Cyanobacterial harmful algal blooms (CyanoHABs) are increasingly a global concern because CyanoHABs pose a threat to human and aquatic ecosystem health and cause economic damages. Despite advances in scientific understanding of cyanobacteria and associated compounds, many unanswered questions remain about occurrence, environmental triggers for toxicity, and the ability to predict the timing, duration, and toxicity of CyanoHABs. U.S. Geological Survey (USGS) scientists are leading a diverse range of studies to address CyanoHAB issues in water bodies throughout the United States, using a combination of traditional methods and emerging technologies, and in collaboration with numerous partners. By providing practical applications of cutting edge CyanoHAB research, USGS studies have advanced scientific understanding, enabling the development of approaches to help protect ecological and human health.
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States\"}}]}","edition":"Version 1.0: Originally posted September 29, 2016; Version 1.1: December 18, 2017","contact":"Coordinator, National Water Quality Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The Bi-State distinct population segment (DPS) of greater sage-grouse (Centrocercus urophasianus) that occurs along the Nevada–California border was proposed for listing as threatened under the Endangered Species Act (ESA) by the U.S. Fish and Wildlife Service (FWS) in October 2013. However, in April 2015, the FWS determined that the Bi-State DPS no longer required protection under the ESA and withdrew the proposed rule to list the Bi-State DPS (U.S. Fish and Wildlife Service, 2015). The Bi-State DPS occupies portions of Alpine, Mono, and Inyo Counties in California, and Douglas, Esmeralda, Lyon, Carson City, and Mineral Counties in Nevada. Unique threats facing this population include geographic isolation, expansion of single-leaf pinyon (Pinus monophylla) and Utah juniper (Juniperus osteosperma), anthropogenic activities, and recent changes in predator communities. Estimating population vital rates, identifying seasonal habitat, quantifying threats, and identifying movement patterns are important first steps in developing effective sage-grouse management and conservation plans. During 2011–15, we radio- and Global Positioning System (GPS)-marked (2012–14 only) 44, 47, 17, 9, and 3 sage-grouse, respectively, for a total of 120, in the Pine Nut Mountains Population Management Unit (PMU). No change in lek attendance was detected at Mill Canyon (maximum=18 males) between 2011 and 2012; however, 1 male was observed in 2014 and no males were observed in 2013 and 2015. Males were observed near Bald Mountain in 2013, making it the first year this lek was observed to be active during the study period. Males were observed at a new site in the Buckskin Range in 2014 during trapping efforts and again observed during surveys in 2015. Findings indicate that pinyon-juniper is avoided by sage-grouse during every life stage. Nesting females selected increased sagebrush cover, sagebrush height, and understory horizontal cover, and brood-rearing females selected similar areas, but also preferred increased perennial forb abundance. Using maximum likelihood estimation, nest survival for the Pine Nut Mountains PMU during 2011–14 was 23.8 percent (95-percent confidence interval [CI]=0.3–40.6 percent) and appeared lower in comparison to the average 42 percent nest success for sage-grouse range-wide.
Brood survival for 50-day brood-rearing phase in the Pine Nut Mountains PMU during 2011–14 was 53.8 percent (95-percent CI=30.0–73.4 percent). Adult survival during 2011–15 was 67.4 percent (95-percent CI=56.1–76.5 percent). During 2011–14, 696 raptor/raven surveys were completed and results indicate a greater number of raven detections (n=464) in the Pine Nut Mountains PMU than at other study areas in Nevada. These data will be used to develop a predator index. We conducted a more minimal monitoring effort of sage-grouse populations during the 2015 field season, which included trapping efforts, general telemetry, brood monitoring, and GPS monitoring. Nest monitoring, microhabitat sampling, and raptor/raven surveys were not conducted in the 2015 season. Deployment of GPS transmitters has expanded our knowledge of movement corridors and fine-scale movement patterns by sage-grouse in the Pine Nut Mountains PMU. Movement corridors between seasonal habitats were identified with one sage-grouse traveling greater than 100 kilometers south to the Bodie Mountains in California for the winter season. The use of GPS technology to monitor movements in conjunction with intensive field efforts will be important in developing habitat models and maps for the Pine Nut Mountains PMU.
Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
A hydrogeologic framework was constructed to represent the altitudes and thicknesses of hydrogeologic units within the Ozark Plateaus aquifer system as part of a regional groundwater-flow model supported by the U.S. Geological Survey Water Availability and Use Science Program. The Ozark Plateaus aquifer system study area is nearly 70,000 square miles and includes parts of Arkansas, Kansas, Missouri, and Oklahoma. Nine hydrogeologic units were selected for delineation within the aquifer system and include the Western Interior Plains confining system, the Springfield Plateau aquifer, the Ozark confining unit, the Ozark aquifer, which was divided into the upper, middle, and lower Ozark aquifers to better capture the spatial variation in the hydrologic properties, the St. Francois confining unit, the St. Francois aquifer, and the basement confining unit. Geophysical and well-cutting logs, along with lithologic descriptions by well drillers, were compiled and interpreted to create hydrologic altitudes for each unit. The final compiled dataset included more than 23,000 individual altitude points (excluding synthetic points) representing the nine hydrogeologic units within the Ozark Plateaus aquifer system.
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U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
This is the eighth annual report highlighting U.S. Geological Survey (USGS) science and decision-support activities conducted for the Wyoming Landscape Conservation Initiative (WLCI). The activities address specific management needs identified by WLCI partner agencies. In 2015, USGS scientists continued 24 WLCI projects in 5 categories: (1) acquiring and analyzing resource-condition data to form a foundation for understanding and monitoring landscape conditions and projecting changes; (2) using new technologies to improve the scope and accuracy of landscape-scale monitoring and assessments, and applying them to monitor indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms that drive wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them to use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. Of the 24 projects, 21 were ongoing, including those that entered new phases or more in-depth lines of inquiry, 2 were new, and 1 was completed.
A highlight of 2015 was the WLCI science conference sponsored by the USGS, Bureau of Land Management, and National Park Service in coordination with the Wyoming chapter of The Wildlife Society. Of 260 participants, 41 were USGS professionals representing 13 USGS science centers, field offices, and Cooperative Wildlife Research Units. Major themes of USGS presentations included using new technologies for developing more efficient research protocols for modeling and monitoring natural resources, researching effects of energy development and other land uses on wildlife species and habitats of concern, and modeling species distributions, population trends, habitat use, and effects of land-use changes. There was also a special session on the effectiveness of Wyoming’s Sage-Grouse Executive Order. Combined, USGS presentations provided WLCI partners with a wealth of information and conservation tools.
The project completed in 2015 yielded an index of important agricultural lands in the WLCI region. The index improves upon existing measures of agricultural productivity and provides planners and managers with additional values to consider when making decisions about land use and conservation actions. The two new projects include an analysis of satellite imagery to quantify sagebrush productivity and mortality, and an evaluation of how groundwater and small streams interact in the upper Green River Basin. Initiated in response to concern among WLCI partners that large areas of sagebrush appear to have died recently, the sagebrush study objectives are to assess effects of these mortality events on overall sagebrush ecosystem productivity, evaluate the feasibility of using satellite imagery to detect patterns in sagebrush mortality over time, and identify factors driving these mortality events. The groundwater-streamflow interaction study is being conducted by hydrologists and fish ecologists to better understand how groundwater-streamflow interactions are affected by energy-resource development and how native fish communities are affected by these factors. Expected outcomes of both new projects will provide WLCI partners with additional information and decision-support tools.
Highlights of ongoing science foundation activities included simulations of nine alternative build-out scenarios for oil and gas development and an associated online fact sheet that explains how the simulations were conducted, with an applied example for the Atlantic Rim. Also completed in 2015 was an update of the USGS online inventory of mineral resources data, and publication of a USGS uranium resource survey for the WLCI region. Combined, the outcomes of this work provide decisionmakers and managers with important baseline information for existing and (or) future planning and monitoring efforts.
