Volcanic eruptions are rare, but when they occur, they can profoundly affect nearby communities. In order to determine which communities are at risk, and in order for those communities to mitigate their risk, communities need to know whether they are in or near volcano hazard zones and have basic information about the hazards within those zones. In addition, individuals need to know whether they live in, work or go to school in, or cross volcano hazard zones as part of their routine so they can plan for what to do in the event of an eruption.
The purpose of this product is to serve as a starting point for dialogue with Indian Tribes of the Pacific Northwest who may be at risk from future volcanic eruptions. The map shows Tribal land boundaries and land-based volcano hazard zones, allowing Tribes to determine quickly if they are at risk from these hazards. A rose diagram in the map explanation shows typical Pacific Northwest wind directions and, hence, the most likely directions airborne material (tephra) from explosive eruptions will travel (primarily to the northeast, east, and southeast). We also provide basic information about the hazards and simple protective actions to take during unrest and eruptions, guidance for finding information about current volcanic activity and preparedness, and additional resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip209","collaboration":"Prepared in collaboration with the U.S. Geological Survey Office of Tribal Relations","usgsCitation":"Gardner, C.A., and Bard, J.A., 2021, How would a volcanic eruption affect your Tribe?: U.S. Geological Survey General Information Product 209, https://doi.org/10.3133/gip209.","productDescription":"1 Sheet: 66.00 x 36.00 inches","ipdsId":"IP-120998","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0209/covrthb.jpg"},{"id":385549,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0209/gip209.pdf","size":"17 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.41992187499999,\n 41.902277040963696\n ],\n [\n -118.38867187500001,\n 41.902277040963696\n ],\n [\n -118.38867187500001,\n 48.980216985374994\n ],\n [\n -125.41992187499999,\n 48.980216985374994\n ],\n [\n -125.41992187499999,\n 41.902277040963696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Hazards Program
Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Vancouver, Washington, 98683-9589
Accurate population estimates provide the foundation for managing feral horses (Equus caballus ferus) across the western United States. Certain feral horse populations are protected by the Wild and Free-Roaming Horses and Burros Act of 1971 and managed by the Bureau of Land Management (BLM) or the United States Forest Service on designated herd management areas (HMAs) or wild horse territories, respectively. Horses are managed to achieve an appropriate management level (AML), which represents the number of horses determined by BLM to contribute to a thriving natural ecological balance and avoid deterioration of the range. To achieve AML for each HMA, BLM resource managers need accurate and precise population estimates. We tested the use of non-invasive fecal samples in a genetic capture-recapture framework to estimate population size in a closed horse population at the Little Book Cliffs HMA, Colorado, USA, with a known size of 153 individuals. We collected 1,957 samples over 3 independent sampling periods in 2014 and amplified them at 8 microsatellite loci. We applied mark-recapture models to determine population size using 954 samples that amplified at all 8 loci. We subsampled and reanalyzed our dataset to simulate different data collection protocols and evaluated effects on accuracy and precision of estimates using N-mixture modeling, full likelihood closed-capture modeling, and capwire single-occasion modeling that used data from all 3 sampling periods. Our model results were accurate and precise for analyses that used data from all 3 occasions; however, capwire single-occasion modeling was not accurate when we analyzed each sampling period separately. For all subsampling analysis scenarios, reducing sample size decreased precision, whether by reducing number of field staff, field days, or geographic areas surveyed on each period. Reducing spatial coverage of the survey area did not result in accurate population estimates and only marginally lowered the number of samples that would need to be collected to maintain accuracy. Because laboratory analysis contributes the greatest expense for this method ($80 U.S./sample), reducing fecal sample size is advantageous. Our results demonstrate that non-invasive sampling combined with good survey design and careful genetic and capture-recapture analyses can provide an alternative method to estimate the number of feral horses in a closed population. This method may be especially appropriate in situations where aerial inventories are not practical or accurate because of low sighting conditions. But the higher costs associated with laboratory sample analyses may reduce the method's feasibility compared to helicopter surveys.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.22056","usgsCitation":"Schoenecker, K., King, S.R., Ekernas, L.S., and Oyler-McCance, S.J., 2021, Using fecal DNA and closed-capture models to estimate feral horse population size: Journal of Wildlife Management, v. 85, no. 6, p. 1150-1161, https://doi.org/10.1002/jwmg.22056.","productDescription":"12 p.","startPage":"1150","endPage":"1161","ipdsId":"IP-103976","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":396432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Little Book Cliffs Horse management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.49136352539062,\n 39.13432124527173\n ],\n [\n -108.34304809570312,\n 39.13432124527173\n ],\n [\n -108.34304809570312,\n 39.27691581029594\n ],\n [\n -108.49136352539062,\n 39.27691581029594\n ],\n [\n -108.49136352539062,\n 39.13432124527173\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"85","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sarah R. B. 0000-0002-9316-7488","orcid":"https://orcid.org/0000-0002-9316-7488","contributorId":280063,"corporation":false,"usgs":false,"family":"King","given":"Sarah","email":"","middleInitial":"R. B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":835962,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ekernas, L. Stefan 0000-0002-9205-1985","orcid":"https://orcid.org/0000-0002-9205-1985","contributorId":223034,"corporation":false,"usgs":true,"family":"Ekernas","given":"L.","email":"","middleInitial":"Stefan","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835963,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":835964,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70220306,"text":"70220306 - 2021 - Surface Rupture Map of the 2020 M 6.5 Monte Cristo Range earthquake, Esmeralda and Mineral counties, Nevada","interactions":[],"lastModifiedDate":"2021-06-03T11:53:49.707121","indexId":"70220306","displayToPublicDate":"2021-05-10T10:02:04","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5655,"text":"Nevada Bureau of Mines and Geology Map","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"190","title":"Surface Rupture Map of the 2020 M 6.5 Monte Cristo Range earthquake, Esmeralda and Mineral counties, Nevada","docAbstract":"The 15 May 2020, M6.5 Monte Cristo Range earthquake was the largest earthquake in Nevada in over 66 years and occurred in a sparsely populated area of western Nevada about 74 km southeast of the town of Hawthorne. The earthquake produced surface rupture distributed across a 28-km-long zone along the eastward projection of the Candelaria fault in the Mina deflection of the central Walker Lane. Post-event field surveys mapped surface ruptures and measured displacements, which reached up to ~20 cm of oblique slip. Additional detailed mapping was completed using centimeter-resolution orthomosaics generated from Uncrewed Aerial Vehicle surveys. The rupture observations and displacement data are compiled into this 1:14,000-scale map, data tables, and accompanying digital dataset. The rupture consists of two distinct deformational domains roughly separated by U.S. Highway 95: ENE-trending ruptures with normal and left-oblique displacements in the western domain, and N- to NNE-trending ruptures with normal and right-oblique displacement in the eastern domain. The complex pattern of surface rupture is consistent with the projections of mapped bedrock and Quaternary faults in the area and illustrates the kinematics of slip partitioning at the junction of variably oriented structures in the shallow subsurface.
