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USGS2021

New geochemical tools for investigating resource and energy functions at deep-sea cold seeps using amino-acid δ15N in chemosymbiotic mussels (Bathymodiolus childressi)

In order to reconstruct the ecosystem structure of chemosynthetic environments in the fossil record, geochemical proxies must be developed. Here, we present a suite of novel compound-specific isotope parameters for tracing chemosynthetic production with a focus on understanding nitrogen dynamics in deep-sea cold seep environments. We examined the chemosymbiotic bivalve Bathymodiolus childressi from three geographically distinct seep sites on the NE Atlantic Margin and compared isotope data to non-chemosynthetic littoral mussels to test whether water depth, seep activity, and/or mussel bed size are linked to differences in chemosynthetic production. The bulk isotope analysis of carbon (δ 13 C) and nitrogen (δ 15 N), and δ 15 N values of individual amino acids (δ 15 N AA ) in both gill and muscle tissues, as well as δ 15 N AA- derived parameters including trophic level (TL), baseline δ 15 N value (δ 15 N Phe ), and a microbial resynthesis index (Σ V ), were used to investigate specific geochemical signatures of chemosynthesis. Our results show that δ 15 N AA values provide a number of new proxies for relative reliance on chemosynthesis, including TL, ∑V, and both δ 15 N values and molar percentages (Gly/Glu mol% index) of specific AA. Together, these parameters suggested that relative chemoautotrophy is linked to both degree of venting from seeps and mussel bed size. Finally, we tested a Bayesian mixing model using diagnostic AA δ 15 N values, showing that percent contribution of chemoautotrophic versus heterotrophic production to seep mussel nutrition can be directly estimated from δ 15 N AA values. Our results demonstrate that δ 15 N AA analysis can provide a new set of geochemical tools to better understand mixotrophic ecosystem function and energetics, and suggest extension to the study of ancient chemosynthetic environments in the fossil record.

Geobiology↗

USGS1996

Mitochondrial-DNA variation among subspecies and populations of sea otters (Enhydra lutris)

We used restriction-enzyme analysis of polymerase-chain reaction-amplified, mitochondrial DNA (mtDNA) to assess genetic differentiation of subspecies and populations of sea otters, Enhydra lutris , throughout the range of the species. There were several haplotypes of mtDNA in each subspecies and geographically separate populations. MtDNA sequence divergence of haplotypes of sea otters was 0.0004–0.0041 base substitutions per nucleotide. E. L nereis appears to have monophyletic mitochondrial DNA, while E. I. lutris and E. I. kenyoni do not. Different frequencies of haplotypes of mtDNA among populations reflect current restriction of gene flow and the unique histories of different populations. There are two or three haplotypes of mtDNA and diversity of haplotypes is 0.1376–0.5854 in each population of otters. This is consistent with theoretical work, which suggests that population bottlenecks of sea otters probably did not result in major losses of genetic variation for individual populations, or the species as a whole.

Journal of Mammalogy↗

USGS2007

Land-Cover Trends of the Southern California Mountains Ecoregion

This report presents an assessment of land-use and land-cover (LU/LC) change in the Southern California Mountains ecoregion for the period 1973-2001. The Southern California Mountains is one of 84 Level-III ecoregions as defined by the U.S. Environmental Protection Agency (EPA). Ecoregions have served as a spatial framework for environmental resource management, denoting areas that contain a geographically distinct assemblage of biotic and abiotic phenomena including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The established Land Cover Trends methodology generates estimates of change for ecoregions using a probability sampling approach and change-detection analysis of thematic land-cover images derived from Landsat satellite imagery.

Scientific Investigations Report↗

USGS2019

Hydrogeology of Lower Amargosa Valley and groundwater discharge to the Amargosa Wild and Scenic River, Inyo and San Bernardino Counties, California, and adjacent areas in Nye and Clark Counties, Nevada

