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At least 811 records · Page 45Linked to original sources
USGS2015

Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual

The geographic information system (GIS) tool, S ocial V alues for E cosystem S ervices (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 3.0 continues to extend the functionality 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 their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with previous versions, SolVES 3.0 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 3.0 is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relationship 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 methodology can be evaluated. SolVES 3.0 provides an improved 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 physical and social contexts ranging from forest and rangeland to coastal and marine.

Open-File Report↗
USGS2001

Coastal change analysis program implemented in Louisiana

Landsat Thematic Mapper images from 1990 to 1996 and collateral data sources were used to classify the land cover of the Mermentau River Basin (MRB) within the Chenier Plain of coastal Louisiana. Landcover classes followed the definition of the National Oceanic and Atmospheric Administration's Coastal Change Analysis Program; however, classification methods had to be developed as part of this study for attainment of these national classification standards. Classification method developments were especially important when classes were spectrally inseparable, when classes were part of spatial and spectral continuums, when the spatial resolution of the sensor included more than one landcover type, and when human activities caused abnormal transitions in the landscape. Most classification problems were overcome by using one or a combination of techniques, such as separating the MRB into subregions of commonality, applying masks to specific land mixtures, and highlighting class transitions between years that were highly unlikely. Overall, 1990, 1993, and 1996 classification accuracy percentages (associated kappa statistics) were 80% (0.79), 78% (0.76), and 86% (0.84), respectively. Most classification errors were associated with confusion between managed (cultivated land) and unmanaged grassland classes; scrub shrub, grasslands and forest classes; water, unconsolidated shore and bare land classes; and especially in 1993, between water and floating vegetation classes. Combining cultivated land and grassland classes and water and floating vegetation classes into single classes accuracies for 1990, 1993, and 1996 increased to 82%, 83%, and 90%, respectively. To improve the interpretation of landcover change, three indicators of landcover class stability were formulated. Location stability was defined as the percentage of a landcover class that remained as the same class in the same location at the beginning and the end of the monitoring period. Residence stability was defined as the percent change in each class within the entire MRB during the monitoring period. Turnover was defined as the addition of other landcover classes to the target landcover class during the defined monitoring period. These indicators allowed quick assessment of the dynamic nature of landcover classes, both in reference to a spatial location and to retaining their presence throughout the MRB. Examining the landcover changes between 1990 to 1993 and 1993 to 1996, led us to five principal findings: (1) Landcover turnover is maintaining a near stable logging cycle, although the locations of grassland, scrub shrub, and forest areas involved in the cycle appeared to change. (2) Planting of seedlings is critical to maintaining cycle stability. (3) Logging activities tend to replace woody land mixed forests with woody land evergreen forests. (4) Wetland estuarine marshes are expanding slightly. (5) Wetland palustrine marshes and mature forested wetlands in the MRB are relatively stable.

Louisiana↗
USGS2024

Deep learning for water quality

Understanding and predicting the quality of inland waters are challenging, particularly in the context of intensifying climate extremes expected in the future. These challenges arise partly due to complex processes that regulate water quality, and arduous and expensive data collection that exacerbate the issue of data scarcity. Traditional process-based and statistical models often fall short in predicting water quality. In this Review, we posit that deep learning represents an underutilized yet promising approach that can unravel intricate structures and relationships in high-dimensional data. We demonstrate that deep learning methods can help address data scarcity by filling temporal and spatial gaps and aid in formulating and testing hypotheses via identifying influential drivers of water quality. This Review highlights the strengths and limitations of deep learning methods relative to traditional approaches, and underscores its potential as an emerging and indispensable approach in overcoming challenges and discovering new knowledge in water-quality sciences.

Nature Water↗
USGS2012

Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database

The U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database contains estimates of bottom stress and sediment mobility for the U.S. continental shelf. This U.S. Geological Survey database provides information that is needed to characterize sea floor ecosystems and evaluate areas for human use. The estimates contained in the database are designed to spatially and seasonally resolve the general characteristics of bottom stress over the U.S. continental shelf and to estimate sea floor mobility by comparing critical stress thresholds based on observed sediment texture data to the modeled stress. This report describes the methods used to make the bottom stress and mobility estimates, statistics used to characterize stress and mobility, data validation procedures, and the metadata for each dataset and provides information on how to access the database online.

