is classified as mainstem or tributary in origin. Mainstem alluvium is the largest volumetrically; it is mainly light-colored sand derived from upstream sources that accumulated on now abandoned flood plains (or terraces) by overbank deposition. Tributary sediment is typically dark colored, coarse-grained sand or gravel transported to the alluvial valley by streamflow or debris flow. Tributary and mainstem sediment are interbedded near the margin of the valley, and the older deposits are truncated parallel to the river, suggesting that in time the river removes both its own deposits and those of tributaries. In the natural flow regimen, the river probably maintains a balance between erosion and deposition of mainstem and tributary deposits. Four terraces and the active channel and flood plain are widespread along the Virgin River; from oldest to youngest these are the prehistoric, settlement, historic, and modern terraces. Dating was done by archeologic context, tree-ring methods, historic documents, relocation of early photographs, and correlation with other streams on the southern Colorado Plateau. Results indicate that prehistoric deposition ended by about A.D. 1100–1200, deposition of the settlement alluvium was from about A.D. 1400–1880, development of the historic terrace was from after 1883 until 1926, deposition of the modern alluvium was from 1940–1980, and development of the active channel and flood plain was after about 1980. The principal deposits (prehistoric, settlement, and modern alluviums) are separated by two periods of stream entrenchment and channel widening referred to as the prehistoric and historic arroyo cutting, respectively. Erosional activity of roughly similar age occurred in most southern Colorado Plateau streams. The early erosion is not well dated in the study area, although regional relations suggest A.D. 1200–1400, if not somewhat earlier. Historic arroyo cutting began after 1883 in the study area and continued until around 1940 when deposition of the modern alluvium began. Both erosions affected the human population of the region. Although the dating is imprecise, the Anasazi probably abandoned the region during prehistoric arroyo cutting, partly because of adverse environmental conditions. Likewise, historic arroyo cutting caused major losses of property and economic hardship among Anglo settlers. Erosion and deposition were largely contemporaneous with variations in streamflow. Long-term streamflow of the Virgin River was estimated from calibration of annual tree growth with measured streamflow. Results indicate that erosion was during periods of unusually high streamflow and that deposition was during periods of relatively low streamflow. These relations are best illustrated by historic arroyo cutting and subsequent deposition of the modern alluvium. Precipitation and runoff immediately before and during historic arroyo cutting were the most unusual of the past 300 years; they varied from the driest immediately preceding erosion to the wettest during erosion. Deposition of the modern alluvium was during relatively low runoff after 1940. High runoff destabilizes the channel, enhancing flood erosion. Conversely, relatively low runoff increases channel stability, reducing the erosional effect of floods and enhancing flood plain deposition. Adjustments in the width and depth of the channel are frequent, even after relatively small, short-term variations of streamflow.

Utah↗

USGS1984

Statistical relations among earthquake magnitude, surface rupture length, and surface fault displacement

In order to refine correlations of surface-wave magnitude, fault rupture length at the ground surface, and fault displacement at the surface by including the uncertainties in these variables, the existing data were critically reviewed and a new data base was compiled. Earthquake magnitudes were redetermined as necessary to make them as consistent as possible with the Gutenberg methods and results, which make up much of the data base. Measurement errors were estimated for the three variables for 58 moderate to large shallow-focus earthquakes. Regression analyses were then made utilizing the estimated measurement errors. The regression analysis demonstrates that the relations among the variables magnitude, length, and displacement are stochastic in nature. The stochastic variance, introduced in part by incomplete surface expression of seismogenic faulting, variation in shear modulus, and regional factors, dominates the estimated measurement errors. Thus, it is appropriate to use ordinary least squares for the regression models, rather than regression models based upon an underlying deterministic relation in which the variance results primarily from measurement errors. Significant differences exist in correlations of certain combinations of length, displacement, and magnitude when events are grouped by fault type or by region, including attenuation regions delineated by Evernden and others. Estimates of the magnitude and the standard deviation of the magnitude of a prehistoric or future earthquake associated with a fault can be made by correlating M s with the logarithms of rupture length, fault displacement, or the product of length and displacement. Fault rupture area could be reliably estimated for about 20 of the events in the data set. Regression of M s on rupture area did not result in a marked improvement over regressions that did not involve rupture area. Because no subduction-zone earthquakes are included in this study, the reported results do not apply to such zones.

