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At least 289 records · Page 16Linked to original sources
USGS2012

Field evaluation of distance-estimation error during wetland-dependent bird surveys

Context: The most common methods to estimate detection probability during avian point-count surveys involve recording a distance between the survey point and individual birds detected during the survey period. Accurately measuring or estimating distance is an important assumption of these methods; however, this assumption is rarely tested in the context of aural avian point-count surveys. Aims: We expand on recent bird-simulation studies to document the error associated with estimating distance to calling birds in a wetland ecosystem. Methods: We used two approaches to estimate the error associated with five surveyor's distance estimates between the survey point and calling birds, and to determine the factors that affect a surveyor's ability to estimate distance. Key results: We observed biased and imprecise distance estimates when estimating distance to simulated birds in a point-count scenario ( x̄ error = -9 m, s.d. error = 47 m) and when estimating distances to real birds during field trials ( x̄ error = 39 m, s.d. error = 79 m). The amount of bias and precision in distance estimates differed among surveyors; surveyors with more training and experience were less biased and more precise when estimating distance to both real and simulated birds. Three environmental factors were important in explaining the error associated with distance estimates, including the measured distance from the bird to the surveyor, the volume of the call and the species of bird. Surveyors tended to make large overestimations to birds close to the survey point, which is an especially serious error in distance sampling. Conclusions: Our results suggest that distance-estimation error is prevalent, but surveyor training may be the easiest way to reduce distance-estimation error. Implications: The present study has demonstrated how relatively simple field trials can be used to estimate the error associated with distance estimates used to estimate detection probability during avian point-count surveys. Evaluating distance-estimation errors will allow investigators to better evaluate the accuracy of avian density and trend estimates. Moreover, investigators who evaluate distance-estimation errors could employ recently developed models to incorporate distance-estimation error into analyses. We encourage further development of such models, including the inclusion of such models into distance-analysis software.

Wildlife Research↗
USGS2016

An automated approach to Litchfield and Wilcoxon's evaluation of dose–effect experiments using the R package LW1949

The authors developed a package, LW1949, for use with the statistical software R to automatically carry out the manual steps of Litchfield and Wilcoxon's method of evaluating dose–effect experiments. The LW1949 package consistently finds the best fitting dose–effect relation by minimizing the chi-squared statistic of the observed and expected number of affected individuals and substantially speeds up the line-fitting process and other calculations that Litchfield and Wilcoxon originally carried out by hand. Environ Toxicol Chem 2016;9999:1–4. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US Government work and, as such, is in the public domain in the United States of America.

Environmental Toxicology and Chemistry↗
USGS2003

Pop-up archival transmitting (PAT) tags: A method to investigate the migration and behavior of Pacific halibut ( Hippoglossus stenolepis ) in the Gulf of Alaska

Pop-up archival transmitting (PAT) tags provide a fisheries-independent method of collecting environmental preference data (depth and ambient water temperature) and migration distance. In this study, we evaluate the use of pop-up archival transmitting tags as a method to investigate demersal fish. We report the results from eight pop-up archival transmitting tagged Pacific halibut Hippoglossus stenolepis (from 107 to 165 cm FL) that were released in and around Resurrection Bay, Alaska. Commercial fishermen recovered three tags, while five tags transmitted data to Argos satellites. Horizontal migration was not consistent among fish as four Pacific halibut remained in the vicinity of release while the other four traveled up to 358 km from the release site. Vertical movement was not consistent among fish or over time; however, they spent most of their time at depths of 150 to 350 m. The minimum and maximum depths reached by any of the Pacific halibut were 2 m and 502 m, respectively. The fish preferred water temperatures of approximately 6°C, but experienced temperatures between 4.3 and 12.2°C. Light attenuation with depth prevented geolocation software and light sensing hardware from accurately estimating geoposition for the majority of days. The methods, adapted from investigations on large pelagic fish, proved to be effective for studying Pacific halibut in the northern Gulf of Alaska. PAT tags allowed us to obtain high accuracy locations of the fish at the end of the tag deployments as well as preliminary data to identify approximate seasonal locations and to characterize their depth and temperature characteristics. By using PAT tags, we will be able to ensure tag returns during the winter season (which is closed to fishing) and gain valuable biological information even if fish migrate large distances or to unexpected locations.