Open-File Report↗
USGS2010

Hydrogeomorphic segments and hydraulic microhabitats of the Niobrara River, Nebraska— With special emphasis on the Niobrara National Scenic River

The Niobrara River is an ecologically and economically important resource in Nebraska. The Nebraska Department of Natural Resources’ recent designation of the hydraulically connected surface- and groundwater resources of the Niobrara River Basin as “fully appropriated” has emphasized the importance of understanding linkages between the physical and ecological dynamics of the Niobrara River so it can be sustainably managed. In cooperation with the Nebraska Game and Parks Commission, the U.S. Geological Survey investigated the hydrogeomorphic and hydraulic attributes of the Niobrara River in northern Nebraska. This report presents the results of an analysis of hydrogeomorphic segments and hydraulic microhabitats of the Niobrara River and its valley for the approximately 330-mile reach from Dunlap Diversion Dam to its confluence with the Missouri River. Two spatial scales were used to examine and quantify the hydrogeomorphic segments and hydraulic microhabitats of the Niobrara River: a basin scale and a reach scale. At the basin scale, digital spatial data and hydrologic data were analyzed to (1) test for differences between 36 previously determined longitudinal hydrogeomorphic segments; (2) quantitatively describe the hydrogeomorphic characteristics of the river and its valley; and (3) evaluate differences in hydraulic microhabitat over a range of flow regimes among three fluvial geomorphic provinces. The statistical analysis of hydrogeomorphic segments resulted in reclassification rates of 3 to 28 percent of the segments for the four descriptive geomorphic elements. The reassignment of classes by discriminant analysis resulted in a reduction from 36 to 25 total hydrogeomorphic segments because several adjoining segments shared the same ultimate class assignments. Virtually all of the segment mergers were in the Canyons and Restricted Bottoms (CRB) fluvial geomorphic province. The most frequent classes among hydrogeomorphic segments, and the dominant classes per unit length of river, are: a width-restricted valley confinement condition, sinuous-planview pattern, irregular channel width, and an alternate bar configuration. The Niobrara River in the study area flows through a diversity of fluvial geomorphic settings in its traverse across northern Nebraska. In the Meandering Bottoms (MB) fluvial geomorphic province, river discharge magnitudes are low, and the valley exerts little control on the channel-planview pattern. Within the CRB province, the river flows over a diversity of geologic formations, and the valley and river narrow and expand in approximate synchronicity. In the Braided Bottoms (BB) fluvial geomorphic province, the river primarily flows over Cretaceous Pierre Shale, the valley and channel are persistently wide, and the channel slope is generally uniform. The existence of vegetated islands and consequent multithread channel environments, indicated by a higher braided index, mostly coincided with reaches having gentler slopes and less unit stream power. Longitudinal hydrology curves indicate that the flow of the Niobrara River likely is dominated by groundwater as far downstream as Norden. Unit stream power values in the study area vary between 0 and almost 2 pounds per foot per second. Within the MB province, unit stream power steadily increases as the Niobrara gains discharge from groundwater inflow, and the channel slope steepens. The combination of steep slopes, a constrained channel width, and persistent flow within the CRB province results in unit stream power values that are between three and five times greater than those in less confined segments with comparable or greater discharges. With the exception of hydrogeomorphic segment 3, which is affected by Spencer Dam, unit stream power values in the BB province are generally uniform. Channel sinuosity values in the study area varied generally between 1 and 2.5, but with locally higher values measured in the MB province and at the entrenched bedrock meanders of hydrogeomorphic segment 18 in the CRB province. The differences in channel morphology and hydraulic geometries between fluvial geomorphic provinces are evident in the types, relative abundance, and response of hydraulic