While the importance of reducing impacts of non-native species is increasingly recognized in conservation, the feasibility of such actions is highly dependent upon several key uncertainties including stage of invasion, size of the ecosystem being restored, and magnitude of the restoration activity. Here, we present results of a multi-year, non-native brown trout (Salmo trutta) removal and native Bonneville cutthroat trout (Oncorhynchus clarkii utah) response to this removal in a small tributary in the Intermountain West, United States. We monitored trout for 10 years prior to the onset of eradication efforts, which included 2 years of mechanical removal followed by 2 years of chemical treatment. Cutthroat trout were then seeded with low numbers of both eggs and juvenile trout. We monitored demographics and estimated population growth rates and carrying capacities for cutthroat trout from long-term depletion estimate data, assuming logistic population growth. Following brown trout eradication and initial seeding efforts, cutthroat trout in this tributary have responded rapidly and have approached their estimated carrying capacity within 6 years. Population projections suggest a 95% probability that cutthroat trout will be at or above 90% of their carrying capacity within 10 years of the eradication of brown trout. Additionally, at least four age-classes are present including adults large enough to satisfy angling demand. These results demonstrate native trout species have substantial capacity to rapidly recover following removal of invasive species in otherwise minimally altered habitats. While tributaries such as like this study location are likely limited in extent individually, collectively they may serve such as source populations for larger connected systems. In such cases, these source populations may provide additional conservation potential through biotic resistance.
Elevated nitrogen concentrations in streams and rivers in the Chesapeake Bay watershed have adversely affected the ecosystem health of the bay. Much of this nitrogen is derived as nitrate from groundwater that discharges to streams as base flow. In this study, boosted regression trees (BRTs) were used to relate nitrate concentrations in base flow (n = 156) to explanatory variables describing nitrogen sources, geology, and soil and catchment characteristics. From these relations, a BRT model was developed to predict base flow nitrate concentrations in streams throughout the Chesapeake Bay watershed. The highest base flow nitrate concentrations were associated with intensive agricultural land use, carbonate geology, and sparse riparian canopy, which suggested that reduced nitrogen inputs, particularly over carbonate terrane, are critical for limiting nitrate concentrations. The lowest nitrate concentrations in the BRT model were associated with extensive riparian canopy, high levels of organic carbon in soils, and suboxic conditions at shallow depths, which suggested that denitrification in the subsurface, particularly in the riparian zone, is limiting base flow nitrate concentrations. Nitrate transport from aquifers to streams can take decades to occur, resulting in decades-long lag times between the time when a land-use activity is implemented and when its effects are fully observed in streams. Predictive models of base flow nitrate concentrations in streams will help identify which portions of a watershed are likely to have large fractions of total stream nitrogen load derived from pathways with significant lag times.
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Center","active":true,"usgs":true}],"preferred":true,"id":807557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tesoriero, Anthony J. 0000-0003-4674-7364 tesorier@usgs.gov","orcid":"https://orcid.org/0000-0003-4674-7364","contributorId":2693,"corporation":false,"usgs":true,"family":"Tesoriero","given":"Anthony","email":"tesorier@usgs.gov","middleInitial":"J.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terziotti, Silvia 0000-0003-3559-5844 seterzio@usgs.gov","orcid":"https://orcid.org/0000-0003-3559-5844","contributorId":1613,"corporation":false,"usgs":true,"family":"Terziotti","given":"Silvia","email":"seterzio@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70217206,"text":"70217206 - 2021 - The birth of a Hawaiian fissure eruption","interactions":[],"lastModifiedDate":"2021-01-12T12:59:59.391343","indexId":"70217206","displayToPublicDate":"2020-12-04T06:52:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The birth of a Hawaiian fissure eruption","docAbstract":"Most basaltic explosive eruptions intensify abruptly, allowing little time to document processes at the start of eruption. One opportunity came with the initiation of activity from fissure 8 (F8) during the 2018 eruption on the lower East Rift Zone of Kīlauea, Hawaii. F8 erupted in four episodes. We recorded 28 min of high‐definition video during a 51‐min period, capturing the onset of the second episode on 5 May. From the videos, we were able to analyze the following in‐flight parameters: frequency and duration of explosions; ejecta heights; pyroclast exit velocities; in‐flight total mass and estimated mass eruption rates; and the in‐flight total grain size distributions. The videos record a transition from initial pulsating outgassing, via spaced, but increasingly rapid, discrete explosions, to quasisustained, unsteady fountaining. This transition accompanied waxing intensity (mass flux) of the F8 eruption. We infer that all activity was driven by a combination of the ascent of a coupled mixture of small bubbles and melt, and the buoyant rise of decoupled gas slugs and/or pockets. The balance between these two types of concurrent flow determined the exact form of the eruptive activity at any point in time, and changes to their relative contributions drove the transition we observed at early F8. Qualitative observations of other Hawaiian fountains at Kīlauea suggest that this physical model may apply more generally. This study demonstrates the value of in‐flight parameters derived from high‐resolution videos, which offer a rapid and highly time‐sensitive alternative to measurements based on sampling of deposits posteruption.