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USGS2021

Determination of four arsenic species in environmental water samples by liquid chromatography- inductively coupled plasma - tandem mass spectrometry

Robust and sensitive methods for monitoring inorganic and organic As species As(III), As(V), dimethylarsinate (DMA), and monomethylarsonate (MMA) in environmental water are necessary to understand the toxicity and redox processes of As in a specific environment. The method is sufficiently sensitive and selective to ensure accurate and precise quantitation of As(III), As(V), DMA, and MMA in surface water and groundwater samples with As species concentrations from tens of nanograms per liter to 50 µg/L without dilution of the sample. Mean recoveries of the four species spiked into reagent water, surface water and groundwater and measured periodically over three months ranged from 87.2 % to 108.7 % and relative standard deviation of replicates of all analytes ranged from 1.1 % to 9.0 %. •A PRP-X100 column and nitrate/phosphate mobile phase was used to separate As(III), As(V), DMA, and MMA in 0.45 µm filtered surface water and groundwater matrices. •Oxygen was used in the collision cell of the inductively coupled plasma-mass spectrometer with MS/MS mode to shift the measured As mass from 75 to 91. • The analytical performance of the method and figures of merit including detection limits, precision, accuracy, and interferences when applied to surface water and groundwater matrices were investigated.

MethodsX↗

USGS2021

A customized framework for regional classification of conifers using automated feature extraction

Pinyon and juniper expansion into sagebrush ecosystems is one of the major challenges facing land managers in the Great Basin. Effective pinyon and juniper treatment requires maps that accurately and precisely depict tree location and degree of woodland development so managers can target restoration efforts for early stages of pinyon and juniper expansion. However, available remotely sensed layers that cover a regional spatial extent lack the spatial resolution or accuracy to meet this need. Accuracy can be improved using object-based image analysis methods such as automated feature extraction, which has proven successful in accurately classifying land cover at the site-level but to date has yet to be applied to regional extents due to time and computational limitations. Using Feature Analyst™, we implement our framework with 1-m 2 reference imagery provided by National Agricultural Imagery Program to classify conifers across Nevada and northeastern California. Our resulting binary conifer map has an overall accuracy of 86%. We discuss the advantages to accuracy and precision our framework provides compared to other classification methods

Oregon, California, Nevada, Utah↗

USGS2022

Using near–surface temperature data to vicariously calibrate high-resolution thermal infrared imagery and estimate physical surface properties

Thermal response of the surface to solar insolation is a function of the topography and the thermal physical characteristics of the landscape, which include bulk density, heat capacity, thermal conductivity and surface albedo and emissivity. Thermal imaging is routinely used to constrain thermal physical properties by characterizing or modeling changes in the diurnal temperature profiles. Images need to be acquired throughout the diurnal cycle – typically this is done twice during a diurnal cycle, but we suggest multiple times. Comparison of images acquired over 24 hours requires that either the data be calibrated to surface temperature, or the response of the thermal camera is linear and stable over the image acquisition period. Depending on the type and age of the thermal instrument, imagery may be self-calibrated in radiance, corrected for atmospheric effects, and pixels converted to surface temperature. We used an experimental instrumentation where the calibration should be stable, but calibration coefficients are unknown. Cases may occur where one wishes to validate the camera's calibration. We present a method to validate and calibrate the instrument and characterize the thermal physical properties for areas of interest. Finally, in situ high-temporal-resolution oblique thermal imaging can be invaluable in preparation for conducting overflight missions. We present the following: • The use of oblique thermal high temporal resolution thermal imaging over diurnal or multiday periods for the characterization of landscapes has not been widespread but poses great potential. • A method of collecting and analyzing thermal data that can be used to either determine or validate thermal camera calibration coefficients. • An approach to characterize thermophysical properties of the landscape using oblique temporally high-resolution thermal imaging, combined with in situ ground measurements.

MethodsX↗

USGS2023

A Bayesian multi-stage modelling framework to evaluate impacts of energy development on wildlife populations: An application to Greater Sage-Grouse (Centrocercus urophasianus)

Increased demand for domestic production of renewable energy has led to expansion of energy infrastructure across western North America. Much of the western U.S. comprises remote landscapes that are home to a variety of vegetation communities and wildlife species, including the imperiled sagebrush ecosystem and indicator species such as greater sage-grouse ( Centrocercus urophasianus ). Geothermal sources in particular have potential for continued development across the western U.S. but impacts to greater sage-grouse and other species are unknown. To address this information gap, we describe a novel two-pronged methodology that analyzes impacts of geothermal energy production on pattern and process of greater sage-grouse populations using (a) before-after control-impact (BACI) measures of population growth and lek absence rates and (b) concurrent-to-operation evaluations of demographic rates. Growth and absence rate analyses utilized 14 years of lek survey data collected prior (2005–2011) and concurrent (2012–2018) to geothermal operations at two sites in Nevada, USA. Demographic analyses utilized relocation data, restricted inference to concurrent years, and incorporated 17 additional control sites. Demographic results were applied to >100 potential geothermal sites distributed across the study region to generate spatially explicit predictions of unrealized population-level impacts.

MethodsX↗

USGS2026

Statewide agent-based model for management of chronic wasting disease in white-tailed deer: PAOvCWD

Chronic wasting disease (CWD) is an always-fatal disease infecting wild cervids globally. Ecologically and economically important, CWD presents a challenge for managing white-tailed deer ( Odocoileus virginianus ). We built an agent-based model to simulate CWD transmission and assess potential management actions that could slow disease spread: PAOvCWD . We developed PAOvCWD using contact rates and other behavioral and ecological metrics estimated from deer monitored in Pennsylvania, USA. We programmed potential management responses (e.g., culling, altered hunter harvest) for all 22 Pennsylvania wildlife management units and validated the efficacy of PAOvCWD using a deer population in south-central Pennsylvania infected with CWD for > 10 years. To support applications of our model, we developed a user-friendly R pipeline that allows implementation with relatively minor modifications. Our pipeline includes four steps: • Steps 1 and 2 generate regional percent forest cover rasters and curate population-level demographics. • Step 3 initializes landscapes and agents using our PAOvPOP model. • Step 4 assesses CWD transmission and management responses using our PAOvCWD model.

Pennsylvania↗

USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗

USGS2026

Method development and validation for microscopic measurement of the fluorescence spectrum of sedimentary organic matter in geologic samples

The goal of this study was to develop and validate a standard operating procedure for measuring the fluorescence emission of sedimentary organic matter (SOM), a proxy used to assess thermal maturity conditions in petroliferous basins. We tested the performance of a spectrometer integrated with an epi-fluorescence imaging microscope, and evaluated instrument calibration, dark-current correction, time duration for instrument stabilization, light delivery optimization, and the number of measurements necessary to optimize precision. These tests were used to guide instrument operation, ensure measurement accuracy, and characterize performance limitations of the system as SOM transitions to higher thermal maturity with accompanying signal deterioration. Adhering to these newly established guidelines enhances the reproducibility of fluorescence spectroscopy measurements. More importantly, this work endeavors to reach the overall objective of demonstrating the utility of fluorescence spectroscopy for evaluating the thermal maturity of SOM. Method for fluorescence spectroscopy of sedimentary organic matter. Internal calibration via diffuse halogen light reflected from polytetrafluoroethylene (PTFE). Evaluates emission response via λ max and red-green and blue-green quotients.

MethodsX↗