microhabitats to changing discharges. The four gaging stations chosen for hydraulic microhabitat analysis are distributed among three different fluvial geomorphic provinces. In the MB province, the smaller channel and lower discharges resulted in the dominance of shallow and intermediate-depth hydraulic environments with the vast majority of hydraulic microhabitat restricted to shallow categories even during upper-decile discharges. In the CRB province, intermediate depth hydraulic conditions, particularly intermediate-swift, dominate over all ranges of discharge. Hydraulic microhabitat conditions were most diverse in the BB province, with most hydraulic microhabitat categories present over the entire range of discharges analyzed. The calculated differences in hydraulic microhabitat distributions, abundance, and adjustments between streamflow-gaging stations were the result of differences in physical structure of the channel and subsequent channel hydraulic geometry. At the reach scale, field measurements made in water years 2008 and 2009 in four study reaches within the Scenic Reach were used to (1) characterize the elevation and geomorphic processes associated with fluvial landforms, (2) build hydraulic geometry relations, (3) examine flow hydraulics over a range of discharges, and (4) examine the types and responses of hydraulic microhabitats to a range of flow magnitudes. Four landform groups were identified and named in order of increasing elevation: low flood plains, intermediate flood plains, low terraces, and high terraces. The terraces were poorly characterized because the surveys did not extend across the full width of the alluvial valley bottom. The two lowest fluvial landforms are likely active in the modern hydroclimatic regime. Sediment samples obtained in the study reaches indicate that the primary bed material in the active channel ranged in size from coarse silt to coarse sand. Grain-size distributions from samples also indicate that the bed of the Niobrara River among the study reaches coarsens and has increasing grainsize variability in the downstream direction. Values of at-a-station hydraulic geometry exponents indicate that the Niobrara River in the study reaches adjusts its geometry to changing discharges primarily through increases in flow depth and velocity. Relations at one cross section indicated that, at least locally, changes in width were also an important channel adjustment mechanism. Hydraulic behavior over the range of flows measured was not consistent among all study reaches, but two general modes of hydraulic behavior were observed in the reaches with substantial coverage of the bed by fine sediment. At the Sunny Brook and Muleshoe study reaches, average boundary-shear stress remained approximately constant, and hydraulic resistance decreased, for discharges below 900 cubic feet per second (ft 3 /s). Above 900 ft 3 /s, average boundary shear stress and hydraulic resistance both increased. The Rock Barn study reach did not exhibit the same two-mode hydraulic behavior observed at the Sunny Brook and Muleshoe reaches. The coincident increase in boundary shear stress above 900 ft 3 /s observed at the Sunny Brook and Muleshoe study reaches represents a potential hydraulic threshold above which bedload transport rates were likely to increase markedly. No consistent bed-adjustment pattern (scour or fill) was identified in the study reaches over the range of flows or over the measurement season. Analysis of hydraulic microhabitats over the range of discharges measured at the study reaches indicates that some percentage of most habitat niche categories was available for at least one discharge condition, but the majority of hydraulic habitat available was within the intermediate-swift and deepswift habitat niche categories. Deep-swift conditions dominated nearly all study reaches under all measured discharge conditions. Slight differences in habitat distributions were observed between the study reaches with substantial coverage of the bed by fine sediment—Sunny Brook, Muleshoe, and Rock Barn—and the bedrock-dominated reach, Crooked Creek. Although the four study reaches occupy three different hydrogeomorphic segments, the types, relative abundance, and response of hydraulic microhabitat niche distributions to changing discharge conditions generally were similar among all reaches.