In 2009, Congress designated certain reaches of the Amargosa River in Inyo County, California between the town of Shoshone and Dumont Dunes as a Wild and Scenic River. As part of the management of the Amargosa Wild and Scenic River, the Bureau of Land Management cooperated with the U.S. Geological Survey to assess the surface and groundwater resources of the Tecopa basin. Groundwater is the primary source of water to the perennial reaches of the Amargosa River. The U.S. Geological Survey studied the surface and groundwater systems in the basin, and assessed the sources and volume of groundwater discharging into the perennial reaches of the Amargosa Wild and Scenic River. The springs within the Tecopa basin (and the greater Lower Amargosa Valley Hydrographic Area) can be generally grouped by spring type and geographic location. There are four types of groundwater discharge points in the Tecopa basin—regional carbonate-rock springs and seeps, Tecopa Hills springs and seeps, thermal springs and seeps, and Amargosa Canyon hillslope springs and seeps. Results of chemical analysis indicate that water from all of these springs in the Lower Amargosa Valley and particularly in the Tecopa basin, is sourced in the carbonate-rock aquifer, with a local component of recharge. Groundwater is recharged in the Spring Mountains and moves through and around the Nopah and Resting Spring Ranges and into the Tecopa basin. A small (less than 1 cubic foot per second [ft 3 /s] or 500 acre‑feet per year) component of flow from the Amargosa Desert moves through the river channel alluvium and basin fill from the north. The location and type of spring appear to be controlled by the geology and geologic structure of the Lower Amargosa Valley. The regional springs (such as Shoshone and Borax Springs) and associated seeps tend to occur along the west side of the basin whereas other carbonate-rock aquifer springs discharge from adjacent mountain ranges, such as the Resting Spring Range, and as a result of low-permeability barriers, such as the Tecopa Hills. The thermal springs and seeps discharge from an area near the town of Tecopa, California. The Amargosa Canyon hillslope springs and seeps discharge directly into the river. Salt-crusted soils adjacent to the river indicate additional areas of diffuse discharge where groundwater is being evaporated. Perennial flow in the main channel of the Amargosa River appears to originate in an area of thermal springs near Tecopa. Persistent groundwater-fed pools begin to appear along the river channel just to the south of the Tecopa Hills. Flow between these pools is evident, but difficult to measure. During the synoptic seepage measurement survey in February 2014, flow in the Amargosa River at the Tecopa streamgage (U.S. Geological Survey site 10251300, Amargosa River at Tecopa, California) was approximately 1 ft 3 /s. Just to the south of the Tecopa streamgage, a line of cooler water springs (the Amargosa Canyon hillslope springs) emerges east of the river channel and continues for approximately 1 mile along the Amargosa Canyon wall. At the end of the spring reach, the flow in the river increased to just over 4 ft 3 /s. Flow then decreased to approximately 3 ft 3 /s at the confluence of Willow Creek, approximately 3.5 miles downstream. Downstream from the confluence of Willow Creek, the river consistently loses water and was dry just north of Dumont Dunes during the February 2014 synoptic seepage measurement survey.

California, Nevada↗

USGS2019

Multi-resource analysis: A proof of concept study of natural resource tradeoffs in the Piceance Basin, Colorado, using the net resources assessment (NetRA) decision support tool

Executive Summary The U.S. Geological Survey (USGS) is developing a multi-resource analysis (MRA) line of products to inform land-use decision makers. Specifically, MRA products will integrate scientific information, include considerations for natural resource interrelations, and quantify the effects of resource management decisions in biophysical, economic, and societal terms. As part of the establishment of the MRA, the USGS, in collaboration with the University of New Mexico, has developed the Net Resources Assessment (NetRA) decision support tool. As a proof of concept analysis, the NetRA was applied to the Piceance basin in Colorado in a hypothetical example to illustrate how resource managers could use the NetRA to consider tradeoffs of natural resources among alternative development plans and land cover patterns within a geographic region. The NetRA is a policy-relevant approach to assess the availability of multiple natural resources. It is an analytical toolset that may be used to examine the spatiotemporal relations between development of energy and mineral resources and delivery of biological natural resources. The NetRA operates at multiple map scales and contains a set of integrated, compatible submodels with specific data requirements for natural resource stocks, engineering economics, biophysical, and ecological data for ecosystem services stocks, market prices, regulations, and nonmarket values. The NetRA includes an explicit process to consider the interdependence between development and conservation, which is a crucial consideration in land-management and land-use decisions. The NetRA is used to estimate an expected net resource value (NRV). The NRV is the expected, present value, economic benefit from the extraction of a resource (for example, natural gas) minus the total cost of production, which is the aggregation of the development, production, and social costs. Social costs include private costs plus any external costs. There can be external social benefits associated with natural gas production, such as increased demand for locally produced goods and increased employment in the local area through backward and forward linkages of natural gas production. The NRV is used to compare development outcomes (scenarios) from a range of exploration and development plans for cumulative energy production. The Piceance basin application of the NetRA uses the NRV to assess the tradeoff between continuous natural gas extraction and the effects to the local populations of Odocoileus hemionus (mule deer) and aquatic species and to consumptive water uses for an area the size and resolution of a USGS energy resource assessment unit. In the proof of concept simulation, the 2.9-square-mile-area of USGS oil and gas assessment unit 50200263 (Piceance basin continuous gas unit of the Mesaverde Total Petroleum System) was gridded into 588 cells. From this area, seven clusters with potential for development and three that cannot be developed were identified; the three clusters that cannot be developed were identified as wilderness study areas, areas of critical environmental concern, and national forests. On the basis of these criteria, there are 118 cells unsuitable for development in the oil and gas assessment unit: 84 are in national forests, 23 are areas of critical environmental concern, and 11 are wilderness study areas. The remaining cells in the oil and gas assessment unit can be developed on both private and public lands. Two scenarios were considered that are distinguished as plan 1 and plan 2. Plan 1 keeps the amount of land disturbance unchanged and limits the number of development locations to 140 grid cells for the production period, which constrains the amount of the energy resources available for development; the plan requires the usage of the Bureau of Land Management (BLM) unsuitability criteria. Plan 2 also limits the number of development locations to 140 grid cells for the production period but provides a constant volume of energy production by increasing the density of well pads within the cells. The effects of plan 2 to the NRV when there are five wells per pad and five pads per square mile happen mostly in the first 5 years of development, even though the effects on the population of mule deer continue in later years. This outcome is the result of the upfront development and investment costs and the initial effect to the ecosystem services.