","language":"English","publisher":"University of Nevada, Reno","usgsCitation":"Dee, S., Koehler, R.D., Elliott, A.J., Hatem, A.E., Pickering, A., Pierce, I., Seitz, G.G., Collett, C.M., Dawson, T.E., De Masi, C., dePolo, C.M., Hartsorn, E., Madugo, C., Trexler, C.C., Verdugo, D.M., Wesnousky, S.G., and Zachariasen, J., 2021, Surface Rupture Map of the 2020 M 6.5 Monte Cristo Range earthquake, Esmeralda and Mineral counties, Nevada: Nevada Bureau of Mines and Geology Map 190, Report: 26 p.; 2 Sheets: 42.00 x 42.00 inches; GIS Files.","productDescription":"Report: 26 p.; 2 Sheets: 42.00 x 42.00 inches; GIS Files","ipdsId":"IP-127048","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":386127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":386126,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.nbmg.unr.edu/Monte-Cristo-Range-EQ-p/m190.htm"}],"country":"United States","state":"Nevada","county":"Esmeralda County, Mineral County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.16506958007812,\n 36.97622678464096\n ],\n [\n -117.16781616210936,\n 38.003737861469666\n ],\n [\n -117.6910400390625,\n 38.47401919222663\n ],\n [\n -118.35296630859374,\n 37.896530447543\n ],\n [\n -118.42437744140625,\n 37.896530447543\n ],\n [\n -117.16506958007812,\n 36.97622678464096\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.6910400390625,\n 38.47294404791815\n ],\n [\n -118.19503784179688,\n 38.922023851268925\n ],\n [\n -118.19641113281249,\n 38.99997583555929\n ],\n [\n -117.88055419921875,\n 39.07144530820888\n ],\n [\n -118.91738891601561,\n 39.07784203269269\n ],\n [\n -119.02175903320311,\n 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0000-0003-0777-6939","orcid":"https://orcid.org/0000-0003-0777-6939","contributorId":215895,"corporation":false,"usgs":false,"family":"Koehler","given":"Richard","email":"","middleInitial":"D","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":815087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, Austin John 0000-0001-5924-7268","orcid":"https://orcid.org/0000-0001-5924-7268","contributorId":248824,"corporation":false,"usgs":true,"family":"Elliott","given":"Austin","email":"","middleInitial":"John","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":815088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatem, Alexandra Elise 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Reno","active":true,"usgs":false}],"preferred":false,"id":815091,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Seitz, Gordon G.","contributorId":139062,"corporation":false,"usgs":false,"family":"Seitz","given":"Gordon","email":"","middleInitial":"G.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":815092,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Collett, Camille Marie 0000-0003-4836-0243","orcid":"https://orcid.org/0000-0003-4836-0243","contributorId":257819,"corporation":false,"usgs":true,"family":"Collett","given":"Camille","email":"","middleInitial":"Marie","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":815093,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dawson, Timothy 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Survey","active":true,"usgs":false}],"preferred":false,"id":815094,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"De Masi, Conni","contributorId":257820,"corporation":false,"usgs":false,"family":"De Masi","given":"Conni","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":815095,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"dePolo, Craig M","contributorId":257821,"corporation":false,"usgs":false,"family":"dePolo","given":"Craig","email":"","middleInitial":"M","affiliations":[{"id":6689,"text":"Nevada Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":815096,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Hartsorn, Evan","contributorId":257822,"corporation":false,"usgs":false,"family":"Hartsorn","given":"Evan","email":"","affiliations":[{"id":16138,"text":"Desert Research Institute","active":true,"usgs":false}],"preferred":false,"id":815097,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Madugo, Christopher","contributorId":225600,"corporation":false,"usgs":false,"family":"Madugo","given":"Christopher","email":"","affiliations":[{"id":41169,"text":"Pacific Gas and Electric Company","active":true,"usgs":false}],"preferred":false,"id":815098,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Trexler, Charles Cashman 0000-0001-5046-9729","orcid":"https://orcid.org/0000-0001-5046-9729","contributorId":257823,"corporation":false,"usgs":true,"family":"Trexler","given":"Charles","email":"","middleInitial":"Cashman","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":815099,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Verdugo, Danielle M","contributorId":257824,"corporation":false,"usgs":false,"family":"Verdugo","given":"Danielle","email":"","middleInitial":"M","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":815100,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Wesnousky, Steven G.","contributorId":193416,"corporation":false,"usgs":false,"family":"Wesnousky","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":33746,"text":"Center for Neotectonic Studies, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":815101,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Zachariasen, Judith","contributorId":195131,"corporation":false,"usgs":false,"family":"Zachariasen","given":"Judith","email":"","affiliations":[],"preferred":false,"id":815102,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70220545,"text":"70220545 - 2021 - Large-scale wildfire reduces population growth in a peripheral population of sage-grouse","interactions":[],"lastModifiedDate":"2021-05-20T11:57:01.486743","indexId":"70220545","displayToPublicDate":"2021-05-10T07:55:01","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale wildfire reduces population growth in a peripheral population of sage-grouse","docAbstract":"Drastic increases in wildfire size and frequency threaten western North American sagebrush (Artemisia L. spp.) ecosystems. At relatively large spatial scales, wildfire facilitates type conversion of sagebrush-dominated plant communities to monocultures of invasive annual grasses (e.g., Bromus tectorum L.). Annual grasses provide fine fuels that promote fire spread, contributing to a positive grass–fire feedback cycle that affects most sagebrush ecosystems, with expected habitat loss for resident wildlife populations. Greater sage-grouse (Centrocercus urophasianus Bonaparte, 1827) are sagebrush obligate species that are indicators of sagebrush ecosystem function because they rely on different components of sagebrush ecosystems to meet seasonal life history needs. Because wildfire cannot be predicted, chronic impacts of wildfire on sage-grouse populations have been largely limited to correlative studies. Thus, evidence from well-designed experiments is needed to understand the specific mechanisms by which wildfire is detrimental to sage-grouse population dynamics.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-021-00099-z","usgsCitation":"Dudley, I., Coates, P.S., Prochazka, B.G., O’Neil, S.T., Gardner, S.C., and Delehanty, D.J., 2021, Large-scale wildfire reduces population growth in a peripheral population of sage-grouse: Fire Ecology, v. 17, 15, 13 p., https://doi.org/10.1186/s42408-021-00099-z.","productDescription":"15, 13 p.","ipdsId":"IP-122119","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":452316,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-021-00099-z","text":"Publisher Index Page"},{"id":436375,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J3KRIZ","text":"USGS data release","linkHelpText":"Greater Sage-Grouse Nest Observations Before and After Wildfire Disturbance in Northeastern California 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Ian F","contributorId":258209,"corporation":false,"usgs":false,"family":"Dudley","given":"Ian F","affiliations":[{"id":52236,"text":"former WERC, Idaho State University","active":true,"usgs":false}],"preferred":false,"id":815959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":815962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":815963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Delehanty, David J.","contributorId":195584,"corporation":false,"usgs":false,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":815964,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227197,"text":"70227197 - 2021 - Zircon geochronology and geochemistry of Quaternary rhyolite domes of the Coso volcanic field, Inyo County, California","interactions":[],"lastModifiedDate":"2022-01-04T14:03:38.97849","indexId":"70227197","displayToPublicDate":"2021-05-10T07:54:59","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Zircon geochronology and geochemistry of Quaternary rhyolite domes of the Coso volcanic field, Inyo County, California","docAbstract":"The Quaternary Coso volcanic field (CVF) is a compositionally bimodal volcanic field located within a releasing bend along the eastern range-front Sierra Nevada fault zone in California's southern Owens Valley. The erupted products of CVF silicic magmatism since ~1 Ma comprise 38 high-silica rhyolite domes, with the volumetric majority (~99%) of rhyolite emplaced within the past ~300 ka. The CVF hosts an economically important geothermal field driven by heat associated with a shallow (~5 km) igneous intrusion. The CVF is potentially an immature analog to the nearby Long Valley system, which culminated in generation and eruption of the voluminous and widespread Bishop Tuff. As such, the CVF represents a considerable volcanic hazard, making a detailed understanding of the eruptive history and pre-eruptive conditions of the system critically important. We present uranium-series isochron dates from zircon ± allanite crystal surfaces and zircon trace element geochemical data on the youngest 17 rhyolite domes at Coso, which represent ~60% (by volume) of the silicic magma erupted by the system. These data suggest: (1) a shorter emplacement duration than previously recognized for these domes, with a duration of 20 ± 5 ka; (2) 4 shorter-duration eruption pulses within this interval, all of which occur during the marine isotope stage (MIS) 5 interglacial period; (3) an uptick in the volume of CVF magma erupted between ~200 ka and ~ 78 ka relative to that emplaced over the lifetime of the system; (4) near-coeval eruption of geochemically distinct magma in close geographic proximity, either sourced from different portions of the same magma system at depth or from discrete, uncommunicating bodies; (5) ambiguity with respect to whether or not CVF magmatism is time-predictable, as previously suggested, or erupted as a series of punctuated episodes; (6) no rhyolite volcanism in the past ~78 kyr.
