The Great Plains of North America is defined as the land mass that encompasses the entire central portion of the North American continent that, at the time of European settlement, was an unbroken expanse of primarily herbaceous vegetation. The Great Plains extend from central Saskatchewan and Alberta to central Mexico and from Indiana to the Rocky Mountains. The expanses of herbaceous vegetation are often referred to as native prairie or native grasslands. Native grasslands share the characteristics of a general uniformity in vegetation structure, dominance by grasses and forbs, a near absence of trees and shrubs, annual precipitation ranging from 25 to 100 centimeters, extreme intra-annual fluctuations in temperature and precipitation, and a flat to rolling topography over which fires can spread. To the west of the Great Plains lie the sagebrush communities of the Great Basin, which extend from British Columbia and Saskatchewan to northern Arizona and New Mexico and from the eastern slopes of the Sierra Nevada and Cascade mountain ranges to western South Dakota. Sagebrush communities share similar characteristics to native grasslands, but their location east of the Rocky Mountains creates a more moderating influence from prevailing westerly winds that affect timing of peak precipitation and growth form of dominant vegetation. Native grasslands and sagebrush communities harbor a diverse array of grassland, wetland, and woodland plant and animal communities that are uniquely adapted to the natural forces of the Great Plains and Great Basin, namely the interactive forces of climate, fire, and grazing. The arrival of European settlers to North America brought profound change to native grassland and sagebrush communities, including the establishment of permanent towns and cities, the proliferation of cropland-based agricultural systems, and the suppression of wildfires. The near extirpation of bison by the 1860s paved the way for dramatic changes in the dominant grazers and a shift in the disturbance patterns that historically influenced vegetation structure. The greatest threat to native grasslands and sagebrush communities in modern times is their loss due to conversion to rowcrop agriculture and to urbanization. Concomitant with habitat loss is a precipitous decline in populations of bird species that evolved with, and are uniquely adapted to, the native grassland and sagebrush habitats. Avian population trends are linked strongly to agricultural land use. Besides outright loss of suitable breeding habitat, agricultural practices affect birds through factors such as pesticide exposure, habitat fragmentation, shifts in predator community composition, and occurrence of brood parasites. Bird populations face other stressors, such as loss of habitat to and behavioral avoidance of urbanized areas, roads, and infrastructure associated with energy production.
Despite the many anthropogenic changes to North American grassland and sagebrush communities, some bird species are adaptable and opportunistic in their habitat selection and now utilize one or more human-created habitats. Human-created habitats include pastures, hayfields, agricultural terraces, crop buffer strips, field borders, grassed waterways, fencerows, road rights-of-way, airports, reclaimed coal mines, and planted wildlife cover. Fields of seeded grasslands enrolled in Federal long-term set-aside programs, such as the Conservation Reserve Program in the United States and the Permanent Cover Program in Canada, provide important nesting habitat for grassland bird species. The array of habitats used by birds makes habitat and avian management a complex undertaking, and the scale (for example, local, regional, international) at which management actions can be implemented are such that a universal approach to managing grasslands for the conservation of the entire suite of bird species does not exist. Experienced land managers recognize that it is impossible to manage for all bird species simultaneously, and thus, prioritization is necessary towards those habitats or bird species that the manager or management agency ranks highest for a specific region or management unit. The primary tools available for management are burning, grazing, mowing, herbicide application, and idling, but before choosing a particular practice, a manager will want to consider issues of seasonality, intensity, and frequency.
Despite the thousands of studies that are cited in this compendium, much remains unknown about the effects of management practices on bird species. The series of species accounts in this compendium review the current state of knowledge regarding management of grassland and sagebrush bird species and summarize information on the effects of management practices on individual species. The accounts do not give definitive statements on the effects of management practices for any particular species, primarily because there are very few replicated studies in which identical management practices have been applied in the same geographical area with consistent results, which are elements necessary to provide concrete recommendations for the management of a particular species in a particular area. Documentation of the effects of management treatments on individual species through statistically sound methods that incorporate multiple years and locations will further scientists’ and land managers’ knowledge far more than 1–2-year studies that are limited in scope as well as time, but studies of that scope and breadth are rare.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The effects of management practices on grassland birds (Professional Paper 1842)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1842A","usgsCitation":"Shaffer, J.A., and DeLong, J.P., 2019, The effects of management practices on grassland birds—An introduction to North American grasslands and the practices used to manage grasslands and grassland birds (ver. 1.1, March 2022), chap. A of Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 63 p., https://doi.org/10.3133/pp1842A.","productDescription":"v, 63 p.","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097670","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":397809,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/pp/1842/a/versionhist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":365495,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/a/pp1842a.pdf","text":"Report","size":"8.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842 Chapter A"},{"id":365494,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/a/coverthb2.jpg"}],"edition":"Version 1.0: July 26, 2019; Version 1.1: March 31, 2022","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