Terrestrial monitoring activities in 2015 emphasized the use of satellite data in combination with other technologies and field data to monitor, assess, and (or) forecast distribution patterns and (or) trends in sagebrush ecosystems, seasonal and migration stopover habitats used by mule deer and elk, and semi-arid aspen woodlands. Several professional papers detailing new monitoring models and results have been published. Combined, this and related work will help managers understand distribution patterns and trends among priority habitats, identify areas in need of restoration or conservation, and monitor the effectiveness of habitat-management actions.
Aquatic monitoring activities entailed not only the new groundwater-streamflow interaction study already mentioned, but also continued monitoring with streamgages paired with nearby wells in the Green River Basin to assess groundwater effects on streamflow and surface water temperatures. A map that portrays groundwater levels and general direction of flow in the Green River Basin was published as well. Overall, outcomes of USGS hydrological research and monitoring will inform WLCI partners about water resources in the WLCI region and help to explain fish-community responses to energy-resource development.
In 2015, USGS terrestrial wildlife ecologists continued to make crucial strides towards better understanding wildlife species responses to energy-resource development and other land-use changes. This body of research includes six taxa that require or heavily depend on sagebrush habitats: sage-grouse, pygmy rabbits, 3 songbird species, and mule deer. Native fish communities are also being evaluated. Approaches include modeling and mapping wildlife species distributions, abundances, and trends; using satellite and other technologies to track wildlife seasonal movements; conducting successive phases of research that build on the knowledge gained through prior phases to reveal the specific factors or thresholds that drive population- or individual-level responses to changes; and conducting population viability analyses. Additionally, wildlife habitat association models for pygmy rabbit and sage-grouse were combined with the oil and gas build-out scenarios to project species responses to alternative energy development scenarios. Outcomes of the wildlife response research are helping decisionmakers and managers identify specific factors that contribute to species population trends, the potential for spatial overlap between important wildlife habitats and proposed energy-resource development, locations of priority habitats for restoration and conservation, and more.
Data and WLCI Web site management highlights of 2015 included not only ongoing software upgrades, but also an update of the datasets displayed in two of the online products developed for the WLCI effort: (1) a map of 15,532 oil and natural gas well pad scars and other features associated with oil and gas extraction, and (2) a map of oil and gas, oil shale, uranium, and solar energy production, both for southwestern Wyoming. In addition, a map viewer was developed for a previously published map of coal and wind production in relation to sage-grouse distribution and core management areas in southwestern Wyoming. Combined, these maps place valuable decision-support tools in the hands of WLCI partners.
The USGS coordination efforts on behalf of the WLCI in 2015 included significant work on planning and executing the WLCI science conference. They also included ongoing efforts to support Local Project Development Teams and the WLCI Coordination Team (CT) with developing conservation priorities and strategies, identifying priority areas for future conservation actions, supporting the evaluation and ranking of conservation projects, and evaluating the ways in which proposed habitat projects relate to WLCI priorities. In 2015, the USGS also assisted the WLCI CT with updating the WLCI Conservation Action Plan.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161141","usgsCitation":"Bowen, Z.H., Aldridge, C.L., Anderson, P.J., Assal, T.J., Bartos, T.T., Chalfoun, A.D., Chong, G.W., Dematatis, M.K., Eddy-Miller, C.A., Garman, S.L., Germaine, S.S., Homer, C.G., Huber, C.C., Kauffman, M.J., Manier, D.J., Melcher, C.P., Miller, K.A., Norkin, Tamar, Sanders, L.E., Walters, A.W., Wilson, A.B., and Wyckoff, T.B., 2016, U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2015 annual report: U.S. Geological Survey Open-File Report 2016–1141, 59 p., https://dx.doi.org/10.3133/ofr20161141.","productDescription":"viii, 59 p.","onlineOnly":"Y","ipdsId":"IP-075182","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":329020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1141/coverthb.jpg"},{"id":329021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1141/ofr20161141.pdf","text":"Report","size":"36.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1141"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.07177734375,\n 43.40504748787035\n ],\n [\n -111.0498046875,\n 41\n ],\n [\n -105.99609375,\n 41\n ],\n [\n -105.99609375,\n 41.80407814427234\n ],\n [\n -105.35888671875,\n 41.82045509614034\n ],\n [\n -105.380859375,\n 42.47209690919285\n ],\n [\n -106.5673828125,\n 42.52069952914966\n ],\n [\n -107.20458984375,\n 42.48830197960227\n ],\n [\n -107.70996093749999,\n 42.53689200787315\n ],\n [\n -108.5009765625,\n 42.779275360241904\n ],\n [\n -108.80859375,\n 42.98857645832184\n ],\n [\n -109.22607421875,\n 43.229195113965005\n ],\n [\n -109.3798828125,\n 43.42100882994726\n ],\n [\n -109.79736328125,\n 43.5326204268101\n ],\n [\n -110.41259765625,\n 43.56447158721811\n ],\n [\n -111.07177734375,\n 43.40504748787035\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The U.S. Geological Survey (USGS) conducts Asian carp research focused on early detection, risk assessment, and development of control tools and strategies. The goals are to prevent the establishment of invasive Asian carp in the Great Lakes and to reduce their impacts in the Ohio River and Mississippi River Basins and elsewhere. Managers can use the information, tools, and strategies for early detection of Asian carp and to control them when their presence is first evident. New detection and control tools are designed to accommodate expansion to other invasive species and application in geographically diverse areas.
This USGS focus complements goals of the Great Lakes Restoration Initiative (GLRI), a multi-agency collaboration started in 2010 to protect and restore the Great Lakes. As a member of the Asian Carp Regional Coordinating Committee, which guides Asian carp efforts, the USGS works closely with Federal and State agencies, Canada, and others to address high-priority Asian carp issues and provide science to inform management decisions.
The USGS has gained extensive knowledge of Asian carp biology and life history over the past 30 years. That knowledge guides the design, development, and application of control strategies, and is essential for developing approaches in line with modern principles and practices of integrated pest management (IPM). IPM is a process used to solve pest problems while minimizing risks to people and the environment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163063","usgsCitation":"Kolar, C.S., and Morrison, S.S., 2016, USGS science and technology help managers battle invading Asian carp: U.S. Geological Survey Fact Sheet 2016-3063, 4 p., https:/dx.doi.org/10.3133/fs20163063.","productDescription":"4 p.","ipdsId":"IP-077431","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":329024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3063/fs20163063.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3063"},{"id":329023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3063/coverthb.jpg"}],"contact":"Ecosystems Mission Area
http://www.usgs.gov/ecosystems/
Inferring the factors responsible for declines in abundance is a prerequisite to preventing the extinction of wild populations. Many of the policies and programmes intended to prevent extinctions operate on the assumption that the factors driving the decline of a population can be determined. Exogenous factors that cause declines in abundance can be statistically confounded with endogenous factors such as density dependence. To demonstrate the potential for confounding, we used an experiment where replicated populations were driven to extinction by gradually manipulating habitat quality. In many of the replicated populations, habitat quality and density dependence were confounded, which obscured causal inference. Our results show that confounding is likely to occur when the exogenous factors that are driving the decline change gradually over time. Our study has direct implications for wild populations, because many factors that could drive a population to extinction change gradually through time.
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Since its opening, the focus of the SE CSC has been on working with partners in the identification and development of research-based information that can assist managers, including cultural and natural resource managers, in adapting to global change processes, such as climate and land use change, that operate at local to global scales and affect resources important to the DOI mission. The SE CSC was organized to accomplish three goals:
This report provides an overview of the SE CSC and the projects developed by the SE CSC since its inception. An important goal of this report is to provide a framework for understanding the evolution of the SE CSC science agenda, which has evolved over the first 5 years of the Center’s operation.
