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USGS2023

Numbers of wildlife fatalities at renewable energy facilities in a targeted development region

Increased interest in renewable energy has fostered development of wind and solar energy facilities globally. However, energy development sometimes has negative environmental impacts, such as wildlife fatalities. Efforts by regional land managers to balance energy potential while minimizing fatality risk currently rely on datasets that are aggregated at continental, but not regional scales, that focus on single species, or that implement meta-analyses that inappropriately use inferential statistics. We compiled and summarized fatality data from 87 reports for solar and wind facilities in the Mojave and Sonoran Deserts region of southern California within the Desert Renewable Energy Conservation Plan area. Our goal was to evaluate potential temporal and guild-specific patterns in fatalities, especially for priority species of conservation concern. We also aimed to provide a perspective on approaches interpreting these types of data, given inherent limitations in how they were collected. Mourning doves ( Zenaida macroura ), Chukar ( Alectoris chukar ) and California Quail ( Callipepla californica ), and passerines ( Passeriformes ), accounted for the most commonly reported fatalities. However, our aggregated count data were derived from raw, uncorrected totals, and thus reflect an absolute minimum number of fatalities for the monitored period. Additionally, patterns in the raw data suggested that many species commonly documented as fatalities (e.g., waterbirds and other nocturnal migrants, bats) are rarely counted during typical pre-construction use surveys. This may explain the more commonly observed mismatch between pre-construction risk assessment and actual fatalities. Our work may serve to guide design of future scientific research to address temporal and spatial patterns in fatalities and to apply rigorous guild-specific survey methodologies to estimate populations at risk from renewable energy development.

California↗

USGS2021

Evaluating natural experiments in ecology: Using synthetic controls in assessments of remotely sensed land treatments

Many important ecological phenomena occur on large spatial scales and/or are unplanned and thus do not easily fit within analytical frameworks that rely on randomization, replication, and interspersed a priori controls for statistical comparison. Analyses of such large‐scale, natural experiments are common in the health and econometrics literature, where techniques have been developed to derive insight from large, noisy observational data sets. Here, we apply a technique from this literature, synthetic control, to assess landscape change with remote sensing data. The basic data requirements for synthetic control include (1) a discrete set of treated and untreated units, (2) a known date of treatment intervention, and (3) time series response data that include both pre‐ and post‐treatment outcomes for all units. Synthetic control generates a response metric for treated units relative to a no‐action alternative based on prior relationships between treated and unexposed groups. Using simulations and a case study involving a large‐scale brush‐clearing management event, we show how synthetic control can intuitively infer treatment effect sizes from satellite data, even in the presence of confounding noise from climate anomalies, long‐term vegetation dynamics, or sensor errors. We find that accuracy depends on the number and quality of potential control units, highlighting the importance of selecting appropriate control populations. Although we consider the synthetic control approach in the context of natural experiments with remote sensing data, we expect the methodology to have wider utility in ecology, particularly for systems with large, complex, and poorly replicated experimental units.

Ecological Applications↗

USGS1987

Stratification of a cityscape using census and land use variables for inventory of building materials

A cityscape (or any landscape) can be stratified into environmental units using multiple variables of information. For the purposes of sampling building materials, census and land use variables were used to identify similar strata. In the Metropolitan Statistical Area of a cityscape, the census tract is the smallest unit for which census data are summarized and digitized boundaries are available. For purposes of this analysis, census data on total population, total number of housing units, and number of singleunit dwellings were aggregated into variables of persons per square kilometer and proportion of housing units in single-unit dwellings. The level 2 categories of the U.S. Geological Survey's land use and land cover data base were aggregated into variables of proportion of residential land with buildings, proportion of nonresidential land with buildings, and proportion of open land. The cityscape was stratified, from these variables, into environmental strata of Urban Central Business District, Urban Livelihood Industrial Commercial, Urban Multi-Family Residential, Urban Single Family Residential, Non-Urban Suburbanizing, and Non-Urban Rural. The New England region was chosen as a region with commonality of building materials, and a procedure developed for trial classification of census tracts into one of the strata. Final stratification was performed by discriminant analysis using the trial classification and prior probabilities as weights. The procedure was applied to several cities, and the results analyzed by correlation analysis from a field sample of building materials. The methodology developed for stratification of a cityscape using multiple variables has application to many other types of environmental studies, including forest inventory, hydrologic unit management, waste disposal, transportation studies, and other urban studies. Multivariate analysis techniques have recently been used for urban stratification in England. ?? 1987 Annals of Regional Science.