Coral reefs are effective natural coastal flood barriers that protect adjacent communities. Coral degradation compromises the coastal protection value of reefs while also reducing their other ecosystem services, making them a target for restoration. Here we provide a physics-based evaluation of how coral restoration can reduce coastal flooding for various types of reefs. Wave-driven flooding reduction is greatest for broader, shallower restorations on the upper fore reef and between the middle of the reef flat and the shoreline than for deeper locations on the fore reef or at the reef crest. These results indicate that to increase the coastal hazard risk reduction potential of reef restoration, more physically robust species of coral need to be outplanted to shallower, more energetic locations than more fragile, faster-growing species primarily being grown in coral nurseries. The optimization and quantification of coral reef restoration efforts to reduce coastal flooding may open hazard risk reduction funding for conservation purposes.
Anticoagulant rodenticides (ARs) used to control mammalian pest populations cause secondary exposure of predatory species throughout much of the world. It is important to understand the drivers of non-target AR exposure patterns as context for assessing long-term effects and developing effective mitigation for these toxicants. In Australia, however, little is known about exposure and effects of ARs on predators. We detected AR residues in 74% of 50 opportunistically collected carcasses of the Tasmanian wedge-tailed eagle (Aquila audax fleayi), an endangered apex predator. In 22% of birds tested, or 31% of those exposed, liver concentrations of second generation ARs (SGARs) were >0.1 mg/kg ww. Eagles were exposed to flocoumafen, a toxicant only available from agricultural suppliers, at an exceptionally high rate (40% of birds tested). Liver SGAR concentrations were positively associated with the proportion of agricultural habitat and human population density in the area around where each eagle died. The high exposure rate in a species not known to regularly prey upon synanthropic rodents supports the hypothesis that apex predators are vulnerable to SGARs. Our results indicate that AR exposure constitutes a previously unrecognized threat to Tasmanian wedge-tailed eagles and highlight the importance of efforts to address non-target AR exposure in Australia.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2021.147673","usgsCitation":"Pay, J.M., Katzner, T., Hawkins, C.E., Barmuta, L.A., Brown, W.E., Koch, A.J., Mooney, N.J., and Cameron, E.Z., 2021, Endangered Australian top predator is frequently exposed to anticoagulant rodenticides: Science of the Total Environment, v. 788, 147673, 9 p., https://doi.org/10.1016/j.scitotenv.2021.147673.","productDescription":"147673, 9 p.","ipdsId":"IP-126326","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":452326,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":387408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Tasmania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 143.26171875,\n -44.087585028245165\n ],\n [\n 149.23828125,\n -44.087585028245165\n ],\n [\n 149.23828125,\n -40.44694705960048\n ],\n [\n 143.26171875,\n -40.44694705960048\n ],\n [\n 143.26171875,\n -44.087585028245165\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"788","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pay, James M.","contributorId":245078,"corporation":false,"usgs":false,"family":"Pay","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":819878,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":819879,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawkins, Clare E.","contributorId":245079,"corporation":false,"usgs":false,"family":"Hawkins","given":"Clare","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":819880,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barmuta, Leon A.","contributorId":261351,"corporation":false,"usgs":false,"family":"Barmuta","given":"Leon","email":"","middleInitial":"A.","affiliations":[{"id":52830,"text":"School of Natural Sciences, University of Tasmania, Hobart, TAS, Australia","active":true,"usgs":false}],"preferred":false,"id":819881,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brown, William E. 0000-0003-1595-9655","orcid":"https://orcid.org/0000-0003-1595-9655","contributorId":245082,"corporation":false,"usgs":false,"family":"Brown","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":819882,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Koch, Amelia J.","contributorId":245080,"corporation":false,"usgs":false,"family":"Koch","given":"Amelia","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":819883,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mooney, Nick J.","contributorId":245083,"corporation":false,"usgs":false,"family":"Mooney","given":"Nick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":819884,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cameron, Elissa Z.","contributorId":245084,"corporation":false,"usgs":false,"family":"Cameron","given":"Elissa","email":"","middleInitial":"Z.","affiliations":[],"preferred":false,"id":819885,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70220421,"text":"70220421 - 2021 - Virus shedding kinetics and unconventional virulence tradeoffs","interactions":[],"lastModifiedDate":"2021-05-13T12:02:23.891402","indexId":"70220421","displayToPublicDate":"2021-05-10T07:01:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2981,"text":"PLoS Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"Virus shedding kinetics and unconventional virulence tradeoffs","docAbstract":"Tradeoff theory, which postulates that virulence provides both transmission costs and benefits for pathogens, has become widely adopted by the scientific community. Although theoretical literature exploring virulence-tradeoffs is vast, empirical studies validating various assumptions still remain sparse. In particular, truncation of transmission duration as a cost of virulence has been difficult to quantify with robust controlled in vivo studies. We sought to fill this knowledge gap by investigating how transmission rate and duration were associated with virulence for infectious hematopoietic necrosis virus (IHNV) in rainbow trout (Oncorhynchus mykiss). Using host mortality to quantify virulence and viral shedding to quantify transmission, we found that IHNV did not conform to classical tradeoff theory. More virulent genotypes of the virus were found to have longer transmission durations due to lower recovery rates of infected hosts, but the relationship was not saturating as assumed by tradeoff theory. Furthermore, the impact of host mortality on limiting transmission duration was minimal and greatly outweighed by recovery. Transmission rate differences between high and low virulence genotypes were also small and inconsistent. Ultimately, more virulent genotypes were found to have the overall fitness advantage, and there was no apparent constraint on the evolution of increased virulence for IHNV. However, using a mathematical model parameterized with experimental data, it was found that host culling resurrected the virulence tradeoff and provided low virulence genotypes with the advantage. Human-induced or natural culling, as well as host population fragmentation, may be some of the mechanisms by which virulence diversity is maintained in nature. This work highlights the importance of considering non-classical virulence tradeoffs.
