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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 811 records · Page 45Linked to original sources
USGS2023

Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal

The negative impact of large carnivore presence in human-dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio-ecological and management issue. We estimated the occurrence of leopard attacks in Nepal from human-leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density. The human population density effect may be indicative of a density-dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks. We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards. This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human-wildlife conflict at a national scale.

People and Nature↗
USGS2025

Public support for puma reintroduction in the eastern United States

Pumas ( Puma concolor ) are among the species identified as having the potential to enhance ecosystem function. Previous research highlights sufficient ecological habitat to support pumas in the eastern United States; however, their reintroduction requires social and institutional support as well. To this end, we conducted research to assess attitudes about puma reintroduction among key constituencies like hunters, rural residents, and young people. We sampled 2756 respondents across seven states (Massachusetts, Maine, New Hampshire, New York, Pennsylvania, Vermont, and West Virginia). Ratios of strong support (for puma reintroduction) to strong opposition across states ranged from 4:1 to 13:1, and support outweighed opposition in every state. Our results contrasted with common assumptions that hunters, rural residents, and people who identify as politically conservative oppose carnivore conservation and reintroduction. We found marginal differences among categories of people, but overall little variation in support exhibited by different groups. People who identified very strongly as hunters were more supportive of reintroduction than those who did not identify as hunters at all. Taken together, the presence of quality habitat and support for puma restoration warrant further exploration. However, federal funding for state-based restoration efforts likely requires the inclusion of pumas in State Wildlife Action Plans (SWAPs), which are currently under a 10-year revision due to be published this year (2025).

Maine, Massachusetts, New Hampshire, New York, Pen↗
USGS2014

DigitalCrust – a 4D data system of material properties for transforming research on crustal fluid flow

Fluid circulation in the Earth's crust plays an essential role in surface, near surface, and deep crustal processes. Flow pathways are driven by hydraulic gradients but controlled by material permeability, which varies over many orders of magnitude and changes over time. Although millions of measurements of crustal properties have been made, including geophysical imaging and borehole tests, this vast amount of data and information has not been integrated into a comprehensive knowledge system. A community data infrastructure is needed to improve data access, enable large-scale synthetic analyses, and support representations of the subsurface in Earth system models. Here, we describe the motivation, vision, challenges, and an action plan for a community-governed, four-dimensional data system of the Earth's crustal structure, composition, and material properties from the surface down to the brittle–ductile transition. Such a system must not only be sufficiently flexible to support inquiries in many different domains of Earth science, but it must also be focused on characterizing the physical crustal properties of permeability and porosity, which have not yet been synthesized at a large scale. The DigitalCrust is envisioned as an interactive virtual exploration laboratory where models can be calibrated with empirical data and alternative hypotheses can be tested at a range of spatial scales. It must also support a community process for compiling and harmonizing models into regional syntheses of crustal properties. Sustained peer review from multiple disciplines will allow constant refinement in the ability of the system to inform science questions and societal challenges and to function as a dynamic library of our knowledge of Earth's crust.

Geofluids↗
USGS2018

Evidence and opportunities for integrating landscape ecology into natural resource planning across multiple-use landscapes

Enhancing natural resource management has been a focus of landscape ecology since its inception, but numerous authors argue that landscape ecology has not yet been effective in achieving the underlying goal of planning and designing sustainable landscapes. We developed nine questions reflecting the application of fundamental research topics in landscape ecology to the landscape planning process and reviewed two recent landscape-scale plans in western North America for evidence of these concepts in plan decisions. Both plans considered multiple resources, uses, and values, including energy development, recreation, conservation, and protection of cultural and historic resources. We found that land use change and multiscale perspectives of resource uses and values were very often apparent in planning decisions. Pattern-process relationships, connectivity and fragmentation, ecosystem services, landscape history, and climate change were reflected less frequently. Landscape sustainability was considered only once in the 295 decisions reviewed, and outputs of landscape models were not referenced. We suggest six actionable opportunities for further integrating landscape ecology concepts into landscape planning efforts: 1) use landscape sustainability as an overarching goal, 2) adopt a broad ecosystem services framework, 3) explore the role of landscape history more comprehensively, 4) regularly consider and accommodate potential effects of climate change, 5) use landscape models to support plan decisions, and 6) promote a greater presence of landscape ecologists within agencies that manage large land bases and encourage active involvement in agency planning efforts. Together these actions may improve the defensibility, durability, and sustainability of landscape plan decisions.