Colorado↗

USGS2003

Probability of detecting elevated concentrations of nitrate in ground water in a six-county area of south-central Idaho

A probability map constructed for this study identified several areas in a six-county region of south-central Idaho with high probabilities of detecting elevated concentrations (greater than 2 milligrams per liter) of nitrate. An increasing proportion of Idaho’s ground water being used for drinking water and large increases in the inputs of nitrogen to ground water in Cassia, Gooding, Jerome, Lincoln, Minidoka, and Twin Falls Counties have prompted concerns about the quality of the resource. The probability map was constructed to assist regulatory and resource agencies in managing land use and protecting water resources. To construct the probability map, hydrogeologic and anthropogenic data were integrated with ground-water quality data in a geographic information system. The resulting data set contained land use, geology, precipitation, soil characteristics, depth to ground water, nitrogen input, and ground-water velocity information for each of the 1,365 samples collected from 1991 to 2001. Logistic regression analysis was used to determine the most statistically significant variables related to the detection of elevated nitrate concentrations. The resulting multivariate probability model showed that ground-water velocity, nitrogen input, precipitation, soil drainage, land use, and depth to ground water were significantly correlated with elevated nitrate concentrations. A subset of the water-quality data set was used to verify these results. Linear regression of the percentage of predicted probabilities of elevated nitrate concentrations and the actual percentage of elevated nitrate concentrations with the model data set and the verification data set both showed good correlations: r-squared values were 0.96 and 0.97, respectively. Statistical comparisons of both data sets showed that ground-water samples containing elevated nitrate concentrations had significantly higher probabilities of detection (p < 0.001) than samples without elevated nitrate concentrations. On the basis of these results, a map identifying the probability of detecting elevated nitrate concentrations was constructed. High-probability areas on the map coincided with regions of agricultural land use and high nitrogen input, except in southern Gooding County and western Jerome County. In these areas, high ground-water velocities representing a predominance of regional ground water resulted in a low probability of detecting elevated nitrate concentrations. Areas of poor prediction tended to be congregated along the transition zone between high and low ground-water velocities in Jerome and Gooding Counties, indicating a mix of regional and recently recharged ground water.

Idaho↗

USGS2024

Diet of Myotis ciliolabrum from six sites in the southwestern United States

With bat populations declining in many parts of the world, detailed life history information will be critical for assessing vulnerabilities of bat populations and associated trophic effects. Myotis ciliolabrum (western small-footed bat) is a species of insectivorous bat distributed from the Great Plains to the Pacific Coast and from British Columbia to Central Mexico. The species is spottily distributed within this wider range but is locally abundant in areas containing appropriate rocky habitat. Despite M. ciliolabrum being relatively common, little information is available about its feeding ecology. Earlier studies have suggested that skull morphology can be used to determine whether insectivorous bats select for soft- or hard-bodied prey, but we hypothesized that M. ciliolabrum may feed opportunistically on a variety of insect types. To test this hypothesis, we examined the feeding habits of western small-footed bats captured during 2000–2022 at 6 national parks and 1 national conservation area across the Southwest. Visual analysis of prey remains in guano revealed that western small-footed bats within our study area consumed insects belonging to 7 orders (Lepidoptera, Coleoptera, Hymenoptera, Hemiptera, Neuroptera, Diptera, and Odonata) and 20 families. Diet varied over time and across geographic space, though we observed a general trend in which the orders Lepidoptera, Coleoptera, and Hymenoptera were consumed at the highest volumes. This varied diet indicates opportunistic feeding in which M. ciliolabrum makes use of locally abundant resources.