Demographic models provide insight into which vital rates and life stages contribute most to population growth. Integral projection models (IPMs) offer flexibility in matching model structure to a species’ demography. For many rare species, data are lacking for key vital rates, and uncertainty might dissuade researchers from attempting to build a demographic model. We present work that highlights how the implications of uncertainties and unknowns can be explored by building and analyzing alternative models. We constructed IPMs for the threatened giant gartersnake (Thamnophis gigas) based on published studies to determine where management efforts could be targeted to have the greatest effect on population persistence and what unknowns remain for future research. Given uncertainty in the survival of snakes during their first year, and in the form of the size‐survival relationship, we modeled a range of scenarios and evaluated where models agree about factors influencing population growth and where discrepancies exist. For most scenarios, the survival of large adult females had the greatest influence on population growth, but the relative importance of juvenile versus adult somatic growth for population growth was dependent on the recruitment probability and the shape of the size‐survival function. More data on temporal variation and covariance among vital rates would improve stochastic models for the giant gartersnake. This paper demonstrates the effectiveness of IPMs for studying the demography of reptiles and the value of the model‐building process for formalizing what is known and unknown about the demography of rare species. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21728","usgsCitation":"Rose, J.P., Ersan, J., Wylie, G., Casazza, M.L., and Halstead, B., 2019, Demographic factors affecting population growth in giant gartersnakes: Journal of Wildlife Management, v. 83, no. 7, p. 1540-1551, https://doi.org/10.1002/jwmg.21728.","productDescription":"12 p.","startPage":"1540","endPage":"1551","ipdsId":"IP-101812","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":437380,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IBSR18","text":"USGS data release","linkHelpText":"Code and Data Files to Construct an Integral Projection Model for Giant Gartersnakes (Thamnophis gigas) in the Sacramento Valley, California, 1995-2017"},{"id":366444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.06909179687501,\n 38.0091482264894\n ],\n [\n -121.20666503906249,\n 38.0091482264894\n ],\n [\n -121.20666503906249,\n 39.57605638518604\n ],\n [\n -122.06909179687501,\n 39.57605638518604\n ],\n [\n -122.06909179687501,\n 38.0091482264894\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"83","issue":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Rose, Jonathan P. 0000-0003-0874-9166 jprose@usgs.gov","orcid":"https://orcid.org/0000-0003-0874-9166","contributorId":199339,"corporation":false,"usgs":true,"family":"Rose","given":"Jonathan","email":"jprose@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":768109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ersan, Julia 0000-0002-1549-7561","orcid":"https://orcid.org/0000-0002-1549-7561","contributorId":218034,"corporation":false,"usgs":true,"family":"Ersan","given":"Julia","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":768110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Glenn D. 0000-0002-7061-6658","orcid":"https://orcid.org/0000-0002-7061-6658","contributorId":207594,"corporation":false,"usgs":false,"family":"Wylie","given":"Glenn D.","affiliations":[],"preferred":false,"id":768111,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":768112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":768108,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206393,"text":"70206393 - 2019 - A spatial model of streaked horned lark breeding habitat in the Columbia River, USA","interactions":[],"lastModifiedDate":"2019-11-04T10:00:40","indexId":"70206393","displayToPublicDate":"2019-07-26T06:58:04","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"A spatial model of streaked horned lark breeding habitat in the Columbia River, USA","docAbstract":"The streaked horned lark (hereafter “lark”; Eremophila alpestris strigata) is a federally listed bird subspecies of the Pacific Northwest that occupies open landscapes with short vegetation and abundant bare ground. Across its breeding range, which has contracted dramatically, the lark relies primarily on human-modified habitats maintained in early successional states (e.g., agricultural fields, airfields, deposition islands). The focus of our study is the lower Columbia River where larks primarily occupy deposition islands created as a byproduct of shipping channel deepening (dredging) projects. The U.S. Army Corps of Engineers has proactively adopted a shifting-habitat-mosaic management approach when placing dredge (sand) materials to maintain lark habitat throughout the project area. To help achieve their goal, we created a geospatial tool capable of quantifying and tracking habitat suitability for larks throughout the project area with satellite imagery. We created spatial models of lark breeding habitat by incorporating lark survey data, Sentinel-2 satellite imagery, dredge-deposition maps, and surface-elevation models. We built candidate predictive models of lark breeding habitat after combining survey data (years 2016 and 2017), predictor variables, and logistic regression. In addition, we created a novel seral-stage predictor variable to identify young, mature, old, and unsuitable locations; critical information for lark conservation planning and dredge-disposal operational planning. We challenged probability models the year they were constructed (2016) and the following year (2017) with set-aside survey data. The best model contained terrain ruggedness, deposition age, vegetation greenness (e.g., lushness and density of vegetation) inside a 10-m cell, and heterogeneity in greenness within a 100-m radius. Verification accuracy ranged from 75 to 83% depending on the model tested and year. Importantly, the seral-stage variable allowed us to quantify and locate early, optimal, and late habitats. Model results will facilitate conservation planning decisions by informing real-time management decisions. Furthermore, they provide a foundation for application in other human-modified habitats across the species’ range.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2019.108734","usgsCitation":"Hatten, J., Slater, G.L., Treadwell, J.L., and Stevenson, M.R., 2019, A spatial model of streaked horned lark breeding habitat in the Columbia River, USA: Ecological Modelling, v. 409, 108734, 23 p., https://doi.org/10.1016/j.ecolmodel.2019.108734.","productDescription":"108734, 23 p.","ipdsId":"IP-104993","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":467421,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2019.108734","text":"Publisher Index Page"},{"id":368862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Columbia 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\"}}]}","volume":"409","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hatten, James 0000-0003-4676-8093","orcid":"https://orcid.org/0000-0003-4676-8093","contributorId":220165,"corporation":false,"usgs":true,"family":"Hatten","given":"James","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":774381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Gary L.","contributorId":220166,"corporation":false,"usgs":false,"family":"Slater","given":"Gary","email":"","middleInitial":"L.","affiliations":[{"id":40136,"text":"Center for Natural Lands Management, Olympia,WA","active":true,"usgs":false}],"preferred":false,"id":774382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Treadwell, Jerrmaine L.","contributorId":220167,"corporation":false,"usgs":false,"family":"Treadwell","given":"Jerrmaine","email":"","middleInitial":"L.","affiliations":[{"id":40136,"text":"Center for Natural Lands Management, Olympia,WA","active":true,"usgs":false}],"preferred":false,"id":774383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stevenson, Matthew R.","contributorId":220168,"corporation":false,"usgs":false,"family":"Stevenson","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":40137,"text":"CoreGIS, Seattle,WA","active":true,"usgs":false}],"preferred":false,"id":774384,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70206149,"text":"70206149 - 2019 - Three-layered silver nanoparticles to trace dissolution and association to a green alga","interactions":[],"lastModifiedDate":"2019-10-24T06:53:33","indexId":"70206149","displayToPublicDate":"2019-07-26T06:52:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2809,"text":"Nanotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Three-layered silver nanoparticles to trace dissolution and association to a green alga","docAbstract":"Core-shell silver nanoparticles (NPs) consisting of an inner Ag core and successive layers of Au and Ag (Ag@Au@Ag) were used to measure the simultaneous association of Ag NPs and ionic Ag by