Current Landscape Ecology Reports↗
USGS2024

Exploring the dynamic interactions between the Southern San Andreas Fault and a normal fault under the Salton Sea

We investigate the dynamic interactions between the Southern San Andreas Fault (SSAF) and a proximal normal fault (NF) beneath the Salton Sea in southern California. The NF, positioned near the SSAF terminus at Bombay Beach, exhibits 11–15 displacement events across 14 stratigraphic sequences, with a range of 0.2–1.4 m of vertical offset since ∼2–3 ka. Notably, four of these events may align temporally with SSAF earthquakes, raising questions about the possible interplay between the two faults. Utilizing dynamic rupture models, we analyze the coseismic interactions between the SSAF and NF, addressing under what conditions the SSAF induces slip on the NF. Our findings reveal that a suite of SSAF ruptures, particularly those propagating from north to south, can trigger slip on the normal fault and replicate observed vertical offsets. If the SSAF extends beneath the Salton Sea, earthquakes originating south of the NF intersection are less likely to trigger normal fault slip, although we cannot exclude this possibility. Some SSAF ruptures do not trigger discernible slip on the NF, rendering such events undetectable in the stratigraphic record. Our research contributes toward discussions regarding the seismic hazard in southern California, shedding light on the interplay between the SSAF and NF.

California↗
USGS2016

Sea level driven marsh expansion in a coupled model of marsh erosion and migration

Coastal wetlands are among the most valuable ecosystems on Earth, where ecosystem services such as flood protection depend nonlinearly on wetland size and are threatened by sea level rise and coastal development. Here we propose a simple model of marsh migration into adjacent uplands and couple it with existing models of seaward edge erosion and vertical soil accretion to explore how ecosystem connectivity influences marsh size and response to sea level rise. We find that marsh loss is nearly inevitable where topographic and anthropogenic barriers limit migration. Where unconstrained by barriers, however, rates of marsh migration are much more sensitive to accelerated sea level rise than rates of edge erosion. This behavior suggests a counterintuitive, natural tendency for marsh expansion with sea level rise and emphasizes the disparity between coastal response to climate change with and without human intervention.

Geophysical Research Letters↗
USGS2013

Runoff-generated debris flows: observations and modeling of surge initiation, magnitude, and frequency

Runoff during intense rainstorms plays a major role in generating debris flows in many alpine areas and burned steeplands. Yet compared to debris flow initiation from shallow landslides, the mechanics by which runoff generates a debris flow are less understood. To better understand debris flow initiation by surface water runoff, we monitored flow stage and rainfall associated with debris flows in the headwaters of two small catchments: a bedrock-dominated alpine basin in central Colorado (0.06 km 2 ) and a recently burned area in southern California (0.01 km 2 ). We also obtained video footage of debris flow initiation and flow dynamics from three cameras at the Colorado site. Stage observations at both sites display distinct patterns in debris flow surge characteristics relative to rainfall intensity (I). We observe small, quasiperiodic surges at low I; large, quasiperiodic surges at intermediate I; and a single large surge followed by small-amplitude fluctuations about a more steady high flow at high I. Video observations of surge formation lead us to the hypothesis that these flow patterns are controlled by upstream variations in channel slope, in which low-gradient sections act as “sediment capacitors,” temporarily storing incoming bed load transported by water flow and periodically releasing the accumulated sediment as a debris flow surge. To explore this hypothesis, we develop a simple one-dimensional morphodynamic model of a sediment capacitor that consists of a system of coupled equations for water flow, bed load transport, slope stability, and mass flow. This model reproduces the essential patterns in surge magnitude and frequency with rainfall intensity observed at the two field sites and provides a new framework for predicting the runoff threshold for debris flow initiation in a burned or alpine setting.