Colorado, New Mexico, Texas↗

USGS2001

Space-time modelling of lightning-caused ignitions in the Blue Mountains, Oregon

Generalized linear mixed models (GLMM) were used to study the effect of vegetation cover, elevation, slope, and precipitation on the probability of ignition in the Blue Mountains, Oregon, and to estimate the probability of ignition occurrence at different locations in space and in time. Data on starting location of lightning-caused ignitions in the Blue Mountains between April 1986 and September 1993 constituted the base for the analysis. The study area was divided into a pixela??time array. For each pixela??time location we associated a value of 1 if at least one ignition occurred and 0 otherwise. Covariate information for each pixel was obtained using a geographic information system. The GLMMs were fitted in a Bayesian framework. Higher ignition probabilities were associated with the following cover types: subalpine herbaceous, alpine tundra, lodgepole pine (Pinus contorta Dougl. ex Loud.), whitebark pine (Pinus albicaulis Engelm.), Engelmann spruce (Picea engelmannii Parry ex Engelm.), subalpine fir (Abies lasiocarpa (Hook.) Nutt.), and grand fir (Abies grandis (Dougl.) Lindl.). Within each vegetation type, higher ignition probabilities occurred at lower elevations. Additionally, ignition probabilities are lower in the northern and southern extremes of the Blue Mountains. The GLMM procedure used here is suitable for analysing ignition occurrence in other forested regions where probabilities of ignition are highly variable because of a spatially complex biophysical environment.

Canadian Journal of Forest Research↗

USGS1984

Habitat Suitability Index Models and Instream Flow Suitability Curves: Spotted bass

The Habitat Suitability Index (HSI) models presented in this publication aid in identifying habitat variable important to the growth and survival of spotted bass (Micropterus punctulatus). Facts, ideas, and concepts obtained from the research literature and expert reviews are synthesized and presented in a format that can be used for impact assessment. The models are hypotheses of species-habitat relationships, and model users should recognize that the degree of veracity of the HSI model, SI graphs, and assumptions will vary according to geographical area and the extent of the data base for individual variables. A brief discussion of selected Suitability Index (SI) curves as used in the Instream Flow Incremental Methodology (IFIM), and a discussion of SI curves available for the IFIM analysis of Spotted bass habitat are also included.

FWS/OBS↗

USGS2024

Analysis and review of fishery-dependent data for Hawaiian nearshore noncommercial fisheries