The Annals of Regional Science↗

USGS2009

Land Cover Change in the Boston Mountains, 1973-2000

The U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-cover change. The objectives of the study are to: (1) to develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data to measure regional land-cover change across the United States; (2) to characterize the types, rates, and temporal variability of change for a 30-year period; (3) to document regional driving forces and consequences of change; and (4) to prepare a national synthesis of land-cover change (Loveland and others, 1999). The 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) provide the geographic framework for the geospatial data collected between 1973 and 2000. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000, and the data are evaluated using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historic aerial photographs from similar time frames and other ancillary data, such as census statistics and published literature, are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and determination of the driving forces of change identified in an ecoregion.

Open-File Report↗

USGS2025

A systematic review and meta-analysis of post-fire seeding and herbicide treatment effectiveness for controlling exotic annual grasses in the sagebrush biome

Introduction Outcomes of ecological restoration treatments can be highly variable and challenging to generalize, even for the same treatment type applied in similar ecological communities at different times and places. Notable examples are the herbicide and seeding treatments that have been extensively applied across the perennial sagebrush steppe of the United States to reduce impacts of fire-promoting exotic annual grasses (EAGs) such as Cheatgrass ( Bromus tectorum ). Objectives We asked if statistically based generalizations about the effects of pre-emergent herbicide and drill seeding of perennials, implemented following wildfires when threats of annual-grass invasion are greatest, could be made from the available literature. Methods We conducted a meta-analysis of these treatment effects for 1228 treatment-control comparisons from 35 studies published from 1990 to 2023 that met basic criteria for topical relevance and repeatability. Results EAGs and forbs were each reduced by herbicides and by seeding perennial grasses. The combination of herbicide and seeding reduced annuals and led to the largest increases in perennials. Although these outcomes support the intended effects of the treatments, there was high variability in outcomes among studies. Conclusions Combined use of pre-emergent herbicides and seeding can increase the success of restoration interventions that are aimed at reducing the invasion of exotic annual grasses and increasing perennials after fire in sagebrush steppe. Our analysis revealed, however, that the available literature was not suited to answering more specific questions, in spite of the massive amount of post-fire herbicide and seedings that have been applied in burned sagebrush steppe. Specifically, there were too few topically relevant studies with adequate scientific reporting to properly evaluate differences among specific treatment methodologies, including specific herbicides, that affect restoration success.

Restoration Ecology↗

USGS2020

Multi‐species occupancy models: Review, roadmap, and recommendations

Recent technological and methodological advances have revolutionized wildlife monitoring. Although most biodiversity monitoring initiatives are geared towards focal species of conservation concern, researchers are increasingly studying entire communities, specifically the spatiotemporal drivers of community size and structure and interactions among species. This has resulted in the emergence of multi‐species occupancy models (MSOMs) as a promising and efficient approach for the study of community ecology. Given the potential of MSOMs for conservation and management action, it is critical to know whether study design and model assumptions are consistent with inference objectives. This is especially true for studies that are designed for a focal species but can give insights about a community. Here, we review the recent literature on MSOMs, identify areas of improvement in the multi‐species study workflow, and provide a reference model for best practices for focal species and community monitoring study design. We reviewed 92 studies published between 2009 and early 2018, spanning 27 countries and a variety of taxa. There is a consistent under‐reporting of details that are central to determining the adequacy of designs for generating data that can be used to make inferences about community‐level patterns of occupancy, including the spatial and temporal extent, types of detectors used, covariates considered, and choice of field methods and statistical tools. This reporting bias could consequently result in skewed estimates, affecting conservation actions and management plans. On the other hand, comprehensive reporting is likely to help researchers working on MSOMs assess the robustness of inferences, in addition to making strides in terms of reproducibility and reusability of data. We use our literature review to inform a roadmap with best practices for MSOM studies, from simulations to design considerations and reporting, for the collection of new data as well as those involving existing datasets.