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Southeast Climate Science Center
North Carolina State University
Campus Box 7617
Raleigh, NC 27695-7617
https://www.doi.gov/csc/southeast/
https://globalchange.ncsu.edu/secsc/
Current range expansions of large terrestrial carnivores are occurring following human-induced range contraction. Contractions are often incomplete, leaving small remnant groups in refugia throughout the former range. Little is known about the underlying ecological and evolutionary processes that influence how remnant groups are affected during range expansion. We used data from a spatially explicit, long-term genetic sampling effort of grizzly bears (Ursus arctos) in the Northern Continental Divide Ecosystem (NCDE), USA, to identify the demographic processes underlying spatial and temporal patterns of genetic diversity. We conducted parentage analysis to evaluate how reproductive success and dispersal contribute to spatio-temporal patterns of genetic diversity in remnant groups of grizzly bears existing in the southwestern (SW), southeastern (SE) and east-central (EC) regions of the NCDE. A few reproductively dominant individuals and local inbreeding caused low genetic diversity in peripheral regions that may have persisted for multiple generations before eroding rapidly (approx. one generation) during population expansion. Our results highlight that individual-level genetic and reproductive dynamics play critical roles during genetic assimilation, and show that spatial patterns of genetic diversity on the leading edge of an expansion may result from historical demographic patterns that are highly ephemeral.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2016.1467","usgsCitation":"Mikle, N., Graves, T.A., Kovach, R.P., Kendall, K.C., and Macleod, A., 2016, Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore: Proceedings of the Royal Society B: Biological Sciences, v. 283, no. 1839, https://doi.org/10.1098/rspb.2016.1467.","ipdsId":"IP-072646","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470553,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2016.1467","text":"Publisher Index Page"},{"id":334686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335575,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7Q81B63","text":"Northern Continental Divide Ecosystem grizzly bear (Ursus arctos) genetic profiles (1998-2012)"}],"country":"United States","otherGeospatial":"Northern Continental Divide Ecosystem","volume":"283","issue":"1839","noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"5895a4c0e4b0fa1e59bc1e02","contributors":{"authors":[{"text":"Mikle, Nathaniel 0000-0002-6529-8210 nmikle@usgs.gov","orcid":"https://orcid.org/0000-0002-6529-8210","contributorId":177026,"corporation":false,"usgs":true,"family":"Mikle","given":"Nathaniel","email":"nmikle@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":662475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Tabitha A. 0000-0001-5145-2400 tgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":5898,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha","email":"tgraves@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":662476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kovach, Ryan P. rkovach@usgs.gov","contributorId":5772,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","middleInitial":"P.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":662477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, Katherine C. 0000-0002-4831-2287 kkendall@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":3081,"corporation":false,"usgs":true,"family":"Kendall","given":"Katherine","email":"kkendall@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":662478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Macleod, Amy C.","contributorId":65739,"corporation":false,"usgs":true,"family":"Macleod","given":"Amy C.","affiliations":[],"preferred":false,"id":662479,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176620,"text":"sir20165135 - 2016 - Potential sources of analytical bias and error in selected trace element data-quality analyses","interactions":[],"lastModifiedDate":"2016-09-29T09:10:27","indexId":"sir20165135","displayToPublicDate":"2016-09-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5135","title":"Potential sources of analytical bias and error in selected trace element data-quality analyses","docAbstract":"Potential sources of analytical bias and error associated with laboratory analyses for selected trace elements where concentrations were greater in filtered samples than in paired unfiltered samples were evaluated by U.S. Geological Survey (USGS) Water Quality Specialists in collaboration with the USGS National Water Quality Laboratory (NWQL) and the Branch of Quality Systems (BQS).
Causes for trace-element concentrations in filtered samples to exceed those in associated unfiltered samples have been attributed to variability in analytical measurements, analytical bias, sample contamination either in the field or laboratory, and (or) sample-matrix chemistry. These issues have not only been attributed to data generated by the USGS NWQL but have been observed in data generated by other laboratories. This study continues the evaluation of potential analytical bias and error resulting from matrix chemistry and instrument variability by evaluating the performance of seven selected trace elements in paired filtered and unfiltered surface-water and groundwater samples collected from 23 sampling sites of varying chemistries from six States, matrix spike recoveries, and standard reference materials.
Filtered and unfiltered samples have been routinely analyzed on separate inductively coupled plasma-mass spectrometry instruments. Unfiltered samples are treated with hydrochloric acid (HCl) during an in-bottle digestion procedure; filtered samples are not routinely treated with HCl as part of the laboratory analytical procedure. To evaluate the influence of HCl on different sample matrices, an aliquot of the filtered samples was treated with HCl. The addition of HCl did little to differentiate the analytical results between filtered samples treated with HCl from those samples left untreated; however, there was a small, but noticeable, decrease in the number of instances where a particular trace-element concentration was greater in a filtered sample than in the associated unfiltered sample for all trace elements except selenium. Accounting for the small dilution effect (2 percent) from the addition of HCl, as required for the in-bottle digestion procedure for unfiltered samples, may be one step toward decreasing the number of instances where trace-element concentrations are greater in filtered samples than in paired unfiltered samples.
The laboratory analyses of arsenic, cadmium, lead, and zinc did not appear to be influenced by instrument biases. These trace elements showed similar results on both instruments used to analyze filtered and unfiltered samples. The results for aluminum and molybdenum tended to be higher on the instrument designated to analyze unfiltered samples; the results for selenium tended to be lower. The matrices used to prepare calibration standards were different for the two instruments. The instrument designated for the analysis of unfiltered samples was calibrated using standards prepared in a nitric:hydrochloric acid (HNO3:HCl) matrix. The instrument designated for the analysis of filtered samples was calibrated using standards prepared in a matrix acidified only with HNO3. Matrix chemistry may have influenced the responses of aluminum, molybdenum, and selenium on the two instruments. The best analytical practice is to calibrate instruments using calibration standards prepared in matrices that reasonably match those of the samples being analyzed.
Filtered and unfiltered samples were spiked over a range of trace-element concentrations from less than 1 to 58 times ambient concentrations. The greater the magnitude of the trace-element spike concentration relative to the ambient concentration, the greater the likelihood spike recoveries will be within data control guidelines (80–120 percent). Greater variability in spike recoveries occurred when trace elements were spiked at concentrations less than 10 times the ambient concentration. Spike recoveries that were considerably lower than 90 percent often were associated with spiked concentrations substantially lower than what was present in the ambient sample. Because the main purpose of spiking natural water samples with known quantities of a particular analyte is to assess possible matrix effects on analytical results, the results of this study stress the importance of spiking samples at concentrations that are reasonably close to what is expected but sufficiently high to exceed analytical variability. Generally, differences in spike recovery results between paired filtered and unfiltered samples were minimal when samples were analyzed on the same instrument.
Analytical results for trace-element concentrations in ambient filtered and unfiltered samples greater than 10 and 40 μg/L, respectively, were within the data-quality objective for precision of ±25 percent. Ambient trace-element concentrations in filtered samples greater than the long-term method detection limits but less than 10 μg/L failed to meet the data-quality objective for precision for at least one trace element in about 54 percent of the samples. Similarly, trace-element concentrations in unfiltered samples greater than the long-term method detection limits but less than 40 μg/L failed to meet this data-quality objective for at least one trace-element analysis in about 58 percent of the samples. Although, aluminum and zinc were particularly problematic, limited re-analyses of filtered and unfiltered samples appeared to improve otherwise failed analytical precision.