Alaska Fishery Research Bulletin↗
USGS1989

Regional lists of plant species that occur in wetlands: data base user's guide

The Data Base List of Plant Species that Occur in Wetlands (LIST) currently contains records for 6,728 plant species. Each record provides information on nomenclature, plant characteristics and lifeforms, distribution, and frequency of occurrence in wetlands. The List of Plant Species that Occur in Wetlands, developed to supplement the U.S. Fish and Wildlife Service's Classification of Wetlands and Deepwater Habitats of the United States (Cowardin et al. 1979), underwent an intensive review by field botanists across the country. This review was coordinated by national and regional interagency wetland plant list review panels composed of representatives from the U. S. Fish and Wildlife Service, U. S. Army Corps of Engineers, Soil Conservation Service, and the Environmental Protection Agency. Initial and updated versions of the Data Base List of Plant Species that Occur in Wetlands are available in hardcopy (Reed 1986, 1988). Regional lists are available as U.S. Fish and Wildlife Service Biological Report Series 88(26.126.13). State lists are available as National Ecology Research Center Report Series 88(18.01-18.50). The computerized data base tracks and documents indicator assignments made by regional interagency review panels and facilitates generation of reports. This user's guide describes the format and contents of the LIST Data Base. The Data Base is available on 5-1/4" floppy disks in ASCII format for use with a data base management system on an IBM PC/XT/AT compatible computer. The LIST Data Base was developed using the QUICKTEXT Data Base Management System (Osborn and Strong 1984). Use of QUICKTEXT with the LIST Data Base is strongly recommended. Instructions for loading LIST into QUICKTEXT are included in this user's guide. Other data base management systems capable of handling variable length fields can be used by individuals familiar with these software packages. LIST distribution disks are available for 13 regions (Table 1). QUICKTEXT (course QT100--Data Base Management Techniques) and regional subsets of the LIST Data Base (distributed as self-tutorial courses, Table 1) are available through the Office of Conference Services, Colorado State University.

Report↗
USGS2018

Behavioral effects of copper on larval white sturgeon

Early–life stage white sturgeon are sensitive to copper (Cu), with adverse behavioral responses observed during previous studies. The objectives of the present study were to quantify the effects of Cu exposure on white sturgeon swimming and feeding behaviors and determine their time to response. Larval sturgeon (1–2, 28, or 35 d posthatch [dph]) were exposed to Cu (0.5–8 μg/L) for 4 to 14 d. Abnormal behavioral changes were observed within the first few days of exposure including loss of equilibrium and immobilization. Digital video tracking software revealed decreased swimming activity with increasing Cu concentration. Significant changes in behavior and mortality occurred at concentrations of Cu between 1 and 8 μg/L. Juvenile white sturgeon, 58 dph, exposed to 12 μg/L Cu consumed 37 to 60% less food than controls after 3 d of exposure. The present results indicate that behavioral endpoints were more sensitive than some standard toxicity test endpoints and can effectively expand the sensitivity of standard toxicity tests for white sturgeon. Swimming behavior was impaired to the extent that survival in the field would likely be jeopardized. Such data would provide managers a useful metric for characterizing the risks of Cu contamination to white sturgeon.