Biological communities, including periphyton, are continuously affected by chemical, physical, and other biological factors, and the health of these communities can reflect the overall health of the aquatic system. A diverse community is more robust, and communities with lower richness and evenness often indicate a degraded community dominated by few taxa tolerant to the degraded conditions, which makes the community more susceptible to ecological changes. Water-quality nutrient samples were collected at sites in the Lower Grand River during 2010 through 2018 and periphyton sample collections began in 2011 to describe the periphyton community and overall ecological health. Nutrient sample concentrations were generally elevated at these sites, which can lead to eutrophication, excessive plant and algae growth, drinking-water taste and odor problems, low dissolved-oxygen concentrations, and harmful algal blooms. Concentrations of total nitrogen were greater than acceptable as described by the U.S. Environmental Protection Agency, and total phosphorus concentrations were greater than reference concentrations. Periphyton communities were dominated by taxa that are tolerant to or indicative of elevated nutrient concentrations; and nuisance algae, or harmful algal bloom producers, were identified at all sites, except one. The presence of these producers indicates that harmful algal blooms may have high potential during optimal conditions at these sites. Chlorophyll concentrations that exceed 100 milligrams per square meter are considered nuisance and were determined in 11 percent of the samples and at every site during September 2012. Samples were collected during low-flow conditions when nutrient concentrations are generally lower than during high-flow and runoff conditions. Elevated nutrient concentrations during low-flow conditions indicate nutrient concentrations are likely elevated throughout most of the year. Agriculture is the primary land use within the Lower Grand River and is likely a primary source of nutrients and sediments. Conservation practices intended to reduce nutrient loss from agriculture fields have increased because of the Mississippi River Basin Healthy Watersheds Initiative and will potentially increase the ecological, chemical, and physical health of these waterways.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215012","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Krempa, H.M., 2021, Periphyton biomass and community compositions as indicators of water quality in the Lower Grand River hydrologic unit, Missouri and Iowa, 2011–18: U.S. Geological Survey Scientific Investigations Report 2021–5012, 51 p., https://doi.org/10.3133/sir20215012.","productDescription":"Report: vi, 51 p.; Data Release; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-117668","costCenters":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":385478,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5012/coverthb.jpg"},{"id":385479,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5012/sir20215012.pdf","text":"Report","size":"2.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5012"},{"id":385480,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BYF1EN","text":"USGS data release","description":"USGs Data Release","linkHelpText":"Periphyton community data within the Lower Grand River hydrologic unit code 10280103, Missouri and Iowa, 2011–2018"},{"id":385481,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"}],"country":"United States","state":"Iowa, Missouri","otherGeospatial":"Lower Grand River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.4716796875,\n 40.97989806962013\n ],\n [\n -94.10888671875,\n 41.36031866306708\n ],\n [\n -94.72412109375,\n 40.83043687764923\n ],\n [\n -94.833984375,\n 40.027614437486655\n ],\n [\n -94.41650390625,\n 39.232253141714885\n ],\n [\n -93.6474609375,\n 38.94232097947902\n ],\n [\n -92.83447265624999,\n 39.16414104768742\n ],\n [\n -92.8125,\n 39.757879992021756\n ],\n [\n -92.94433593749999,\n 40.74725696280421\n ],\n [\n -93.4716796875,\n 40.97989806962013\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Pinyon and juniper expansion into sagebrush ecosystems is one of the major challenges facing land managers in the Great Basin. Effective pinyon and juniper treatment requires maps that accurately and precisely depict tree location and degree of woodland development so managers can target restoration efforts for early stages of pinyon and juniper expansion. However, available remotely sensed layers that cover a regional spatial extent lack the spatial resolution or accuracy to meet this need. Accuracy can be improved using object-based image analysis methods such as automated feature extraction, which has proven successful in accurately classifying land cover at the site-level but to date has yet to be applied to regional extents due to time and computational limitations. Using Feature Analyst™, we implement our framework with 1-m2 reference imagery provided by National Agricultural Imagery Program to classify conifers across Nevada and northeastern California. Our resulting binary conifer map has an overall accuracy of 86%. We discuss the advantages to accuracy and precision our framework provides compared to other classification methods
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mex.2021.101379","usgsCitation":"Roth, C.L., Coates, P.S., Gustafson, K.B., Chenaille, M.P., Ricca, M.A., Sanchez-Chopitea, E., and Casazza, M.L., 2021, A customized framework for regional classification of conifers using automated feature extraction: MethodsX, v. 8, 101379, 16 p., https://doi.org/10.1016/j.mex.2021.101379.","productDescription":"101379, 16 p.","ipdsId":"IP-098781","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":452330,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mex.2021.101379","text":"Publisher Index Page"},{"id":386335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, California, Nevada, Utah","otherGeospatial":"the Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.3671875,\n 41.44272637767212\n ],\n [\n -118.21289062499999,\n 43.99281450048989\n ],\n [\n -120.62988281249999,\n 44.5278427984555\n ],\n [\n -122.34374999999999,\n 41.934976500546604\n ],\n [\n -120.62988281249999,\n 38.51378825951165\n ],\n [\n -116.5869140625,\n 35.42486791930558\n ],\n [\n -115.31249999999999,\n 37.09023980307208\n ],\n [\n -114.0380859375,\n 36.4566360115962\n ],\n [\n -114.08203125,\n 38.06539235133249\n ],\n [\n -111.22558593749999,\n 38.09998264736481\n ],\n [\n -111.09374999999999,\n 42.09822241118974\n ],\n [\n -116.3671875,\n 41.44272637767212\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roth, Cali L. 0000-0001-9077-2765 croth@usgs.gov","orcid":"https://orcid.org/0000-0001-9077-2765","contributorId":174422,"corporation":false,"usgs":true,"family":"Roth","given":"Cali","email":"croth@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":817208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gustafson, K. Benjamin 0000-0003-3530-0372 kgustafson@usgs.gov","orcid":"https://orcid.org/0000-0003-3530-0372","contributorId":166818,"corporation":false,"usgs":true,"family":"Gustafson","given":"K.","email":"kgustafson@usgs.gov","middleInitial":"Benjamin","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chenaille, Michael P. 0000-0003-3387-7899 mchenaille@usgs.gov","orcid":"https://orcid.org/0000-0003-3387-7899","contributorId":194661,"corporation":false,"usgs":true,"family":"Chenaille","given":"Michael","email":"mchenaille@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817212,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanchez-Chopitea, Erika 0000-0003-2942-8417 esanchez-chopitea@usgs.gov","orcid":"https://orcid.org/0000-0003-2942-8417","contributorId":199468,"corporation":false,"usgs":true,"family":"Sanchez-Chopitea","given":"Erika","email":"esanchez-chopitea@usgs.gov","affiliations":[],"preferred":true,"id":817213,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":817214,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227122,"text":"70227122 - 2021 - White-nose syndrome-related changes to Mid-Atlantic bat communities across an urban-to-rural gradient","interactions":[],"lastModifiedDate":"2022-01-03T15:34:37.44233","indexId":"70227122","displayToPublicDate":"2021-05-09T08:14:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9972,"text":"BMC Zoology","active":true,"publicationSubtype":{"id":10}},"title":"White-nose syndrome-related changes to Mid-Atlantic bat communities across an urban-to-rural gradient","docAbstract":"White-nose Syndrome (WNS) has reduced the abundance of many bat species within the United States’ Mid-Atlantic region. To determine changes within the National Park Service National Capital Region (NCR) bat communities, we surveyed the area with mist netting and active acoustic sampling (2016–2018) and compared findings to pre-WNS (2003–2004) data.