The evaluation of analytical bias using standard reference materials indicate a slight low bias for results for arsenic, cadmium, selenium, and zinc. Aluminum and molybdenum show signs of high bias. There was no observed bias, as determined using the standard reference materials, during the analysis of lead.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165135","usgsCitation":"Paul, A.P., Garbarino, J.R., Olsen, L.D., Rosen, M.R., Mebane, C.A., and Struzeski, T.M., 2016, Potential sources of analytical bias and error in selected trace-element data quality analyses: U.S. Geological Survey Scientific Investigations Report 2016–5135, 58 p., https://dx.doi.org/10.3133/sir20165135.","productDescription":"vi, 58 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-074836","costCenters":[{"id":5066,"text":"Office of the Director USGS","active":true,"usgs":true}],"links":[{"id":329081,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5135/sir20165135.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5138"},{"id":329080,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5135/coverthb.jpg"}],"contact":"Chief, Water Science Field Team
U.S. Geological Survey
520 North Park Avenue
Tucson, Arizona 85721
http://az.water.usgs.gov/
In support of a multiagency project for assessing induction hazards, we present maps of extreme-value geoelectric amplitudes over about half of the continental United States. These maps are constructed using a parameterization of induction: estimates of Earth surface impedance, obtained at discrete geographic sites from magnetotelluric survey data, are convolved with latitude-dependent statistical maps of extreme-value geomagnetic activity, obtained from decades of magnetic observatory data. Geoelectric amplitudes are estimated for geomagnetic waveforms having 240 s sinusoidal period and amplitudes over 10 min that exceed a once-per-century threshold. As a result of the combination of geographic differences in geomagnetic activity and Earth surface impedance, once-per-century geoelectric amplitudes span more than 2 orders of magnitude and are an intricate function of location. For north-south induction, once-per-century geoelectric amplitudes across large parts of the United States have a median value of 0.26 V/km; for east-west geomagnetic variation the median value is 0.23 V/km. At some locations, once-per-century geoelectric amplitudes exceed 3 V/km.
","language":"English","publisher":"Wiley","doi":"10.1002/2016GL070469","usgsCitation":"Love, J.J., Pulkkinen, A., Bedrosian, P.A., Jonas, S., Kelbert, A., Rigler, E., Finn, C., Balch, C., Rutledge, R., Waggel, R., Sabata, A., Kozyra, J., and Black, C., 2016, Geoelectric hazard maps for the continental United States: Geophysical Research Letters, v. 43, no. 18, p. 9415-9424, https://doi.org/10.1002/2016GL070469.","productDescription":"10 p.","startPage":"9415","endPage":"9424","ipdsId":"IP-079237","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470551,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl070469","text":"Publisher Index Page"},{"id":336739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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Dakota","docAbstract":"The city of Sioux Falls is the fastest growing community in South Dakota. In response to this continued growth and planning for future development, Sioux Falls requires a sustainable supply of municipal water. Planning and managing sustainable groundwater supplies requires a thorough understanding of local groundwater resources. The Big Sioux aquifer consists of glacial outwash sands and gravels and is hydraulically connected to the Big Sioux River, which provided about 90 percent of the city’s source-water production in 2015. Managing sustainable groundwater supplies also requires an understanding of groundwater availability. An effective mechanism to inform water management decisions is the development and utilization of a groundwater-flow model. A groundwater-flow model provides a quantitative framework for synthesizing field information and conceptualizing hydrogeologic processes. These groundwater-flow models can support decision making processes by mapping and characterizing the aquifer. Accordingly, the city of Sioux Falls partnered with the U.S. Geological Survey to construct a groundwater-flow model. Model inputs will include data from advanced geophysical techniques, specifically airborne electromagnetic methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163075","collaboration":"Prepared in cooperation with the City of Sioux Falls","usgsCitation":"Valder, J.F., Delzer, G.C., Carter, J.M., Smith, B.D., and Smith, D.V., 2016, Construction of a groundwater-flow model for the Big Sioux aquifer using airborne electromagnetic methods, Sioux Falls, South Dakota: U.S. Geological Survey Fact Sheet 2016–3075, 4 p., https://dx.doi.org/10.3133/fs20163075.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-079092","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":328947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3075/fs20163075.pdf","text":"Fact Sheet","size":"4.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016–3075"},{"id":328946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3075/coverthb.jpg"}],"country":"United States","state":"South Dakota","city":"Sioux Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.79023742675781,\n 43.56098868633536\n ],\n [\n -96.79023742675781,\n 43.823133635349556\n ],\n [\n -96.69136047363281,\n 43.823133635349556\n ],\n [\n -96.69136047363281,\n 43.56098868633536\n ],\n [\n -96.79023742675781,\n 43.56098868633536\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
Assessments of streamflow (discharge) parameters, water quality, physical habitat, and biological communities were completed between May and September 2014 as part of a monitoring program in the Big Wood River watershed of south-central Idaho. The sampling was conducted by the U.S. Geological Survey in cooperation with Blaine County, Trout Unlimited, the Nature Conservancy, and the Wood River Land Trust to help identify the status of aquatic resources at selected locations in the watershed. Information in this report provides a basis with which to evaluate and monitor the long-term health of the Big Wood River and its major tributaries. Sampling sites were co-located with existing U.S. Geological Survey streamgaging stations: three on the main stem Big Wood River and four on the North Fork Big Wood River (North Fork), Warm Springs Creek (Warm Sp), Trail Creek (Trail Ck), and East Fork Big Wood River (East Fork) tributaries.
The analytical results and quality-assurance information for water quality, physical habitat, and biological community samples collected at study sites during 2 weeks in September 2014 are summarized. Water-quality data include concentrations of major nutrients, suspended sediment, dissolved oxygen, and fecal-coliform bacteria. To assess the potential effects of nutrient enrichment on algal growth, concentrations of periphyton biomass (chlorophyll-a and ash free dry weight) in riffle habitats were determined at each site. Physical habitat parameters include stream channel morphology, habitat volume, instream structure, substrate composition, and riparian vegetative cover. Biological data include taxa richness, abundance, and stream-health indicator metrics for macroinvertebrate and fish communities. Statistical summaries of the water-quality, habitat, and biological data are provided along with discussion of how these findings relate to the health of aquatic resources in the Big Wood River watershed.
Seasonal discharge patterns using statistical summaries of daily discharge from selected sites are reported for water years 2012–15. Results showed that annual average daily mean discharge increased from the Big Wood River near Ketchum, ID (BW Ketchum) downstream to the Big Wood River at Hailey, ID (BW Hailey), but decreased by nearly 50 percent from BW Hailey downstream to Big Wood River at Stanton Crossing near Bellevue, ID (BW Stanton). Annual variability in daily mean discharge among main-stem sites was highest at BW Stanton, suggesting that this part of the river may be subject to some level of flow alteration.
Hydrologic alterations resulting in flow reduction can contribute to higher water temperature, especially during the summer months when conditions are often most stressful to fish and other stream organisms. Daily water temperature and water temperature trends from June to September 2014 are reported for select tributary and main-stem sites on the Big Wood River and can be used to assess the potential for biological impairment based on aquatic life temperature criteria for cold-water streams. The State of Idaho maximum temperature criteria for protection of cold-water aquatic life of 22 °C was exceeded at Warm Sp and BW Stanton during summer 2014, but at none of the other main-stem or tributary sites. The 13 °C critical temperature criterion for salmonid spawning was exceeded in early July 2014 at BW Ketchum and BW Hailey near the end of the rainbow trout critical spawning and rearing period. Temperature exceedances were most frequent at BW Stanton, where exceedances for rainbow trout and brown trout occurred from May through early July 2014 during most of the critical spawning and rearing period.
Water quality and habitat availability did not seem to be limiting for fish or other aquatic organisms at most sites in the Big Wood River watershed. Water quality assessments in September 2014 determined no exceedances of total maximum daily load target levels. The availability and quality of habitat was limited at BW Stanton, where shallow-water habitat conditions prevailed.
Macroinvertebrate community diversity was high at all sites except for BW Stanton, where low community diversity was attributed to low species richness and high abundances of a few tolerant taxa. Presence of low species diversity and high macroinvertebrate tolerance values at BW Stanton indicates that benthic community condition and stream health were reduced at that location.