Bulletin of the Seismological Society of America↗

USGS2010

Alternative feeding strategies and potential disease transmission in Wisconsin white-tailed deer

We conducted experimental feeding using 3 feeding methods (pile, spread, trough) and 2 quantities (rationed, ad libitum) of shelled corn to compare deer activity and behavior with control sites and evaluate potential direct and indirect transmission of infectious disease in white-tailed deer (Odocoileus virginianus) in central Wisconsin, USA. Deer use was higher at 2 of the feeding sites than at natural feeding areas (P ??? 0.02). Deer spent a higher proportion of time (P < 0.01) feeding at pile (49%) and spread (61%) treatments than at natural feeding areas (36%). We found higher deer use for rationed than ad libitum feeding quantities and feeding intensity was greatest at rationed piles and lowest at ad libitum spreads. We also observed closer pairwise distances (???0.3 m) among deer when corn was provided in a trough relative to spread (P=0.03). Supplemental feeding poses risks for both direct and indirect disease transmission due to higher deer concentration and more intensive use relative to control areas. Concentrated feeding and contact among deer at feeding sites can also increase risk for disease transmission. Our results indicated that restrictions on feeding quantity would not mitigate the potential for disease transmission None of the feeding strategies we evaluated substantially reduced the potential risk for disease transmission and banning supplemental feeding to reduce transmission is warranted.

Journal of Wildlife Management↗

USGS1996

Using GIS and logistic regression to estimate agricultural chemical concentrations in rivers of the midwestern USA

Agricultural chemicals (herbicides, insecticides, other pesticides and fertilizers) in surface water may constitute a human health risk. Recent research on unregulated rivers in the midwestern USA documents that elevated concentrations of herbicides occur for 1-4 months following application in spring and early summer. In contrast, nitrate concentrations in unregulated rivers are elevated during the fall, winter and spring. Natural and anthropogenic variables of river drainage basins, such as soil permeability, the amount of agricultural chemicals applied or percentage of land planted in corn, affect agricultural chemical concentrations in rivers. Logistic regression (LGR) models are used to investigate relations between various drainage basin variables and the concentration of selected agricultural chemicals in rivers. The method is successful in contributing to the understanding of agricultural chemical concentration in rivers. Overall accuracies of the best LGR models, defined as the number of correct classifications divided by the number of attempted classifications, averaged about 66%.

IAHS-AISH Publication↗

USGS2000

Native plant revegetation manual for Denali National Park and Preserve

This manual describes methods to revegetate subarctic sites with native plants. The information is based on 20 years of research and revegetation projects in Denali National Park and Preserve and other Alaskan sites. The manual summarizes information about subarctic ecosystems and discusses using this information to evaluate disturbed sites and plan revegetation projects. Revegetation techniques addressed include promoting natural revegetation, legume and wheatgrass seeding, plant salvage and transplant, bioengineering, containergrown plants, alder seedlings, and willow cuttings. Long-term data for two specific vegetation projects and for each of the 46 native plant species that have been tested or used for revegetation are presented.

Alaska↗

USGS2015

Mortality patterns and detection bias from carcass data: An example from wolf recovery in Wisconsin