Noncommercial, shore-based fisheries provide economic, social, and cultural services to communities throughout the Hawaiian Islands. The State of Hawai‘i Department of Land and Natural Resources (DLNR), Division of Aquatic Resources (DAR) routinely conducts surveys to monitor noncommercial fisheries such that estimates of fishing effort and catch by gear type can be generated and used to implement more sustainable management practices. DAR executes both the Hawai‘i Marine Recreational Fishery Survey (HMRFS), a nationally standardized survey that focuses on intercepting fishers at access points (i.e., boat ramps) across the main Hawaiian Islands, and a set of roving creel surveys on O‘ahu, Maui Nui, and Kaua‘i that observe and intercept fishers at locations along the shoreline outside of those targeted by HMRFS. The latter set of creel surveys were designed to complement HMRFS by expanding its geographic coverage and thus providing a more representative picture of noncommercial fishing in Hawai‘i. Sustainable management priorities set by DAR rely on the availability of statewide, fishery- dependent data. Thus, we collate information from island-based roving creel surveys into a cohesive Statewide Creel Survey Database. Further, we provide preliminary analyses and describe ways that surveys could be streamlined to improve future data collection, analysis, and utility. In so doing, we synthesize the most detailed information to-date about noncommercial shore-based fisheries of Hawai‘i. The unprecedented spatial and temporal coverage of DAR’s dataset reveals the value of their survey efforts over the last decade to address fishery management needs. Our primary objectives, results, and conclusions are summarized below: 1) Integrate DAR roving creel survey data from different islands into a single Statewide Creel Survey Dataset (Chapter II). We describe the collation of creel survey data from O‘ahu, Maui Nui, and Kaua‘i into a statewide dataset. We also offer ways in which these surveys could be streamlined to meet the needs of managers and decision makers. Briefly, these are to create a statewide strategic plan, standardize the execution of standard operating procedures, centralize the creel survey database and associated metadata, and consider using technology that improves the data pipeline, including transitioning from paper-based to electronic systems for data entry and processing. 2) Assess whether the new Statewide Creel Survey Dataset can provide inputs for length-based stock assessments (Chapter III). Only on Maui were interviews conducted with associated catch data. There was reasonably high taxonomic coverage (42 species from 186 interviews with 310 fishers), but low sample sizes for nearly all species precluded the development of length-based stock assessments. We provide summary statistics from the existing data and briefly discuss how technologies could be used to automate analysis of images of noncommercial catch. 3) Analyze the Statewide Creel Survey Dataset for spatial and temporal patterns in fishing effort (Chapter IV): a. Visualizing noncommercial fishing pressure . We found that fishing effort (mean number of fishers observed per survey event at a site) on O'ahu was over three times greater than that recorded during similar surveys conducted on Maui or Kaua'i. We create maps that display the distribution of angling and spearfishing effort around each of the three islands. b. Factors that predict fishing “hotspots” around Maui . Fishing effort on Maui was associated with areas with more wave power and less parking availability. There were half as many fishers in areas with parking lots than in areas with parking on the road shoulder only. c. Changes in fishing effort during the COVID-19 pandemic . There was no change in fishing effort on O‘ahu during the first year of the pandemic, but there was a 20% decline in year 2 and a 33% decline in year 3, both in comparison to pre-pandemic levels. Pre-pandemic creel survey data were unavailable for Maui and Kaua‘i, but fishing effort on these islands also declined as the pandemic progressed at similar or greater rates than those observed on O‘ahu. 4) Quantify potential bias in survey methods by experimentally deriving fisher detection probabilities of shore-based and drone-based surveys (Chapter V): a. Shore-based surveys . We conducted roving creel surveys for four months at three locations around Hilo Bay, designed to emulate and estimate the efficacy of DAR standard operating procedures. There was high agreement between paired observers in counting fishers, leading to near-perfect detection probabilities of both anglers (94%) and spearfishers (97%), but relatively low agreement and detection probabilities of other fishers (throw net, ‘opihi picking, etc.) (52%). b. Drone-based surveys . We used an unmanned aerial vehicle (UAV; operated by DAR staff) to collect imagery of fishers along the Hilo Bay shoreline. We used still images and video clips (with known fishing activity) to build an online survey that was distributed to DAR and HCFRU personnel, asking them to count and categorize resource users as a snorkeler, spearfisher, angler, or other fisher. Only 40.0% of the responses correctly counted and categorized resource users in the image. Anglers were correctly identified and enumerated in 90.0% of the responses, but the correct response rates of the other three user categories ranged from 67.8% – 79.4%. Snorkelers and anglers tended to be undercounted while spearfishers and other fishers were overcounted. 5) Review the potential for incorporating emerging technologies that will improve, augment, and evolve creel survey data collection, especially for spearfishing (Chapter VI). Within the context of monitoring shore-based noncommercial fishing, we review the use of electronic data entry/processing systems with geospatial and image capabilities, field cameras, drones, smart buoys, citizen science apps, data mining social media, artificial intelligence and machine learning. We highlight several of the challenges and considerations when implementing these technologies into creel surveys and provide a synthesis of options that could be used to better estimate spearfishing. The general conclusion of this assessment is that the DAR roving creel survey program is collecting valuable data that supplement the existing HMRFS efforts. However, there are a number of areas that could be improved to make these efforts a more effective tool for decision-making processes in resource management and conservation: 1) Establishment of clear statewide and island objectives for the Statewide Creel Survey Dataset. Currently, data collection efforts are focused towards addressing a very broad purpose – supplementing the HMRFS data collection efforts. However, the results of the preliminary analyses conducted as part of this project suggest that the data could be used to address other areas of need if these objectives were clearly defined. Further, the design of the creel survey would benefit from greater standardization of survey protocols between islands and an effort to define a) the acceptable margins of error associated with the estimates generated by these data and b) the minimum level of change that the surveys would need to detect to be useful to managers. 2) Centralization of data entry, data quality assessment, and data accessibility. Currently, each DAR office manages data entry, checks the data for errors, and is responsible for managing and storing the data. Instituting a centralized data entry system, particularly an online database that can receive survey data from tablets or smartphones running a standardized data collection application would improve efficiency, reduce data entry errors, and accelerate the availability of data to managers. A substantial amount of time and effort from the project described in this report was devoted to checking the dataset for errors. The development and application of data quality assurance protocols would ensure that the data are reliable and available in a timely fashion to support management decisions. 3) Address lingering questions regarding the efficacy of current survey protocols to capture and characterize the spearfishing component of the noncommercial fishery. The results presented in the report suggest that the current creel survey protocols do a good job detecting spearfishers when present but are not capturing sufficient data about their catch or total effort. There are also questions remaining as to whether the survey times and sites are sufficiently capturing the behavior of spearfishers in Hawai‘i. A more thorough assessment – whether through additional research, alteration of survey design, or review of data by representatives of the spearfishing community – would provide insight on how to use the Statewide Creel Survey Database to inform management of spearfishing. 4) Investigate the integration of technological advancements into the creel survey methods. As priorities and needs are developed and formalized, it would be valuable to consider how various technological advancements might enhance and streamline data collection or open new avenues of inquiry.