Ecography↗

USGS2006

Estimated ground-water availability in the Delaware River basin, 1997-2000

Ground-water availability using a watershed-based approach was estimated for the 147 watersheds that make up the Delaware River Basin. This study, conducted by the U.S. Geological Survey in cooperation with the Delaware River Basin Commission (DRBC), supports the DRBC's Water Resources Plan for the Delaware River Basin. Different procedures were used to estimate ground-water availability for the region underlain by fractured rocks in the upper part of the basin and for surficial aquifers in the region underlain by unconsolidated sediments in the lower part of the basin. The methodology is similar to that used for the Delaware River Basin Commission's Ground-Water Protected Area in Pennsylvania. For all watersheds, ground-water availability was equated to average annual base flow. Ground-water availability for the 109 watersheds underlain by fractured rocks in Delaware, New Jersey, New York, and Pennsylvania was based on lithology and physiographic province. Lithology was generalized by grouping 183 geologic units into 14 categories on the basis of rock type and physiographic province. Twenty-three index streamflow-gaging stations were selected to represent the 14 categories. A base-flow-recurrence analysis was used to determine the average annual 2-, 5-, 10-, 25-, and 50-year-recurrence intervals for each index station. A GIS analysis used lithology and base flow at the index stations to determine the average annual base flow for the 109 watersheds. Average annual base flow for these watersheds ranged from 0.313 to 0.915 million gallons per day per square mile for the 2-year-recurrence interval to 0.150 to 0.505 million gallons per day per square mile for the 50-year-recurrence interval. Ground-water availability for watersheds underlain by unconsolidated surficial aquifers was based on predominant surficial geology and land use, which were determined from statistical tests to be the most significant controlling factors of base flow. Twenty-one index streamflow-gaging stations were selected to represent the 13 categories of predominant surficial geology and land use for the 38 Coastal Plain watersheds. A base-flow-recurrence analysis was used to determine the average annual 2-, 5-, 10-, 25-, and 50-year-recurrence intervals for each group of predominant surficial geology and land use. Average annual base flow for these watersheds ranged from 0.465 to 1.169 million gallons per day per square mile for the 2-year-recurrence interval to 0.178 to 0.670 million gallons per day per square mile for the 50-year-recurrence interval. Estimated 2-, 5-, 10-, 25-, and 50-year annual base-flow-recurrence interval values for each watershed in the Delaware River Basin are considered to be the quantity of ground water available for each watershed over a range of climatic conditions. The recurrence intervals are considered to be relative indicators of climatic difference; the 2-year-recurrence value represents wetter years, and the 50-year-recurrence value represents drier years. The remaining available ground water in each watershed was determined by subtracting current (1997-2000) ground-water withdrawals and consumptive domestic use and adding water recharged by agricultural irrigation and land application of treated-sewage effluent. Ground-water use ranged from 0 to 60.8 percent of available ground water for the 2-year-recurrence interval; it exceeded 25 percent in four watersheds and 50 percent in two watersheds. Ground-water use ranged from 0 to 75.9 percent of available ground water for the 5-year-recurrence interval; it exceeded 25 percent in five watersheds and 50 percent in three watersheds. Ground-water use ranged from 0 to 84.5 percent of available ground water for the 10-year-recurrence interval; it exceeded 25 percent in seven watersheds and 50 percent in four watersheds. Ground-water use ranged from 0 to 103 percent of available ground water for the 25-year-recurrence interval; it exceeded 25 percent in nine watersheds, 5

Delaware, New Jersey, New York, Pennsylvania↗

USGS2020

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects . This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Mato Grosso↗

USGS2007

Vertical distribution of fish biomass in Lake Superior: Implications for day bottom trawl surveys

