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USGS2006

Regional survey of structural properties and cementation patterns of fault zones in the northern part of the Albuquerque Basin, New Mexico - Implications for ground-water flow

Motivated by the need to document and evaluate the types and variability of fault zone properties that potentially affect aquifer systems in basins of the middle Rio Grande rift, we systematically characterized structural and cementation properties of exposed fault zones at 176 sites in the northern Albuquerque Basin. A statistical analysis of measurements and observations evaluated four aspects of the fault zones: (1) attitude and displacement, (2) cement, (3) lithology of the host rock or sediment, and (4) character and width of distinctive structural architectural components at the outcrop scale. Three structural architectural components of the fault zones were observed: (1) outer damage zones related to fault growth; these zones typically contain deformation bands, shear fractures, and open extensional fractures, which strike subparallel to the fault and may promote ground-water flow along the fault zone; (2) inner mixed zones composed of variably entrained, disrupted, and dismembered blocks of host sediment; and (3) central fault cores that accommodate most shear strain and in which persistent low- permeability clay-rich rocks likely impede the flow of water across the fault. The lithology of the host rock or sediment influences the structure of the fault zone and the width of its components. Different grain-size distributions and degrees of induration of the host materials produce differences in material strength that lead to variations in width, degree, and style of fracturing and other fault-related deformation. In addition, lithology of the host sediment appears to strongly control the distribution of cement in fault zones. Most faults strike north to north-northeast and dip 55? - 77? east or west, toward the basin center. Most faults exhibit normal slip, and many of these faults have been reactivated by normal-oblique and strike slip. Although measured fault displacements have a broad range, from 0.9 to 4,000 m, most are <100 m, and fault zones appear to have formed mainly at depths less than 1,000 m. Fault zone widths do not exceed 40 m (median width = 15.5 m). The mean width of fault cores (0.1 m) is nearly one order of magnitude less than that of mixed zones (0.75 m) and two orders of magnitude less than that of damage zones (9.7 m). Cements, a proxy for localized flow of ancient ground water, are common along fault zones in the basin. Silica cements are limited to faults that are near and strike north to northwest toward the Jemez volcanic field north of the basin, whereas carbonate fault cements are widely distributed. Coarse sediments (gravel and sand) host the greatest concentrations of cement within fault zones. Cements fill some extension fractures and, to a lesser degree, are concentrated along shear fractures and deformation bands within inner damage zones. Cements are commonly concentrated in mixed zones and inner damage zones on one side of a fault and thus are asymmetrically distributed within a fault zone, but cement does not consistently lie on the basinward side of faults. From observed spatial patterns of asymmetrically distributed fault zone cements, we infer that ancient ground-water flow was commonly localized along, and bounded by, faults in the basin. It is apparent from our study that the Albuquerque Basin contains a high concentration of faults. The geometry of, internal structure of, and cement and clay distribution in fault zones have created and will continue to create considerable heterogeneity of permeability within the basin aquifers. The characteristics and statistical range of fault zone features appear to be predictable and consistent throughout the basin; this predictability can be used in ground-water flow simulations that consider the influence of faults.

New Mexico↗

USGS2020

Spatial variability in seasonal snowpack trends across the Rio Grande headwaters (1984 - 2017)

This study evaluated the spatial variability of trends in simulated snowpack properties across the Rio Grande headwaters of Colorado using the SnowModel snow evolution modeling system. SnowModel simulations were performed using a grid resolution of 100 m and 3-hourly time step over a 34-yr period (1984–2017). Atmospheric forcing was provided by phase 2 of the North American Land Data Assimilation System, and the simulations accounted for temporal changes in forest canopy from bark beetle and wildfire disturbances. Annual summary values of simulated snowpack properties [snow metrics; e.g., peak snow water equivalent (SWE), snowmelt rate and timing, and snow sublimation] were used to compute trends across the domain. Trends in simulated snow metrics varied depending on elevation, aspect, and land cover. Statistically significant trends did not occur evenly within the basin, and some areas were more sensitive than others. In addition, there were distinct trend differences between the different snow metrics. Upward trends in mean winter air temperature were 0.3°C decade −1 , and downward trends in winter precipitation were −52 mm decade −1 . Middle elevation zones, coincident with the greatest volumetric snow water storage, exhibited the greatest sensitivity to changes in peak SWE and snowmelt rate. Across the Rio Grande headwaters, snowmelt rates decreased by 20% decade −1 , peak SWE decreased by 14% decade −1 , and total snowmelt quantity decreased by 13% decade −1 . These snow trends are in general agreement with widespread snow declines that have been reported for this region. This study further quantifies these snow declines and provides trend information for additional snow variables across a greater spatial coverage at finer spatial resolution.