California;Colorado↗
USGS2010

Hydromythology and ethnohydrology in the New World

From mythology, archeology, and chronicles of early explorers we can learn how early Americans viewed the cause and effect relations of hydrologic phenomena. Hopes and fears are the basis of religion, and it was through religion that water management was first practiced. Early people used their water resources to develop diverse civilizations in various parts of the western hemisphere. Not only was the rise of these earlier civilizations hydrologically influenced, but also the downfall of some was related to natural or man-made hydrological crises in which gods and mythology continued to play a role.

Water Resources Research↗
USGS2009

Experimental Advanced Airborne Research Lidar (EAARL) Data Processing Manual

The Experimental Advanced Airborne Research Lidar (EAARL) is an example of a Light Detection and Ranging (Lidar) system that utilizes a blue-green wavelength (532 nanometers) to determine the distance to an object. The distance is determined by recording the travel time of a transmitted pulse at the speed of light (fig. 1). This system uses raster laser scanning with full-waveform (multi-peak) resolving capabilities to measure submerged topography and adjacent coastal land elevations simultaneously (Nayegandhi and others, 2009). This document reviews procedures for the post-processing of EAARL data using the custom-built Airborne Lidar Processing System (ALPS). ALPS software was developed in an open-source programming environment operated on a Linux platform. It has the ability to combine the laser return backscatter digitized at 1-nanosecond intervals with aircraft positioning information. This solution enables the exploration and processing of the EAARL data in an interactive or batch mode. ALPS also includes modules for the creation of bare earth, canopy-top, and submerged topography Digital Elevation Models (DEMs). The EAARL system uses an Earth-centered coordinate and reference system that removes the necessity to reference submerged topography data relative to water level or tide gages (Nayegandhi and others, 2006). The EAARL system can be mounted in an array of small twin-engine aircraft that operate at 300 meters above ground level (AGL) at a speed of 60 meters per second (117 knots). While other systems strive to maximize operational depth limits, EAARL has a narrow transmit beam and receiver field of view (1.5 to 2 milliradians), which improves the depth-measurement accuracy in shallow, clear water but limits the maximum depth to about 1.5 Secchi disk depth (~20 meters) in clear water. The laser transmitter [Continuum EPO-5000 yttrium aluminum garnet (YAG)] produces up to 5,000 short-duration (1.2 nanosecond), low-power (70 microjoules) pulses each second. Each pulse is focused into an illumination area that has a radius of about 20 centimeters on the ground. The pulse-repetition frequency of the EAARL transmitter varies along each across-track scan to produce equal cross-track sample spacing and near uniform density (Nayegandhi and others, 2006). Targets can have varying physical and optical characteristics that cause extreme fluctuations in laser backscatter complexity and signal strength. To accommodate this dynamic range, EAARL has the real-time ability to detect, capture, and automatically adapt to each laser return backscatter. The backscattered energy is collected by an array of four high-speed waveform digitizers connected to an array of four sub-nanosecond photodetectors. Each of the four photodetectors receives a finite range of the returning laser backscatter photons. The most sensitive channel receives 90% of the photons, the least sensitive receives 0.9%, and the middle channel receives 9% (Wright and Brock, 2002). The fourth channel is available for detection but is not currently being utilized. All four channels are digitized simultaneously into 65,536 samples for every laser pulse. Receiver optics consists of a 15-centimeter-diameter dielectric-coated Newtonian telescope, a computer-driven raster scanning mirror oscillating at 12.5 hertz (25 rasters per second), and an array of sub-nanosecond photodetectors. The signal emitted by the pulsed laser transmitter is amplified as backscatter by the optical telescope receiver. The photomultiplier tube (PMT) then converts the optical energy into electrical impulses (Nayegandhi and others, 2006). In addition to the full-waveform resolving laser, the EAARL sensor suite includes a down-looking 70-centimeter-resolution Red-Green-Blue (RGB) digital network camera, a high-resolution color infrared (CIR) multispectral camera (14-centimeter-resolution), two precision dual-frequency kinematic carrier-phase global positioning system (GPS) receivers, and an