the green alga Chlamydomonas (C.) reinhardtii. Dissolution of the inner Ag core was prevented by a gold (Au) layer, while the outer Ag layer was free to dissolve. In short term experiments, we exposed C. reinhardtii to a range of environmentally realistic Ag concentrations added as AgNO3 or as NPs. Results provide three lines of evidence for the greater cell-association of NPs compared to dissolved Ag over the concentration range tested, assuming that cell-association comprises both uptake and adsorption. First, the cell-association rate constants (kuw) for total Ag (AgNP+D), NPs (AgNP) and AuNP were similar and 2.2-fold higher than the one from AgD exposure, suggesting predominant association of the particles over the dissolved form. Second, model calculations based upon Ag fluxes suggested that only 6-33% of algal burden was from AgD. Thirdly, the significantly lower AgNP/Au ratio measured with the algae after exposure (2.1 ± 0.1) compared to the AgNP/Au ratio of the NPs in the media (2.47 ± 0.05) suggests cell-association of NPs depleted in Ag. Core-shell NPs provide an innovative tool to understand NP behavior and to directly delineate Ag accumulation from ion and NPs in aquatic systems.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/17435390.2019.1640912","usgsCitation":"Ponton, D., Croteau, M.N., Luoma, S.N., Pourhoseini, S., Merrifield, R., and Jamie Lead, 2019, Three-layered silver nanoparticles to trace dissolution and association to a green alga: Nanotoxicology, v. 13, no. 9, p. 1149-1160, https://doi.org/10.1080/17435390.2019.1640912.","productDescription":"12 p.","startPage":"1149","endPage":"1160","ipdsId":"IP-087209","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":368546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Ponton, Dominic","contributorId":219987,"corporation":false,"usgs":false,"family":"Ponton","given":"Dominic","email":"","affiliations":[{"id":40104,"text":"University of Montreal, Canada","active":true,"usgs":false}],"preferred":false,"id":773729,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":773728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luoma, Samuel N","contributorId":219988,"corporation":false,"usgs":false,"family":"Luoma","given":"Samuel","email":"","middleInitial":"N","affiliations":[{"id":40105,"text":"UC Davis, CA","active":true,"usgs":false}],"preferred":false,"id":773730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pourhoseini, Sahar","contributorId":219989,"corporation":false,"usgs":false,"family":"Pourhoseini","given":"Sahar","email":"","affiliations":[{"id":40106,"text":"University of South Carolina, SC","active":true,"usgs":false}],"preferred":false,"id":773731,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Merrifield, Ruth","contributorId":219990,"corporation":false,"usgs":false,"family":"Merrifield","given":"Ruth","email":"","affiliations":[{"id":40106,"text":"University of South Carolina, SC","active":true,"usgs":false}],"preferred":false,"id":773732,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jamie Lead","contributorId":219991,"corporation":false,"usgs":false,"family":"Jamie Lead","affiliations":[{"id":40106,"text":"University of South Carolina, SC","active":true,"usgs":false}],"preferred":false,"id":773733,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70205196,"text":"70205196 - 2019 - Wetland management strategy to reduce mercury export in water and bioaccumulation in fish","interactions":[],"lastModifiedDate":"2019-10-09T09:57:15","indexId":"70205196","displayToPublicDate":"2019-07-25T15:27:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Wetland management strategy to reduce mercury export in water and bioaccumulation in fish","docAbstract":"Wetland environments provide numerous ecosystem services but also facilitate methylmercury (MeHg) production and bioaccumulation. We developed a wetland‐management technique to reduce MeHg concentrations in wetland fish and water. We physically modified seasonal wetlands by constructing open‐ and deep‐water treatment cells at the downstream end of seasonal wetlands to promote naturally occurring MeHg‐removal processes. We assessed the effectiveness of reducing mercury (Hg) concentrations in surface water and western mosquitofish that were caged at specific locations within 4 control and 4 treatment wetlands. Methylmercury concentrations in wetland water were successfully decreased within treatment cells during only the third year of study; however, treatment cells were not effective for reducing total Hg concentrations. Furthermore, treatment cells were not effective for reducing total Hg concentrations in wetland fish. Mercury concentrations in fish were not correlated with total Hg concentrations in filtered, particulate, or whole water; and the slope of the correlation with water MeHg concentrations differed between months. Fish total Hg concentrations were weakly correlated with water MeHg concentrations in April when fish were introduced into cages but were not correlated in May when fish were retrieved from cages. Fish total Hg concentrations were greater in treatment wetlands than in control wetlands the year after the treatment wetlands’ construction but declined by the second year. During the third year, fish total Hg concentrations increased in both control and treatment wetlands after an unexpected regional flooding event. Overall, we found limited support for the use of open‐ and deep‐water treatment cells at the downstream end of wetlands to reduce MeHg concentrations in water but not fish. We suggest that additional evaluation over a longer period of time is necessary.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4535","usgsCitation":"Ackerman, J., Fleck, J., Eagles-Smith, C.A., Marvin-DiPasquale, M.C., Windham-Myers, L., Herzog, M.P., and McQuillen, H.L., 2019, Wetland management strategy to reduce mercury export in water and bioaccumulation in fish: Environmental Toxicology and Chemistry, v. 38, no. 10, p. 2178-2196, https://doi.org/10.1002/etc.4535.","productDescription":"19 p.","startPage":"2178","endPage":"2196","ipdsId":"IP-104169","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437381,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NUANQU","text":"USGS data release","linkHelpText":"Wetland Management Strategy to Reduce Mercury Export in Water and Bioaccumulation in Fish"},{"id":367232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":770315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":770317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":770318,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Windham-Myers, Lisamarie lwindham-myers@usgs.gov","contributorId":218804,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":770319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":770320,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McQuillen, Harry L.","contributorId":218805,"corporation":false,"usgs":false,"family":"McQuillen","given":"Harry","email":"","middleInitial":"L.","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":770321,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70207453,"text":"70207453 - 2019 - The effect of stress changes on time-dependent earthquake probabilities for the central Wasatch Fault Zone, Utah, USA","interactions":[],"lastModifiedDate":"2019-12-19T14:43:31","indexId":"70207453","displayToPublicDate":"2019-07-25T14:41:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"The effect of stress changes on time-dependent earthquake probabilities for the central Wasatch Fault Zone, Utah, USA","docAbstract":"Static and quasi-static Coulomb stress changes produced by large earthquakes can modify the probability of occurrence of subsequent events on neighboring faults. This approach is based on physical (Coulomb stress changes) and statistical (probability calculations) models, which are influenced by the quality and quantity of data available in the study