Colorado↗

USGS2015

Linking biophysical models and public preferences for ecosystem service assessments: a case study for the Southern Rocky Mountains

Through extensive research, ecosystem services have been mapped using both survey-based and biophysical approaches, but comparative mapping of public values and those quantified using models has been lacking. In this paper, we mapped hot and cold spots for perceived and modeled ecosystem services by synthesizing results from a social-values mapping study of residents living near the Pike–San Isabel National Forest (PSI), located in the Southern Rocky Mountains, with corresponding biophysically modeled ecosystem services. Social-value maps for the PSI were developed using the Social Values for Ecosystem Services tool, providing statistically modeled continuous value surfaces for 12 value types, including aesthetic, biodiversity, and life-sustaining values. Biophysically modeled maps of carbon sequestration and storage, scenic viewsheds, sediment regulation, and water yield were generated using the Artificial Intelligence for Ecosystem Services tool. Hotspots for both perceived and modeled services were disproportionately located within the PSI’s wilderness areas. Additionally, we used regression analysis to evaluate spatial relationships between perceived biodiversity and cultural ecosystem services and corresponding biophysical model outputs. Our goal was to determine whether publicly valued locations for aesthetic, biodiversity, and life-sustaining values relate meaningfully to results from corresponding biophysical ecosystem service models. We found weak relationships between perceived and biophysically modeled services, indicating that public perception of ecosystem service provisioning regions is limited. We believe that biophysical and social approaches to ecosystem service mapping can serve as methodological complements that can advance ecosystem services-based resource management, benefitting resource managers by showing potential locations of synergy or conflict between areas supplying ecosystem services and those valued by the public.

Regional Environmental Change↗

USGS2015

Mapping of coal quality using stochastic simulation and isometric logratio transformation with an application to a Texas lignite

Coal is a chemically complex commodity that often contains most of the natural elements in the periodic table. Coal constituents are conventionally grouped into four components (proximate analysis): fixed carbon, ash, inherent moisture, and volatile matter. These four parts, customarily measured as weight losses and expressed as percentages, share all properties and statistical challenges of compositional data. Consequently, adequate modeling should be done in terms of a logratio transformation, a requirement that is commonly overlooked by modelers. The transformation of choice is the isometric logratio transformation because of its geometrical and statistical advantages. The modeling is done through a series of realizations prepared by applying sequential simulation for the purpose of displaying the parts in maps incorporating uncertainty. The approach makes realistic assumptions and the results honor the data and basic considerations, such as percentages between 0 and 100, all four parts adding to 100% at any location in the study area, and a style of spatial fluctuation in the realizations equal to that of the data. The realizations are used to prepare different results, including probability distributions across a deposit, E-type maps displaying average properties, and probability maps summarizing joint fluctuations of several parts. Application of these maps to a lignite bed clearly delineates the deposit boundary, reveals a channel cutting across, and shows that the most favorable coal quality is to the north and deteriorates toward the southeast.

International Journal of Coal Geology↗

USGS2022

Large-scale distribution models for optimal prediction of Eastern black rail habitat within tidal ecosystems

Eastern black rails ( Laterallus jamaicensis jamaicensis ) are among the rarest and least-studied birds in North America and were recently listed as threatened under the U.S. Endangered Species Act. Spatial models that predict habitat quality across the subspecies range are therefore needed to inform conservation, recovery, and monitoring efforts for this rare bird. We used data from 47,585 call-broadcast surveys collected at 7906 sites over a 3-decade period (1990s, 2000s, 2010s; 23 total years) to build species distribution models for eastern black rails. We used hierarchical Bayesian occupancy models and predictive model selection to develop multi-scale models that optimally predict habitat suitability for eastern black rails within tidal wetlands while also accounting for imperfect detection of these cryptic birds during field surveys. We also used raster regression techniques to translate model predictions into 30-m resolution maps of habitat suitability for eastern black rails within tidal wetlands along the eastern seaboard of the United States. The model predicted suitability of breeding habitat as a function of wetland attributes (e.g., cover of high marsh and terrestrial border), hydrologic modification, and disturbance from human development measured over multiple spatial scales. We also found differences in habitat relationships for eastern black rails when compared to models that included both North American subspecies of black rail. Important results included negative effects of shrub-scrub wetlands, and strong positive effects of high marsh, terrestrial border, and impoundments on breeding season occupancy. Our study provides an example of integrating detection-non-detection data and modern statistical methods to build predictive distribution models for an extremely rare species, while also providing rigorous predictions of breeding habitat quality for the eastern black rail within tidal wetlands. These models will facilitate optimal monitoring, habitat conservation, and recovery planning efforts for eastern black rails and provide a foundation for future research and conservation of this imperiled bird.