We developed models and provide computer code to make carcass recovery data more useful to wildlife managers. With these tools, wildlife managers can understand the spatial, temporal (e.g., across time periods, seasons), and demographic patterns in mortality causes from carcass recovery datasets. From datasets of radio-collared and non-collared carcasses, managers can calculate the detection bias by mortality cause in a non-collared carcass dataset compared to a collared carcass dataset. As a first step, we provide a standard procedure to assign mortality causes to carcasses. We provide an example of these methods for radio-collared wolves ( n  = 208) and non-collared wolves ( n  = 668) found dead in Wisconsin (1979–2012). We analyzed differences in mortality cause relative to season, age and sex classes, wolf harvest zones, and recovery phase (1979–1995: initial recovery, 1996–2002: early growth, 2003–2012: late growth). Seasonally, illegal kills and natural deaths were proportionally higher in winter (Oct–Mar) than summer (Apr–Sep) for collared wolves, whereas vehicle strikes and legal kills were higher in summer than winter. Spatially, more illegally killed collared wolves occurred in eastern wolf harvest zones where wolves reestablished more slowly and in the central forest region where optimal habitat is isolated by agriculture. Natural mortalities of collared wolves (e.g., disease, intraspecific strife, or starvation) were highest in western wolf harvest zones where wolves established earlier and existed at higher densities. Calculating detection bias in the non-collared dataset revealed that more than half of the non-collared carcasses on the landscape are not found. The lowest detection probabilities for non-collared carcasses (0.113–0.176) occurred in winter for natural, illegal, and unknown mortality causes.

Wisconsin↗

USGS2025

Review: The hydrogeology of critical mineral resources relevant to the energy transition

Attaining the goals of the international treaty on climate change (the Paris Agreement) will greatly increase the demand for the critical minerals required to implement clean-energy technologies. This poses both challenges and opportunities to the hydrogeologic community from several perspectives. Here, important insights that the hydrogeological sciences have to offer for mineral exploration, mineral production, and addressing environmental issues related to mining and mine decommissioning are summarized. This study focuses on copper, cobalt, lithium, and rare earths to represent the broad spectrum of critical minerals and illustrate their relevance by referring to projected demands and production rates. The current understanding of the hydrogeologic processes that form major deposits of these minerals are then summarized. Ore is defined as the naturally occurring material from which minerals of economic value can be extracted, where most ore deposits are the products of complex hydrogeologic couplings between fluid flow, heat transport, solute transport, chemical reactions, and mechanical deformation. Exploration models for the discovery of deeper, hidden deposits are potentially informed by hydrogeologic theory and hydrogeochemical processes. Hydrogeologic understanding and methods are also essential to production and recovery. Longstanding challenges are mine dewatering and (conversely) mine water supply, as well as mineral-extraction practices such as spoil heap leaching and in situ mining. New challenges arise from element extraction from subsurface brines. Finally, the quantity of water use and potential environmental impacts of mining on water quality are at the core of ‘social license’: the approval and acceptance of society to mining activities.

Hydrogeology Journal↗

USGS2014

Establishing endangered species recovery criteria using predictive simulation modeling

Listing a species under the Endangered Species Act (ESA) and developing a recovery plan requires U.S. Fish and Wildlife Service to establish specific and measurable criteria for delisting. Generally, species are listed because they face (or are perceived to face) elevated risk of extinction due to issues such as habitat loss, invasive species, or other factors. Recovery plans identify recovery criteria that reduce extinction risk to an acceptable level. It logically follows that the recovery criteria, the defined conditions for removing a species from ESA protections, need to be closely related to extinction risk. Extinction probability is a population parameter estimated with a model that uses current demographic information to project the population into the future over a number of replicates, calculating the proportion of replicated populations that go extinct. We simulated extinction probabilities of piping plovers in the Great Plains and estimated the relationship between extinction probability and various demographic parameters. We tested the fit of regression models linking initial abundance, productivity, or population growth rate to extinction risk, and then, using the regression parameter estimates, determined the conditions required to reduce extinction probability to some pre-defined acceptable threshold. Binomial regression models with mean population growth rate and the natural log of initial abundance were the best predictors of extinction probability 50 years into the future. For example, based on our regression models, an initial abundance of approximately 2400 females with an expected mean population growth rate of 1.0 will limit extinction risk for piping plovers in the Great Plains to less than 0.048. Our method provides a straightforward way of developing specific and measurable recovery criteria linked directly to the core issue of extinction risk. Published by Elsevier Ltd.

Biological Conservation↗