region. Here, we focus on the Wasatch Fault Zone (WFZ), a well-studied active normal fault system having abundant geologic and paleoseismological data. Paleoseismological trench investigations of the WFZ indicate that at least 24 large, surface-faulting earthquakes have ruptured the fault’s five central, 35–59-km long segments since ~7 ka. Our goal is to determine if the stress changes due to the youngest paleoevents have significantly modified the present-day probability of occurrence of large earthquakes on each of the segments. For each segment, we modeled the cumulative (coseismic + postseismic) Coulomb stress changes (∆CFScum) due to earthquakes younger than the most recent event on the segment in question and applied the resulting values to the time-dependent probability calculations. Results from the Coulomb stress modeling suggest that the Brigham City, Salt Lake City, and Provo segments have accumulated ∆CFScum larger than 10 bars, whereas the Weber segment has experienced a stress decrease of 5 bars, in the scenario of recent rupture of the Great Salt Lake fault to the west. Probability calculations predict high probability of occurrence for the Brigham City and Salt Lake City segments, due to their long elapsed times (>1-2 ka) when compared to the Weber, Provo, and Nephi segments (< 1 ka). The range of calculated coefficients of variation (CV) has a large influence on the final probabilities, mostly in the case of the Brigham City segment. Finally, when the Coulomb stress and the probability models are combined, our results indicate that the ∆CFScum resulting from earthquakes postdating the youngest events on each of the five segments significantly affects the probability calculations for three of the segments: Brigham City, Salt Lake City, and Provo. The probability of occurrence of a large earthquake in the next 50 years on these three segments may therefore be underestimated if a time-independent approach, or a time-dependent approach that does not consider ∆CFS, is adopted.","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggz336","usgsCitation":"Verdecchia, A., Carena, S., Pace, B., and DuRoss, C., 2019, The effect of stress changes on time-dependent earthquake probabilities for the central Wasatch Fault Zone, Utah, USA: Geophysical Journal International, v. 219, no. 2, p. 1065-1081, https://doi.org/10.1093/gji/ggz336.","productDescription":"17 p.","startPage":"1065","endPage":"1081","ipdsId":"IP-105869","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467422,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/bw6ur/","text":"External Repository"},{"id":370511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.046551,41.251716],[-111.046723,40.997959],[-110.750727,40.996847],[-110.715026,40.996347],[-110.539819,40.996346],[-110.500718,40.994746],[-110.375714,40.994947],[-110.250709,40.996089],[-110.237848,40.995427],[-110.125709,40.99655],[-110.121639,40.997101],[-110.048476,40.997555],[-110.006495,40.997815],[-110.000708,40.997352],[-109.999838,40.99733],[-109.97553,40.997912],[-109.855299,40.997614],[-109.854302,40.997661],[-109.715409,40.998191],[-109.713877,40.998266],[-109.676421,40.998395],[-109.534926,40.998143],[-109.500694,40.999127],[-109.250735,41.001009],[-109.231985,41.002059],[-109.173682,41.000859],[-109.050076,41.000659],[-109.048455,40.826081],[-109.049088,40.714562],[-109.048373,40.662602],[-109.048249,40.653601],[-109.048044,40.619231],[-109.050074,40.540358],[-109.049955,40.539901],[-109.050698,40.499963],[-109.050314,40.495092],[-109.050946,40.444368],[-109.050969,40.222662],[-109.050973,40.180849],[-109.050944,40.180712],[-109.050813,40.059579],[-109.050873,40.058915],[-109.050615,39.87497],[-109.05104,39.660472],[-109.051363,39.497674],[-109.050765,39.366677],[-109.051512,39.126095],[-109.052436,38.999985],[-109.053292,38.942878],[-109.053233,38.942467],[-109.053797,38.905284],[-109.053943,38.904414],[-109.054189,38.874984],[-109.057388,38.795456],[-109.059541,38.719888],[-109.060253,38.599328],[-109.059962,38.499987],[-109.060062,38.275489],[-109.054648,38.244921],[-109.041762,38.16469],[-109.041837,38.153022],[-109.04282,37.999301],[-109.042819,37.997068],[-109.043121,37.97426],[-109.041058,37.907236],[-109.041653,37.88117],[-109.041844,37.872788],[-109.041723,37.842051],[-109.041754,37.835826],[-109.041461,37.800105],[-109.042098,37.74999],[-109.041636,37.74021],[-109.04176,37.713182],[-109.041732,37.711214],[-109.042269,37.666067],[-109.042089,37.623795],[-109.042131,37.617662],[-109.041806,37.604171],[-109.041865,37.530726],[-109.041915,37.530653],[-109.043137,37.499992],[-109.043464,37.484711],[-109.04581,37.374993],[-109.046039,37.249993],[-109.045584,37.249351],[-109.045487,37.210844],[-109.045978,37.201831],[-109.045995,37.177279],[-109.045156,37.112064],[-109.045203,37.111958],[-109.045173,37.109464],[-109.045189,37.096271],[-109.044995,37.086429],[-109.045058,37.074661],[-109.045166,37.072742],[-109.045223,36.999084],[-109.181196,36.999271],[-109.233848,36.999266],[-109.246917,36.999346],[-109.26339,36.999263],[-109.268213,36.999242],[-109.270097,36.999266],[-109.378039,36.999135],[-109.381226,36.999148],[-109.495338,36.999105],[-109.625668,36.998308],[-109.875673,36.998504],[-110.000677,36.997968],[-110.000876,36.998502],[-110.021778,36.998602],[-110.47019,36.997997],[-110.490908,37.003566],[-110.50069,37.00426],[-110.599512,37.003448],[-110.625605,37.003416],[-110.62569,37.003721],[-110.75069,37.003197],[-111.066496,37.002389],[-111.133718,37.000779],[-111.254853,37.001077],[-111.278286,37.000465],[-111.405517,37.001497],[-111.405869,37.001481],[-111.412784,37.001478],[-112.35769,37.001025],[-112.368946,37.001125],[-112.534545,37.000684],[-112.538593,37.000674],[-112.540368,37.000669],[-112.545094,37.000734],[-112.558974,37.000692],[-112.609787,37.000753],[-112.899366,37.000319],[-112.966471,37.000219],[-113.965907,36.999976],[-113.965907,37.000025],[-114.0506,37.000396],[-114.051749,37.088434],[-114.051822,37.090976],[-114.052827,37.103961],[-114.051867,37.134292],[-114.052179,37.14711],[-114.051673,37.172368],[-114.051405,37.233854],[-114.051974,37.283848],[-114.051974,37.284511],[-114.0518,37.293044],[-114.0518,37.293548],[-114.051927,37.370459],[-114.051927,37.370734],[-114.051765,37.418083],[-114.052448,37.43144],[-114.052701,37.492014],[-114.052685,37.502513],[-114.052718,37.517264],[-114.052689,37.517859],[-114.052962,37.592783],[-114.052472,37.604776],[-114.051728,37.745997],[-114.051785,37.746249],[-114.05167,37.746958],[-114.051109,37.756276],[-114.049919,37.765586],[-114.048473,37.809861],[-114.049677,37.823645],[-114.049928,37.852508],[-114.049658,37.881368],[-114.050423,37.999961],[-114.049903,38.148601],[-114.050138,38.24996],[-114.049417,38.2647],[-114.05012,38.404536],[-114.050091,38.404673],[-114.050485,38.499955],[-114.049834,38.543784],[-114.049862,38.547764],[-114.050154,38.57292],[-114.049883,38.677365],[-114.049749,38.72921],[-114.049168,38.749951],[-114.049465,38.874949],[-114.048521,38.876197],[-114.048054,38.878693],[-114.049104,39.005509],[-114.047079,39.499943],[-114.047728,39.542742],[-114.047273,39.759413],[-114.047783,39.79416],[-114.047214,39.821024],[-114.047134,39.906037],[-114.046555,39.996899],[-114.046835,40.030131],[-114.046386,40.097896],[-114.046741,40.104231],[-114.046683,40.116931],[-114.046153,40.231971],[-114.046178,40.398313],[-114.045826,40.424823],[-114.045218,40.430282],[-114.045518,40.494474],[-114.045577,40.495801],[-114.045281,40.506586],[-114.043505,40.726292]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\"}}]}","volume":"219","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Verdecchia, A.","contributorId":221418,"corporation":false,"usgs":false,"family":"Verdecchia","given":"A.","affiliations":[{"id":40369,"text":"Institute of Geology, Mineralogy and Geophysics, Ruhr-University Bochum, Bochum, Germany; Department of Earth and Environmental Sciences, Ludwig-Maximilians University, Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":778107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carena, S.","contributorId":221419,"corporation":false,"usgs":false,"family":"Carena","given":"S.","email":"","affiliations":[{"id":40370,"text":"Department of Earth and Environmental Sciences, Ludwig-Maximilians University, Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":778108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pace, B.","contributorId":221420,"corporation":false,"usgs":false,"family":"Pace","given":"B.","email":"","affiliations":[{"id":40371,"text":"DiSPUTer, Universita' G. d'Annunzio di Chieti-Pescara, Chieti, Italy","active":true,"usgs":false}],"preferred":false,"id":778109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778110,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204456,"text":"70204456 - 2019 - Alongshore momentum balance over shoreface-connected ridges, Fire Island, NY","interactions":[],"lastModifiedDate":"2019-07-26T09:51:59","indexId":"70204456","displayToPublicDate":"2019-07-25T12:47:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Alongshore momentum balance over shoreface-connected ridges, Fire Island, NY","docAbstract":"Hydrodynamic and hydrographic data collected on the inner shelf of Fire Island, NY, over a region of shoreface-connected ridges (SFCRs) are used to describe wind-driven circulation over uneven topographies along relatively straight coastlines. The data revealed a predominantly alongshore flow, under westward wind forcing, with localized offshore current veering over the SFCR crests associated with an onshore veering over the adjacent troughs. Momentum balance analysis of the observations revealed that local acceleration, advective acceleration, and bottom stress are balanced by wind stress and regional (>100 km) pressure gradient force. Numerical model results based on simulations of an idealized SFCR bathymetry, as in Warner et al. (2014) but forced with the observed winds, are used to verify the experimentally derived results and constraint inaccuracies in the momentum balance term relationships revealed using the field data. As with previous SFCR studies, our experimental results indicate a current veering over ridge crests. Veering is driven primarily by two processes: cross-shore variation of alongshore advective acceleration which creates cross-shore pressure gradient and drives flow (described as a Bernoulli-like process), and, bottom frictional-torque.\nA synthesis of the numerical and experimental data revealed that the total pressure gradient force can be considered as the sum of a local and a regional pressure gradient force. The former is correlated with the alongshore advective acceleration that develops over the crest of the ridges resembling a Bernoulli-like pressure-flow relationship. The regional pressure gradient force is related to wind stress with which maintains a strong, negative relationship. The realistic driving force analysis revealed the different contributions of the local and regional scale pressure gradients. Under realistic and variable wind conditions the regional pressure gradients are more important and the influence of the local scale pressure gradient increases as the flow reaches quasi steady-state conditions. A time scale of 6 hours was defined as the temporal scale required for the local pressure gradients to have an effect","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2019.07.005","usgsCitation":"Ofsthun, C., Wu, X., Voulgaris, G., and Warner, J., 2019, Alongshore momentum balance over shoreface-connected ridges, Fire Island, NY: Continental Shelf Research, v. 186, p. 21-33, https://doi.org/10.1016/j.csr.2019.07.005.","productDescription":"13 p.","startPage":"21","endPage":"33","ipdsId":"IP-093237","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467423,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2019.07.005","text":"Publisher Index Page"},{"id":365951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.31863403320312,\n 40.66709790906187\n ],\n [\n -72.46444702148438,\n 40.66709790906187\n ],\n [\n -72.46444702148438,\n 40.85537053192494\n ],\n [\n -73.31863403320312,\n 40.85537053192494\n ],\n [\n -73.31863403320312,\n 40.66709790906187\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"186","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ofsthun, Conor","contributorId":217600,"corporation":false,"usgs":false,"family":"Ofsthun","given":"Conor","email":"","affiliations":[],"preferred":false,"id":767148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Xiaodong","contributorId":217601,"corporation":false,"usgs":false,"family":"Wu","given":"Xiaodong","email":"","affiliations":[],"preferred":false,"id":767149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voulgaris, George","contributorId":26377,"corporation":false,"usgs":false,"family":"Voulgaris","given":"George","email":"","affiliations":[{"id":27143,"text":"University of South Carolina, Columbia, SC","active":true,"usgs":false}],"preferred":false,"id":767150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767151,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204483,"text":"70204483 - 2019 - Towards recovery of an endangered island endemic: Distributional and behavioral responses of Key Largo woodrats associated with exotic predator removal","interactions":[],"lastModifiedDate":"2019-07-31T14:06:49","indexId":"70204483","displayToPublicDate":"2019-07-25T11:34:45","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Towards recovery of an endangered island endemic: Distributional and behavioral responses of Key Largo woodrats associated with exotic predator removal","docAbstract":"Exotic predators create novel ecological contexts for native species, particularly when prey exhibit predator naïve behaviors. Population recovery of island endemic species following predator eradication has been documented broadly, but studies examining mammalian prey behavioral responses to exotic predator removal are less common. The Key Largo woodrat (Neotoma floridana smalli) is an endangered Florida endemic species that exhibited drastic declines, signified by the loss of natural stick-nests, over the past three decades due to habitat loss and effects from exotic predators. We conducted camera trap surveys of woodrats at supplemental nests and used dynamic multistate occupancy models to evaluate changes in woodrat distribution and stick-nest building behavior over a two-year period of exotic predator (domestic cats [Felis catus] and Burmese pythons [Python bivittatus]) removal. The distribution of woodrats using supplemental nests increased from 27% to 39% in the two-year period, while the proportion of occupied supplemental nests with stick-nests increased from 37% in 2013 to 54% in 2015. The probabilities of supplemental nest use and stick-nest building behavior increased over time following a gradient away from the northern extent of Key Largo, an area associated with high cat activity and the only sites of python captures during the surveys. Woodrats that built stick-nests were more detectable than those that did not, which suggests that stick-nest building could make woodrats more susceptible to predation from novel predators when performing the behavior. We documented increasing woodrat occurrence, along with increasing stick-nest building behavior, which supports recovery and management objectives focused on exotic predator removal.