Fish surveys done in September 2014 did not indicate any significant reductions in native fish communities in the Big Wood River or its tributaries. Native rainbow trout (Oncorhynchus mykiss) and Wood River sculpin (Cottus leiopomus) were the dominant fish species in the drainage and were found at all tributary and main-stem sites. Non-native brown (Salmo trutta) and brook trout (Salvelinus fontinalis) were limited to lower drainage sites on the Big Wood River (BW Hailey and BW Stanton), and occurred in relatively low numbers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165128","collaboration":"Prepared in cooperation with Blaine County, Trout Unlimited, The Nature Conservancy, and the Wood River Land Trust","usgsCitation":"MacCoy, D.E., and Short, T.M., 2016, Aquatic biological communities and associated habitats at selected sites in the Big Wood River watershed, south-central Idaho, 2014: U.S. Geological Survey Scientific Investigations Report 2016–5128, 37 p., https://dx.doi.org/10.3133/sir20165128.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-061251","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":329075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5128/sir20165128.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5128"},{"id":329074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5128/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Wood River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.58465576171875,\n 43.2622061978402\n ],\n [\n -114.58465576171875,\n 43.81471121600004\n ],\n [\n -114.01473999023438,\n 43.81471121600004\n ],\n [\n -114.01473999023438,\n 43.2622061978402\n ],\n [\n -114.58465576171875,\n 43.2622061978402\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
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U.S. Geological Survey (USGS) Professional Paper 1794–D is the fourth in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Eastern United States between 1973 and 2000. Volumes A, B, and C provide similar analyses for the Western United States, the Great Plains of the United States, and the Midwest–South Central United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation.
Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Eastern United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Eastern United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research.
This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov.
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\"}}]}","contact":"Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
http://eros.usgs.gov/
Warm Mineral Springs, located in southern Sarasota County, Florida, is a warm, highly mineralized, inland spring. Since 1946, a bathing spa has been in operation at the spring, attracting vacationers and health enthusiasts. During the winter months, the warm water attracts manatees to the adjoining spring run and provides vital habitat for these mammals. Well-preserved late Pleistocene to early Holocene-age human and animal bones, artifacts, and plant remains have been found in and around the spring, and indicate the surrounding sinkhole formed more than 12,000 years ago. The spring is a multiuse resource of hydrologic importance, ecological and archeological significance, and economic value to the community.
The pool of Warm Mineral Springs has a circular shape that reflects its origin as a sinkhole. The pool measures about 240 feet in diameter at the surface and has a maximum depth of about 205 feet. The sinkhole developed in the sand, clay, and dolostone of the Arcadia Formation of the Miocene-age to Oligocene-age Hawthorn Group. Underlying the Hawthorn Group are Oligocene-age to Eocene-age limestones and dolostones, including the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. Mineralized groundwater, under artesian pressure in the underlying aquifers, fills the remnant sink, and the overflow discharges into Warm Mineral Springs Creek, to Salt Creek, and subsequently into the Myakka River. Aquifers described in the vicinity of Warm Mineral Springs include the surficial aquifer system, the intermediate aquifer system within the Hawthorn Group, and the Upper Floridan aquifer in the Suwannee Limestone, Ocala Limestone, and Avon Park Formation. The Hawthorn Group acts as an upper confining unit of the Upper Floridan aquifer.
Groundwater flow paths are inferred from the configuration of the potentiometric surface of the Upper Floridan aquifer for September 2010. Groundwater flow models indicate the downward flow of water into the Upper Floridan aquifer in inland areas, and upward flow toward the surface in coastal areas, such as at Warm Mineral Springs. Warm Mineral Springs is located in a discharge area. Changes in water use in the region have affected the potentiometric surface of the Upper Floridan aquifer. Historical increase in groundwater withdrawals resulted in a 10- to 20-foot regional decline in the potentiometric surface of the Upper Floridan aquifer by May 1975 relative to predevelopment levels and remained at approximately that level in May 2007 in the area of Warm Mineral Springs. Discharge measurements at Warm Mineral Springs (1942–2014) decreased from about 11–12 cubic feet per second in the 1940s to about 6–9 cubic feet per second in the 1970s and remained at about that level for the remainder of the period of record. Similarity of changes in regional water use and discharge at Warm Mineral Springs indicates that basin-scale changes to the groundwater system have affected discharge at Warm Mineral Springs. Water temperature had no significant trend in temperature over the period of record, 1943–2015, and outliers were identified in the data that might indicate inconsistencies in measurement methods or locations.
Within the regional groundwater basin, Warm Mineral Springs is influenced by deep Upper Floridan aquifer flow paths that discharge toward the coast. Associated with these flow paths, the groundwater temperatures increase with depth and toward the coast. Multiple lines of evidence indicate that a source of warm groundwater to Warm Mineral Springs is likely the permeable zone of the Avon Park Formation within the Upper Floridan aquifer at a depth of about 1,400 to 1,600 feet, or deeper sources. The permeable zone contains saline groundwater with water temperatures of at least 95 degrees Fahrenheit.
The water quality of Warm Mineral Springs, when compared with other springs in Florida had the highest temperature and the greatest mineralized content. Warm Mineral Springs water is characterized by a slight-green color, with varying water clarity, low dissolved oxygen (indicative of deep groundwater), and a hydrogen sulfide odor. Water-quality samples detected ammonium-nitrogen and nitrates, but at low concentrations. The drinking water standard for nitrate adopted by the U.S. Environmental Protection Agency is 10 milligrams per liter, measured as nitrogen. Water samples collected at spring vents by divers on April 29, 2015, had concentrations of 0.9 milligram per liter nitrate-nitrogen at vent A and 0.04–0.05 milligram per liter at vents B, C, and D. Typically, the water clarity is highest in the morning (about 30 feet Secchi depth) and often decreases throughout the day.
Analysis of existing data provided some insight into the hydrologic processes affecting Warm Mineral Springs; however, data have been sparsely and discontinuously collected since the 1940s. Continuous monitoring of hydrologic characteristics such as discharge, water temperature, specific conductance, and water-quality indicators, such as nitrate and turbidity (water clarity), would be valuable for monitoring and development of models of spring discharge and water quality. In addition, water samples could be analyzed for isotopic tracers, such as strontium, and the results used to identify and quantify the sources of groundwater that discharge at Warm Mineral Springs. Groundwater flow/transport models could be used to evaluate the sensitivity of the quality and quantity of water flowing from Warm Mineral Springs to changes in climate, aquifer levels, and water use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161166","collaboration":"Prepared in cooperation with the City of North Port and Sarasota County ","usgsCitation":"Metz, P.A., 2016, Discharge, water temperature, and water quality of Warm Mineral Springs, Sarasota County, Florida: A retrospective analysis: U.S. Geological Survey Open-File Report 2016–1166, 31 p., https://dx.doi.org/10.3133/ofr20161166.","productDescription":"vi, 31 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-066216","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":328877,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1166/coverthb2.jpg"},{"id":328878,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1166/ofr20161166.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1166"}],"country":"United States","state":"Florida","county":"Sarasota County","otherGeospatial":"Warm Mineral Springs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.26177334785461,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.060654482992454\n ],\n [\n -82.25942373275757,\n 27.058867814427533\n ],\n [\n -82.26177334785461,\n 27.058867814427533\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
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(813) 498-5000
Or visit the Caribbean-Florida Water Science Center Web page at
http://fl.water.usgs.gov
Resource nationalism encompasses a broad range of political and economic actions taken by Governments to regulate the extraction of natural resources within their borders. Policies such as increased tariffs or export restrictions can have far-reaching economic effects on international trade. As the Governments of several developing countries consider enacting nationalistic policies, an examination of the 2014 mineral export ban in Indonesia provides an instructive example of the possible impacts of resource nationalism. Significant changes in the production and trade of unprocessed (that is, ores and concentrates) and processed (that is, refined metal) aluminum, copper, and nickel before and after the export ban form the basis of this study.
The U.S. Geological Survey (USGS) National Minerals Information Center (NMIC) tracks production and trade of mineral commodities between producer and consumer countries. Materials flow studies clarify the effects of an export ban on different mineral commodities by assessing changes in production, processing capacity, and trade. Using extensive data collection and monitoring procedures, the USGS NMIC investigated the effects of resource nationalism on the flow of mineral commodities from Indonesia to the global economy.