Open-File Report↗
USGS2025

Precipitation timing mediates life-stage and population-level associations with climate for an indicator species

Global climate change is contributing to declines in biodiversity, although changes vary across geographic regions and species. The iconic greater sage-grouse (Centrocercus urophasianus; sage-grouse) is central to conservation within the North American sagebrush ecosystem, yet its vulnerability to climate effects remains poorly understood. We used hierarchical models to explore weather and climatic influences on sage-grouse across nearly four decades, focusing first on pattern (population change), then process (demographic life stage). We quantified eight indicators of temperature and/or moisture conditions across time lags of 0–1.5 years leading up to current year breeding activities. Sage-grouse population growth tended to increase following above-average growing season precipitation. Precipitation or drought timing influenced whether process effects were positive or negative. More summer and/or fall moisture corresponded with increases in subsequent year brood and adult survival, while concurrent seasonal drought led to reductions in nest survival. Positive concurrent spring drought associations with adult and brood survival were largely outweighed by positive prior year moisture effects. Density-dependence and indirect effects of precipitation through vegetation and forage resource pathways likely contributed to nuanced responses across life stages. Our research improves mechanistic understanding of this indicator species’ sensitivity to climatic factors, while reinforcing the importance of large-scale conservation initiatives for sagebrush ecosystems.

Scientific Reports↗
USGS2019

Speaking the same language: Can the Sustainable Development Goals translate the needs of inland fisheries into irrigation decisions?

Irrigated agriculture and inland fisheries both make important contributions to food security, nutrition, livelihoods, and well-being. Typically, in modern irrigation systems, these components operate independently. Some practices, commonly associated with water use and intensification of crop production, can be in direct conflict with and have adverse impacts on fisheries. Food security objectives may be compromised if fish are not considered in the design phases of irrigation systems. The 2030 Agenda for Sustainable Development provides a framework that can serve as a backdrop to help integrate both sectors in policy discussions and optimize their contributions to achieving the Sustainable Development Goals (SDGs). Inland fisheries systems do play an important role in supporting many SDG objectives, but these contributions can sometimes be at odds with irrigated agriculture. Using case studies of two globally important river catchments, the Lower Mekong and Murray-Darling Basins, we highlight the conflicts and opportunities for improved outcomes between irrigated agriculture and inland fisheries. We explore SDG 2 (Zero Hunger) as a path to advance our irrigation systems as a means to benefit both agriculture and inland fisheries, preserving biodiversity and enhancing the economic, environmental, and social benefits they both provide to people.

Marine and Freshwater Research↗
USGS2026

Can a physics-based fire behavior model predict burn severity and post-fire debris flow hazard?

Post-wildfire flooding and debris flows pose a threat to ecosystems and infrastructure. As the frequency and size of severe wildfires increase, there is a growing need for predictive debris flow hazard modeling in unburned but fire-prone landscapes. However, no crosswalks have been established between physics-based models of fire behavior and the remotely sensed burn severity inputs needed for debris flow modeling. Here, we explore this connection by creating a large ensemble of fire behavior simulations using QUIC-Fire – a fast-running three-dimensional fire model – in basins across five major-disaster wildfires in California and Washington. We then conducted generalized linear mixed modeling (GLMM) and Random Forest modeling to identify QUIC-Fire outputs that best predicted remotely sensed burn severity. We found that the selected linear predictors exhibited weak and unintuitive relationships with soil burn severity and differenced Normalized Burn Ratio. Moreover, model evaluations of GLMMs and Random Forests showed they were poorly predictive of both metrics of remotely sensed burn severity. This suggests that there are barriers to integrating QUIC-Fire into a wildfire-hazards modeling framework, which could include mismatches in scale between fire models and remotely sensing, or simplifications of weather data and fire initiation. Further research is needed to establish connections between the fire physics outputs of QUIC-Fire and post-fire effects to vegetation and soils that are essential for evaluating debris flow hazard.