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.07.032","usgsCitation":"Cove, M., Simons, T., Gardner, B., and O’Connell, A.F., 2019, Towards recovery of an endangered island endemic: Distributional and behavioral responses of Key Largo woodrats associated with exotic predator removal: Biological Conservation, v. 237, p. 423-429, https://doi.org/10.1016/j.biocon.2019.07.032.","productDescription":"7 p.","startPage":"423","endPage":"429","ipdsId":"IP-106113","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467424,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2019.07.032","text":"Publisher Index Page"},{"id":365984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Crocodile Lake National Wildlife Refuge, North Key Largo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.33512115478516,\n 25.242522196751892\n ],\n [\n -80.32379150390625,\n 25.229168280105522\n ],\n [\n -80.27847290039062,\n 25.301510302409604\n ],\n [\n -80.27503967285155,\n 25.311752681576287\n ],\n [\n -80.2606201171875,\n 25.326028492609215\n ],\n [\n -80.25581359863281,\n 25.333786379654885\n ],\n [\n -80.27778625488281,\n 25.335027595439435\n ],\n [\n -80.28980255126953,\n 25.324787184543645\n ],\n [\n -80.29151916503906,\n 25.315787320493133\n ],\n [\n -80.30593872070311,\n 25.30678678767568\n ],\n [\n -80.33306121826172,\n 25.286610751172574\n ],\n [\n -80.34095764160156,\n 25.290956642751954\n ],\n [\n -80.36567687988281,\n 25.28536903925994\n ],\n [\n -80.36602020263672,\n 25.280402064492023\n ],\n [\n -80.34164428710938,\n 25.264568475331583\n ],\n [\n -80.3323745727539,\n 25.263947508176397\n ],\n [\n -80.33512115478516,\n 25.242522196751892\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"237","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cove, Michael V.","contributorId":176507,"corporation":false,"usgs":false,"family":"Cove","given":"Michael V.","affiliations":[],"preferred":false,"id":767193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simons, Theodore","contributorId":217660,"corporation":false,"usgs":false,"family":"Simons","given":"Theodore","affiliations":[{"id":39678,"text":"NC State","active":true,"usgs":false}],"preferred":false,"id":767194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":767195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":767192,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223427,"text":"70223427 - 2019 - Population dynamics and evaluation of management scenarios for white sturgeon in the Sacramento-San Joaquin River basin","interactions":[],"lastModifiedDate":"2021-08-26T16:58:08.151328","indexId":"70223427","displayToPublicDate":"2019-07-25T11:26:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics and evaluation of management scenarios for white sturgeon in the Sacramento-San Joaquin River basin","docAbstract":"Recent surveys suggest a declining population of White Sturgeon Acipenser transmontanus in the Sacramento–San Joaquin River basin (SSJ), California. Probable reasons for the decline include overharvest and habitat degradation compounded by poor recruitment during recent droughts. Despite the importance and status of White Sturgeon, knowledge of their population dynamics in the SSJ remains incomplete and additional information is needed to further inform management decisions. The purpose of this study was to evaluate the population dynamics of White Sturgeon in the SSJ and use the information to estimate the population-level response under plausible management scenarios. White Sturgeon in the SSJ exhibited fast growth and high rates of mortality and experienced relatively high levels of exploitation. Under current conditions, the population will likely continue to decrease (population growth rate λ = 0.97); however, there was considerable uncertainty in estimates of future population growth. Population growth of White Sturgeon in the SSJ was most influenced by the survival of sexually mature adults. The models also suggested that White Sturgeon in the SSJ could reach the replacement rate (i.e., λ ≥ 1.00) if total annual mortality for age-3 and older fish does not exceed 6%. Low levels of exploitation (i.e., <3%) would likely be required to maintain a stable population.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10316","usgsCitation":"Blackburn, S.E., Gingras, M.L., DuBois, J., Jackson, Z.J., and Quist, M.C., 2019, Population dynamics and evaluation of management scenarios for white sturgeon in the Sacramento-San Joaquin River basin: North American Journal of Fisheries Management, v. 39, no. 5, p. 896-912, https://doi.org/10.1002/nafm.10316.","productDescription":"7 p.","startPage":"896","endPage":"912","ipdsId":"IP-103139","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":388552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.728271484375,\n 37.337408137077986\n ],\n [\n -121.54998779296874,\n 37.337408137077986\n ],\n [\n -121.54998779296874,\n 38.26621945628273\n ],\n [\n -122.728271484375,\n 38.26621945628273\n ],\n [\n -122.728271484375,\n 37.337408137077986\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Blackburn, Shannon E.","contributorId":264816,"corporation":false,"usgs":false,"family":"Blackburn","given":"Shannon","email":"","middleInitial":"E.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":822019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gingras, Marty L.","contributorId":264817,"corporation":false,"usgs":false,"family":"Gingras","given":"Marty","email":"","middleInitial":"L.","affiliations":[{"id":54562,"text":"cdfw","active":true,"usgs":false}],"preferred":false,"id":822020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DuBois, Jason","contributorId":264818,"corporation":false,"usgs":false,"family":"DuBois","given":"Jason","email":"","affiliations":[{"id":54562,"text":"cdfw","active":true,"usgs":false}],"preferred":false,"id":822021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Zachary J.","contributorId":264819,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","email":"","middleInitial":"J.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":822022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":822018,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204755,"text":"70204755 - 2019 - Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat","interactions":[],"lastModifiedDate":"2019-08-15T11:11:11","indexId":"70204755","displayToPublicDate":"2019-07-25T10:50:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat","docAbstract":"Coastal storms have consequences for human lives and infrastructure but also create important early successional habitats for myriad species. For example, storm-induced overwash creates nesting habitat for shorebirds like piping plovers (Charadrius melodus). We examined how piping plover habitat extent and location changed on barrier islands in New York, New Jersey, and Virginia after Hurricane Sandy made landfall following the 2012 breeding season. We modeled nesting habitat using a nest presence/absence dataset that included characterizations of coastal morphology and vegetation. Using a Bayesian network, we predicted nesting habitat for each study site for the years 2010/2011, 2012, and 2014/2015 based on remotely sensed spatial datasets (e.g., lidar, orthophotos). We found that Hurricane Sandy increased piping plover habitat by 9 to 300% at 4 of 5 study sites but that one site saw a decrease in habitat by 27%. The amount, location, and longevity of new habitat appeared to be influenced by the level of human development at each site. At three of the five sites, the amount of habitat created and the time new habitat persisted were inversely related to the amount of development. Furthermore, the proportion of new habitat created in high-quality overwash was inversely related to the level of development on study areas, from 17% of all new habitat in overwash at one of the most densely developed sites to 80% of all new habitat at an undeveloped site. We also show that piping plovers exploited new habitat after the storm, with 14–57% of all nests located in newly created habitat in the 2013 breeding season. Our results quantify the importance of storms in creating and maintaining coastal habitats for beach-nesting species like piping plovers, and these results suggest a negative correlation between human development and beneficial ecological impacts of these natural disturbances.