The results indicated the continued presence of the threatened Myotis septentrionalis (Northern Long-eared bat) and species of conservation concern, including Perimyotis subflavus (Tri-colored bat), Myotis leibii (Eastern Small-footed bat) and Myotis lucifugus (Little Brown bat). However, we documented a significant reduction in the abundance and distribution of M. lucifugus and P. subflavus, a decrease in the distribution of M. septentrionalis, and an increase in the abundance of Eptesicus fuscus (Big Brown bat).
Documented post-WNS M. septentrionalis recruitment suggests that portions of the NCR may be important bat conservation areas. Decreases in distribution and abundance of P. subflavus and M. lucifugus indicate probable extirpation from many previously occupied portions of the region.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s40850-021-00079-5","usgsCitation":"Deeley, S.M., Johnson, J., Ford, W., and Gates, J.E., 2021, White-nose syndrome-related changes to Mid-Atlantic bat communities across an urban-to-rural gradient: BMC Zoology, v. 6, p. 1-11, https://doi.org/10.1186/s40850-021-00079-5.","productDescription":"12, 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-112528","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":452334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40850-021-00079-5","text":"Publisher Index Page"},{"id":393647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia, West Virginia","otherGeospatial":"District of Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.244384765625,\n 37.900865092570065\n ],\n [\n -75.904541015625,\n 37.900865092570065\n ],\n [\n -75.904541015625,\n 39.64799732373418\n ],\n [\n -79.244384765625,\n 39.64799732373418\n ],\n [\n -79.244384765625,\n 37.900865092570065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","noUsgsAuthors":false,"publicationDate":"2021-05-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Deeley, Sabrina M.","contributorId":270674,"corporation":false,"usgs":false,"family":"Deeley","given":"Sabrina","email":"","middleInitial":"M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":829727,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Joshua B.","contributorId":270675,"corporation":false,"usgs":false,"family":"Johnson","given":"Joshua B.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":829728,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":829726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gates, J. Edward","contributorId":270676,"corporation":false,"usgs":false,"family":"Gates","given":"J.","email":"","middleInitial":"Edward","affiliations":[{"id":39006,"text":"Frostburg State University","active":true,"usgs":false}],"preferred":false,"id":829729,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250184,"text":"70250184 - 2021 - The 4th paradigm in multiscale data representation: Modernizing the National Geospatial Data Infrastructure","interactions":[],"lastModifiedDate":"2023-11-28T18:00:43.540846","indexId":"70250184","displayToPublicDate":"2021-05-08T11:45:15","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The 4th paradigm in multiscale data representation: Modernizing the National Geospatial Data Infrastructure","docAbstract":"The need of citizens in any nation to access geospatial data in readily usable form is critical to societal well-being, and in the United States (US), demands for information by scientists, students, professionals and citizens continue to grow. Areas such as public health, urbanization, resource management, economic development and environmental management require a variety of data collected from many sources to identify problems, monitor trends and propose solutions. Such information needs and demands have driven the coordination of federal and regional government agencies with respective private sector participation to develop national geospatial data infrastructures in many countries.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of big geospatial data","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-55462-0_23","usgsCitation":"Buttenfield, B.P., Stanislawski, L., Kronenfeld, B.J., and Shavers, E.J., 2021, The 4th paradigm in multiscale data representation: Modernizing the National Geospatial Data Infrastructure, chap. of Handbook of big geospatial data, p. 589-618, https://doi.org/10.1007/978-3-030-55462-0_23.","productDescription":"30 p.","startPage":"589","endPage":"618","ipdsId":"IP-125863","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":423017,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"editors":[{"text":"Werner, Martin","contributorId":331851,"corporation":false,"usgs":false,"family":"Werner","given":"Martin","email":"","affiliations":[],"preferred":false,"id":888929,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Chiang, Yao-Yi","contributorId":288084,"corporation":false,"usgs":false,"family":"Chiang","given":"Yao-Yi","email":"","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":888930,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Buttenfield, Barbara P. 0000-0001-5961-5809","orcid":"https://orcid.org/0000-0001-5961-5809","contributorId":206887,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[{"id":16144,"text":"University of Colorado-Boulder","active":true,"usgs":false}],"preferred":false,"id":888724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanislawski, Larry 0000-0002-9437-0576","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":217849,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888725,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kronenfeld, Barry J. 0000-0002-9518-2462","orcid":"https://orcid.org/0000-0002-9518-2462","contributorId":207104,"corporation":false,"usgs":false,"family":"Kronenfeld","given":"Barry","email":"","middleInitial":"J.","affiliations":[{"id":5043,"text":"Eastern Illinois University","active":true,"usgs":false}],"preferred":false,"id":888726,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shavers, Ethan J. 0000-0001-9470-5199 eshavers@usgs.gov","orcid":"https://orcid.org/0000-0001-9470-5199","contributorId":206890,"corporation":false,"usgs":true,"family":"Shavers","given":"Ethan","email":"eshavers@usgs.gov","middleInitial":"J.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":888727,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222511,"text":"70222511 - 2021 - Bridging the research-implementation gap in avian conservation with translational ecology","interactions":[],"lastModifiedDate":"2021-08-03T12:06:42.241668","indexId":"70222511","displayToPublicDate":"2021-05-08T09:15:23","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Bridging the research-implementation gap in avian conservation with translational ecology","docAbstract":"The recognized gap between research and implementation in avian conservation can be overcome with translational ecology, an intentional approach in which science producers and users from multiple disciplines work collaboratively to co-develop and deliver ecological research that addresses management and conservation issues. Avian conservation naturally lends itself to translational ecology because birds are well studied, typically widespread, often exhibit migratory behaviors transcending geopolitical boundaries, and necessitate coordinated conservation efforts to accommodate resource and habitat needs across the full annual cycle. In this perspective, we highlight several case studies from bird conservation practitioners and the ornithological and conservation social sciences exemplifying the 6 core translational ecology principles introduced in previous studies: collaboration, engagement, commitment, communication, process, and decision-framing. We demonstrate that following translational approaches can lead to improved conservation decision-making and delivery of outcomes via co-development of research and products that are accessible to broader audiences and applicable to specific management decisions (e.g., policy briefs and decision-support tools). We also identify key challenges faced during scientific producer–user engagement, potential tactics for overcoming these challenges, and lessons learned for overcoming the research-implementation gap. Finally, we recommend strategies for building a stronger translational ecology culture to further improve the integration of these principles into avian conservation decisions. By embracing translational ecology, avian conservationists and ornithologists can be well positioned to ensure that future management decisions are scientifically informed and that scientific research is sufficiently relevant to managers. Ultimately, such teamwork can help close the research-implementation gap in the conservation sciences during a time when environmental issues are threatening avian communities and their habitats at exceptional rates and at broadening spatial scales worldwide.