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020903","usgsCitation":"Houghton, B.F., Tisdale, C.M., Llewellin, E.W., Taddeucci, J., Orr, T.R., Walker, B.H., and Patrick, M.R., 2021, The birth of a Hawaiian fissure eruption: Journal of Geophysical Research: Solid Earth, v. 126, no. 1, e2020JB020903, 17 p., https://doi.org/10.1029/2020JB020903.","productDescription":"e2020JB020903, 17 p.","ipdsId":"IP-120595","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":454165,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1255250","text":"External Repository"},{"id":382080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Hawaii","otherGeospatial":"Island of Hawai'i","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.11572265624997,\n 18.875102750356465\n ],\n [\n -154.79736328124997,\n 18.875102750356465\n ],\n [\n -154.79736328124997,\n 20.324023603422518\n ],\n [\n -156.11572265624997,\n 20.324023603422518\n ],\n [\n -156.11572265624997,\n 18.875102750356465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"126","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":807999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tisdale, Caroline M.","contributorId":247598,"corporation":false,"usgs":false,"family":"Tisdale","given":"Caroline","middleInitial":"M.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":808000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Llewellin, Edward W. 0000-0003-2165-7426","orcid":"https://orcid.org/0000-0003-2165-7426","contributorId":247599,"corporation":false,"usgs":false,"family":"Llewellin","given":"Edward","email":"","middleInitial":"W.","affiliations":[{"id":25252,"text":"Durham University","active":true,"usgs":false}],"preferred":true,"id":808001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taddeucci, Jacopo 0000-0002-0516-3699","orcid":"https://orcid.org/0000-0002-0516-3699","contributorId":184101,"corporation":false,"usgs":false,"family":"Taddeucci","given":"Jacopo","email":"","affiliations":[],"preferred":false,"id":808002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orr, Tim R. 0000-0003-1157-7588 torr@usgs.gov","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":149803,"corporation":false,"usgs":true,"family":"Orr","given":"Tim","email":"torr@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walker, Brett H.","contributorId":225523,"corporation":false,"usgs":false,"family":"Walker","given":"Brett","email":"","middleInitial":"H.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":808004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":808005,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217650,"text":"70217650 - 2021 - The induced Mw 5.0 March 2020 west Texas seismic sequence","interactions":[],"lastModifiedDate":"2021-01-27T13:03:11.497441","indexId":"70217650","displayToPublicDate":"2020-12-04T06:42:46","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The induced Mw 5.0 March 2020 west Texas seismic sequence","docAbstract":"On March 26, 2020, a M 5.0 earthquake occurred in the Delaware Basin, Texas, near the border between Reeves and Culberson Counties. This was the third largest earthquake recorded in Texas and the largest earthquake in the Central and Eastern United States since the three M 5.0–5.8 induced events in Oklahoma during 2016. Using multistation waveform template matching, we detect 3,940 earthquakes in the sequence with the first event in the area occurring in May 2018. The M 5.0 earthquake sequence occurred on a ENE (∼082°) normal fault dipping ∼37° toward the south. The earthquake caused 6 mm of oblique surface deformation, and geodetic slip inversion suggests slip was isolated above 6 km depth. We find that the sequence was most likely induced by nearby wastewater disposal operations, and seismicity rates in the region surrounding the M 5.0 will likely continue to increase in the future if disposal operations continue unaltered.
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These potential co-management approaches represent agricultural and urban runoff, wastewater treatment plant effluent, and combined sewer overflow replacements. Twelve estrogenic compounds and their metabolites were analysed by gas chromatography–mass spectrometry. Estrogenic activity (E2Eq) was measured by in vitro bioassay. We detected estrone E1 (0.05–6.97 ng L−1) and estriol E3 (below detection-8.13 ng L−1) and one conjugated estrogen (estrone-3-sulfate E1-3S; below detection-8.13 ng L−1). E1 was widely distributed and positively correlated with E2Eq, water temperature, and dissolved organic carbon (DOC). Among nonpoint sources, E2Eq, and concentrations of E1, soluble reactive phosphorus (SRP) and total dissolved nitrogen (TDN) decreased by 51–61%, 77–82%, 62–64%, 4–16% in restored urban and agricultural streams with best management practices (BMPs) relative to unrestored streams without BMPs. In a wastewater treatment plant (Blue Plains WWTP), >94% of E1, E1-3S, E3, E2Eq and TDN were removed while SRP increased by 305% during nitrification/denitrification as a part of advanced wastewater treatment. Consequently, E1 and TDN concentrations in WWTP effluents were comparable or even lower than those observed in the receiving stream or river waters, and the effects of wastewater discharges on downstream E1 and TDN concentrations were minor. Highest E2Eq value and concentrations of E1, E3, and TDN were detected in combined sewer overflow (CSO). This study suggests that WWTP upgrades with biological nutrient removal, CSO management, and certain agricultural and urban BMPs for nutrient controls have the potential to remove estrogens from point and nonpoint sources along with other contaminants in streams and rivers.