Evaluation of the biases in sampling methodology is essential for understanding the limitations of abundance and biomass estimates of fish populations. Estimates from surveys that rely solely on bottom trawls may be particularly vulnerable to bias if pelagic fish are numerous. We evaluated the variability in the vertical distribution of fish biomass during the U.S. Geological Survey's annual spring bottom trawl survey of Lake Superior using concurrent hydroacoustic observations to (1) test the assumption that fish are generally demersal during the day and (2) evaluate the potential for predictive models to improve bottom trawl–determined biomass estimates. Our results indicate that the assumption that fish exhibit demersal behavior during the annual spring bottom trawl survey in Lake Superior is unfounded. Bottom trawl biomass (B BT ) estimates (mean ± SE) for species known to exhibit pelagic behavior (cisco Coregonus artedi, bloater C. hoyi, kiyi C. kiyi, and rainbow smelt Osmerus mordax; 3.01 ± 0.73 kg/ha) were not significantly greater than mean acoustic pelagic zone biomass (B APZ ) estimates (6.39 ± 2.03 kg/ha). Mean B APZ estimates were 1.6- to 4.8-fold greater than mean B BT estimates over 4 years of sampling. The relationship between concurrent B APZ and B BT estimates was marginally significant and highly variable. Predicted B APZ estimates using cross-validation models were sensitive to adjustments for back-transforming from the logarithmic to the linear scale and poorly corresponded to observed B APZ estimates. We conclude that statistical models to predict B APZ from day B BT cannot be developed. We propose that night sampling with multiple gears will be necessary to generate better biomass estimates for management needs.

North American Journal of Fisheries Management↗

USGS2006

Factors Affecting Firm Yield and the Estimation of Firm Yield for Selected Streamflow-Dominated Drinking-Water-Supply Reservoirs in Massachusetts

Factors affecting reservoir firm yield, as determined by application of the Massachusetts Department of Environmental Protection's Firm Yield Estimator (FYE) model, were evaluated, modified, and tested on 46 streamflow-dominated reservoirs representing 15 Massachusetts drinking-water supplies. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes the 1960s drought-of-record. The FYE methodology to estimate streamflow to the reservoir at an ungaged site was tested by simulating streamflow at two streamflow-gaging stations in Massachusetts and comparing the simulated streamflow to the observed streamflow. In general, the FYE-simulated flows agreed well with observed flows. There were substantial deviations from the measured values for extreme high and low flows. A sensitivity analysis determined that the model's streamflow estimates are most sensitive to input values for average annual precipitation, reservoir drainage area, and the soil-retention number-a term that describes the amount of precipitation retained by the soil in the basin. The FYE model currently provides the option of using a 1,000-year synthetic record constructed by randomly sampling 2-year blocks of concurrent streamflow and precipitation records 500 times; however, the synthetic record has the potential to generate records of precipitation and streamflow that do not reflect the worst historical drought in Massachusetts. For reservoirs that do not have periods of drawdown greater than 2 years, the bootstrap does not offer any additional information about the firm yield of a reservoir than the historical record does. For some reservoirs, the use of a synthetic record to determine firm yield resulted in as much as a 30-percent difference between firm-yield values from one simulation to the next. Furthermore, the assumption that the synthetic traces of streamflow are statistically equivalent to the historical record is not valid. For multiple-reservoir systems, the firm-yield estimate was dependent on the reservoir system's configuration. The firm yield of a system is sensitive to how the water is transferred from one reservoir to another, the capacity of the connection between the reservoirs, and how seasonal variations in demand are represented in the FYE model. Firm yields for 25 (14 single-reservoir systems and 11 multiple-reservoir systems) reservoir systems were determined by using the historical records of streamflow and precipitation. Current water-use data indicate that, on average, 20 of the 25 reservoir systems in the study were operating below their estimated firm yield; during months with peak demands, withdrawals exceeded the firm yield for 8 reservoir systems.