Environmental Toxicology and Chemistry↗
USGS2011

Evaluation of landslide monitoring in the Polish Carpathians

In response to the June 15, 2010 request from the Polish Geological Institute (PGI) to the U.S. Geological Survey (USGS) for assistance and advice regarding real-time landslide monitoring, landslide specialists from the USGS Landslide Hazard Program visited PGI headquarters and field sites in September 2010. During our visit we became familiar with characteristics of landslides in the Polish Carpathians, reviewed PGI monitoring techniques, and assessed needs for monitoring at recently activated landslides. Visits to several landslides that are monitored by PGI (the Just, Hańczowa, Szymbark, Siercza and Łasńica landslides) revealed that current data collection (monthly GPS and inclinometer surveys, hourly piezometers readings) is generally sufficient for collecting basic information about landslide displacement, depth, and groundwater conditions. Large landslides are typically hydrologically complex, and we would expect such complexity in Carpathian landslides, given the alternating shale and sandstone stratigraphy and complex geologic structures of the flysch bedrock. Consequently groundwater observations could be improved by installing several piezometers that sample the basal shear zone of each landslide being monitored by PGI. These could be supplemented by additional piezometers at shallower depths to help clarify general flow directions and hydraulic gradients. Remedial works at Hańczowa make the landslide unsuitable for monitoring as part of an early warning network. Monitoring there should focus on continued performance of the remedial works. Our suggestions for new monitoring at recently activated landslides are summarized in table 1. Displacement monitoring using extensometers and (or) GPS is a high priority at Kłodne, Łaśnica, Łazki, and Siedloki. Geomorphologic mapping of active surface features (scarps, cracks, shear zones, folds, and thrusts) in sufficient detail to reveal the kinematics of each landslide would greatly help in planning subsurface exploration and monitoring. Mapping should take advantage of existing and future airborne lidar data sets of specific areas, where available. Borehole inclinometers and piezometers would complete the basic monitoring package for these landslides. The landslide at Kłodne may be well suited for more detailed monitoring for landslide process research, although research opportunities exist at the other landslides as well. The landslide near Siedloki may be a good candidate for terrestrial laser scanning (TLS). Tandem streamflow gages upstream and downstream from the Siedloki landslide, or laser distance meters to monitor advancement of the toe, may be needed to provide warning of stream blockage of Potok Milowski. A real-time warning system specifically for the Łazki landslide might be considered due to potential concerns about catastrophic movement into Międzybrodzie Reservoir. Challenges associated with the establishment of a complete real-time monitoring and early warning system are far greater than just the technical and logistical aspects of installing remote monitoring systems at a large number of landslides. Long-term maintenance of a landslide monitoring network will involve considerable effort and expense as sensors break-down from exposure to weather, landslide movement, and harsh underground environmental conditions. Once PGI’s planned pilot network of 10-20 monitored landslides is operating, a period of observation and analysis will be needed to establish appropriate alert levels and criteria for issuing alerts and warnings. Simultaneously, discussions with authorities will be needed to develop action plans for responding to landslide notifications and (or) warnings. Public resistance to landslide warnings and mandated evacuations may be high given the low historical incidence of fatalities and injuries resulting from Carpathian landslides and the small potential for warnings to reduce landslide damage to homes and land. Careful weighing of purpose, advantages, and costs of a large-scale monitoring and early warning program is needed early in the planning process and should be revisited regularly throughout pilot and final implementation. In this report, we present a generic plan for monitoring of a hypothetical Carpathian landslide that illustrates how our suggestions for each of the specific landslides could be implemented. The plan includes basic pore pressure, displacement, and weather monitoring, along with supplemental monitoring for special conditions at specific landslides. Table 2 summarizes the overall approach and basic equipment and software requirements.

Open-File Report↗
USGS2011

Effects of recreational flow releases on natural resources of the Indian and Hudson Rivers in the Central Adirondack Mountains, New York, 2004-06

The U.S. Geological Survey (USGS), the New York State Department of Environmental Conservation (NYSDEC), and Cornell University carried out a cooperative 2-year study from the fall of 2004 through the fall of 2006 to characterize the potential effects of recreational-flow releases from Lake Abanakee on natural resources in the Indian and Hudson Rivers. Researchers gathered baseline information on hydrology, temperature, habitat, nearshore wetlands, and macroinvertebrate and fish communities and assessed the behavior and thermoregulation of stocked brown trout in study reaches from both rivers and from a control river. The effects of recreational-flow releases (releases) were assessed by comparing data from affected reaches with data from the same reaches during nonrelease days, control reaches in a nearby run-of-the-river system (the Cedar River), and one reach in the Hudson River upstream from the confluence with the Indian River. A streamgage downstream from Lake Abanakee transmitted data by satellite from November 2004 to November 2006; these data were used as the basis for developing a rating curve that was used to estimate discharges for the study period. River habitat at most study reaches was delineated by using Global Positioning System and ArcMap software on a handheld computer, and wetlands were mapped by ground-based measurements of length, width, and areal density. River temperature in the Indian and Hudson Rivers was monitored continuously at eight sites during June through September of 2005 and 2006; temperature was mapped in 2005 by remote imaging made possible through collaboration with the Rochester Institute of Technology. Fish communities at all study reaches were surveyed and characterized through quantitative, nearshore electrofishing surveys. Macroinvertebrate communities in all study reaches were sampled using the traveling-kick method and characterized using standard indices. Radio telemetry was used to track the movement and persistence of stocked brown trout (implanted with temperature-sensitive transmitters) in the Indian and Hudson Rivers during the summer of 2005 and in all three rivers during the summer of 2006. The releases had little effect on river temperatures, but increased discharges by about one order of magnitude. Regardless of the releases, river temperatures at all study sites commonly exceeded the threshold known to be stressful to brown trout. At most sites, mean and median water temperatures on release days were not significantly different, or slightly lower, than water temperatures on nonrelease days. Most differences were very small and, thus, were probably not biologically meaningful. The releases generally increased the total surface area of fast-water habitat (rapids, runs, and riffles) and decreased the total surface area of slow-water habitat (pools, glides, backwater areas, and side channels). The total surface areas of wetlands bordering the Indian River were substantially smaller than the surface areas bordering the Cedar River; however, no channel geomorphology or watershed soil and topographic data were assessed to determine whether the releases or other factors were mainly responsible for observed differences. Results from surveys of resident biota indicate that the releases generally had a limited effect on fish and macroinvertebrate communities in the Indian River and had no effect on communities in the Hudson River. Compared to fish data from Cedar River control sites, the impoundment appeared to reduce total density, biomass, and richness in the Indian River at the first site downstream from Lake Abanakee, moderately reduce the indexes at the other two sites on the Indian River, and slightly reduce the indexes at the first Hudson River site downstream from the confluence with the Indian River. The densities of individual fish populations at all Indian River sites were also reduced, but related effects on fish populations in the Hudson River were less evident. Altho