Hawaii↗

USGS2014

Introduction: Hazard mapping

Twenty papers were accepted into the session on landslide hazard mapping for oral presentation. The papers presented susceptibility and hazard analysis based on approaches ranging from field-based assessments to statistically based models to assessments that combined hydromechanical and probabilistic components. Many of the studies have taken advantage of increasing availability of remotely sensed data and nearly all relied on Geographic Information Systems to organize and analyze spatial data. The studies used a range of methods for assessing performance and validating hazard and susceptibility models. A few of the studies presented in this session also included some element of landslide risk assessment. This collection of papers clearly demonstrates that a wide range of approaches can lead to useful assessments of landslide susceptibility and hazard.

Book chapter↗

USGS2019

Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations

In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the Factor of Safety, F_s) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated F_s values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantle’s properties (hydraulic, geotechnical and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference ‘truth’ Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and ‘null’ periods using multivariate frequency distribution-based metrics such as the False Discovery and False Omission Rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicate their inability to accurately characterize hillslope stability.

North Carolina↗

USGS2014

A spatial analysis of population dynamics and climate change in Africa: potential vulnerability hot spots emerge where precipitation declines and demographic pressures coincide

We present an integrative measure of exposure and sensitivity components of vulnerability to climatic and demographic change for the African continent in order to identify “hot spots” of high potential population vulnerability. Getis-Ord Gi* spatial clustering analyses reveal statistically significant locations of spatio-temporal precipitation decline coinciding with high population density and increase. Statistically significant areas are evident, particularly across central, southern, and eastern Africa. The highly populated Lake Victoria basin emerges as a particularly salient hot spot. People located in the regions highlighted in this analysis suffer exceptionally high exposure to negative climate change impacts (as populations increase on lands with decreasing rainfall). Results may help inform further hot spot mapping and related research on demographic vulnerabilities to climate change. Results may also inform more suitable geographical targeting of policy interventions across the continent.

Population and Environment↗

USGS2017

Hierarchical, quantitative biogeographic provinces for all North American turtles and their contribution to the biogeography of turtles and the continent

Our study represents the first attempt to describe biogeographic provinces for North American (México, United States, and Canada) turtles. We analyzed three nested data sets separately: (1) all turtles, (2) freshwater turtles, and (3) aquatic turtles. We georeferenced North American turtle distributions, then we created presence–absence matrices for each of the three data sets. We used watershed unit as biogeographic units. We conducted an unweighted pair-group method with arithmetic mean clustering analysis on each Jaccard index distance matrix from our watershed species matrices to delineate biogeographic provinces. Provinces were then tested for significant differences in species compositions in a global model with the use of a one-way analysis of similarity. We conducted a best subset of environmental variables with maximum (rank) correlation with community dissimilarities that determined the best model of abiotic variables explaining province delineation (i.e., climate, topography, and stream channel). To identify which species contributed the most to province delineations, we conducted an indicator species analysis and a similarity-percentage analysis. There were 16 all-turtle provinces, 15 freshwater provinces, and 13 aquatic provinces. Species compositions delineating the provinces were explained by abiotic variables, including mean annual precipitation, mean precipitation seasonality, and diversity of streams. Province delineations correspond closely with geographical boundaries, many of which have Pleistocene origins. For example, rivers with a history of carrying glacial runoff (e.g., Arkansas, Mississippi) sometimes dissect upland provinces, especially for aquatic and semiaquatic turtles. Compared with freshwater fishes, turtles show greater sensitivity to decreased temperature with restriction of most taxa south of the last permafrost maximum. Turtles also exhibit higher sensitivity to climatic, geomorphic, and tectonic instability, with richness and endemism concentrated along the more stable Gulf of México and Atlantic (south of the last permafrost maximum) coasts. Although distribution data indicate two aquatic turtles are most cold tolerant (i.e., Chrysemys picta , Chelydra serpentina ), aquatic turtles overall show the most restriction to warmer, wetter climates. Sequential addition of semiaquatic and terrestrial turtles into analyses shows, as expected, that these taxa flesh out turtle faunas in climatically harsh (e.g., grasslands) or remote (e.g., California, Sonoran Desert) regions. The turtle assemblages of southwestern versus southeastern North America are distinct. But there is a transition zone across the semiarid plains of the Texas Gulf Coast, High Plains, and Chihuahuan Desert, including a strong boundary congruent with the Cochise Filter-Barrier. This is not a simple subdivision of Neotropical versus Nearctic taxa, as some lineages from both realms span the transition zone.