Scientific Investigations Report↗

USGS2025

Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy

The Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked by section 7002 (“Mineral Security”) of title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Congress) with reviewing and revising the methodology used to evaluate mineral commodity supply risk and the U.S. List of Critical Minerals (LCM) no less than every 3 years. Following two previous LCM assessments, this analysis represents the latest technical input for evaluating each mineral commodity’s supply risk and determining their recommended status on the LCM. We evaluated mineral commodity supply risk using two criteria: (1) an economic effects assessment that quantified the potential effects of various trade disruption scenarios on the U.S. economy, and (2) an examination of whether the mineral commodity’s U.S. supply chain relied on a sole domestic producer that represented a single point of failure. For the first criterion, postdisruption equilibrium quantities and prices for each mineral commodity were calculated based on their price elasticities of supply and demand and the availability of excess production capacity for each yearlong foreign trade disruption scenario. Subsequently, a nonlinear optimization routine was used with detailed economic input-output tables to estimate the potential economic effects on the U.S. economy of over 1,200 scenarios for 84 mineral commodities. After accounting for the probability of each scenario’s occurrence, the overall results are presented in terms of changes in U.S. gross domestic product (GDP) by individual industry and the economy overall. The results, which ranged from a net decrease in U.S. GDP of nearly $4.5 billion to a net increase of $33 million, largely reflect U.S. import dependency and world production concentration. Using the Jenks natural breaks optimization method, a statistical classification technique, we categorized the mineral commodities into several classes based on this overall risk quantification. Mineral commodities with annualized probability-weighted net decreases in U.S. GDP greater than $2 million were recommended for inclusion on the LCM. If a mineral commodity did not meet the threshold for inclusion on the LCM under the first criterion, its domestic supply chain was examined under the second criterion, which recommended a mineral commodity for inclusion on the LCM if there was only a single domestic producer. Ultimately, the two criteria resulted in the recommendation of the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the LCM. By using an economic effects assessment, the results of this analysis provide a prioritization that can also be compared directly against other risk analyses and the cost of various risk mitigation strategies.

Open-File Report↗

USGS2002

Occurrence and distribution of microbiological contamination and enteric viruses in shallow ground water in Baltimore and Harford counties, Maryland

The U.S. Geological Survey, in cooperation with the Maryland Department of the Environment and the Wisconsin State Laboratory of Hygiene, conducted a study to characterize the occurrence and distribution of viral contamination in small (withdrawing less than 10,000 gallons per day) public water-supply wells screened in the shallow aquifer in the Piedmont Physiographic Province in Baltimore and Harford Counties, Maryland. Two hundred sixty-three small public water-supply wells were in operation in these counties during the spring of 2000. Ninety-one of these sites were selected for sampling using a methodology that distributed the samples evenly over the population and the spatial extent of the study area. Each site, and its potential susceptibility to microbiological contamination, was evaluated with regard to hole depth, casing interval, and open interval. Each site was evaluated using characteristics such as on-site geology and on-site land use.Samples were collected by pumping between 200 and 400 gallons of untreated well water through an electropositive cartridge filter. Water concentrates were subjected to cell-culture assay for the detection of culturable viruses and reverse-transcription polymerase chain reaction/gene probe assays to detect viral ribonucleic acid; grab samples were analyzed for somatic and male-specific coliphages, Bacteroides fragilis, Clostridium perfringens, enterococci, Escherichia coli, total coliforms, total oxidized nitrogen, nitrite, organic nitrogen, total phosphate, ortho-phosphate, calcium, magnesium, sodium, potas-sium, chloride, sulfate, iron, acid-neutralizing capacity, pH, specific conductance, temperature, and dissolved oxygen.One sample tested positive for the presence of the ribonucleic acid of rotavirus through poly-merase chain-reaction analysis. Twenty-nine per-cent of the samples (26 of 90) had bacterial con-tamination. About 7 percent of the samples (6 of 90) were contaminated with either male-specific coliphage, somatic coliphage, or bacteriophages of Bacteroides fragilis. About 3 percent of the sam-ples (3 of 87) had oxidized nitrogen concentra-tions that exceeded the U.S. Environmental Protection Agency?s Maximum Contaminant Level of 10.0 milligrams per liter. A statistical analysis showed that no significant relation exists between the presence of bacteria or coliphage and all variables, except the mean temperature of the water sample as measured in the field. Additionally, the concentration of total coliform bacteria had a statistically significant, moderately strong cor-relation with the concentration of sulfate and sample pH as measured at the U.S. Geological Survey National Water-Quality Laboratory in Denver, Colorado.