California, Washington↗
USGS2011

Unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance

Ecological research uses data collection techniques that are prone to substantial and unique types of measurement error to address scientific questions about species abundance and distribution. These data collection schemes include a number of survey methods in which unmarked individuals are counted, or determined to be present, at spatially- referenced sites. Examples include site occupancy sampling, repeated counts, distance sampling, removal sampling, and double observer sampling. To appropriately analyze these data, hierarchical models have been developed to separately model explanatory variables of both a latent abundance or occurrence process and a conditional detection process. Because these models have a straightforward interpretation paralleling mechanisms under which the data arose, they have recently gained immense popularity. The common hierarchical structure of these models is well-suited for a unified modeling interface. The R package unmarked provides such a unified modeling framework, including tools for data exploration, model fitting, model criticism, post-hoc analysis, and model comparison.

Journal of Statistical Software↗
USGS1977

High-resolution gamma-ray spectrometry in uranium exploration

Sedimentary-type uranium deposits accumulate at favorable sites along a migration path which may be kilometers in length. Their source is a large volume of rock from which the uranium has been leached. The geochemical mobilities and half lives of uranium and its daughter products vary widely so that they are transported from the source rocks, at different rates, along the migration path to their ultimate site. The radioactive disequilibrium resulting from this process has been well documented in the immediate vicinity of ore deposits, and disequilibrium is commonly recorded on gamma-ray logs up the hydraulic gradient from uranium ore. Little is known about the state of secular equilibrium in the leached host rocks, which often represent the only part of the migration path that is at or near the surface and is thus most accessible to the exploration geophysicist. High-resolution gamma-ray spectrometry provides a means of investigating the disequilibrium associated with uranium leaching and migration. Direct measurement of uranium can be made by this method, and the equivalent weight percents can be determined for six of the seven daughter-product decay groups that characterize the state of radioactive equilibrium. The technique has been used quantitatively in laboratory studies, where the results compare favorably with radiochemical analyses; field experiments suggest that semi-quantitative data may be obtained at the outcrop.

Journal of Research of the U.S. Geological Survey↗
USGS2013

The NAS Alert System: A look at the first eight years

The U.S. Geological Survey's Nonindigenous Aquatic Species (NAS) database program (http://nas.er.usgs.gov) tracks the distribution of introduced aquatic organisms across the United States. Awareness of, and timely response to, novel species introductions by those involved in nonindigenous aquatic species management and research requires a framework for rapid dissemination of occurrence data as it is incorporated into the NAS database. In May 2004, the NAS program developed an alert system to notify registered users of new introductions as part of a national early detection/rapid response system. This article summarizes information on system users and dispatched alerts from the system's inception through the end of 2011. The NAS alert system has registered over 1,700 users, with approximately 800 current subscribers. A total of 1,189 alerts had been transmitted through 2011. More alerts were sent for Florida (134 alerts) than for any other state. Fishes comprise the largest taxonomic group of alerts (440), with mollusks, plants, and crustaceans each containing over 100 alerts. Most alerts were for organisms that were intentionally released (414 alerts), with shipping, escape from captivity, and hitchhiking also representing major vectors. To explore the archive of sent alerts and to register, the search and signup page for the alert system can be found online at http://nas.er.usgs.gov/AlertSystem/default.aspx.