Nebraska↗
USGS2013

Sediment distribution and hydrologic conditions of the Potomac aquifer in Virginia and parts of Maryland and North Carolina

Sediments of the heavily used Potomac aquifer broadly contrast across major structural features of the Atlantic Coastal Plain Physiographic Province in eastern Virginia and adjacent parts of Maryland and North Carolina. Thicknesses and relative dominance of the highly interbedded fluvial sediments vary regionally. Vertical intervals in boreholes of coarse-grained sediment commonly targeted for completion of water-supply wells are thickest and most widespread across the central and southern parts of the Virginia Coastal Plain. Designated as the Norfolk arch depositional subarea, the entire sediment thickness here functions hydraulically as a single interconnected aquifer. By contrast, coarse-grained sediment intervals are thinner and less widespread across the northern part of the Virginia Coastal Plain and into southern Maryland, designated as the Salisbury embayment depositional subarea. Fine-grained intervals that are generally avoided for completion of water-supply wells are increasingly thick and widespread northward. Fine-grained intervals collectively as thick as several hundred feet comprise two continuous confining units that hydraulically separate three vertically spaced subaquifers. The subaquifers are continuous northward but merge southward into the single undivided Potomac aquifer. Lastly, far southeastern Virginia and northeastern North Carolina are designated as the Albemarle embayment depositional subarea, where both coarse- and fine-grained intervals are of only moderate thickness. The entire sediment thickness functions hydraulically as a single interconnected aquifer. A substantial hydrologic separation from overlying aquifers is imposed by the upper Cenomanian confining unit. Potomac aquifer sediments were deposited by a fluvial depositional complex spanning the Virginia Coastal Plain approximately 100 to 145 million years ago. Westward, persistently uplifted granite and gneiss source rocks sustained a supply of coarse-grained sand and gravel. Immature, high-gradient braided streams deposited longitudinal bars and channel fills across the Norfolk arch subarea. By contrast, across the Salisbury and Albemarle embayment subareas, mature, medium- to low-gradient meandering streams deposited medium- to coarse-grained channel fills and point bars segregated from fine-grained overbank deposits. The Virginia depositional complex merged northward across the Salisbury embayment subarea with another complex in Maryland. Here, additional sediments were received from schist source rocks that underwent three cycles of initial uplift and rapid erosion followed by crustal stability and erosional leveling. Because of the predominance of coarse-grained sediments, transmissivity, hydraulic conductivity, and regional velocities of lateral flow through the Potomac aquifer are greatest across the Norfolk arch depositional subarea, but decrease progressively northward with increasingly fine-grained sediments. Confining units hydraulically separate the Potomac aquifer from overlying aquifers, as indicated by large vertical hydraulic gradients. By contrast, most of the Potomac aquifer internally functions hydraulically as a single interconnected aquifer, as indicated by uniformly small vertical gradients. Most fine-grained sediments within the aquifer do not hydraulically separate overlying and underlying coarse-grained sediments. Across the Salisbury embayment depositional subarea, however, hydraulic separation among the vertically spaced subaquifers is imposed by the intervening confining units. The Potomac aquifer is the largest and most heavily used source of groundwater in the Virginia Coastal Plain. Water-level declines as great as 200 feet create the potential for saltwater intrusion. Conventional stratigraphic correlation has been generally ineffective at accurately characterizing complexly distributed fluvial sediments that compose the Potomac aquifer. Consequently, the aquifer’s internal hydraulic connectivity and overall hydrologic function have not been well understood. Water-supply planning and development efforts have been hampered, and interpretations of regulatory criteria for allowable water-level declines have been ambiguous. An investigation undertaken during 2010–11 by the U.S. Geological Survey, in cooperation with the Virginia Department of Environmental Quality, provides a comprehensive regional description of the spatial distribution of Potomac aquifer sediments and their relation to hydrologic conditions. Altitudes and thicknesses of 2,725 vertical sediment intervals represent the spatial distribution of Potomac aquifer sediments in the Virginia Coastal Plain and adjacent parts of Maryland and North Carolina. Sediment intervals are designated as either dominantly coarse or fine grained and were determined by interpretation of geophysical logs and ancillary information from 456 boreholes. Sediment-interval and borehole summary statistical data indicate regional trends in sediment lithology and stratigraphic continuity, upon which three structurally based and hydrologically distinct sediment depositional subareas are designated. Broad patterns of sediment deposition over time are inferred from published sediment pollen-age data. Discrepancies in previously drawn hydrostratigraphic relations between southeastern Virginia and northeastern North Carolina are partly resolved based on borehole geophysical logs and a recently documented geologic map and corehole. A conceptual model theorizes the depositional history of the sediments and geologically accounts for their distribution. Documented pumping tests of the Potomac aquifer at 197 locations produced 336 values of transmissivity and 127 values of storativity. Based on effective aquifer thicknesses, 296 values of sediment hydraulic conductivity and 113 values of sediment specific storage are calculated. Vertical hydraulic gradients are calculated from 9,479 pairs of water levels measured between November 17, 1953, and October 4, 2011, in 129 closely spaced pairs of wells. Borehole sediment-interval and related data provide a means to achieve high yielding production wells in the Potomac aquifer by site-specific targeting of drilling operations toward water-bearing coarse-grained sand and gravel. Advance knowledge of the potential of different parts of the aquifer also aids in planning optimal groundwater-development areas. Depositional subareas further provide a possible context for resource management. Current (2013) regulatory limits on water-level declines are relative to top surfaces of subdivided upper, middle, and lower Potomac aquifers across the entire Virginia Coastal Plain, but have the potential to exceed the same limit relative to a single undivided Potomac aquifer. By contrast, designation of the sediments as a single aquifer in the Norfolk arch and Albemarle embayment subareas—and as a series of vertically spaced subaquifers and intervening confining units in the Salisbury embayment subarea—best reflects understanding of the Potomac aquifer and can avoid the potential for excessive water-level declines. Simulation modeling to evaluate effects of groundwater withdrawals could be designed similarly, including vertical discretization and (or) zonation of the Potomac aquifer based on depositional subareas and a geostatistical distribution of aquifer properties derived from borehole sediment-interval data. Further resource-management information needs extend beyond the developed part of the Potomac aquifer, particularly across the Northern Neck and Middle Peninsula where only the shallowest part of the aquifer is known, and include structural aspects such as faults, basement bedrock, and the Chesapeake Bay impact crater.