","language":"English","publisher":"American Ornithological Society","doi":"10.1093/ornithapp/duab018","usgsCitation":"Saunders, S.P., Wu, J.X., Gow, E.A., Adams, E.A., Bateman, B.L., Bayard, T., Beilke, S., Dayer, A.A., Fournier, A., Fox, K., Hamilton, C., Heglund, P., Lerman, S.B., Michel, N.L., Paxton, E.H., Sekercioglu, C.H., Smith, M., Thogmartin, W.E., Woodrey, M.S., and van Riper, C., 2021, Bridging the research-implementation gap in avian conservation with translational ecology: Ornithological Applications, v. 123, no. 3, duab018, https://doi.org/10.1093/ornithapp/duab018.","productDescription":"duab018","ipdsId":"IP-118107","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"links":[{"id":452341,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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variation and useful indicators of foraging habitat quality in Lesser Scaup","docAbstract":"Energy acquisition and storage are important for survival and fecundity of birds during resource-limited periods such as spring migration. Plasma-lipid metabolites (i.e. triglyceride [TRIG], β-hydroxybutyrate [BOHB]) have been used to index changes in lipid stores and, thus, have utility for assessing foraging habitat quality during migration. However, such an index may be affected by energetic maintenance costs, diet, and other factors, and further validation under experimental conditions is needed to understand potential sources of variation and verify existing indices. We evaluated a plasma-lipid metabolite index using 30 female and 28 male wild Lesser Scaup (Aythya affinis; hereafter scaup) held in short-term captivity (~24 hr) during spring migration. Similar to previous observational studies, BOHB was negatively associated and TRIG was positively associated with mass change (R2 = 0.68). BOHB estimates were nearly identical to those published on free-living scaup, but TRIG estimates differed from free-living scaup and varied by sex, with females having a greater rate of predicted mass change than captive and free-living males. Our results suggest TRIG may be a better measure of energy income than deposition because lipid deposition likely varies with energetic maintenance costs, stress, and underlying physiological processes while TRIG relates primarily to energy income. In contrast, BOHB was a reliable predictor of negative mass change across sexes. The sex-based differences in apparent lipid deposition rates warrant further research before a generalizable model is advisable for comparing mass change predictions across studies. However, if predictions are standardized, this technique is generally robust to variations in energy income vs. lipid deposition across sexes. Accordingly, our evaluation provides verification for the utility of plasma-lipid metabolites as an indicator of foraging habitat quality during migration.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithology/ukab029","usgsCitation":"Smith, E.J., Anteau, M.J., Hagy, H.M., and Jacques, C.N., 2021, Plasma metabolite indices are robust to extrinsic variation and useful indicators of foraging habitat quality in Lesser Scaup: Ornithology, v. 138, no. 3, ukab029, 11 p., https://doi.org/10.1093/ornithology/ukab029.","productDescription":"ukab029, 11 p.","ipdsId":"IP-101470","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":396096,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Mississippi River, Pool 19","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.43131256103514,\n 40.39336516184327\n ],\n [\n -91.32110595703125,\n 40.39336516184327\n ],\n [\n -91.32110595703125,\n 40.541199704952014\n ],\n [\n -91.43131256103514,\n 40.541199704952014\n ],\n [\n -91.43131256103514,\n 40.39336516184327\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"138","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Eric J.","contributorId":333129,"corporation":false,"usgs":false,"family":"Smith","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":892052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":835229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hagy, Heath M.","contributorId":172326,"corporation":false,"usgs":false,"family":"Hagy","given":"Heath","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":835230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacques, Christopher N.","contributorId":274285,"corporation":false,"usgs":false,"family":"Jacques","given":"Christopher","email":"","middleInitial":"N.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":835231,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70222489,"text":"70222489 - 2021 - The timing and magnitude of changes to Hortonian overland flow at the watershed scale during the post-fire recovery process","interactions":[],"lastModifiedDate":"2021-07-30T13:19:06.765468","indexId":"70222489","displayToPublicDate":"2021-05-08T08:16:04","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The timing and magnitude of changes to Hortonian overland flow at the watershed scale during the post-fire recovery process","docAbstract":"Extreme hydrologic responses following wildfires can lead to floods and debris flows with costly economic and societal impacts. Process-based hydrologic and geomorphic models used to predict the downstream impacts of wildfire must account for temporal changes in hydrologic parameters related to the generation and subsequent routing of infiltration-excess overland flow across the landscape. However, we lack quantitative relationships showing how parameters change with time-since-burning, particularly at the watershed scale. To assess variations in best-fit hydrologic parameters with time, we used the KINEROS2 hydrological model to explore temporal changes in hillslope saturated hydraulic conductivity (Ksh) and channel hydraulic roughness (nc) following a wildfire in the upper Arroyo Seco watershed (41.5 km2), which burned during the 2009 Station fire in the San Gabriel Mountains, California, USA. This study explored runoff-producing storms between 2008 and 2014 to infer watershed hydraulic properties by calibrating the model to observations at the watershed outlet. Modelling indicates Ksh is lowest in the first year following the fire and then increases at an average rate of approximately 4.2 mm/h/year during the first 5 years of recovery. The estimated values for Ksh in the first year following the fire are similar to those obtained in previous studies on smaller watersheds (<1.5 km2) following the Station fire, suggesting hydrologic changes detected here can be applied to lower-order watersheds. Hydraulic roughness, nc, was lowest in the first year following the fire, but increased by a factor of 2 after 1 year of recovery. Post-fire observations suggest changes in nc are due to changes in grain roughness and vegetation in channels. These results provide quantitative constraints on the magnitude of fire-induced hydrologic changes following severe wildfires in chaparral-dominated ecosystems as well as the timing of hydrologic recovery.