Scientific Investigations Report↗
USGS2020

One-Water Hydrologic Flow Model: A MODFLOW based conjunctive-use simulation software

The U.S. Geological Survey’s (USGS) Modular Ground-Water Flow Model (MODFLOW-2005) is a computer program that simulates groundwater flow by using finite differences. The MODFLOW-2005 framework uses a modular design that allows for the easy development and incorporation of new features called processes and packages that work with or modify inputs to the groundwater-flow equation. A process solves a flow equation or set of equations. For example, the central part of MODFLOW is the groundwater-flow process that solves the groundwater-flow equation; the surface-water routing process is an additional process that solves the surface-water flow equation. Packages are code related to the groundwater-flow process. For example, the subsidence package modifies the groundwater-flow process by including aquifer compaction effects on flow. With the development of new packages and processes, the MODFLOW-2005 base framework diverged into multiple independent versions designed for specific simulation needs. This divergence limited each independent MODFLOW release to its specific purpose, so that there was no longer a single, comprehensive, general-purpose hydraulic-simulation framework. The MODFLOW One-Water Hydrologic Flow Model (MF-OWHM, also informally known as OneWater) is an integrated hydrologic flow model that combines multiple MODFLOW-2005 variants in one cohesive simulation software; changes were made to enable multiple capabilities in one code. This fusion of the MODFLOW-2005 versions resulted in a simulation software that can be used to address and analyze a wide class of conjunctive-use, water-management, water-food-security, and climate-crop-water scenarios. As a second core version of MODFLOW-2005, MF-OWHM maintains backward compatibility with existing MODFLOW-2005 versions, with features that include the following: Process-based simulation. Saturated groundwater flow (three-dimensional). Surface-water flow (one- and two-dimensional). Stream and river flow. Lake and reservoir storage. Landscape simulation and irrigated agriculture. Land-use and crop simulation. Root uptake of groundwater. Actual evapotranspiration. Estimated irrigation demand. Reservoir operations. Aquifer compaction and subsidence by vertical model-grid deformation. Seawater intrusion by a sharp-interface assumption. Karst-aquifer and fractured-bedrock flow. Turbulent and laminar-pipe network flow. Unsaturated groundwater flow (one-dimensional). Internal linkages among the processes that couple hydraulic head, flow, and deformation. Redesigned code for faster simulation, increased user-input options, easier model updates, and more robust error reporting than in previous models. MF-OWHM is a MODFLOW-2005 based integrated hydrologic model that can simulate and analyze varying environmental conditions to allow for the evaluation of management options from many components of human and natural water movement through a physically based, supply and demand framework. The term “integrated,” in the context of this report, refers to the tight coupling of groundwater flow, surface-water flow, landscape processes, aquifer compaction and subsidence, reservoir operations, and conduit (karst) flow. Another benefit of this integrated hydrologic model is that models developed to run by MODFLOW-2005, MODFLOW-NWT, MODFLOW-CFP, or MODFLOW-FMP can also be simulated with MF-OWHM. At the time of this report’s publication, MF-OWHM version 2 (MF-OWHM2) does not include a direct internal simulation of snowmelt, advanced mountainous watershed rainfall-runoff simulation, detailed shallow soil-moisture accounting, or atmospheric moisture content. Atmospheric moisture may be accounted for indirectly by, optionally, specifying a pan-evaporation rate, reference evapotranspiration, and precipitation. These features are not included to ensure that simulation runtime remains short enough to enable the use of automated methods of calibrating model parameters to field observations, which typically require many simulation model runs. The MF-OWHM approach is to include as much detail as possible to simulate hydrological processes, providing the simulation runtimes remain reasonable enough to allow for robust parameter estimation and model calibration. To represent both natural and human-influenced flow, MF-OWHM integrates physically based flow processes derived from MODFLOW-2005 in a supply and demand framework. From this integration, the physically based movement of groundwater, surface water, imported water, and precipitation serve as supply to meet consumptive demands associated with irrigated and non-irrigated agriculture, natural vegetation, and urban water uses. Water consumption is determined by balancing the available water supply with water demand, leading to the concept of a demand-driven, supply-constrained simulation. The MF-OWHM Supply-and-Demand Framework is especially useful for the analysis of agricultural water use, where there are often few data available to describe changes in land-use through time, such as crop type and distribution, and the associated changes in groundwater pumpage. This framework attempts to satisfy each land-use water demand with available water supplies—that is, groundwater uptake, precipitation, and irrigation. An option provided in MF-OWHM2 is to automatically increase groundwater pumping for irrigation, which often is unknown, by the calculated residual between demand and the other available sources of supply. From large- to small-scale applications, the physically based supply and demand framework provides key capabilities for simulating and analyzing historical, current, and future conjunctive-use of surface water and groundwater. To achieve the physically based supply and demand framework, the MODFLOW-2005 standard of no inter-package and -process communication was relaxed for MF-OWHM2. Traditional MODFLOW simulation models required that all packages and processes interact through the groundwater-flow equation or by removing the water flow from the simulation domain. For example, the MODFLOW-2005 representation of a groundwater well extracts water from the groundwater-flow equation (by subtraction) and removes it from the simulation domain. This feature is available in the MF-OWHM framework, but options have been added to allow the specification of a use or destination of pumped groundwater within the model domain, for example, it can be used for irrigation, managed aquifer recharge, or return-flow to streams.