Maryland, North Carolina, Virginia↗
USGS2013

Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are deterministic. These models extend spatially the static stability models adopted in geotechnical engineering and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the existing models is the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of shallow rainfall-induced landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a stochastic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, i.e. the Frontignano (Italy) and the Mukilteo (USA) areas, respectively. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the Message Passing Interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

Geoscientific Model Development and Discussions↗
USGS2014

Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of the Vital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year −1 for all indicators and is appropriate for detecting a 1 % trend·year −1 in most indicators.

New Jersey, Pennsylvania, Virginia, West Virginia↗
USGS2016

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4–8. Training data were selected from map products of the U.S. Geological Survey’s Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening ‘‘Function of mask” (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2021

Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas

Ostracoda (bivalved Crustacea) comprise a significant part of the benthic meiofauna in the Pacific-Arctic region, including more than 50 species, many with identifiable ecological tolerances. These species hold potential as useful indicators of past and future ecosystem changes. In this study, we examined benthic ostracodes from nearly 300 surface sediment samples, >34,000 specimens, from three regions—the northern Bering, Chukchi and Beaufort Seas—to establish species’ ecology and distribution. Samples were collected during various sampling programs from 1970 through 2018 on the continental shelves at 20 to ~100m water depth. Ordination analyses using species’ relative frequencies identified six species, Normanicythere leioderma , Sarsicytheridea bradii , Paracyprideis pseudopunctillata , Semicytherura complanata , Schizocythere ikeyai , and Munseyella mananensis , as having diagnostic habitat ranges in bottom water temperatures, salinities, sediment substrates and/or food sources. Species relative abundances and distributions can be used to infer past bottom environmental conditions in sediment archives for paleo-reconstructions and to characterize potential changes in Pacific-Arctic ecosystems in future sampling studies. Statistical analyses further showed ostracode assemblages grouped by the summer water masses influencing the area. Offshore-to-nearshore transects of samples across different water masses showed that complex water mass characteristics, such as bottom temperature, productivity, as well as sediment texture, influenced the relative frequencies of ostracode species over small spatial scales. On the larger biogeographic scale, synoptic ordination analyses showed dominant species— N . leioderma (Bering Sea), P . pseudopunctillata (offshore Chukchi and Beaufort Seas), and S . bradii (all regions)—remained fairly constant over recent decades. However, during 2013–2018, northern Pacific species M . mananensis and S . ikeyai increased in abundance by small but significant proportions in the Chukchi Sea region compared to earlier years. It is yet unclear if these assemblage changes signify a meiofaunal response to changing water mass properties and if this trend will continue in the future. Our new ecological data on ostracode species and biogeography suggest these hypotheses can be tested with future benthic monitoring efforts.

PLoS ONE↗
USGS2020

Black oystercatcher (Haematopus bachmani) population size, use of marine reserve complexes, and spatial distribution in Oregon

The Black Oystercatcher is a large shorebird found along the west coast of North America. Because of their small global population size, low reproductive rate, and dependence on rocky intertidal habitats, they are considered a “species of high conservation concern” and may act as an indicator of intertidal ecosystem health. In 2015, the Audubon Society of Portland initiated a 3-year shore-based population survey in Oregon building upon long-term monitoring previously conducted by the U.S. Geological Survey (USGS) and others. The objectives were to 1) Estimate the current minimum population of breeding Black Oystercatchers in Oregon and to compare that to previous estimates to better understand the population trend; 2) Document oystercatcher abundance adjacent to the Oregon’s system of Marine Reserves and Marine Protected Areas; and 3) Describe spatial distribution of breeding oystercatchers along the coast. We targeted all rocky shoreline habitats along Oregon’s coastline to perform abundance surveys each spring. A total of 75 survey routes were sampled using a standardized protocol. Trained volunteer community scientists conducted the majority of the surveys. We used N-mixture statistical models to estimate oystercatcher population size and probability of detection. Population estimates from the best fitting models were consistent, with estimates ranging from 506 oystercatchers in 2016 (95% credible interval, 463-560) to 629 (548-743) in 2015. These estimates indicated a small but stable population. Probability of detection remained consistent across years (ranging from 0.51 to 0.53). The effect of geographic region corresponded with greater bird density in the southern region of Oregon. Oystercatcher abundance adjacent to MR/MPAs accounted for between 12.4-18.3% of the total population estimate which was lower than expected (~25%). We recommend that subsequent conservation efforts directed on Black Oystercatchers in Oregon balance limiting human disturbance, particularly on the north and central coasts, with ensuring protection of core habitats on the south coast where much of the population resides.