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Structured decision making addresses these considerations by identifying realistic fundamental objectives and building achievable management alternatives, within a quantitative modeling framework. The process is driven by participation of stakeholders that represent diverse objectives, policy mandates, and opinions regarding decision alternatives. We applied structured decision making to evaluate reintroduction of Bull Trout Salvelinus confluentus in the lower Pend Oreille River in northeastern Washington State. We engaged stakeholders from Tribal, municipal, county, state and federal agencies to specify fundamental objectives, formulate feasible reintroduction decisions, and conceptualize a modeling framework that includes biological information and stakeholder assumptions. Stakeholders requested iterative decision sets to determine the optimal recipient streams and release strategies. The optimal decision, based on the fundamental objective of maximizing adult abundance at year 10, was artificial propagation of 4500 juvenile Bull Trout coupled with translocation of 25 adult migrants to be reintroduced into a tributary and lake system that produced at least 18% more adult fish relative to alternatives. Sensitivity analyses were robust to the identity of the recipient stream (i.e., Sullivan Lake/Harvey Creek was always the optimal recipient stream) but suggested that maximizing the number of artificially produced juveniles released could produce a similar number of adult Bull Trout as the coupled release strategy. Results also suggested that ensuring fish passage at the Albeni Falls Dam in the mainstem Pend Oreille River could increase the abundance of adult fish. The process followed for this case study can be adapted to similar decisions regarding reintroduction or other translocations of fish in other systems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10334","usgsCitation":"Benjamin, J.R., Brignon, W.R., and Dunham, J.B., 2019, Decision analysis for the reintroduction of Bull Trout into the lower Pend Oreille River, Washington: North American Journal of Fisheries Management, v. 39, no. 5, p. 1026-1045, https://doi.org/10.1002/nafm.10334.","productDescription":"20 p.","startPage":"1026","endPage":"1045","additionalOnlineFiles":"N","ipdsId":"IP-104456","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":366328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Pend Oreille River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.48779296875,\n 48.07257353224749\n ],\n [\n -116.74072265625,\n 48.07257353224749\n ],\n [\n -116.74072265625,\n 48.99103162515999\n ],\n [\n -117.48779296875,\n 48.99103162515999\n ],\n [\n -117.48779296875,\n 48.07257353224749\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":767827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brignon, William R.","contributorId":193087,"corporation":false,"usgs":false,"family":"Brignon","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":767828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":767829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223294,"text":"70223294 - 2019 - Spatial and temporal variation of ecosystem properties at macroscales","interactions":[],"lastModifiedDate":"2021-08-20T14:04:32.279269","indexId":"70223294","displayToPublicDate":"2019-07-25T08:59:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation of ecosystem properties at macroscales","docAbstract":"Although spatial and temporal variation in ecological properties has been well-studied, crucial knowledge gaps remain for studies conducted at macroscales and for ecosystem properties related to material and energy. We test four propositions of spatial and temporal variation in ecosystem properties within a macroscale (1000 km's) extent. We fit Bayesian hierarchical models to thousands of observations from over two decades to quantify four components of variation – spatial (local and regional) and temporal (local and coherent); and to model their drivers. We found strong support for three propositions: (1) spatial variation at local and regional scales are large and roughly equal, (2) annual temporal variation is mostly local rather than coherent, and, (3) spatial variation exceeds temporal variation. Our findings imply that predicting ecosystem responses to environmental changes at macroscales requires consideration of the dominant spatial signals at both local and regional scales that may overwhelm temporal signals.
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To be successful, conservation strategies now need to account for geographical patterns in traits sensitive to climate change, as well as climate threats to species-level diversity. As part of an effort to provide such information, we conducted a climate vulnerability assessment that included all Pacific salmon and steelhead (Oncorhynchus spp.) listed under the U.S. Endangered Species Act. Using an expert-based scoring system, we ranked 20 attributes for the 28 listed units, and 5 additional units. Attributes captured biological sensitivity, or the strength of linkages between each listing unit and the present climate; climate exposure, or the magnitude of projected change in local environmental conditions; and adaptive capacity, or the ability to modify phenotypes to cope with new climatic conditions. 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The U.S. Geological Survey economic analysis method uses a simple engineering cost model approach developed by the U.S. Bureau of Mines that applies mine and mill engineering cost equations to simulated undiscovered deposits. The important characteristics of these deposits are derived from Monte Carlo simulations that combine probabilistic estimates of undiscovered deposits that might occur in a study area and a grade-tonnage model defined for a specific deposit type. This report describes the Resource Assessment Economic Filter (RAEF), a graphical user interface (GUI) tool that applies a set of mine cost equations to the deposits under consideration. RAEF, which is written in the open-source statistical programming language R, is an easy-to-use tool to apply user-defined mine, mill, and study area parameters to simulated deposits. For a given deposit type, it estimates the undiscovered resources that might be economic to extract. 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Satellite-derived spectral indices such as the relativized burn ratio (RBR) allow fire severity maps to be produced in a relatively straightforward manner across multiple fires and broad spatial extents. These indices often have strong relationships with field-based measurements of fire severity, thereby justifying their widespread use in management and science. However, satellite-derived spectral indices have been criticized because their non-standardized units render them difficult to interpret relative to on-the-ground fire effects. In this study, we built a Random Forest model describing a field-based measure of fire severity, the composite burn index (CBI), as a function of multiple spectral indices, a variable representing spatial variability in climate, and latitude. CBI data primarily representing forested vegetation from 263 fires (8075 plots) across the United States and Canada were used to build the model. Overall, the model performed well, with a cross-validated R2 of 0.72, though there was spatial variability in model performance. The model we produced allows for the direct mapping of CBI, which is more interpretable compared to spectral indices. Moreover, because the model and all spectral explanatory variables were produced in Google Earth Engine, predicting and mapping of CBI can realistically be undertaken on hundreds to thousands of fires. We provide all necessary code to execute the model and produce maps of CBI in Earth Engine. This study and its products will be extremely useful to managers and scientists in North America who wish to map fire effects over large landscapes or regions.
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The purpose of this study was to provide agencies and private landowners with a framework of decision-support tools to help manage pheasant populations in California. During winter, spring, and autumn of 2013–17, we radio- or Global Positioning System-marked 227 female pheasant across six study sites. Data collection was focused on investigating nest-site and brood-rearing habitat selection, examining avian predator composition, and estimating population vital rates to improve our understanding of pheasant population dynamics and to identify factors that may contribute to decreases in pheasant populations in California. The cumulative annual adult survival probability across all sites during 2013–17 was 27.6 percent (95-percent confidence interval [CI], 21.9–33.6), and the cumulative nest and brood survival probabilities were 34.5 percent (95-percent CI, 27.0–42.2) and 54.2 percent (95-percent CI, 43.7–63.5), respectively. Evidence from microhabitat surveys completed at nest-sites, brood locations, and random locations suggested that marked female pheasant tended to select increasing vertical cover and residual vegetation cover and tended to avoid areas of increasing bare ground cover regardless of life-history stage. However, females at nest-sites selected increasing grass cover and height, whereas brood-rearing females tended to select increasing forb cover and height. Only perennial grass cover and perennial grass height were shown to have a positive influence on nest survival, which suggests that increasing perennial grass cover in areas occupied by pheasant may increase nest survival. Analysis of environmental factors linked to vital rate information are ongoing and will continue with investigations at increased spatial scales (that is, macro-habitat) to develop integrated population models that can incorporate abundance estimates from crow count data with vital rates from telemetry data. This report includes results from 5 years of data collection and should be interpreted with caution, as these findings are preliminary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191062","collaboration":"Prepared in cooperation with the California Department of Fish and Wildlife and Pheasants Forever","usgsCitation":"=Dwight, I.A., Coates, P.S., Vogt, J.H., Atkinson, J.L., Fleskes, J.P., Connelly, D.P., Meshriy, M.C., Gardner, S.C., Stoute, S.T., and Pitesky M.E., 2019, Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17: U.S. Geological Survey Open-File Report 2019–1062, 90 p., https://doi.org/10.3133/ofr20191062.","productDescription":"90 p.","onlineOnly":"Y","ipdsId":"IP-099248","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":365826,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1062/ofr20191062.pdf","text":"Report","size":"44.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1062"},{"id":365825,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1062/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.9644775390625,\n 37.55328764595765\n ],\n [\n -119.5147705078125,\n 37.55328764595765\n ],\n [\n -119.5147705078125,\n 39.89709437260048\n ],\n [\n -122.9644775390625,\n 39.89709437260048\n ],\n [\n -122.9644775390625,\n 37.55328764595765\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
Modoc Hall, Room 4004
Sacramento, California 95819
This scientific investigations report describes an effort by the U.S. Geological Survey (USGS) that used research, monitoring data, and modeling to develop a methodology to assess both the current and future population-level consequences of wind energy development on species of birds and bats that are present in the United States during any part of their life cycle. The methodology is currently applicable to birds and bats, focuses primarily on the effects of collisions with turbines, and can be applied to any species that breeds in, migrates through, or otherwise uses any part of the United States. The methodology assesses species at the national and regional scales and identifies those species potentially in need of more detailed study, as well as those species that are likely at low risk from wind energy development. This approach is fundamentally different from existing methods focusing on impacts at individual facilities.