Any large, multifaceted data collection that is challenging to handle with traditional management practices can be branded ‘Big Data.’ Any big data containing geo-referenced attributes can be considered big geospatial data. The increased proliferation of big geospatial data is currently reforming the geospatial industry into a data-driven enterprise. Challenges in the big spatial data domain can be summarized as the ‘Big Vs’ – variety, volume, velocity, veracity and value. Big spatial data sources can be considered in two broad classes, active and passive, as each is impacted to varying degrees. Some of these challenges may be alleviated by reducing unprocessed, or minimally processed, (raw) data to features, which we refer to as the extraction of Elements of Interest (EOI). In fact, many applications require EOI extraction from raw data to enable their basic employment. This chapter presents current state-of-the-art methods to create EOI from some types of georeferenced big data. We classify the data types into two realms: active and passive. Active data are those collected specifically for the purpose to which they are applied. Passive data are those collected for purposes other than those for which they are utilized, included those ‘collected’ for no particular purpose at all. The chapter then presents use cases from both the active and passive spatial realms, including the active applications of terrain feature extraction from digital elevation models and vegetation mapping from remotely-sensed imagery and passive applications like building identification from VGI and point-of-interest data mining from social networks for land use classification. Finally, the chapter concludes with future research needs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Handbook of big geospatial data","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-55462-0_5","usgsCitation":"Arundel, S., and Usery, E., 2021, Spatial data reduction through element -of-interest (EOI) extraction, chap. of Handbook of big geospatial data, p. 119-134, https://doi.org/10.1007/978-3-030-55462-0_5.","productDescription":"16 p.","startPage":"119","endPage":"134","ipdsId":"IP-113380","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":385704,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":815856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Usery, E. Lynn 0000-0002-2766-2173","orcid":"https://orcid.org/0000-0002-2766-2173","contributorId":204684,"corporation":false,"usgs":true,"family":"Usery","given":"E. Lynn","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":815857,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70220569,"text":"70220569 - 2021 - Understanding constraints on submersed vegetation distribution in a large, floodplain river: The role of water level fluctuations, water clarity and river geomorphology","interactions":[],"lastModifiedDate":"2021-05-21T13:33:40.508668","indexId":"70220569","displayToPublicDate":"2021-05-08T07:26:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Understanding constraints on submersed vegetation distribution in a large, floodplain river: The role of water level fluctuations, water clarity and river geomorphology","docAbstract":"Aquatic vegetation is a key component of large floodplain river ecosystems. In the Upper Mississippi River System (UMRS), there is a long-standing interest in restoring aquatic vegetation in areas where it has declined or disappeared. To better understand what constrains vegetation distribution in large river ecosystems and inform ongoing efforts to restore submersed aquatic vegetation (SAV), we delineated areas in ~1200 river km of the UMRS where the combined effects of water clarity, water level fluctuation, and bathymetry appeared suitable for establishment and persistence of SAV based on a 22-year dataset for total suspended solids (TSS), water surface elevation, and aquatic vegetation distribution. We found a large increase in suitable area downstream from a large natural riverine lake near the northern end of the UMRS (river km 1230) that functions as a sink for suspended material. Downstream from river km 895, there was much less suitable area due to decreased water clarity from tributary input of suspended material, changes in river geomorphology, and increased water level fluctuation. A hypothetical scenario of 75% reduction in TSS resulted in only minor increases in suitable area in the southern portion of the UMRS, indicating limitations by water level fluctuation and/or bathymetry (i.e., limited shallow area). These results improve our understanding of the structure and function of large river systems by illustrating how water clarity, fluctuations in water level, and river geomorphology interact to create complex spatial patterns in habitat suitability for aquatic species and may help to identify locations most and least likely to benefit from management and restoration efforts.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-021-01454-1","usgsCitation":"Carhart, A., Kalas, J., Rogala, J.T., Rohweder, J.J., Drake, D.C., and Houser, J.N., 2021, Understanding constraints on submersed vegetation distribution in a large, floodplain river: The role of water level fluctuations, water clarity and river geomorphology: Wetlands, v. 41, 57, 15 p., https://doi.org/10.1007/s13157-021-01454-1.","productDescription":"57, 15 p.","ipdsId":"IP-119793","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":436377,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TWZXVZ","text":"USGS data release","linkHelpText":"Predicted total number of years and percentage of years from 1993-2014 with conditions suitable for submersed aquatic vegetation based on light availability and water level fluctuations for the Upper Mississippi River System data"},{"id":385752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.033203125,\n 37.09023980307208\n ],\n [\n -89.12109375,\n 39.436192999314095\n ],\n [\n -88.9453125,\n 42.032974332441405\n ],\n [\n -88.857421875,\n 43.54854811091286\n ],\n [\n -89.3408203125,\n 45.1510532655634\n ],\n [\n -91.3623046875,\n 46.13417004624326\n ],\n [\n -94.04296874999999,\n 46.13417004624326\n ],\n [\n -95.537109375,\n 45.42929873257377\n ],\n [\n -95.4052734375,\n 42.71473218539458\n ],\n [\n -94.306640625,\n 40.245991504199026\n ],\n [\n -92.59277343749999,\n 38.20365531807149\n ],\n [\n -90.4833984375,\n 36.98500309285596\n ],\n [\n -89.47265625,\n 36.80928470205937\n ],\n [\n -89.033203125,\n 37.09023980307208\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Carhart, Alicia 0000-0002-9977-8124","orcid":"https://orcid.org/0000-0002-9977-8124","contributorId":223884,"corporation":false,"usgs":false,"family":"Carhart","given":"Alicia","email":"","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":816042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalas, John","contributorId":223883,"corporation":false,"usgs":false,"family":"Kalas","given":"John","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":816043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":816044,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rohweder, Jason J. 0000-0001-5131-9773 jrohweder@usgs.gov","orcid":"https://orcid.org/0000-0001-5131-9773","contributorId":150539,"corporation":false,"usgs":true,"family":"Rohweder","given":"Jason","email":"jrohweder@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":816045,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Drake, Deanne C.","contributorId":207846,"corporation":false,"usgs":false,"family":"Drake","given":"Deanne","email":"","middleInitial":"C.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":816046,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Houser, Jeffrey N. 0000-0003-3295-3132 jhouser@usgs.gov","orcid":"https://orcid.org/0000-0003-3295-3132","contributorId":2769,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey","email":"jhouser@usgs.gov","middleInitial":"N.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":816047,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70220388,"text":"70220388 - 2021 - Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA","interactions":[],"lastModifiedDate":"2024-05-16T15:27:57.216807","indexId":"70220388","displayToPublicDate":"2021-05-08T06:59:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA","docAbstract":"Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.
","language":"English","publisher":"MDPI","doi":"10.3390/fire4020026","usgsCitation":"Teske, C., Vanderhoof, M.K., Hawbaker, T., Noble, J., and Hires, J.K., 2021, Using the Landsat Burned Area products to derive fire history relevant for fire management and conservation in the state of Florida, southeastern USA: Fire, v. 4, no. 2, 26, 21 p., https://doi.org/10.3390/fire4020026.","productDescription":"26, 21 p.","ipdsId":"IP-126697","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":452347,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire4020026","text":"Publisher Index Page"},{"id":385562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Panhandle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.64892578125,\n 29.554345125748267\n ],\n [\n -83.43017578125,\n 29.554345125748267\n ],\n [\n -83.43017578125,\n 30.939924331023445\n ],\n [\n -87.64892578125,\n 30.939924331023445\n ],\n [\n -87.64892578125,\n 29.554345125748267\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-05-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Teske, Casey","contributorId":224732,"corporation":false,"usgs":false,"family":"Teske","given":"Casey","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":815369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":815372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":815371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Joe","contributorId":257938,"corporation":false,"usgs":false,"family":"Noble","given":"Joe","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":815370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hires, J. Kevin","contributorId":257941,"corporation":false,"usgs":false,"family":"Hires","given":"J.","email":"","middleInitial":"Kevin","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":815373,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221481,"text":"70221481 - 2021 - Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study","interactions":[],"lastModifiedDate":"2021-06-17T11:49:03.530012","indexId":"70221481","displayToPublicDate":"2021-05-08T06:44:56","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic inversion of gravity, magnetic, tracer, lithology, and fault data for geologically realistic structural models: Patua Geothermal Field case study","docAbstract":"Financial risk due to geological uncertainty is a major barrier for geothermal development. Production from a geothermal well depends on the unknown location of subsurface geological structures, such as faults that contain hydrothermal fluids. Traditionally, geoscientists collect many different datasets, interpret the datasets manually, and create a single model estimating faults' locations. This method, however, does not provide information about the uncertainty regarding the location of faults and often does not fully respect all observed datasets. Previous researchers investigated the use of stochastic inversion schemes for addressing geological uncertainty, but often at the expense of geologic realism. In this paper, we present algorithms and open-source code to stochastically invert five typical datasets for creating geologically realistic structural models. Using a case study with real data from the Patua Geothermal Field, we show that these inversion algorithms are successful in finding an ensemble of structural models that are geologically realistic and match the observed data sufficiently. Geoscientists can use this ensemble of models to optimize reservoir management decisions given structural uncertainty.