Oregon↗
USGS2013

Mercury bioaccumulation in fishes from subalpine lakes of the Wallowa-Whitman National Forest, northeastern Oregon and western Idaho

Mercury (Hg) is a globally distributed pollutant that poses considerable risks to human and wildlife health. Over the past 150 years since the advent of the industrial revolution, approximately 80 percent of global emissions have come from anthropogenic sources, largely fossil fuel combustion. As a result, atmospheric deposition of Hg has increased by up to 4-fold above pre-industrial times. Because of their isolation, remote high-elevation lakes represent unique environments for evaluating the bioaccumulation of atmospherically deposited Hg through freshwater food webs, as well as for evaluating the relative importance of Hg loading versus landscape influences on Hg bioaccumulation. The increase in Hg deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in Hg emissions may propagate to changes in Hg bioaccumulation and ecological risk. In this study, we evaluated Hg concentrations in fishes of high-elevation, sub-alpine lakes in the Wallowa-Whitman National Forest in northeastern Oregon and western Idaho. Our goals were to (1) assess the magnitude of Hg contamination in small-catchment lakes to evaluate the risk of atmospheric Hg to human and wildlife health, (2) quantify the spatial variability in fish Hg concentrations, and (3) determine the ecological, limnological, and landscape factors that are best correlated with fish total mercury (THg) concentrations in these systems. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. Importantly, our top statistical model explained 87 percent of the variability in fish THg concentrations among lakes with four key landscape and limnological variables— catchment conifer density (basal area of conifers within a lake’s catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. The basal area of conifers within a lake’s catchment was by far the most important variable explaining fish THg concentrations, with an increase in THg concentrations of more than 400 percent across the forest density spectrum. Across all study lakes, fish THg concentrations ranged from 0.004 to 0.438 milligrams per kilogram wet weight (mg/kg ww). Only a single individual fish sample exceeded the U.S. Environmental Protection Agency’s (USEPA) human health tissue residue criteria of 0.3 mg/kg ww. However, 54 percent of fish (N=177) exceeded the more stringent tissue residue criteria (0.04 mg/kg ww) adopted by the Oregon Department of Environmental Quality to better protect subsistence fishers. Additionally, 2 and 10 percent of fish exceeded levels associated with reduced common loon reproduction and behavior, respectively. Whereas 25 and 68 percent of fish sampled exceeded concentrations deemed protective of mink and kingfisher, respectively. These results suggest that THg concentrations may be present in these lakes at levels associated with ecological risk. It is important to note however, that accurate inference on potential impairment cannot be made within the context of this study design and further research is needed to better quantify these risks.

Oregon;Idaho↗
USGS2020

Modeling occupancy of rare stream fish species in the upper Cumberland and Kentucky River Basins

Biological conservation often requires an understanding of how environmental conditions affect species occurrence and detection probabilities. We used a hierarchical framework to evaluate these effects for several Appalachian stream fish species of conservation concern: Chrosomus cumberlandensis (BSD; blackside dace), Etheostoma sagitta (CAD; Cumberland arrow darter), and Etheostoma spilotum (KAD; Kentucky arrow darter). Etheostoma susanae (Cumberland darter) also is present in the study area but was too rare to model in this analysis. In this study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, fish and habitat data were collected from 205 randomly selected stream sites in the upper Cumberland and Kentucky River Basins (120 and 85 sites, respectively) of Kentucky and Tennessee. Sites were sampled with 10 spatial replicates (2 meter x 5 meter electrofishing zones) to enable estimation of detection probabilities and environmental effects. The best models (that is, lowest Akaike information criterion scores) showed the effects of agriculture (negative) on occurrence of BSD and stream conductivity (negative) on occurrence of CAD and KAD. These effects were statistically more important than measures of basin area, elevation, and substrate size. Conductivity and agriculture showed nonlinear effects on species occurrence, and effects of conductivity were more precise above 400 microsiemens per centimeter than below this threshold. Models incorporated detection-level effects of electrofishing time (positive), flow velocity (negative), sand substrate (positive), and gravel/cobble substrate (negative). Models accounting for detection of BSD estimated occupancy rates similar to the observed proportion of occupied sites (0.10), but the best-supported models for CAD and KAD increased expected occupancy by about 4 percent for each species (from 0.17 to 0.21 for CAD and from 0.07 to 0.11 for KAD). Results of this study provide new inferences for modeling stream fish occurrence and detection processes and highlight the importance of continued monitoring and assessment of rare fish species in Appalachian headwater streams.