Global Ecology and Conservation↗

USGS2010

Geomorphic Framework to assess changes to aquatic habitat due to flow regulation and channel and floodplain alteration, Cedar River, Washington

Flow regulation, bank armoring, and floodplain alteration since the early 20th century have contributed to significant changes in the hydrologic regime and geomorphic processes of the Cedar River in Washington State. The Cedar River originates in the Cascade Range, provides drinking water to the Seattle metropolitan area, and supports several populations of anadromous salmonids. Flow regulation currently has limited influence on the magnitude, duration, and timing of high-flow events, which affect the incubation of salmonids as well as the production and maintenance of their habitat. Unlike structural changes to the channel and floodplain, flow regulation may be modified in the short-term to improve the viability of salmon populations. An understanding of the effects of flow regulation on those populations must be discerned over a range of scales from individual floods that affect the size of individual year classes to decadal high flow regime that influences the amount and quality of channel and off-channel habitat available for spawning and rearing. We present estimates of reach-scale sediment budgets and changes to channel morphology derived from historical orthoimagery, specific gage analyses at four long-term streamflow-gaging stations to quantify trends in aggradation, and hydrologic statistics of the magnitude and duration of peak streamflows. These data suggest a gradient of channel types from unconfined, sediment-rich segments to confined, sediment-poor segments that are likely to have distinct responses to high flows. Particle-size distribution data and longitudinal water surface and streambed profiles for the 56 km downstream of Chester Morse Lake measured in 2010 show the spatial extent of preferred salmonid habitat along the Cedar River. These historical and current data constitute a geomorphic framework to help assess different river management scenarios for salmonid habitat and population viability. PDF version of a presentation on changes to aquatic habitat at the Cedar River in Washington state. Presented at the American Geophysical Union Fall Meeting 2010.

Washington↗

USGS2016

Environmental drivers of differences in microbial community structure in crude oil reservoirs across a methanogenic gradient

Stimulating in situ microbial communities in oil reservoirs to produce natural gas is a potentially viable strategy for recovering additional fossil fuel resources following traditional recovery operations. Little is known about what geochemical parameters drive microbial population dynamics in biodegraded, methanogenic oil reservoirs. We investigated if microbial community structure was significantly impacted by the extent of crude oil biodegradation, extent of biogenic methane production, and formation water chemistry. Twenty-two oil production wells from north central Louisiana, USA, were sampled for analysis of microbial community structure and fluid geochemistry. Archaea were the dominant microbial community in the majority of the wells sampled. Methanogens, including hydrogenotrophic and methylotrophic organisms, were numerically dominant in every well, accounting for, on average, over 98% of the total Archaea present. The dominant Bacteria groups were Pseudomonas, Acinetobacter , Enterobacteriaceae, and Clostridiales, which have also been identified in other microbially-altered oil reservoirs. Comparing microbial community structure to fluid (gas, water, and oil) geochemistry revealed that the relative extent of biodegradation, salinity, and spatial location were the major drivers of microbial diversity. Archaeal relative abundance was independent of the extent of methanogenesis, but closely correlated to the extent of crude oil biodegradation; therefore, microbial community structure is likely not a good sole predictor of methanogenic activity, but may predict the extent of crude oil biodegradation. However, when the shallow, highly biodegraded, low salinity wells were excluded from the statistical analysis, no environmental parameters could explain the differences in microbial community structure. This suggests that the microbial community structure of the 5 shallow, up-dip wells was different than the 17 deeper, down-dip wells. Also, the 17 down-dip wells had statistically similar microbial communities despite significant changes in environmental parameters between oil fields. Together, this implies that no single microbial population is a reliable indicator of a reservoir's ability to degrade crude oil to methane, and that geochemistry may be a more important indicator for selecting a reservoir suitable for microbial enhancement of natural gas generation.