This report supersedes USGS Scientific Investigations Report 2015–5066 by the same authors, which described a preliminary version of the methodology. Following reviews of the preliminary methodology by a panel of external experts, public comments, and additional internal review, the methodology was revised and finalized.
The three components of the refined methodology described in this new report rely on publicly available fatality information, population estimates, species range maps, turbine location data, biological characteristics of species, and population models. First, three metrics are combined to determine direct and indirect relative effects from wind energy facilities to generate a list of species scores. Second, a generic population model estimates the expected change in population trend caused by the additive mortality from collisions with wind turbines. Third, the methodology combines an estimate of observed fatalities and an estimate of potential biological removal to assess the possibility of a decrease in population size. The latter two components are quantitative. In a test case, the methodology was used to analyze data for six bird species and three bat species.
Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable or may require further study. These assumptions should be carefully considered when using outputs from the methodology. Increases in the quality of data for fatalities from collisions with wind turbines, species distributions, abundance, and demography will likely improve results for uses of the methodology.
The methodology’s design identifies and prioritizes a subset of the bird and bat species that may experience population-level impacts from collisions with wind turbines, both currently and from future wind energy development in the United States. Results of an assessment using this methodology could focus future research to improve our understanding of those impacts and to guide avoidance and minimization strategies. In addition, this methodology can be used to identify species for more intensive demographic modeling or to highlight those species that may not require any additional research because effects of wind energy development on their populations are projected to be small. The effects of wind energy facilities on nine unidentified species used in the test case described in this report have not been assessed. Their data were simply used to show the application of the methodology to real-world data and the types of outputs it would produce.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185157","usgsCitation":"Diffendorfer, J.E., Beston, J.A., Merrill, M.D., Stanton, J.C., Corum, M.D., Loss, S.R., Thogmartin, W.E., Johnson, D.H., Erickson, R.A., and Heist, K.W., 2019, A methodology to assess the national and regional impacts of U.S. wind energy development on birds and bats: U.S. Geological Survey Scientific Investigations Report 2018–5157, 45 p., https://doi.org/10.3133/sir20185157. [Supersedes USGS Scientific Investigations Report 2015–5066.]","productDescription":"ix, 45 p.","onlineOnly":"Y","ipdsId":"IP-079749","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365690,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5157/coverthb.jpg"},{"id":365691,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5157/sir20185157.pdf","text":"Report","size":"1.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5157"}],"publicComments":"Scientific Investigations Report 2018-5157 supersedes Scientific Investigations Report 2015-5066.","contact":"Director, Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956
12201 Sunrise Valley Drive
Reston, VA 20192
Energy Resources Program
Wind Energy
In support of nutrient reduction efforts, nitrate (as nitrate plus nitrite) and phosphorus loads and yields were computed for selected streams in Iowa based on continuously monitored sensor data for 2008–17 and 2014–17, respectively. Sample data were used to assess nitrate sensor bias and to create phosphorus-turbidity surrogate models. Where needed, nitrate loads were corrected for site-specific sensor bias, which was determined to be as high as 9.25 percent. Nitrate loads presented in this report using continuous (generally 15-minute interval) data were on average 4 percent less, but as much as 38 percent less, than annual loads computed from daily mean nitrate concentrations not corrected for sensor bias. Streamflow-based phosphorus models had poorer fit (adjusted coefficient of determination values less than 0.75) than turbidity-based models (adjusted coefficient of determination approximately 0.9). However, alternate models based on streamflow were used to obtain a more complete annual phosphorus load despite seasonal and fragmentary sensor data.
Mean annual nitrate yields for 18 selected sites (96 site-years) ranged from 1.68 to 164 pounds per square mile per day (lb/mi2/d), compared to 19.4 lb/mi2/d average statewide yield needed to achieve the nitrate-reduction goal. Mean annual phosphorus yields for selected sites on the Maquoketa River, South Raccoon River, and West Nishnabotna River range from 1.57 to 7.19 lb/mi2/d, compared to 1.06 lb/mi2/d average statewide yield needed to achieve the phosphorus-reduction goal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195054","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Garrett, J.D., 2019, The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17: U.S. Geological Survey Scientific Investigations Report 2019–5054, 31 p., https://doi.org/10.3133/sir20195054.","productDescription":"Report: viii, 31 p.; Appendixes: 2","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098143","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":365814,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5054/sir20195054.pdf","text":"Report","size":"1.97 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The diversity of life in the sea is critical to the health of ocean ecosystems that support living resources and therefore essential to the economic, nutritional, recreational, and health needs of billions of people. Yet there is evidence that the biodiversity of many marine habitats is being altered in response to a changing climate and human activity. Understanding this change, and forecasting where changes are likely to occur, requires monitoring of organism diversity, distribution, abundance, and health. It requires a minimum of measurements including productivity and ecosystem function, species composition, allelic diversity, and genetic expression. These observations need to be complemented with metrics of environmental change and socio-economic drivers. However, existing global ocean observing infrastructure and programs often do not explicitly consider observations of marine biodiversity and associated processes. Much effort has focused on physical, chemical and some biogeochemical measurements. Broad partnerships, shared approaches, and best practices are now being organized to implement an integrated observing system that serves information to resource managers and decision-makers, scientists and educators, from local to global scales. This integrated observing system of ocean life is now possible due to recent developments among satellite, airborne, and in situ sensors in conjunction with increases in information system capability and capacity, along with an improved understanding of marine processes represented in new physical, biogeochemical, and biological models.
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