Water-Resources Investigations Report↗

USGS2002

Ground-water quality and discharge to Chincoteague and Sinepuxent Bays adjacent to Assateague Island National Seashore, Maryland

Water-Resources Investigations Report↗

USGS2009

Land-Cover Change in the East Central Texas Plains, 1973-2000

Project Background: The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-use and land-cover change. The objectives of the study are to: (1) develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) data for measuring regional land-cover change across the United States, (2) characterize the types, rates and temporal variability of change for a 30-year period, (3) document regional driving forces and consequences of change, and (4) prepare a national synthesis of land-cover change (Loveland and others, 1999). Using the 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) as the geographic framework, geospatial data collected between 1973 and 2000 were processed and analyzed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000. General land-cover classes such as water, developed, grassland/shrubland, and agriculture for these periods were interpreted from Landsat MSS, TM, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land-Use Land-Cover Classification System for image interpretation. The interpretation of these land-cover classes complement the program objective of looking at land-use change with cover serving as a surrogate for land use. The land-cover change rates are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. For example, the scalar statistics can show the spatial extent of change per cover type with time, as well as the land-cover transformations from one land-cover type to another type occurring with time. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and helps determine the driving forces of change identified in an ecoregion. Management and maintenance of field data, beyond initial use for training and validation of image classifications, is important as improved methods for image classification are developed, and as present-day data become part of the historical legacy for which studies of land-cover change in the future will depend (Loveland and others, 2002). The results illustrate that there is no single profile of land-cover change; instead, there is significant geographic variability that results from land uses within ecoregions continuously adapting to the resource potential created by various environmental, technological, and socioeconomic factors.

Open-File Report↗

USGS2023

Quantification of geodetic strain rate uncertainties and implications for seismic hazard estimates

Geodetic velocity data provide first-order constraints on crustal surface strain rates, which in turn are linked to seismic hazard. Estimating the 2-D surface strain tensor everywhere requires knowledge of the surface velocity field everywhere, while geodetic data such as Global Navigation Satellite System (GNSS) only have spatially scattered measurements on the surface of the Earth. To use these data to estimate strain rates, some type of interpolation is required. In this study, we review methodologies for strain rate estimation and compare a suite of methods, including a new implementation based on the geostatistical method of kriging, to compare variation between methods with uncertainty based on one method. We estimate the velocity field and calculate strain rates in southern California using a GNSS velocity field and five different interpolation methods to understand the sources of variability in inferred strain rates. Uncertainty related to data noise and station spacing (aleatoric uncertainty) is minimal where station spacing is dense and maximum far from observations. Differences between methods, related to epistemic uncertainty, are usually highest in areas of high strain rate due to differences in how gradients in the velocity field are handled by different interpolation methods. Parameter choices, unsurprisingly, have a strong influence on strain rate field, and we propose the traditional L -curve approach as one method for quantifying the inherent trade-off between fit to the data and models that are reflective of tectonic strain rates. Doing so, we find total variability between five representative strain rate models to be roughly 40 per cent, a much lower value than roughly 100 per cent that was found in previous studies (Hearn et al .). Using multiple methods to tune parameters and calculate strain rates provides a better understanding of the range of acceptable models for a given velocity field. Finally, we present an open-source Python package (Materna et al .) for calculating strain rates, Strain_2D, which allows for the same data and model grid to be used in multiple strain rate methods, can be extended with other methods from the community, and provides an interface for comparing strain rate models, calculating statistics and estimating strain rate uncertainty for a given GNSS data set.

Geophysical Journal International↗

USGS2016

Kinematic ground motion simulations on rough faults including effects of 3D stochastic velocity perturbations

We describe a methodology for generating kinematic earthquake ruptures for use in 3D ground‐motion simulations over the 0–5 Hz frequency band. Our approach begins by specifying a spatially random slip distribution that has a roughly wavenumber‐squared fall‐off. Given a hypocenter, the rupture speed is specified to average about 75%–80% of the local shear wavespeed and the prescribed slip‐rate function has a Kostrov‐like shape with a fault‐averaged rise time that scales self‐similarly with the seismic moment. Both the rupture time and rise time include significant local perturbations across the fault surface specified by spatially random fields that are partially correlated with the underlying slip distribution. We represent velocity‐strengthening fault zones in the shallow (<5 km) and deep (>15 km) crust by decreasing rupture speed and increasing rise time in these regions. Additional refinements to this approach include the incorporation of geometric perturbations to the fault surface, 3D stochastic correlated perturbations to the P ‐ and S ‐wave velocity structure, and a damage zone surrounding the shallow fault surface characterized by a 30% reduction in seismic velocity. We demonstrate the approach using a suite of simulations for a hypothetical M w 6.45 strike‐slip earthquake embedded in a generalized hard‐rock velocity structure. The simulation results are compared with the median predictions from the 2014 Next Generation Attenuation‐West2 Project ground‐motion prediction equations and show very good agreement over the frequency band 0.1–5 Hz for distances out to 25 km from the fault. Additionally, the newly added features act to reduce the coherency of the radiated higher frequency ( f >1 Hz) ground motions, and homogenize radiation‐pattern effects in this same bandwidth, which move the simulations closer to the statistical characteristics of observed motions as illustrated by comparison with recordings from the 1979 Imperial Valley earthquake.