Louisiana↗

USGS2024

Increasing seasonal variation in the extent of rivers and lakes from 1984 to 2022

Knowledge of the spatial and temporal distribution of surface water is important for water resource management, flood risk assessment, monitoring ecosystem health, constraining estimates of biogeochemical cycles and understanding our climate. While global-scale spatiotemporal change detection of surface water has significantly improved in recent years due to planetary-scale remote sensing and computing, it has remained challenging to distinguish the changing characteristics of rivers and lakes. Here we analyze the spatial extent of permanent and seasonal rivers and lakes globally over the past 38 years based on new data of river system extents and surface water trends. Results show that while the total permanent surface area of both rivers and lakes has remained relatively constant, the areas with intermittent seasonal coverage have increased by 12 % and 27 % for rivers and lakes, respectively. The increase is statistically significant in over 84 % of global water catchments based on Spearman's rank correlations (rho) above 0.05 and p values less than 0.05. The seasonal river extent is nearly 32 % larger than the previously observed annual mean river extent, suggesting large seasonal variations that impact not only ecosystem health but also estimations of terrestrial biogeochemical cycles of carbon. The outcomes of our analysis are shared as the Surface Area of Rivers and Lakes (SARL) database, serving as a valuable resource for monitoring and research of hydrological cycles, ecosystem accounting, and water management.

Hydrology and Earth System Sciences↗

USGS2008

Data to support statistical modeling of instream nutrient load based on watershed attributes, southeastern United States, 2002

This report presents and describes the digital datasets that characterize nutrient source inputs, environmental characteristics, and instream nutrient loads for the purpose of calibrating and applying a nutrient water-quality model for the southeastern United States for 2002. The model area includes all of the river basins draining to the south Atlantic and the eastern Gulf of Mexico, as well as the Tennessee River basin (referred to collectively as the SAGT area). The water-quality model SPARROW (SPAtially-Referenced Regression On Watershed attributes), developed by the U.S. Geological Survey, uses a regression equation to describe the relation between watershed attributes (predictors) and measured instream loads (response). Watershed attributes that are considered to describe nutrient input conditions and are tested in the SPARROW model for the SAGT area as source variables include atmospheric deposition, fertilizer application to farmland, manure from livestock production, permitted wastewater discharge, and land cover. Watershed and channel attributes that are considered to affect rates of nutrient transport from land to water and are tested in the SAGT SPARROW model as nutrient-transport variables include characteristics of soil, landform, climate, reach time of travel, and reservoir hydraulic loading. Datasets with estimates of each of these attributes for each individual reach or catchment in the reach-catchment network are presented in this report, along with descriptions of methods used to produce them. Measurements of nutrient water quality at stream monitoring sites from a combination of monitoring programs were used to develop observations of the response variable - mean annual nitrogen or phosphorus load - in the SPARROW regression equation. Instream load of nitrogen and phosphorus was estimated using bias-corrected log-linear regression models using the program Fluxmaster, which provides temporally detrended estimates of long-term mean load well-suited for spatial comparisons. The detrended, or normalized, estimates of load are useful for regional-scale assessments but should be used with caution for local-scale interpretations, for which use of loads estimated for actual time periods and employing more detailed regression analysis is suggested. The mean value of the nitrogen yield estimates, normalized to 2002, for 637 stations in the SAGT area is 4.7 kilograms per hectare; the mean value of nitrogen flow-weighted mean concentration is 1.2 milligrams per liter. The mean value of the phosphorus yield estimates, normalized to 2002, for the 747 stations in the SAGT area is 0.66 kilogram per hectare; the mean value of phosphorus flow-weighted mean concentration is 0.17 milligram per liter. Nutrient conditions measured in streams affected by substantial influx or outflux of water and nutrient mass across surface-water basin divides do not reflect nutrient source and transport conditions in the topographic watershed; therefore, inclusion of such streams in the SPARROW modeling approach is considered inappropriate. River basins identified with this concern include south Florida (where surface-water flow paths have been extensively altered) and the Oklawaha, Crystal, Lower Sante Fe, Lower Suwanee, St. Marks, and Chipola River basins in central and northern Florida (where flow exchange with the underlying regional aquifer may represent substantial nitrogen influx to and outflux from the surface-water basins).