Techniques and Methods↗
USGS2013

Export of dissolved organic carbon from the Penobscot River basin in north-central Maine

Dissolved organic carbon (DOC) flux from the Penobscot River and its major tributaries in Maine was determined using continuous discharge measurements, discrete water sampling, and the LOADEST regression software. The average daily flux during 2004–2007 was 71 kg C ha −1 yr −1 (392 Mt C d −1 ), an amount larger than measured in most northern temperate and boreal rivers. Distinct seasonal variation was observed in the relation between concentration and discharge (C–Q). During June through December (summer/fall), there was a relatively steep positive C–Q relation where concentration increased by a factor of 2–3 over the approximately 20-fold range of observed stream discharge for the Penobscot River near Eddington, Maine. In contrast, during January through May (winter/spring), DOC concentration did not increase with increasing discharge. In addition, we observed a major shift in the C–Q between 2004–2005 and 2006–2007, apparently resulting from unprecedented rainfall, runoff, and soil flushing beginning in late fall 2005. The relative contribution to the total Penobscot River basin DOC flux from each tributary varied dramatically by season, reflecting the role of large regulated reservoirs in certain basins. DOC concentration and flux per unit watershed area were highest in tributaries containing the largest areas in palustrine wetlands. Tributary DOC concentration and flux was positively correlated to percentage wetland area. Climatic or environmental changes that influence the magnitude or timing of river discharge or the abundance of wetlands will likely affect the export of DOC to the near-coastal ocean.

Maine↗
USGS2003

Bathymetric mapping, sediment quality, and water quality of Lake Delhi, Iowa, 2001-02