Bulletin of the Seismological Society of America↗

USGS2006

Genetic analyses of captive Alala (Corvus hawaiiensis) using AFLP analyses

Population level studies of genetic diversity can provide information about population structure, individual genetic distinctiveness and former population size. They are especially important for rare and threatened species like the Alala, where they can be used to assess extinction risks and evolutionary potential. In an ideal situation multiple methods should be used to detect variation, and these methods should be comparable across studies. In this report, we discuss AFLP (Amplified Fragment Length Polymorphism) as a genetic approach for detecting variation in the Alala , describe our findings, and discuss these in relation to mtDNA and microsatellite data reported elsewhere in this same population. AFLP is a technique for DNA fingerprinting that has wide applications. Because little or no prior knowledge of the particular species is required to carry out this method of analysis, AFLP can be used universally across varied taxonomic groups. Within individuals, estimates of diversity or heterozygosity across genomes may be complex because levels of diversity differ between and among genes. One of the more traditional methods of estimating diversity employs the use of codominant markers such as microsatellites. Codominant markers detect each allele at a locus independently. Hence, one can readily distinguish heterozygotes from homozygotes, directly assess allele frequencies and calculate other population level statistics. Dominant markers (for example, AFLP) are scored as either present or absent (null) so heterozygotes cannot be directly distinguished from homozygotes. However, the presence or absence data can be converted to expected heterozygosity estimates which are comparable to those determined by codominant markers. High allelic diversity and heterozygosity inherent in microsatellites make them excellent tools for studies of wild populations and they have been used extensively. One limitation to the use of microsatellites is that heterozygosity estimates are affected by the mutation rate at microsatellite loci, thus introducing a bias. Also, the number of loci that can be studied is frequently limited to fewer than 10. This theoretically represents a maximum of one marker for each of 10 chromosomes. Dominant markers like AFLP allow a larger fraction of the genome to be screened. Large numbers of loci can be screened by AFLP to resolve very small individual differences that can be used for identification of individuals, estimates of pairwise relatedness and, in some cases, for parentage analyses. Since AFLP is a dominant marker (can not distinguish between +/+ homozygote versus +/- heterozygote), it has limitations for parentage analyses. Only when both parents are homozygous for the absence of alleles (-/-) and offspring show a presence (+/+ or +/-) can the parents be excluded. In this case, microsatellites become preferable as they have the potential to exclude individual parents when the other parent is unknown. Another limitation of AFLP is that the loci are generally less polymorphic (only two alleles/locus) than microsatellite loci (often >10 alleles/locus). While generally fewer than 10 highly polymorphic microsatellite loci are enough to exclude and assign parentage, it might require up to 100 or more AFLP loci. While there are pros and cons to different methodologies, the total number of loci evaluated by AFLP generally offsets the limitations imposed due to the dominant nature of this approach and end results between methods are generally comparable. Overall objectives of this study were to evaluate the level of genetic diversity in the captive population of Alala, to compare genetic data with currently available pedigree information, and to determine the extent of relatedness of mating pairs and among founding individuals.