Open-File Report↗

USGS2026

ENSO and PDO drive shoreline position anomalies in the U.S. Pacific Northwest

Sandy beaches act as buffers against various coastal hazards but are vulnerable to episodic (seasonal) and chronic (interannual) erosion. Understanding the variation of shoreline position, a key metric in coastal morphology, over a spectrum of time scales is therefore crucial in assessing hazard vulnerability. Long-standing research has investigated the role of El Niño-Southern Oscillation (ENSO), the dominant mode of climate variability in the Pacific Basin, in seasonal shoreline variability. Yet, ENSO’s chronic influence—and that of another Pacific climate mode, the Pacific Decadal Oscillation (PDO)—on shoreline anomalies remains poorly understood. Here, we examine the variability of sandy beaches in the US Pacific Northwest, a ∼750 km long coastal region on the US West Coast. We leverage 40 years (1984–2024) of shoreline data from publicly available Earth-observing (Landsat) satellite imagery at a high spatial resolution (>10,000 shore-normal transects at 50-m alongshore spacing) and employ Convergent Cross Mapping (CCM), a methodology for inferring causality in dynamical systems. We discover that strong El Niño years are signified by erosion (75.1% of transects), and strong La Niña years exhibit accretional behavior (73.4% of transects). Furthermore, we establish, for the first time, that both ENSO and PDO exert a statistically significant control on interannual shoreline variability, particularly on the alongshore component (in 95 and 100% of littoral cells, respectively), with water level fluctuations playing a critical role. This effort advances our understanding of the seasonal-to-interannual interactions between Pacific Basin climate variability and the PNW’s coastal morphodynamics, with implications for sediment management and coastal adaptation.

California, Oregon, Washington↗

USGS2017

Translating statistical species-habitat models to interactive decision support tools

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

PLoS ONE↗

USGS2020

Potential duration of aftershocks of the 2020 southwestern Puerto Rico earthquake

Abstract Aftershocks (earthquakes clustered spatially and chronologically near the occurrence of a causative earthquake) are ongoing in southwestern Puerto Rico after a series of earthquakes, which include a magnitude 6.4 earthquake that occurred near Barrio Indios, Guayanilla, on January 7, 2020, and affected the surrounding area. This report estimates the expected duration of these aftershocks by incorporating observations of aftershocks as of January 17, 2020, into a well-established statistical model of how earthquake sequences behave. Aftershocks will persist for years to decades, although with decreasing frequency, and earthquakes will likely be felt on a daily basis for up to several months. These estimates have significant uncertainty owing to different scenarios of how the earthquake sequence may evolve over time and could also change if a new large aftershock occurs. This report also estimates the amount of time remaining until the annual probability of magnitude 5, 6, and 7 or greater aftershocks—which could cause additional damage—decreases to 50, 25, 10, 5, and 1 percent. As of this writing, the chance of having a magnitude 6 or greater earthquake within a given year, going forward, will not fall below 25 percent for another 3 months to 3 years. The chance of having a magnitude 5 or greater earthquake will not fall below 25 percent for a decade or more. The aftershocks discussed in this report would be located in the same general area as the aftershocks that have already occurred. Our results do not imply a change in the risk of earthquakes in other parts of Puerto Rico. Resumen Las réplicas (terremotos agrupados espacial y cronológicamente cerca de la ocurrencia de un terremoto causante) están en curso en el suroeste de Puerto Rico después de una serie de terremotos, que incluyen un terremoto de magnitud 6.4, ocurrido cerca del Barrio Indios, Guayanilla, el 7 de enero de 2020 y que afectaron las áreas circundantes. Este informe estima la duración esperada de las réplicas incorporando observaciones de réplicas a partir del 17 de enero de 2020 en un modelo estadístico bien establecido de cómo se comportan las secuencias de terremotos. Las réplicas persistirán durante años o décadas, aunque con una frecuencia decreciente, y los terremotos probablemente se sentirán a diario durante varios meses. Estos estimados tienen una incertidumbre significativa debido a diferentes escenarios de cómo la secuencia del terremoto puede evolucionar con el tiempo y también podrían cambiar si ocurre una nueva réplica grande. Este informe también estima la cantidad de tiempo restante hasta que la probabilidad anual de réplicas de magnitud 5, 6 y 7 o más - que podría causar daños adicionales- disminuya a un 50, 25, 10, 5 y 1 por ciento. Al momento de escribir este artículo, la posibilidad de tener un terremoto de magnitud 6 en un año determinado, en el futuro, no caerá por debajo del 25 por ciento durante otros 3 meses a 3 años. La probabilidad de tener un terremoto de magnitud 5 o mayor no será inferior al 25 por ciento durante una década o más. Las réplicas discutidas en este informe se ubicarían en la misma área general que las réplicas que ya han ocurrido. Nuestros resultados no implican un cambio en el riesgo de terremotos en otras partes de Puerto Rico.