Fisheries↗
USGS1977

Exploration geochemical studies of some sandstone copper-uranium deposits, Bradford, Columbia, and Lycoming Counties, Pa

Semi-quantitative spectrographic analyses of mineralized and unmineralized sandstone, siltstone, and claystone from the Catskill Formation of Devonian age in Bradford, Columbia, and Lycoming Counties, Pa., suggest that copper, silver, and uranium are the principal metallic elements concentrated in the mineralized rock. Lead, mercury, and molybdenum may be concentrated slightly in mineralized rock but values are too low to be of use in exploration. The deposits are too small to make large anomalies in stream sediments except in drainage basins of less than a few acres. However, if a large deposit were exposed to weathering, it would probably be detectable by stream sediment sampling. Analyses of oxalic acid leachates of the minus 80-mesh fraction of the stream-sediment samples gave more useful values than analyses of the minus 80-mesh samples in separating drainage basins that have copper deposits from those that have no known copper deposits.

Pennsylvania↗
USGS2023

A novel approach to assessing natural resource injury with Bayesian networks

Quantifying the effects of environmental stressors on natural resources is problematic because of complex interactions among environmental factors that influence endpoints of interest. This complexity, coupled with data limitations, propagates uncertainty that can make it difficult to causally associate specific environmental stressors with injury endpoints. The Natural Resource Damage Assessment and Restoration (NRDAR) regulations under the Comprehensive Environmental Response, Compensation, and Liability Act and Oil Pollution Act aim to restore natural resources injured by oil spills and hazardous substances released into the environment; exploration of alternative statistical methods to evaluate effects could help address NRDAR legal claims. Bayesian networks (BNs) are statistical tools that can be used to estimate the influence and interrelatedness of abiotic and biotic environmental variables on environmental endpoints of interest. We investigated the application of a BN for injury assessment using a hypothetical case study by simulating data of acid mine drainage (AMD) affecting a fictional stream-dwelling bird species. We compared the BN-generated probability estimates for injury with a more traditional approach using toxicity thresholds for water and sediment chemistry. Bayesian networks offered several distinct advantages over traditional approaches, including formalizing the use of expert knowledge, probabilistic estimates of injury using intermediate direct and indirect effects, and the incorporation of a more nuanced and ecologically relevant representation of effects. Given the potential that BNs have for natural resource injury assessment, more research and field-based application are needed to determine their efficacy in NRDAR. We expect the resulting methods will be of interest to many US federal, state, and tribal programs devoted to the evaluation, mitigation, remediation, and/or restoration of natural resources injured by releases or spills of contaminants

Integrated Environmental Assessment and Management↗
USGS2024

Real-time invasive sea lamprey detection using machine learning classifier models on embedded systems

Invasive sea lamprey ( Petromyzon marinus ) has historically inflicted considerable economic and ecological damage in the Great Lakes and continues to be a major threat. Accurately monitoring sea lampreys are critical to enabling the deployment of more targeted and effective control measures to minimize the impact associated with this species. This paper presents the first stand-alone system for real-time detection of sea lamprey attachment on underwater surfaces through the use of classifier models deployed on a microcontroller system. A range of low-complexity models was explored: single-layer artificial neural networks, logistic regression, Gaussian Naive-Bayes, decision trees, random forest, and Scalable, Efficient, and Fast classifieR (SEFR). Threshold models tuned using a multi-objective optimization formulation were also considered. Classifier models were trained with a dataset generated through live animal testing and presented accuracies between 80 and 86%. The models were deployed on an Arduino microcontroller platform and compared in classification accuracy, detection performance, time complexity, and memory size using real-time detection testing. Classification accuracies between 65 and 75% were observed during validation. Models demonstrated good capture rates for lamprey attachments (63–85%), and average detection delays ranging from 9 to 36 s. A video demonstrating the operation of the system during a real-time validation test is also included in this work. While there is room for improving the accuracy of the system, this research presents the first step toward an electronic sea lamprey monitoring system that can provide a detailed view of sea lamprey activity enhancing control and conservation efforts across its entire range.

Neural Computing and Applications↗