Lake Delhi was formed in 1929 when the Interstate Power Company dammed the Maquoketa River near Delhi, Iowa, for generation of hydroelectric power. The resulting 450-acre lake became a popular area in eastern Iowa for boating, swimming, and fishing. Hydroelectric power generation ended in 1973, and lakeside residents purchased the dam to maintain the recreational opportunities of the lake. Increasing concerns about sediment deposition and water quality by lakeside residents led to a 2-year study that included a bathymetric survey, an assessment of sediment quality, and an assessment of water quality of Lake Delhi. A bathymetric map of Lake Delhi was constructed using more than 300,000 data points from echo sounding results and GIS (geographic information system) software. Results of bathymetric mapping showed that the upstream reach through most of the upstream-middle reach of Lake Delhi (approximately 3 miles) from about 0.25 mile upstream from the Greenslades coring site through Clair View Acres were particularly affected by sedimentation, with water depths ranging from less than 1 foot to a few areas that were as much as 10 feet deep. Numerous areas in the upstream-most 1-mile of the lake (about 0.25 mile upstream from the Greenslades coring site to just downstream from The Cedars coring site) had depths of only 1 to 2 feet and were nearly impassable by boats. The middle reach of Lake Delhi (an approximately 2.5-mile segment) from about one-half mile upstream from the Linden Acres coring site to just downstream from the Hartwick Dredge coring site was less affected by sedimentation with water depths from less than 1 to 16 feet. The deepest section (26 feet) of the lake was near the dam. Eleven trace metals and phosphorus were analyzed in 20 samples from seven lake-bottom sediment cores. The median and average traceelement concentrations from the sediment cores were less than the U.S. Environmental Protection Agency threshold-effects-level and probableeffects-level guidelines for toxic biological effects. Water-quality samples from eight sites (Maquoketa River, three lake sites, and four tributaries) were collected for five sampling periods (June 2001–July 2002). Water-quality samples were analyzed for physical properties (specific conductance, pH, temperature, turbidity, dissolved oxygen, and alkalinity), nutrients (nitrate, ammonia, and phosphorus), bacteria (total coliform and E. coli ), and suspended sediment. Selected water samples were analyzed for major ions, trace elements, and pesticides. Water-quality sampling results indicate areas affected by elevated nutrient and bacteria concentrations in the lake and tributary streams. The tributary streams had the highest median nitrate concentrations (12.1 milligrams per liter) when compared to median nitrate concentrations in the lake (8.7 milligrams per liter) or the Maquoketa River (10.5 milligrams per liter). The maximum nitrate concentrations detected for Maquoketa River, lake, and tributary sites were 13.5, 13.5, and 18.6 milligrams per liter, respectively. Nitrate concentrations in the late summer decreased from 2 Bathymetric Mapping, Sediment Quality, and Water Quality of Lake Delhi, Iowa, 2001–02 the upstream (7.8 milligrams per liter) to the downstream (5.0 milligrams per liter) one-third of Lake Delhi and most likely were the result of uptake of nitrate by algae and aquatic biota in the lake. Median concentrations of total coliform and E. coli bacteria for the lake sites were 450 and 17 colonies per 100 milliliters of sample, respectively. The U.S. Environmental Protection Agency criteria for full body contact (swimming or bathing) are 200 colonies per 100 milliliters for fecal bacteria and 126 colonies per 100 milliliters for E. coli bacteria. The highest bacteria concentrations in the lake occurred after a rain and were 25,000 colonies per 100 milliliters total coliform and 1,900 colonies per 100 milliliters E. coli .

Iowa↗
USGS2020

Keeping up with the times: Mapping range-wide habitat suitability for endangered species in a changing environment

Biologists and policy-makers have the difficult task of allocating limited resources to habitat conservation and management for endangered species in the face of changing environmental conditions. Satellite remote sensing can inform conservation because it is an efficient means to obtain environmental data over broad spatial and temporal extents. Yet, the challenges of accessing, processing, and analyzing remote sensing data hinder wider application of these techniques in conservation planning. We used Landsat data and hierarchical statistical models to link satellite-derived habitat measurements with abundance of endangered Yuma Ridgway's rails ( Rallus obsoletus yumanensis ) within the Lower Colorado River Basin and Salton Sink, USA. We addressed many of the challenges facing the application of remote sensing techniques by using the web-based, freely-available Google Earth Engine to process Landsat datasets, apply habitat models, and generate maps to predict habitat suitability at a fine spatial grain (30 m) across the range of the species. These maps are shareable, interactive, and easy to update annually as habitat conditions change using a Google Earth Engine App we developed. Thus, we provide a framework for building habitat suitability models and maps to help target adaptive habitat management over broad extents for sensitive species, enabling biologists to improve conservation and restoration efforts regularly as conditions change in highly variable ecosystems. We demonstrate this approach for Yuma Ridgway's rails, but our methods for merging hierarchical statistical models with open-source mapping software to describe spatial-temporal heterogeneity in habitat quality are applicable to any species, and are especially helpful to species inhabiting highly variable ecosystems.