Herpetological Monographs↗

USGS2002

Alien plant species threat assessment and management prioritization for Sequoia-Kings Canyon and Yosemite National Parks

Executive Summary This document reports the results of alien species surveys at Sequoia-Kings Canyon and Yosemite national parks. It includes the findings of a comprehensive literature review of the biology and ecology of all alien plant species found during these surveys and the ranking of those species for prioritizing management and control programs. Surveys primarily targeted areas of human disturbance, such as campgrounds, corrals, developments, roads, trails and pastures. Alien species richness was compared across elevational gradients within the parks. To compare and contrast species composition among sites, an exploratory cluster analysis of the sites included in the speciesrichness- by-elevation figures was conducted using ordination techniques. All alien species discovered during the directed surveys were grouped into one of four management priority categories based on their attributes, potential impacts, and geographical extent. Category 1 species are aliens that are currently restricted to a relatively small number of sites in each park and have either been shown to greatly affect native vegetation or have a high probability of causing serious impacts. Category 2 species are restricted to a relatively small number of sites and are ones that generally have a lesser effect on native vegetation. Category 3 species are broadly distributed in the parks, are apparently increasing their ranges within the parks, and are those that have been shown to have a great impact on native vegetation. Category 4 species are those that were detected by the surveys but not assigned to one of the three ranked categories and are considered low priority.

Open-File Report↗

USGS2008

Hydrogeology and water quality of the Leetown area, West Virginia

The U.S. Geological Survey’s Leetown Science Center and the co-located U.S. Department of Agriculture’s National Center for Cool and Cold Water Aquaculture both depend on large volumes of cold clean ground water to support research operations at their facilities. Currently, ground-water demands are provided by three springs and two standby production wells used to augment supplies during periods of low spring flow. Future expansion of research operations at the Leetown Science Center is dependent on assessing the availability and quality of water to the facilities and in locating prospective sites for additional wells to augment existing water supplies. The hydrogeology of the Leetown area, West Virginia, is a structurally complex karst aquifer. Although the aquifer is a karst system, it is not typical of most highly cavernous karst systems, but is dominated by broad areas of fractured rock drained by a relatively small number of solution conduits. Characterization of the aquifer by use of fluorometric tracer tests, a common approach in most karst terranes, therefore only partly defines the hydrogeologic setting of the area. In order to fully assess the hydrogeology and water quality in the vicinity of Leetown, a multi-disciplinary approach that included both fractured rock and karst research components was needed. The U.S. Geological Survey developed this multi-disciplinary research effort to include geologic, hydrologic, geophysical, geographic, water-quality, and microbiological investigations in order to fully characterize the hydrogeology and water quality of the Leetown area, West Virginia. Detailed geologic and karst mapping provided the framework on which hydrologic investigations were based. Fracture trace and lineament analysis helped locate potential water-bearing fractures and guided installation of monitoring wells. Monitoring wells were drilled for borehole geophysical surveys, water-quality sampling, water-level measurements, and aquifer tests to characterize the quality of water and the hydraulic properties of the aquifer. Surface geophysical surveys provided a 3-dimensional view of bedrock resistivity in order to assess geologic and lithologic controls on ground-water flow. Borehole geophysical surveys were conducted in monitoring wells to assess the storage and movement of water in subsurface fractures. Numerous single-well, multi-well, and straddle packer aquifer tests and step-drawdown tests were conducted to define the hydraulic properties of the aquifer and to assess the role of bedrock fractures and solution conduits in the flow of ground water. Water samples collected from wells and springs were analyzed to assess the current quality of ground water and provide a baseline for future assessment. Microbiological sampling of wells for indicator bacteria and human and animal DNA provided an analysis of agricultural and suburban development impacts on ground-water quality. Light detection and ranging (LiDAR) data were analyzed to develop digital elevation models (DEMs) for assessing sinkhole distribution, to provide elevation data for development of a ground-water flow model, and to assess the distribution of major fractures and faults in the Leetown area. The flow of ground water in the study area is controlled by lithology and geologic structure. Bedrock, especially low permeability units such as the shale Martinsburg Formation and the Conococheague Limestone, act as barriers to water flowing down gradient and across bedding. This retardation of cross-strike flow is especially pronounced in the Leetown area, where bedding typically dips at steep angles. Highly permeable fault and fracture zones that disrupt the rocks in cross-strike directions provide avenues through which ground water can flow laterally across or through strata of low primary permeability. Significant strike parallel thrust faults and cross-strike faults typically coincide with larger solution conduits and act as drains for the more pervasive network of interconnected diffuse fractures. Results of borehole geophysical surveys indicate that although numerous fractures may intersect a borehole, only one or two of the fractures typically transmit most of the water to a well. The diffuse-flow dominated network of fractures that provides the majority of storage occupies only a small proportion of the total aquifer volume but constitutes the majority of porosity within the aquifer. Solution conduits, while occupying a relatively small volume of the overall aquifer, are especially important because they serve as primary drains for the ground-water flow system. Surface resistivity maps and cross-sectionsshow anomalous areas of low resistivities coincident with the prevailing geologic strike at N. 20º E., with major cross-strike faults, and with major springs in the region. Transmissivity derived from straddle packer tests was highly variable, and ranged over three orders of magnitude (1.8 x 10 -6 to 5.9 x 10 -3 ft 2 /d) in diffuse-flow fractures. A similar large variability in transmissivity was documented by single- and multi-well aquifer tests conducted in conduit-flow dominated portions of the aquifer (2.0 x 10 3 to 1.4 x 10 4 ft 2 /d) in lowland areas immediately adjacent to the Leetown Science Center. A stream-gaging station installed on Hopewell Run near the point where the stream exits the Leetown watershed indicates average daily streamflow for the Hopewell Run of approximately 11.2 ft 3 /s, and ranged from a minimum of 1.80 ft 3 /s on September 28, 2005, to a maximum of 73.0 ft 3 /s on December 11, 2003. Base-flow (ground-water) discharge surveys identified numerous small seeps adjacent to streams in the area. Hydrographs of the stage of Balch Spring show rapid response to individual storms. Strong correlation of the flow of Hopewell Run and Balch Spring indicates the nearby losing stream reach is partly responsible for higher fluctuations in the stage of Balch Spring. A water budget for the study period (2003-2005), based on measured precipitation and hydrograph analyses, is expressed as Precipitation (38.60 in/yr) = Surface Runoff (1.36 in/yr) + Ground-Water Discharge (17.73 in/yr) + Evapotranspiration (24.23 in/yr) – Change in storage (4.72 in/yr). Flow of ground water through the epikarst, a shallow zone of intensely weathered rock and regolith, can be rapid (on the order of days or weeks) as flow is concentrated in solution conduits. Flow within the intermediate and deeper zones is typically much slower. Eight dye-tracer tests conducted in the Leetown area found ground-water flow patterns to be divergent, with velocities ranging from about 12.5 to 610 ft/day and a median velocity of 50 ft/day. Estimates of ground-water age in carbonate rocks in the region are on the order of 15 years in the shallower portions of the aquifer to 50 years or older for deeper portions of the aquifer. Shallow springs can have a significant component of fairly young water (< 5 years in age). Ground-water samples collected from 16 sites (12 wells and 4 springs) in the Leetown area were analyzed for more than 340 constituents. Only turbidity, indicator bacteria, and radon were typically present in concentrations exceeding U.S. Environmental Protection Agency (USEPA) drinking-water or aquatic life standards.