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U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at: http://minerals.usgs.gov/minerals/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-27","noUsgsAuthors":false,"publicationDate":"2016-09-27","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c84c","contributors":{"authors":[{"text":"Lederer, Graham W. glederer@usgs.gov","contributorId":174731,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham W.","email":"glederer@usgs.gov","affiliations":[],"preferred":false,"id":649129,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70176630,"text":"70176630 - 2016 - Influence of demography and environment on persistence in toad populations","interactions":[],"lastModifiedDate":"2016-09-27T09:40:23","indexId":"70176630","displayToPublicDate":"2016-09-27T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Influence of demography and environment on persistence in toad populations","docAbstract":"Effective conservation of rare species requires an understanding of how potential threats affect population dynamics. Unfortunately, information about population demographics prior to threats (i.e., baseline data) is lacking for many species. Perturbations, caused by climate change, disease, or other stressors can lead to population declines and heightened conservation concerns. Boreal toads (Anaxyrus boreas boreas) have undergone rangewide declines due mostly to the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd), with only a few sizable populations remaining in the southern Rocky Mountains, USA, that are disease-free. Despite the apparent region-wide occurrence of Bd, our focal populations in central Colorado were disease free over a 14-year capture-mark-recapture study until the recent discovery of Bd at one of the sites. We used recapture data and the Pradel reverse-time model to assess the influence of environmental and site-specific conditions on survival and recruitment. We then forecast changes in the toad populations with 2 growth models; one using an average lambda value to initiate the projection, and one using the most recent value to capture potential effects of the incursion of disease into the system. Adult survival was consistently high at the 3 sites, whereas recruitment was more variable and markedly low at 1 site. We found that active season moisture, active season length, and breeding shallows were important factors in estimating recruitment. Population growth models indicated a slight increase at 1 site but decreasing trends at the 2 other sites, possibly influenced by low recruitment. Insight into declining species management can be gained from information on survival and recruitment and how site-specific environmental factors influence these demographic parameters. Our data are particularly useful because they provide baseline data on demographics in populations before a disease outbreak and enhance our ability to detect changes in population parameters potentially caused by the disease.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21118","usgsCitation":"Lambert, B.A., Schorr, R.A., Schneider, S.C., and Muths, E.L., 2016, Influence of demography and environment on persistence in toad populations: Journal of Wildlife Management, v. 80, no. 7, p. 1256-1266, https://doi.org/10.1002/jwmg.21118.","productDescription":"11 p.","startPage":"1256","endPage":"1266","ipdsId":"IP-068989","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":329017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-12","publicationStatus":"PW","scienceBaseUri":"57f7c63ce4b0bc0bec09c84e","contributors":{"authors":[{"text":"Lambert, Brad A.","contributorId":173020,"corporation":false,"usgs":false,"family":"Lambert","given":"Brad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":649431,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schorr, Robert A.","contributorId":105239,"corporation":false,"usgs":true,"family":"Schorr","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":649432,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schneider, Scott C.","contributorId":174943,"corporation":false,"usgs":false,"family":"Schneider","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":649727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":649430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70259111,"text":"70259111 - 2016 - Geologic setting of the West Flank, a FORGE site adjacent to the Coso geothermal field","interactions":[],"lastModifiedDate":"2024-09-27T15:03:46.501771","indexId":"70259111","displayToPublicDate":"2016-09-27T07:19:03","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geologic setting of the West Flank, a FORGE site adjacent to the Coso geothermal field","docAbstract":"The West Flank FORGE (Frontier Observatory for Research in Geothermal Energy) site is located immediately west and outside of the Coso geothermal field, eastern California. Coso is a fluid-dominated, high temperature geothermal system that has been producing power continuously since 1987. The reservoir is composed of highly faulted, fractured and hydrothermally altered Cretaceous and Jurassic plutonic basement rocks. The heat source is a shallow, silicic magma chamber associated with overlying, Quaternary rhyolites and basalts of the Coso volcanic field. Over 30 years of development drilling and associated investigations demonstrates that several well-defined boundaries exist at Coso beyond which there is no commercial, hydrothermal geothermal potential. The West Flank is just west of one of these boundaries and it meets all required FORGE temperature (175-225˚C), host rock (crystalline rock), and depth (1.5-4.0 km) criteria.
It has been hypothesized that the Coso volcanic field exists within a right-releasing step-over between two NW-striking, dextral fault systems. Two distinct fault populations yield high permeability drilling targets in the geothermal field. The first population contains WNW-trending with antithetical, NE-trending strike-slip faults and the second includes N- to NNE-trending normal faults. The West Flank appears to be separated from the geothermal field by one such northerly trending fault bounded by a felsic dike swarm. The West Flank’s 83-11 well suggests that the West Flank is comprised of weakly altered, leucogranite and diorites typical of the Jurassic to Cretaceous basement. The stress field in the West Flank has been rotated to 81˚ in contrast to the minimum principal stress orientations within the geothermal field which range from 103˚ to 108˚. Limited drilling, geophysics and other data sets are being assessed and synthesized to develop a working, 3d conceptual geologic model of the West Flank for FORGE.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 41st Workshop on Geothermal Reservoir Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"41st Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 22-24, 2016","conferenceLocation":"Stanford, CA","language":"English","publisher":"Stanford University","usgsCitation":"Sabin, A., Blake, K., Lazaro, M., Meade, D., Blankenship, D., Kennedy, M., McCulloch, J., DeOreo, S., Hickman, S.H., Glen, J.M., Kaven, J., Schoenball, M., Williams, C.F., Phelps, G., Faulds, J., Hinz, N., Calvin, W., Siler, D., and Robertson-Tait, A., 2016, Geologic setting of the West Flank, a FORGE site adjacent to the Coso geothermal field, in Proceedings of the 41st Workshop on Geothermal Reservoir Engineering, Stanford, CA, February 22-24, 2016, 11 p.","productDescription":"11 p.","ipdsId":"IP-073183","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics 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But predicting the impacts of invasive species is daunting, particularly in large systems threatened by multiple invasive species, such as North America’s Laurentian Great Lakes. We developed and evaluated a scenario-building process that relied on an expert panel to assess possible future impacts of aquatic invasive species on recreational fishing in the Great Lakes. To maximize its usefulness to policy makers, this process was designed to be implemented relatively rapidly and consider a range of species. The expert panel developed plausible, internally-consistent invasion scenarios for 5 aquatic invasive species, along with subjective probabilities of those scenarios. We describe these scenarios and evaluate this approach for assessing future invasive species impacts. The panel held diverse opinions about the likelihood of the scenarios, and only one scenario with impacts on sportfish species was considered likely by most of the experts. These outcomes are consistent with the literature on scenario building, which advocates for developing a range of plausible scenarios in decision making because the uncertainty of future conditions makes the likelihood of any particular scenario low. We believe that this scenario-building approach could contribute to policy decisions about whether and how to address the possible impacts of invasive species. 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The Hanford Natural Resource Trustee Council requested that the U.S. Geological Survey perform this interpolation to assess the accuracy of delineations previously conducted by the U.S. Department of Energy and its contractors, in order to assure that the Natural Resource Damage Assessment could rely on these analyses. This study is based on previously existing chemical (or radionuclide) sampling and analysis data downloaded from publicly available Hanford Site Internet sources, geostatistically selected and interpreted as representative of current (from 2009 through part of 2012) but average conditions for groundwater contamination in the study area. The study is limited in scope to five contaminants—hexavalent chromium, tritium, nitrate, strontium-90, and carbon-14, all detected at concentrations greater than regulatory limits in the past.