Puerto Rico↗

USGS1994

Land use in, and water quality of, the Pea Hill Arm of Lake Gaston, Virginia and North Carolina, 1988-90

The City of Virginia Beach currently (1994) supplies water to about 400,000 people in southeastern Virginia. The city plans to withdraw water from the Pea Hill Arm of Lake Gaston to meet projected water needs of the population to the year 2030. The purpose of this report is to (1) describe the temporal and spatial distribution of selected water-quality constituents, (2) document current (1989) land use and land cover in the Pea Hill Arm drainage basin, and (3) discuss relations, if any, between the quality of water in the inlets within the Pea Hill Arm and land uses. The report focuses on water-quality problems in the basin, including changes in concentrations of major ions, nutrients, and algae associated with urban development adjacent to water bodies. The Pea Hill Arm was classified as mesotrophic on the basis of the range of concentrations of total phosphorus (0.001 to 0.61 milligrams per liter); the range of concentrations of total organic-plus-ammonia nitrogen (0.2 to 1.4 milligrams per liter); and the range of concentrations of chlorophyll a (1.4 to 56 micrograms per liter). These water-quality data were collected at 3 feet below the water surface during water years 1989-90. Thermal stratification in Pea Hill Arm generally began in April and ended in September. Water below a depth of about 25 feet generally became anoxic by June. Destratification generally began in late September and was completed by November. Lake Gaston followed the same general stratification and destratification pattern as Pea Hill Arm, except Lake Gaston was partially destratified during the summer when large amounts of water were released from John H. Kerr Reservoir and Lake Gaston Dams. During water year 1988, streamflows were 33 percent below the long-term mean-annual streamflows at one of the major streams to Lake Gaston. Low streamflows contributed to elevated specific conductances and concentrations of sodium, calcium, magnesium, and alkalinity from October 1988 to February 1989 at sampling stations in the Pea Hill Arm and Lake Gaston. About 75 percent of the land use in the Pea Hill Arm is forest land. The remaining 25 percent of the Pea Hill Arm drainage basin is 8 percent pasture/open land, 8 percent open water, 6 percent residential land, and 3 percent cropland. No statistical relations are present between water-quality constituents measured and developed land uses within 11 basins in the Pea Hill Arm Basin, except during periods of stormwater runoff. During a stormwater-runoff event, there was a relation between total nitrite plus nitrate and land use (Kendall's tau correlation coefficient of 0.69). The relation between the developed land use and total nitrite plus nitrate can also be related to the increased ground-water inputs during high base-flow periods. Spatial differences in water-quality constituents as determined by Wilcoxon (matched-pairs) signed-rank tests and cluster analyses were longitudinal and primarily grouped into riverine, transition, and lacustrine zones. These zones were grouped on the basis of flow characteristics and nutrient concentrations.

North Carolina, Virginia↗

USGS2009

Shifts in the trophic base of intermittent stream food webs

Understanding spatial and temporal variation in the trophic base of stream food webs is critical for predicting population and community stability, and ecosystem function. We used stable isotope ratios ( 13 C/ 12 C, and 15 N/ 14 N) to characterize the trophic base of two streams in the Ozark Mountains of northwest Arkansas, U.S.A. We predicted that autochthonous resources would be more important during the spring and summer and allochthonous resources would be more important in the winter due to increased detritus inputs from the riparian zone during autumn leaf drop. We predicted that stream communities would demonstrate increased reliance on autochthonous resources at sites with larger watersheds and greater canopy openness. The study was conducted at three low-order sites in the Mulberry River Drainage (watershed area range: 81-232 km 2 ) seasonally in 2006 and 2007. We used circular statistics to examine community-wide shifts in isotope space among fish and invertebrate consumers in relation to basal resources, including detritus and periphyton. Mixing models were used to quantify the relative contribution of autochthonous and allochthonous energy sources to individual invertebrate consumers. Significant isotopic shifts occurred but results varied by season and site indicating substantial variation in the trophic base of stream food webs. In terms of temporal variation, consumers shifted toward periphyton in the summer during periods of low discharge, but results varied during the interval between summer and winter. Our results did not demonstrate increased reliance on periphyton with increasing watershed area or canopy openness, and detritus was important at all the sites. In our study, riffle-pool geomorphology likely disrupted the expected spatial pattern and stream drying likely impacted the availability and distribution of basal resources.

Hydrobiologia↗

USGS2001

Bird-landscape relations in the Chihuahuan Desert: Coping with uncertainties about predictive models