Open-File Report↗

USGS2020

Gear comparison study for sampling nekton in Barataria Basin marshes

This project was funded by the Louisiana Trustee Implementation Group (LA TIG) to support decisions related to investments in long-term monitoring. The LA TIG seeks to ensure long-term monitoring informs coastal restoration activities with the goal of sustaining and improving fisheries impacted by the Deepwater Horizon (DWH) Oil Spill. The project objective was to compare nekton catch across an estuarine gradient using different sampling gear with the goal of identifying trade-offs among nekton sampling approaches. To accomplish this objective, Louisiana Department of Wildlife and Fisheries (LDWF), The Water Institute of the Gulf (the Institute), Dynamic Solutions, LLC, Louisiana State University Agricultural Center (LSU AgCenter), and the U.S. Geological Survey (USGS) completed a field gear comparison study from 2018 to 2019. This work compared electrofisher and seine sampling at 12 fixed stations in Barataria Basin using data collected by LDWF. In addition, and in conjunction with LDWF monthly sampling, the same 12 fixed stations were sampled in May 2019 using a throw trap to compare nekton catch and assemblages collected with the throw trap, seine and electrofisher. LDWF has been conducting seine sampling since 1986, and seine data are used by the State of Louisiana to assess juvenile shrimp, crab and fish abundances, sizes and overall assemblages. In 2018, LDWF began conducting electrofisher sampling at 12 Barataria Basin seine stations in order to determine if the two gear types sample similar species and assemblages for potential future replacement of long-term seine sampling with electrofishing. Throw traps were included as they provide density estimates, which are ultimately the desired statistic used in modeling trophic webs, and are used in assessing habitat restoration outcomes. The project compared the nekton catch and assemblages collected using seine, electrofisher, and throw trap data from marsh edge habitats located across the estuarine gradient in Barataria Basin. Specifically, catch per unit effort (CPUE), species richness, species-specific total length (mm) distribution and nekton assemblages were compared between gear types. The first dataset was collected in May 2019 with throw trap (Appendix A), seine (LDWF data), and electrofisher (LDWF data) gear, and the second dataset (collected by LDWF) spanned 14 months of seine and electrofisher monthly sampling occurring from May 2018 through June 2019 at 12 stations in Barataria Basin. Key findings include that gear bias was not evident across the range of water quality conditions (salinity, temperature, o C, dissolved oxygen, mg L-1 , turbidity, NTU; Appendix B: scatter plots) captured during this pilot study, but differences in nekton catch per unit effort (CPUE) and assemblages were evident between gear types. However, those differences largely depended on the parameter examined. For example, the overall CPUE was highest for electrofishing, followed by seine, and then throw trap. When grass shrimp (the most abundant taxon collected) were removed from CPUE, the electrofisher and seine results were similar in CPUE. When CPUE was corrected for gear efficiency and total area sampled, the throw trap had the highest reported density of nekton sampled, followed by electrofisher and seine results. Electrofishing captured the highest number of species, which included more unique species compared to seine or throw trap catches, though all gear types captured at least one unique species. These highlight a need for caution in interpreting assemblage and density data when comparing datasets derived from different sampling methodologies. These key findings can help inform implementation and interpretation of long-term monitoring data in Louisiana as management decisions are made about coastal restoration projects to sustain and improve fisheries. There are trade-offs in selecting gear types for estuarine nekton monitoring of density, abundance, species richness, and assemblages. The table below (Table 1) summarizes some considerations when selecting gear types for long-term monitoring of estuarine nekton. In addition to biological and ecological considerations, other important considerations include cost, the labor required to conduct sampling, logistics, and potential uncertainties related to how effective each gear type is for sampling the wide variety of conditions found across Louisiana’s coastal habitats. For example, although electrofishing may capture higher CPUE, the equipment is more expensive to obtain and maintain compared to the other gear types. Most importantly, this table highlights differences in the nekton assemblages sampled by each gear type; this consideration is critical when designing the goals of a long-term monitoring program as it will inform how the data can be used and interpreted in the future. This report provides caveats, assumptions, and recommendations that can help support the Louisiana Coastal Protection and Restoration Authority (CPRA), LDWF and the LA TIG in comparing data from different gear types, and in making decisions for future monitoring. Findings from this study are limited to the range of water quality conditions occurring during these data collection events; these data and analyses could benefit from sampling across a wider range of water quality conditions, and collection of habitat structure and bottom type data which are not routinely collected but critically influence nekton. Further investigation examining how relative differences detected in key species abundances between gear types might impact ecosystem indicators and energetics in a modeled food web would provide valuable input to understand outputs of the Comprehensive Aquatic System Model for Barataria Basin, including the potential impacts of nekton monitoring decisions on food web models.

Louisiana↗