Arizona, California, Nevada↗
USGS1989

A satellite-based digital data system for low-frequency geophysical data

A reliable method for collection, display, and analysis of low-frequency geophysical data from isolated sites, which can be throughout North and South America and the Pacific Rim, has been developed for use with the Geostationary Operational Environmental Satellite (GOES) system. Geophysical data primarily intended for earthquake hazard and crustal deformation monitoring are digitized with either 12-bit or 16-bit resolution and transmitted every 10 min through a satellite link to a bank of UNIX-based computers in Menlo Park, California. There the data are available for analysis and display within a few seconds of their transmit time. This system provides real-time monitoring of crustal deformation parameters such as tilt, strain, fault displacement, local magnetic field, crustal geochemistry, and water levels, as well as meteorological and other parameters, along faults in California and Alaska, and in volcanic regions in the western United States, Rabaul, and other locations in the New Britain region of the South Pacific. Various mathematical, statistical, and graphical algorithms process the incoming data to detect changes in crustal deformation and fault slip that may indicate the first stages of catastrophic fault failure. Alert trigger levels based on physical models, signal resolution, and previous history have been defined for particular instrument types. Computer-driven remote paging and mail systems are used to notify appropriate personnel when alarm status is reached. The system supports continuous historical records of low-frequency geophysical data, software for extensive analysis of these data, and programs for modeling fault rupture with and without seismic radiation, as well as providing an environment for real-time attempts at earthquake prediction.

Bulletin of the Seismological Society of America↗
USGS2019

Revisiting the avian Eco-SSL for lead: Recommendations for revision

The avian ecological soil screening level (Eco-SSL) for lead (11 mg/kg) is within soil background concentrations for >90% of the US. Consequently, its utility as a soil screening level is limited. Site-specific ecological risk-based remedial goals for lead are frequently many times greater. Toxicity reference values (TRVs) play a major role in defining Eco-SSLs. The lead Eco-SSL TRV is driven by reduced egg production in Japanese quail (Coturnix japonica), which displays effects at doses both substantially lower and greater than other tested species. High variability in egg production in Japanese quail has also been observed for other contaminants. Japanese quail egg production may therefore be to variable and unreliable an effect endpoint upon which to base regulatory screening criteria. Toxicity data supporting the Eco-SSL were re-evaluated and only studies reporting both no and lowest observed adverse effect levels (NOAELs and LOAELs) for reproduction, growth, or survival were considered. Dose-response data were extracted from 10 studies both as concentrations and doses. Dose-response relationships were developed using the USEPA Benchmark Dose Software for dietary concentrations and doses for egg production in Japanese quail and chickens. Effect levels (of 10%, 20%, and 50%) were extracted from the dose-response analyses. Species sensitivity distributions and dose-response data indicated reproduction was most sensitive to lead and survival was least sensitive, with growth intermediate. Limited data for ringed turtle doves (Streptopelia risoria) and American kestrels (Falco sparverius) suggests lower sensitivity than chickens to lead. ED10 and ED20 thresholds for chickens were 4.4 and 9.8 mg/kg/d, respectively. Avian lead Eco-SSLs were recalculated based on the chicken ED10 and ED20, with and without a bioavailability adjustment. Revised avian lead Eco-SSLs for the most highly exposed species (American woodcock), based on the ED10 and assuming 100% and 50% bioavailability, were 36.3 mg/kg and 43.7 mg/kg, respectively.