During the springs of 1995–1997, we studied birds and landscapes in the Chihuahuan Desert along part of the Texas–Mexico border. Our objectives were to assess bird–landscape relations and their interannual consistency and to identify ways to cope with associated uncertainties that undermine confidence in using such relations in conservation decision processes. Bird distributions were often significantly associated with landscape features, and many bird–landscape models were valid and useful for predictive purposes. Differences in early spring rainfall appeared to influence bird abundance, but there was no evidence that annual differences in bird abundance affected model consistency. Model consistency for richness (42%) was higher than mean model consistency for 26 focal species (mean 30%, range 0–67%), suggesting that relations involving individual species are, on average, more subject to factors that cause variation than are richness–landscape relations. Consistency of bird–landscape relations may be influenced by such factors as plant succession, exotic species invasion, bird species' tolerances for environmental variation, habitat occupancy patterns, and variation in food density or weather. The low model consistency that we observed for most species indicates the high variation in bird–landscape relations that managers and other decision makers may encounter. The uncertainty of interannual variation in bird–landscape relations can be reduced by using projections of bird distributions from different annual models to determine the likely range of temporal and spatial variation in a species' distribution. Stochastic simulation models can be used to incorporate the uncertainty of random environmental variation into predictions of bird distributions based on bird–landscape relations and to provide probabilistic projections with which managers can weigh the costs and benefits of various decisions. Uncertainty about the true structure of bird–landscape relations (structural uncertainty) can be reduced by ensuring that models meet important statistical assumptions, designing studies with sufficient statistical power, validating the predictive ability of models, and improving model accuracy through continued field sampling and model fitting. Uncertainty associated with sampling variation (partial observability) can be reduced by ensuring that sample sizes are large enough to provide precise estimates of both bird and landscape parameters. By decreasing the uncertainty due to partial observability, managers will improve their ability to reduce structural uncertainty.

Chihuahua, Coahuila, Nuevo León, Tamaulipas, Texas↗

USGS2016

Mortality monitoring design for utility-scale solar power facilities

Introduction Solar power represents an important and rapidly expanding component of the renewable energy portfolio of the United States (Lovich and Ennen, 2011; Hernandez and others, 2014). Understanding the impacts of renewable energy development on wildlife is a priority for the U.S. Fish and Wildlife Service (FWS) in compliance with Department of Interior Order No. 3285 (U.S. Department of the Interior, 2009) to “develop best management practices for renewable energy and transmission projects on the public lands to ensure the most environmentally responsible development and delivery of renewable energy.” Recent studies examining effects of renewable energy development on mortality of migratory birds have primarily focused on wind energy (California Energy Commission and California Department of Fish and Game, 2007), and in 2012 the FWS published guidance for addressing wildlife conservation concerns at all stages of land-based wind energy development (U.S. Fish and Wildlife Service, 2012). As yet, no similar guidelines exist for solar development, and no published studies have directly addressed the methodology needed to accurately estimate mortality of birds and bats at solar facilities. In the absence of such guidelines, ad hoc methodologies applied to solar energy projects may lead to estimates of wildlife mortality rates that are insufficiently accurate and precise to meaningfully inform conversations regarding unintended consequences of this energy source and management decisions to mitigate impacts. Although significant advances in monitoring protocols for wind facilities have been made in recent years, there remains a need to provide consistent guidance and study design to quantify mortality of bats, and resident and migrating birds at solar power facilities (Walston and others, 2015). In this document, we suggest methods for mortality monitoring at solar facilities that are based on current methods used at wind power facilities but adapted for the unique conditions encountered at solar facilities. In particular, unlike at wind-power facilities, the unimpeded access to almost all areas within the facilities, the typically flat terrain, and general absence of thick vegetation allow distance-sampling techniques (Buckland and others, 2001, 2004) to be exploited to advantage at industrial solar sites. These protocols build on the work of Nicolai and others (2011), and as our understanding and techniques for monitoring improve, the methods may be further modified to incorporate improvements in the future. We present case studies based on monitoring methods currently implemented at different utility-scale solar facilities to illustrate how distance-sampling techniques may improve overall detectability without substantially increasing costs. Every facility is unique, and the protocols presented may be adapted based on specific monitoring objectives and conditions at each site. We provide guidance for designing monitoring programs whose objective it is to estimate the total number of bird and bat fatalities occurring at a facility over an extended period of time. We address spatial variation in causes of mortality, as well as potential sources of imperfect detection, for example, animals falling in or moving to unsearched areas, carcasses removed by predators, and carcasses missed by searchers. We suggest methods to estimate and account for each source of imperfect detection. This document focuses on monitoring design only and does not discuss approaches for estimating mortality from collected data. The development of statistically sound estimators relevant to the solar context is a current topic of research, although there are already strong foundations for estimation with distance-sampling methods in similar open, arid environments (Anderson and others, 2001; Freilich and others, 2005). Nonetheless, if protocols described in this document are followed, the resulting data will be adequate and sufficient for estimating mortality using newly formulated estimators.