Distilling my experience in having field mapped in detail the volcanic fields at Laguna del Maule and Long Valley and having worked out their time-volume-composition magmatic histories, I compare and contrast the postglacial rhyolites of the former with six multi-vent eruptive sequences of rhyolite in California. Compilations and discussions are made of volcanic-field areas and longevities, their compositions, vent distributions, individual batch and total volumes, eruptive episodicities, and tectonic influences. Growth of long-lived pluton-scale reservoirs of granitic crystal mush, from which the rhyolite melts separated, are interpreted in terms of conceptual models I published previously—(1) fundamentally basaltic transcrustal magmatism, 1981; (2) the deep-crustal MASH zone model, 1988; and (3) the rhyolite-melt crystal-mush model, 2001. Inferences and speculations are advanced concerning processes and timescales of rhyolite-melt separation from granitic mush and of prompt or long-delayed subsequent eruption.
Anthropogenic activities can lead to the loss, fragmentation, and alteration of wildlife habitats. I reviewed the recent literature (2014–2019) focused on the responses of avian, mammalian, and herpetofaunal species to oil and natural gas development, a widespread and still-expanding land use worldwide. My primary goals were to identify any generalities in species’ responses to development and summarize remaining gaps in knowledge. To do so, I evaluated the directionality of a wide variety of responses in relation to taxon, location, development type, development metric, habitat type, and spatiotemporal aspects.
Studies (n = 70) were restricted to the USA and Canada, and taxonomically biased towards birds and mammals. Longer studies, but not those incorporating multiple spatial scales, were more likely to detect significant responses. Negative responses of all types were present in relatively low frequencies across all taxa, locations, development types, and development metrics but were context-dependent. The directionality of responses by the same species often varied across studies or development metrics.
The state of knowledge about wildlife responses to oil and natural gas development has developed considerably, though many biases and gaps remain. Studies outside of North America and that focus on herpetofauna are lacking. Tests of mechanistic hypotheses for effects, long-term studies, assessment of response thresholds, and experimental designs that isolate the effects of different stimuli associated with development, remain critical. Moreover, tests of the efficacy of habitat mitigation efforts have been rare. Finally, investigations of the demographic effects of development across the full annual cycle were absent for non-game species and are critical for the estimation of population-level effects.
Rabbit hemorrhagic disease, a notifiable foreign animal disease in the US, was reported for the first time in wild native North American lagomorphs in April 2020 in the southwestern US. Affected species included the desert cottontail (Sylvilagus audubonii), mountain cottontail (Sylvilagus nuttallii), black-tailed jackrabbit (Lepus californicus), and antelope jackrabbit (Lepus alleni). Desert cottontails (n=7) and black-tailed jackrabbits (n=7) collected in April and May 2020 were necropsied at the US Geological Survey National Wildlife Health Center and tested positive for Lagovirus europaeus GI.2, also known as rabbit hemorrhagic disease virus 2 (GI.2/RHDV2/b), by real-time PCR at the US Department of Agriculture's Foreign Animal Disease Diagnostic Laboratory. Gross and microscopic lesions were similar to those reported in European rabbits (Oryctolagus cuniculus) and other hare (Lepus) species with GI.2/RHDV2/b infection; they included epistaxis (12/13; 92%); massive hepatocellular dissociation (14/14; 100%) and necrosis or apoptosis (11/11; 100%); pulmonary congestion (12/12; 100%), edema (12/13; 92%), and hemorrhage (11/12; 92%); and acute renal tubular injury (3/8; 38%). As in previous reports, massive hepatocellular dissociation and necrosis or apoptosis were the most diagnostically distinct finding. As North American Sylvilagus and Lepus species appear to be susceptible to fatal GI.2/RHDV2/b infection, additional work is needed to understand the host range, pathogenicity, and potential population effects of GI.2/RHDV2/b in North America.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/JWD-D-20-00207","usgsCitation":"Lankton, J.S., Knowles, S., Keller, S., Shearn-Bochsler, V.I., and Ip, H., 2021, Pathology of Lagovirus europaeus GI.2/RHDV2/b (rabbit hemorrhagic disease virus 2) in native North American lagomorphs: Journal of Wildlife Diseases, v. 57, no. 3, p. 694-700, https://doi.org/10.7589/JWD-D-20-00207.","productDescription":"7 p.","startPage":"694","endPage":"700","ipdsId":"IP-123143","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":436379,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZINO2P","text":"USGS data release","linkHelpText":"Data from pathology of Lagovirus europaeus GI.2/RHDV2/b (rabbit hemorrhagic disease virus 2) in native North American lagomorphs"},{"id":386100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, New Mexico, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.5986328125,\n 29.57345707301757\n ],\n [\n -98.87695312499999,\n 29.57345707301757\n ],\n [\n -98.87695312499999,\n 36.70365959719456\n ],\n [\n -113.5986328125,\n 36.70365959719456\n ],\n [\n -113.5986328125,\n 29.57345707301757\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knowles, Susan 0000-0002-0254-6491 sknowles@usgs.gov","orcid":"https://orcid.org/0000-0002-0254-6491","contributorId":5254,"corporation":false,"usgs":true,"family":"Knowles","given":"Susan","email":"sknowles@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keller, Saskia","contributorId":255627,"corporation":false,"usgs":false,"family":"Keller","given":"Saskia","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":815543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shearn-Bochsler, Valerie I. 0000-0002-5590-6518 vbochsler@usgs.gov","orcid":"https://orcid.org/0000-0002-5590-6518","contributorId":3234,"corporation":false,"usgs":true,"family":"Shearn-Bochsler","given":"Valerie","email":"vbochsler@usgs.gov","middleInitial":"I.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ip, Hon S. 0000-0003-4844-7533","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":126815,"corporation":false,"usgs":true,"family":"Ip","given":"Hon S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815546,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219506,"text":"ofr20211045 - 2021 - Methodology and technical input for the 2021 review and revision of the U.S. Critical Minerals List","interactions":[],"lastModifiedDate":"2021-05-07T19:28:21.952536","indexId":"ofr20211045","displayToPublicDate":"2021-05-07T13:35:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1045","displayTitle":"Methodology and Technical Input for the 2021 Review and Revision of the U.S. Critical Minerals List","title":"Methodology and technical input for the 2021 review and revision of the U.S. Critical Minerals List","docAbstract":"Pursuant to Section 7002 (“Mineral Security”) of Title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Cong.), the Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked with reviewing and revising the methodology used to evaluate mineral criticality and the U.S. Critical Minerals List no less than every 3 years. The initial Critical Minerals List was published in the Federal Register on May 18, 2018, in response to Executive Order No. 13817, A Federal Strategy to Ensure Secure and Reliable Supplies of Critical Minerals (3 CFR, 2017 Comp, p. 397–399). This report documents the updated evaluation methodology and the resultant updated draft list of minerals recommended for inclusion in the Critical Minerals List.
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U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
No abstract available.
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