Kentucky, Tennessee, Virginia↗
USGS2016

Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

Remote Sensing of Environment↗
USGS2026

Using sediment chemical fractions and multivariate statistics on water to identify sources, mobility, and bioavailability of aluminum in the Florida River near Durango, Colorado

The Florida River in southwestern Colorado, USA, flows through the Southern Ute Reservation and is a cultural and water resource to Tribal and non-Tribal communities. High concentrations of total Al, up to 16 400 µg l –1 , have been detected in the Florida River. Elevated Al concentrations in water may affect aquatic organisms’ ability to regulate ions and inhibit respiratory functions. Water chemistry collected during three sampling events in 2022 from the Florida River and two of its tributaries are used here to better understand the spatial distribution, seasonality, and sources of Al concentrations in the Florida River. Streambed sediment and rock chemistry is also used to infer geologic sources of Al in the watershed. A five-stage sequential extraction was performed on streambed sediment and rock samples to help determine Al transport processes. We assessed relations between major and trace elements in water using a principal component analysis, finding that high Al concentrations in the Florida River (>3500 µg l –1 total Al) are caused by the erosion of Al-laden sediments. We used a stepwise multiple linear regression to investigate the relationship between land use and Al concentrations. Land use did not reliably predict Al concentration, though increased streamflow connected to reservoir releases – particularly in the Salt Creek tributary – were found to contribute Al to the Florida River during the irrigation season. In this study, we demonstrate that successful metal source appropriation may be achieved through limited field sampling when performed with sufficient water chemistry analysis, sequential chemical extraction of stream sediments, and statistical and land-use analysis.

Colorado↗
USGS2020

Landscape and climatic influences on actual evapotranspiration and available water using the Operational Simplified Surface Energy Balance (SSEBop) Model in eastern Bernalillo County, New Mexico, 2015

The U.S. Geological Survey, in cooperation with the Bernalillo County Public Works Division, conducted a 1-year study in 2015 to assess the spatial and temporal distribution of evapotranspiration (ET) and available water within the East Mountain area in Bernalillo County, New Mexico. ET and available water vary spatiotemporally because of complex interactions among environmental factors, including vegetation characteristics, soil characteristics, topography, and climate. Precipitation data from the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) ( P ) were used in conjunction with actual ET ( ETa ) data from the Operational Simplified Surface Energy Balance (SSEBop) model to estimate available water ( P – ETa ) at 100-meter (m) resolution in the study area. Maps, descriptive statistics, boxplots, regression analyses (continuous data), and multiple comparison tests (categorical data) were used to characterize P , ETa , and available water and their relations to topographic, soil, and vegetation datasets in the East Mountain area. Five categories of the natural land-cover type (evergreen forest, shrub, herbaceous, deciduous forest, and mixed forest) and four categories of developed land-cover type specific to residential intensity (developed open, developed low, developed medium, and developed high) were analyzed individually and in interaction with multiple elevation, tree canopy, and soil texture classes. Annual mean P in 2015 in the East Mountain area was 608 millimeters (mm), and annual mean ETa was 543 mm (89 percent of annual P in 2015), indicating that in 2015, a spatial mean of about 65 mm of water was available for runoff, soil moisture replenishment, or groundwater recharge. Monthly ETa was greatest in July and smallest in January. The intervening months did not show smooth temporal or consistent spatial changes from month to month. Months with lower ETa (January to March, October to December) also tended to have greater available water, indicating that soil moisture (water supply) and potential ET (water demand) may have been out of phase. Regression analyses showed that monthly ETa data had the highest correlation with annual ETa among the atmospheric, topographic, soil, or vegetation datasets, particularly during the early and late growing season (March, April, May, and September). In contrast, monthly P was highly variable and not as highly correlated with annual ETa . Among landscape variables, correlations with annual ETa were highest for tree canopy cover (coefficient of determination [R 2 ] = 0.46). Correlations between ETa and other landscape variables were lower (R 2 = 0.06–0.19): available soil water in the top 100 centimeters, soil bulk density of layer 1, slope, sand content of soil layer 1, soil depth, available soil water in the top 25 centimeters, leaf area index, aspect eastness, and elevation. Evergreen forest areas had the highest annual median ETa , followed by mixed forest, open residential areas, and deciduous forest. Available water typically was higher in landcover types with lower ETa : herbaceous cover, followed by deciduous forest, high-intensity developed areas, and shrub. Deciduous forest had the second highest median available water, despite having the fourth highest ETa , because deciduous forest had greater P than most other areas. Annual median ETa typically was greatest in the second highest elevation band (2,401–2,800 m above the North American Vertical Datum of 1988 [NAVD 88]), and lower in the highest elevation band (2,801–3,254 m above NAVD 88), despite having greater P , likely because of decreased tree canopy cover or a shift from evergreen to deciduous trees at the highest elevations. Annual median ETa increased with tree canopy cover, regardless of landcover type. ETa correlation was higher with tree canopy than with leaf area index or normalized difference vegetation index. This result indicates that it is important to include the thermal band (from satellite multispectral data) in vegetation indices used to describe ETa , perhaps to account for the influence of energy limitation or water limitation on ET. Of all natural landcover types, finer soils had the most available water, whereas coarser soils had the least available water. Relations of soil type with P – ETa were different than with ETa , indicating ET and available water have a complex response to differences in soil type. Further modeling would be useful in determining soils’ infiltration, storage, conductivity, and plant-water availability relations to individual storms for each position in the landscape, as well as the corresponding effects of these processes on ET and available water. The best multivariate linear model for annual ETa had an R 2 value of 0.62. Monthly ETa models had R 2 values between 0.16 and 0.65. Models usually, but not always, performed best during the growing season. These results indicate that even the best multivariate linear models cannot explain a notable amount of the variability in ET. The monthly ETa models with the highest correlations (August and September) followed a July having almost twice the mean precipitation for July (1981–2010), which indicates that a soil-moisture variable is needed to more accurately model monthly ETa . Further study is needed to better characterize this system, the variables that affect ET and available water, and the partitioning of available water into runoff, soil moisture storage, and groundwater recharge.