West Virginia↗

USGS1998

Mapping the Gulf of Maine with side-scan sonar: A new bottom-type classification for complex seafloors

The bedrock-framed seafloor in the northwestern Gulf of Maine is characterized by extreme changes in bathymetric relief and covered with a wide variety of surficial materials. Traditional methods of mapping cannot accurately represent the great heterogeneity of such a glaciated region. A new mapping scheme for complex seafloors, based primarily on the interpretation of side-scan sonar imagery, utilizes four easily recognized units: rock, gravel, sand and mud. In many places, however, the seafloor exhibits a complicated mixture or extremely 'patchy' distribution of the four basic units, which are too small to map individually. Twelve composite units, each a two-component mixture of the basic units, were established to represent this patchiness at a small scale (1:100,000). Using a geographic information system, these and all other available data (seismic profiles, grab samples, submersible dives and cores) were referenced to a common geographic base, superimposed on bathymetric contours and then integrated into surficial geologic maps of the regional inner continental shelf. This digital representation of the seafloor comprises a multidimensional, interactive model complete with explicit attributes (depth, bottom type) that allow for detailed analysis of marine environments.

Journal of Coastal Research↗

USGS1997

GSLIB-style programs for discriminant analysis and regionalized classification

Discriminant analysis is a statistical technique used to predict the group membership of a set of multivariate observations, each of which is assumed to arise from one of a set of distinct classes or groups. Each group is characterized by a certain distribution in multivariate space, and group allocations are based on the similarity of each sample to each group. Assuming multivariate normality, generalized distance measures based on the squared Mahalanobis distance from each sample to each group centroid arise as the natural measure of similarity. One can allocate samples to groups either on the basis of minimum generalized distance or, equivalently, maximum posterior probability of group membership. In earth science applications samples are often associated with geographic locations. In this situation regionalized classification can be used to produce a map representing group membership throughout the sampled domain. This can be accomplished by interpolating either generalized distances or membership probabilities from sample locations to regularly spaced grid nodes and comparing resulting grids to produce a classification map. This paper presents a set of GSLIB-style FORTRAN programs for performing discriminant analysis and regionalized classification. The program disco performs discriminant analysis and the programs xmd2cls and prb2cls combine interpolated distances and probabilities, respectively, to create a grid of predicted classifications. In addition, the utility program colbind allows the user to combine selected columns from different GSLIB-style data files into one file. ?? 1997 Elsevier Science Ltd.

Computers & Geosciences↗