All recent analytical concentrations (or activities) for each contaminant, adjusted for radioactive decay, non-detections, and co-located wells, were converted to log-normal distributions and these transformed values were averaged for each well location. The log-normally linearized well averages were spatially interpolated on a 50 × 50-meter (m) grid extending across the combined 100-N and 100-K Areas study area but limited to avoid unrepresentative extrapolation, using the minimum curvature geostatistical interpolation method provided by SURFER®data analysis software. Plume extents were interpreted by interpolating the log-normally transformed data, again using SURFER®, along lines of equal contaminant concentration at an appropriate established regulatory concentration . Total areas for each plume were calculated as an indicator of relative environmental damage. These plume extents are shown graphically and in tabular form for comparison to previous estimates. Plume data also were interpolated to a finer grid (10 × 10 m) for some processing, particularly to estimate volumes of contaminated groundwater. However, hydrogeologic transport modeling was not considered for the interpolation. The compilation of plume extents for each contaminant also allowed estimates of overlap of the plumes or areas with more than one contaminant above regulatory standards.
A mapping of saturated aquifer thickness also was derived across the 100-K and 100–N study area, based on the vertical difference between the groundwater level (water table) at the top and the altitude of the top of the Ringold Upper Mud geologic unit, considered the bottom of the uppermost unconfined aquifer. Saturated thickness was calculated for each cell in the finer (10 × 10 m) grid. The summation of the cells’ saturated thickness values within each polygon of plume regulatory exceedance provided an estimate of the total volume of contaminated aquifer, and the results also were checked using a SURFER® volumetric integration procedure. The total volume of contaminated groundwater in each plume was derived by multiplying the aquifer saturated thickness volume by a locally representative value of porosity (0.3).
Estimates of the uncertainty of the plume delineation also are presented. “Upper limit” plume delineations were calculated for each contaminant using the same procedure as the “average” plume extent except with values at each well that are set at a 95-percent upper confidence limit around the log-normally transformed mean concentrations, based on the standard error for the distribution of the mean value in that well; “lower limit” plumes are calculated at a 5-percent confidence limit around the geometric mean. These upper- and lower-limit estimates are considered unrealistic because the statistics were increased or decreased at each well simultaneously and were not adjusted for correlation among the well distributions (i.e., it is not realistic that all wells would be high simultaneously). Sources of the variability in the distributions used in the upper- and lower-extent maps include time varying concentrations and analytical errors.
The plume delineations developed in this study are similar to the previous plume descriptions developed by U.S. Department of Energy and its contractors. The differences are primarily due to data selection and interpolation methodology. The differences in delineated plumes are not sufficient to result in the Hanford Natural Resource Trustee Council adjusting its understandings of contaminant impact or remediation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161161","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Hanford Natural Resource Trustee Council","usgsCitation":"Johnson, K.H., 2016, Groundwater contaminant plume maps and volumes, 100-K and 100–N Areas, Hanford Site, Washington: U.S. Geological Survey Open-File Report 2016–1161, 64 p., https://dx.doi.org/10.3133/ofr20161161.","productDescription":"Report: vi, 64 p.; Appendix A","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-071546","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1161/coverthb.jpg"},{"id":329029,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1161/ofr20161161.pdf","text":"Report","size":"21.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1161"},{"id":329030,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1161/ofr20161161_appendixa.xlsx","text":"Appendix A","size":"2.1 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1161 Appendix A"}],"country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.83886718750001,\n 46.25204849722291\n ],\n [\n -119.83886718750001,\n 46.82637528602131\n ],\n [\n -119.19616699218749,\n 46.82637528602131\n ],\n [\n -119.19616699218749,\n 46.25204849722291\n ],\n [\n -119.83886718750001,\n 46.25204849722291\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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Three different geophysical sensor types were used to characterize the underwater pressure waves and ground velocities generated by the underwater firing of seismic water guns. These studies evaluated the use of water guns as a tool to alter the movement of Asian carp. Asian carp are aquatic invasive species that threaten to move into the Great Lakes Basin from the Mississippi River Basin. Previous studies have identified a threshold of approximately 5 pounds per square inch (lb/in2) for behavioral modification and for structural limitation of a water gun barrier.
Two studies were completed during August 2014 and May 2015 in a backwater pond connected to the Illinois River at a sand and gravel quarry near Morris, Illinois. The August 2014 study evaluated the performance of two 80-cubic-inch (in3) water guns. Data from the 80-in3 water guns showed that the pressure field had the highest pressures and greatest extent of the 5-lb/in2 target value at a depth of 5 feet (ft). The maximum recorded pressure was 13.7 lb/in2, approximately 25 ft from the guns. The produced pressure field took the shape of a north-south-oriented elongated sphere with the 5-lb/in2 target value extending across the entire study area at a depth of 5 ft. Ground velocities were consistent over time, at 0.0067 inches per second (in/s) in the transverse direction, 0.031 in/s in the longitudinal direction, and 0.013 in/s in the vertical direction.
The May 2015 study evaluated the performance of one and two 100-in3 water guns. Data from the 100-in3 water guns, fired both individually and simultaneously, showed that the pressure field had the highest pressures and greatest extent of the 5-lb/in2 target value at a depth of 5 ft. The maximum pressure was 57.4 lb/in2, recorded at the underwater blast sensor closest to the water guns (at a horizontal distance of approximately 3 ft), as two guns fired simultaneously. Pressures and extent of the 5-lb/in2 target value decrease above and below this 5-ft depth, producing a relatively north-south-oriented pressure field shaped like an elongated sphere.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165098","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency as part of the Great Lakes Restoration Initiative","usgsCitation":"Koebel, C.M., and Egly, R.M., 2016, Water pressure and ground vibrations induced by water guns at a backwater pond on the Illinois River near Morris, Illinois: U.S. Geological Survey Scientific Investigations Report 2016–5098, 29 p., https://dx.doi.org/10.3133/sir20165098.","productDescription":"Report: v, 29 p.; Dataset","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-072620","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":328926,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2016/5098/sir20165098_morris_seismic_data.zip","text":"Seismic Data","size":"890.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2016-5098 Seismic Data"},{"id":328934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5098/coverthb.jpg"},{"id":328935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5098/sir20165098.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5098"}],"country":"United States","state":"Illinois","city":"Morris","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.50388526916504,\n 41.32726186584144\n ],\n [\n -88.50388526916504,\n 41.334738165428035\n ],\n [\n -88.46534729003906,\n 41.334738165428035\n ],\n [\n -88.46534729003906,\n 41.32726186584144\n ],\n [\n -88.50388526916504,\n 41.32726186584144\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director , Illinois-Iowa Water Science Center
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http://il.water.usgs.gov
Scientists and technical support staff from the U.S. Geological Survey measured suspended-sediment concentrations, currents, pressure, and water temperature in two tidal creeks, Reedy Creek and Dinner Creek, in Barnegat Bay, New Jersey, from August 11, 2014, to July 10, 2015 as part of the Estuarine Physical Response to Storms project (GS2–2D). The oceanographic and water-quality data quantify suspended-sediment transport in Reedy Creek and Dinner Creek, which are part of a tidal marsh wetland complex in the Edwin B. Forsythe National Wildlife Refuge. All deployed instruments were removed between January 7, 2015, and April 14, 2015, to avoid damage by ice.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161149","usgsCitation":"Suttles, S.E., Ganju, N.K, Montgomery, E.T., Dickhudt, P.J., Borden, Jonathan., Brosnahan, S.M., and Martini, M.A., 2016, Summary of oceanographic and water-quality measurements in Barnegat Bay, New Jersey, 2014–15: U.S. Geological Survey Open-File Report 2016–1149, 22 p., https://dx.doi.org/10.3133/ofr20161149.","productDescription":"Report: vii, 22 p.; Appendix: 1-2","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076598","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328800,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1149/appendix/downloads/adcptransects","text":"Appendix 2 ","description":"OFR 2016-1149","linkHelpText":"- Acoustic Doppler Current Profiler Transect Data, August 2014 and May 2015 for Reedy and Dinner Creeks"},{"id":328792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1149/coverthb.jpg"},{"id":328793,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1149/ofr20161149.pdf","text":"Report","size":"5.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1149"},{"id":328794,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1149/appendix/downloads/watersamples/ofr20161149_appendix1.zip","text":"Appendix 1","size":"40.4 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1149","linkHelpText":"- Water Sample Data, August 2014 to January 2015 and April to July 2015"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.55184936523438,\n 39.36190883564925\n ],\n [\n -74.55184936523438,\n 40.08752795413118\n ],\n [\n -74.02450561523438,\n 40.08752795413118\n ],\n [\n -74.02450561523438,\n 39.36190883564925\n ],\n [\n -74.55184936523438,\n 39.36190883564925\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
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MODPATH is a particle-tracking post-processing program designed to work with MODFLOW, the U.S. Geological Survey (USGS) finite-difference groundwater flow model. MODPATH version 7 is the fourth major release since its original publication. Previous versions were documented in USGS Open-File Reports 89–381 and 94–464 and in USGS Techniques and Methods 6–A41.