Integrated Environmental Assessment and Management↗
USGS2013

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗
USGS2011

Source-water susceptibility assessment in Texas—Approach and methodology

Public water systems provide potable water for the public's use. The Safe Drinking Water Act amendments of 1996 required States to prepare a source-water susceptibility assessment (SWSA) for each public water system (PWS). States were required to determine the source of water for each PWS, the origin of any contaminant of concern (COC) monitored or to be monitored, and the susceptibility of the public water system to COC exposure, to protect public water supplies from contamination. In Texas, the Texas Commission on Environmental Quality (TCEQ) was responsible for preparing SWSAs for the more than 6,000 public water systems, representing more than 18,000 surface-water intakes or groundwater wells. The U.S. Geological Survey (USGS) worked in cooperation with TCEQ to develop the Source Water Assessment Program (SWAP) approach and methodology. Texas' SWAP meets all requirements of the Safe Drinking Water Act and ultimately provides the TCEQ with a comprehensive tool for protection of public water systems from contamination by up to 247 individual COCs. TCEQ staff identified both the list of contaminants to be assessed and contaminant threshold values (THR) to be applied. COCs were chosen because they were regulated contaminants, were expected to become regulated contaminants in the near future, or were unregulated but thought to represent long-term health concerns. THRs were based on maximum contaminant levels from U.S. Environmental Protection Agency (EPA)'s National Primary Drinking Water Regulations. For reporting purposes, COCs were grouped into seven contaminant groups: inorganic compounds, volatile organic compounds, synthetic organic compounds, radiochemicals, disinfection byproducts, microbial organisms, and physical properties. Expanding on the TCEQ's definition of susceptibility, subject-matter expert working groups formulated the SWSA approach based on assumptions that natural processes and human activities contribute COCs in quantities that vary in space and time; that increased levels of COC-producing activities within a source area may increase susceptibility to COC exposure; and that natural and manmade conditions within the source area may increase, decrease, or have no observable effect on susceptibility to COC exposure. Incorporating these assumptions, eight SWSA components were defined: identification, delineation, intrinsic susceptibility, point- and nonpoint-source susceptibility, contaminant occurrence, area-of-primary influence, and summary components. Spatial datasets were prepared to represent approximately 170 attributes or indicators used in the assessment process. These primarily were static datasets (approximately 46 gigabytes (GB) in size). Selected datasets such as PWS surface-water-intake or groundwater-well locations and potential source of contamination (PSOC) locations were updated weekly. Completed assessments were archived, and that database is approximately 10 GB in size. SWSA components currently (2011) are implemented in the Source Water Assessment Program-Decision Support System (SWAP-DSS) computer software, specifically developed to produce SWSAs. On execution of the software, the components work to identify the source of water for the well or intake, assess intrinsic susceptibility of the water- supply source, assess susceptibility to contamination with COCs from point and nonpoint sources, identify any previous detections of COCs from existing water-quality databases, and summarize the results. Each water-supply source's susceptibility is assessed, source results are weighted by source capacity (when a PWS has multiple sources), and results are combined into a single SWSA for the PWS.'SWSA reports are generated using the software; during 2003, more than 6,000 reports were provided to PWS operators and the public. The ability to produce detailed or summary reports for individual sources, and detailed or summary reports for a PWS, by COC or COC group was a unique capability of SWAP-DSS. In 2004, the TCEQ began a rotating schedule for SWSA wherein one-third of PWSs statewide would be assessed annually, or sooner if protection-program activities deemed it necessary, and that schedule has continued to the present. Cooperative efforts by the TCEQ and the USGS for SWAP software maintenance and enhancements ended in 2011 with the TCEQ assuming responsibility for all tasks.

Texas↗
USGS2019

Using the beta distribution to analyze plant cover data

Most plant species are spatially aggregated. Local demographic and ecological processes (e.g. vegetative growth and limited seed dispersal) result in a clustered spatial pattern within an environmentally homogenous area. Spatial aggregation should be considered when modelling plant abundance data. Commonly, plant abundance is quantified by measuring cover within multiple areal plots or along multiple lines randomly placed within a study area. A common practice for analyzing plant cover is to use statistical methods that rely on the normal distribution for quantifying uncertainty. This is problematic because plant cover data tend to be left‐skewed (J‐shaped), right skewed (L‐shaped) or U‐shaped and, therefore, commonly violate classic statistical assumptions, such as normality. We outline statistical analyses that explicitly account for spatial aggregation by assuming that plant cover is beta‐distributed. The beta distribution is a flexible choice because within the open unit interval it can take on a wide range of shapes (L, J, U, or a bell‐shaped). We discuss and introduce extensions to the beta distribution that address common analysis issues encountered in plant cover datasets, such as i) the treatment of zero and one cover values, ii) hierarchical data structures, and iii) observations errors. For heuristic purposes, we focus on single species analyses, but we demonstrate how the outlined methods can be generalized to more species. The assumption that plant cover is beta‐distributed allows us to estimate the degree of spatial aggregation, and the ecological significance of this new knowledge is discussed. We provide a summary of available software for analyses (emphasizing standard R packages) and include worked examples and a simulation study comparing analysis options as supplemental information. Synthesis . Previously, the state of the statistical software made it practically difficult for empirical plant ecologists to analyze their cover data correctly, but new theory and R‐packages have been developed, and this difficulty no longer exists. We recommend that empirical plant ecologists embrace the new statistical possibilities for exploring the exciting ecological features in spatial variation of plant cover.

Journal of Ecology↗
USGS2015

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

AIMS Environmental Science↗
USGS2015

Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.

AIMS Environmental Science↗