New Mexico↗
USGS1999

A temporal and spatial analysis of ground-water levels for effective monitoring in Huron County, Michigan

Quarterly water-level measurements were analyzed to assess the effectiveness of a monitoring network of 26 wells in Huron County, Michigan. Trends were identified as constant levels and autoregressive components were computed at all wells on the basis of data collected from 1993 to 1997, using structural time series analysis. Fixed seasonal components were identified at 22 wells and outliers were identified at 23 wells. The 95- percent confidence intervals were forecast for water-levels during the first and second quarters of 1998. Intervals in the first quarter were consistent with 92.3 percent of the measured values. In the second quarter, measured values were within the forecast intervals only 65.4 percent of the time. Unusually low precipitation during the second quarter is thought to have contributed to the reduced reliability of the second-quarter forecasts. Spatial interrelations among wells were investigated on the basis of the autoregressive components, which were filtered to create a set of innovation sequences that were temporally uncorrelated. The empirical covariance among the innovation sequences indicated both positive and negative spatial interrelations. The negative covariance components are considered to be physically implausible and to have resulted from random sampling error. Graphical modeling, a form of multivariate analysis, was used to model the covariance structure. Results indicate that only 29 of the 325 possible partial correlations among the water-level innovations were statistically significant. The model covariance matrix, corresponding to the model partial correlation structure, contained only positive elements. This model covariance was sequentially partitioned to compute a set of partial covariance matrices that were used to rank the effectiveness of the 26 monitoring wells from greatest to least. Results, for example, indicate that about 50 percent of the uncertainty of the water-level innovations currently monitored by the 26- well network could be described by the 6 most effective wells.

Michigan↗
USGS2008

Mapping regional distribution of a single tree species: Whitebark pine in the Greater Yellowstone Ecosystem

Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine whether using a combination of moderate resolution satellite imagery (Landsat Enhanced Thematic Mapper Plus), extensive stand data collected by land management agencies for other purposes, and modern statistical classification techniques (boosted classification trees) could result in successful mapping of whitebark pine. Overall classification accuracies exceeded 90%, with similar individual class accuracies. Accuracies on a localized basis varied based on elevation. Accuracies also varied among administrative units, although we were not able to determine whether these differences related to inherent spatial variations or differences in the quality of available reference data.

Sensors↗