MODPATH version 7 works with MODFLOW-2005 and MODFLOW–USG. Support for unstructured grids in MODFLOW–USG is limited to smoothed, rectangular-based quadtree and quadpatch grids.
A software distribution package containing the computer program and supporting documentation, such as input instructions, output file descriptions, and example problems, is available from the USGS over the Internet (http://water.usgs.gov/ogw/modpath/).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161086","usgsCitation":"Pollock, D.W., 2016, User guide for MODPATH Version 7—A particle-tracking model for MODFLOW: U.S. Geological Survey Open-File Report 2016–1086, 35 p., https://dx.doi.org/10.3133/ofr20161086. ","productDescription":"v, 35 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073899","costCenters":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"links":[{"id":325509,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr94464","text":"Open-File Report 1994-464","description":"ofr 2016-1086","linkHelpText":"- User's guide for MODPATH/MODPATH-PLOT, Version 3; a particle tracking post-processing package for MODFLOW, the U.S. Geological Survey finite-difference ground-water flow model"},{"id":325510,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm6A41","text":"Techniques and Methods 6-A41","linkFileType":{"id":5,"text":"html"},"description":"ofr 2016-1086","linkHelpText":"- User guide for MODPATH Version 6 - A particle-tracking model for MODFLOW"},{"id":325508,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr89381","text":"Open-File Report 1989-381","description":"ofr 2016-1086","linkHelpText":"- Documentation of computer programs to compute and display pathlines using results from the U.S. Geological Survey modular three-dimensional finite-difference ground-water flow model"},{"id":325506,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1086/coverthb.jpg"},{"id":325507,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1086/ofr20161086.pdf","text":"Report","size":"3.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"ofr 2016-1086"},{"id":328711,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://water.usgs.gov/ogw/modpath/","text":"MODPATH Version 7","description":"ofr 2016-1086","linkHelpText":"- MODPATH: A Particle-Tracking Model for MODFLOW"}],"contact":"Office of Groundwater
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Mail Stop 411
12201 Sunrise Valley Drive
Reston, VA 20192
http://water.usgs.gov/ogw/
Occurrence models that account for imperfect detection of species are increasingly used for estimating geographical range, for determining species-landscape relations and to prioritize conservation actions worldwide. In 2010, we conducted a large-scale survey in Río Muni, the mainland territory of Equatorial Guinea, which aimed to estimate the probabilities of occurrence and detection of threatened mammals based on environmental covariates, and to identify priority areas for conservation. Interviews with hunters were designed to record presence/absence data of seven species (golden cat, leopard, forest elephant, forest buffalo, western gorilla, chimpanzee and mandrill) in 225 sites throughout the region. We fitted single season occupancy models and recently developed models which also include false positive errors (i.e. species detected in places where it actually does not occur), which should provide more accurate estimates for most species, which are susceptible to mis-identification. Golden cat and leopard had the lowest occurrence rates in the region, whereas primates had the highest rates. All species, except gorilla, were affected negatively by human settlements. The southern half of Río Muni showed the highest occurrence of the species studied, and conservation strategies for ensuring the persistence of threatened mammals should be focused on this area.
","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/srep33838","usgsCitation":"Martinez-Marti, C., Jimenez-Franco, M.V., Royle, J., Palazon, J.A., and Calvo, J.F., 2016, Integrating occurrence and detectability patterns based on interview data: a case study for threatened mammals in Equatorial Guinea: Scientific Reports, v. 6, 33838; 9 p., https://doi.org/10.1038/srep33838.","productDescription":"33838; 9 p.","ipdsId":"IP-078834","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470554,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep33838","text":"Publisher Index Page"},{"id":329485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Equatorial Guinea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 9.8162841796875,\n 2.3668802418421357\n ],\n [\n 9.84375,\n 2.3394375828714224\n ],\n [\n 9.832763671875,\n 2.311994386907854\n ],\n [\n 9.832763671875,\n 2.28455066023697\n ],\n [\n 9.8822021484375,\n 2.2406396093827334\n ],\n [\n 9.9151611328125,\n 2.2077054557054083\n ],\n [\n 9.942626953125,\n 2.20221635884472\n ],\n [\n 10.0140380859375,\n 2.180259769681356\n ],\n [\n 10.074462890625,\n 2.169281354771587\n ],\n [\n 10.140380859375,\n 2.169281354771587\n ],\n [\n 10.1788330078125,\n 2.1747705722118864\n ],\n [\n 10.2777099609375,\n 2.180259769681356\n ],\n [\n 11.35986328125,\n 2.1857489471296665\n ],\n [\n 11.348876953125,\n 0.9997051308419692\n ],\n [\n 9.7833251953125,\n 0.9997051308419692\n ],\n [\n 9.73388671875,\n 1.0656123898763876\n ],\n [\n 9.6734619140625,\n 1.0711045990129324\n ],\n [\n 9.569091796875,\n 1.016182073033441\n ],\n [\n 9.5526123046875,\n 1.0601201709472332\n ],\n [\n 9.5086669921875,\n 1.1150419135172274\n ],\n [\n 9.437255859375,\n 1.1095497845377595\n ],\n [\n 9.3878173828125,\n 1.087581167162357\n ],\n [\n 9.3328857421875,\n 1.1479944704491494\n ],\n [\n 9.327392578125,\n 1.2138984340943106\n ],\n [\n 9.3768310546875,\n 1.257833522873487\n ],\n [\n 9.3988037109375,\n 1.323734761011294\n ],\n [\n 9.437255859375,\n 1.3402098002785028\n ],\n [\n 9.4482421875,\n 1.417091829441639\n ],\n [\n 9.51416015625,\n 1.4720060101903352\n ],\n [\n 9.569091796875,\n 1.554374729735434\n ],\n [\n 9.5855712890625,\n 1.6202674001017445\n ],\n [\n 9.5965576171875,\n 1.6861579269987979\n ],\n [\n 9.667968749999998,\n 1.7520462233579808\n ],\n [\n 9.7119140625,\n 1.812441794538039\n ],\n [\n 9.7393798828125,\n 1.8893059628373186\n ],\n [\n 9.7943115234375,\n 1.9277367801405985\n ],\n [\n 9.7393798828125,\n 2.070472083193102\n ],\n [\n 9.766845703125,\n 2.180259769681356\n ],\n [\n 9.766845703125,\n 2.273573022378629\n ],\n [\n 9.7503662109375,\n 2.3504147112508176\n ],\n [\n 9.8162841796875,\n 2.3668802418421357\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-26","publicationStatus":"PW","scienceBaseUri":"57fe679ee4b0824b2d14370f","contributors":{"authors":[{"text":"Martinez-Marti, Chele","contributorId":175261,"corporation":false,"usgs":false,"family":"Martinez-Marti","given":"Chele","email":"","affiliations":[{"id":27549,"text":"Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jimenez-Franco, Maria V.","contributorId":175262,"corporation":false,"usgs":false,"family":"Jimenez-Franco","given":"Maria","email":"","middleInitial":"V.","affiliations":[{"id":27549,"text":"Departamento de Ecología e Hidrología, Facultad de Biología, Universidad de Murcia, Campus de Espinardo, 30100 Murcia, Spain","active":true,"usgs":false}],"preferred":false,"id":650628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. 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