Open-File Report↗

USGS2024

Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020

Peak-flow (flood) frequency analysis is essential to water-resources management applications, including the design of critical infrastructure such as bridges and culverts, and floodplain mapping. Federal guidelines for performing peak-flow flood frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C, which documents the guidelines for determining annual peak streamflow frequency, is that, for basins without major hydrologic alterations (for example, regulation, diversion, and urbanization), statistical properties of the distribution of annual peak streamflows are stationary; that is, the mean, variance, and skew are constant through time. Nonstationarity is a statistical property of a peak-flow series such that the long-term (on the order of decades) distributional properties change one or more times either gradually or abruptly through time. Individual nonstationarities may be attributed to one source such as flow regulation, land-use change, or climate but are often the result of a combination of sources, making detection and attribution of nonstationarities challenging. In response to a growing concern regarding nonstationarity in peak streamflows in the region, the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, assessed the potential nonstationarity in peak streamflows in the north-central United States. This chapter characterizes the effects of natural hydroclimatic shifts and potential climate change on annual peak streamflows in the State of South Dakota. Annual peak and daily streamflow as well as model-simulated gridded climatic data were examined for temporal monotonic trends, change points, and other statistical properties indicative of changing climatic and environmental conditions. Changes in annual peak and daily flows were evaluated among 13, 35, and 81 qualifying U.S. Geological Survey streamgages for the 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, to September 30, 2020) in South Dakota, respectively. No qualifying streamgages were in the 100-year trend period in the State. Statistical tests for autocorrelation (independent and identically distributed assumption), monotonic trends, and change points in the median and scale are analyzed to evaluate potential stationarity violations (nonstationarity) for performing at-site peak-flow flood-frequency analysis. The trends are reported using a likelihood approach as an alternative to simply reporting significant trends with an arbitrary p -value cutoff point. A distinct east-west spatial pattern of likely upward and downward monotonic trends and change points, respectively, was detected in 75- and 50-year trend periods, but an inconsistent spatial pattern was detected in the 30-year trend period. Additionally, change points in the median annual peak streamflows were detected in the late 1970s and early 1980s in the western part of the State, but in the east, the change point was more commonly detected in 1992–93. A similar east-west spatial pattern of likely upward and downward trends was detected in the annual peak-flow timing, the day of the year of the annal peak streamflow. In the western part of the State, the annual peak streamflows are arriving earlier, but in the east, the annual peak streamflows are arriving later. A peaks-over-threshold (POT) analysis where, on average, there are two events per year (POT2) and four events per year (POT4) was also used to evaluate changes in the frequency (count) of daily streamflows exceeding the threshold. Similar to detected changes in the annual peak streamflow, an east-west likely upward or downward change corresponding to an increase or decrease, respectively, in the frequency of daily streamflow greater than a POT2 and POT4 threshold was detected. A monthly water-balance model was used to evaluate hydroclimatic variation in annual and seasonal precipitation, snowfall, potential evapotranspiration, and soil moisture storage for all qualifying streamgages in the 75-, 50-, and 30-year trend periods. Detected trends in the annual hydroclimatic metrics for the 75- and 50-year trend periods indicate a spatially consistent statewide increase in precipitation, decrease in snowfall, increase in potential evapotranspiration, and increase in soil moisture storage. Furthermore, detected trends in seasonal precipitation in the 75- and 50-year trend periods highlight a pronounced change in precipitation in winter and later into the summer season, especially in the 50-year trend period in the eastern part of the State. Statewide increases in seasonal soil moisture storage were also detected, highlighting year-round increasing flood magnitudes, particularly in the eastern part of the State. Based on the results of these stationarity tests for the qualifying streamgages in South Dakota among the 75-, 50-, and 30-year trend periods, consistent temporal and spatial patterns of nonstationarity were detected among the 75- and 50-year trend periods. Furthermore, when nonstationarity is detected in daily streamflow, increased streamflow and volume (increasing frequency in POT), as well as potentially bridge scour, may have implications on culvert and highway design in the eastern part of South Dakota. Thus, when performing at-site peak-flow flood-frequency analyses in South Dakota, potential nonstationarities and alternative approaches are important considerations.

South Dakota↗

USGS2020

Social Values for Ecosystem Services, version 4.0 (SolVES 4.0)—Documentation and user manual

The geographic information system tool, Social Values for Ecosystem Services (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 4.0 provides an open-source version of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by factors such as their attitudes and preferences regarding public uses (for example, motorized recreation and logging). As with previous versions, SolVES 4.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 4.0 has been developed with Python using a QGIS user interface and a PostgreSQL database for required data. SolVES is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relation between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methods can be evaluated. SolVES 4.0 provides an improved open-source, public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of biophysical and social contexts including mountain, forest, coastal, riparian, agricultural, and urban environments around the globe.

Techniques and Methods↗