Long known as the island chain farthest from any continental landmass, the Hawaiian Islands are the subaerial expression of volcanism above the relatively fixed Hawaiian hot spot as the Pacific plate drifts northwest above it. Each island is built by one or several overlapping shield volcanoes, some of the most voluminous on Earth. Plate translation creates the well-known age-progressive sequence of shield volcanoes from northwest to southeast. Total volume of magma produced along the Hawaiian chain has been irregular but generally increasing for the past 50 million years, a trend that has peaked in the last 3 million years.
Hawaiian volcanoes grow through stages that have geologic expression and geochemical differences that reflect position relative to the underlying hot spot. Of these stages, the shield stage is the most productive when an estimated 80–95% of a volcano's ultimate volume is emplaced. The shield stage endures for about 1 million years.
The burden of shield volcanoes depresses the ocean crust near the hot spot, creating the Hawaiian Moat. Greatest rate of subsidence today occurs at the Island of Hawai‘i, 2–3 mm per year along its coast. Flexural rebound occurs as volcanoes move away from the hot spot; the Island of O‘ahu shows the greatest uplift. Slow subsidence resumes downstream from the flexure, leading ultimately to submergence of each island in the chain.
Large landslides, albeit infrequent, can occur at any stage of island evolution. Ground water is the principal source of potable and agricultural water on all islands; its distribution both reflects and influences island geology.
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sinton, John M","contributorId":261682,"corporation":false,"usgs":false,"family":"Sinton","given":"John M","affiliations":[{"id":52956,"text":"University of Hawai‘i at Mānoa, Honolulu, Hawai‘i,","active":true,"usgs":false}],"preferred":false,"id":820408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, David R. 0000-0001-9460-0434 dsherrod@usgs.gov","orcid":"https://orcid.org/0000-0001-9460-0434","contributorId":527,"corporation":false,"usgs":true,"family":"Sherrod","given":"David","email":"dsherrod@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":820409,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70251779,"text":"70251779 - 2021 - Porphyry and epithermal mineral deposits","interactions":[],"lastModifiedDate":"2024-02-28T15:46:44.606969","indexId":"70251779","displayToPublicDate":"2020-12-02T09:45:21","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Porphyry and epithermal mineral deposits","docAbstract":"Porphyry and epithermal mineral deposits form large economic ore bodies that provide the global economy with copper, molybdenum, gold, silver and other byproducts (Re, Te, Se). They form in the upper crust and are related to sulfur- and water-rich intermediate to silicic magmatic sources of hydrothermal fluids that move upward and produce extensive hydrolytic and alkali wall-rock alteration, quartz veins, and sulfides. Porphyry-type deposits are formed above magma chambers where fluids hydrofracture rock at 700–350 °C and at pressures ranging from supra-lithostatic to supra-hydrostatic. The depth of formation ranges from 2 to 10 km and influences orebody geometries and the types and mineralogy of veins, sulfides and wall-rock alteration. The temporal evolution of hydrothermal events is documented by cross-cutting veins and is commonly characterized by a decline in fluid temperature and concordant evolution from potassic alteration to sericitic alteration, with attendant increase in sulfidation state of copper-iron sulfides.
In some localities porphyry copper deposits transition upwards to lower temperature base metal lodes (350–200 °C) and eventually the formation of near surface (<1.5 km depth) intermediate- and high-sulfidation epithermal deposits (~300–120 °C). Extensional environments are often characterized by porphyry molybdenum and low-sulfidation epithermal deposits. In the base metal lode and epithermal environments, mixtures of magmatic and meteoric fluids produce ore fluids at hydrostatic pressures that advect freely both vertically and laterally along permeability provided by faults, joints, and porous lithologies. Wall-rock alteration ranges from hydrolytic to alkali-carbonate, and from high- to low-sulfidation state sulfide assemblages, respectively.
In porphyry, base metal lode, and epithermal environments, geology and the zonation of wall-rock alteration, veins, sulfide assemblages, and metals are useful for exploration.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology (secind editon)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-102908-4.00005-9","usgsCitation":"Dilles, J.H., and John, D.A., 2021, Porphyry and epithermal mineral deposits, chap. of Encyclopedia of geology (secind editon), p. 847-866, https://doi.org/10.1016/B978-0-08-102908-4.00005-9.","productDescription":"20 p.","startPage":"847","endPage":"866","ipdsId":"IP-116791","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":426066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dilles, John H","contributorId":214317,"corporation":false,"usgs":false,"family":"Dilles","given":"John","email":"","middleInitial":"H","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":895532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":895533,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216879,"text":"70216879 - 2021 - Ocean floor manganese deposits","interactions":[],"lastModifiedDate":"2020-12-11T14:49:39.09465","indexId":"70216879","displayToPublicDate":"2020-12-02T08:46:13","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Ocean floor manganese deposits","docAbstract":"Much of the dissolved Mn delivered to the oceans is slowly oxidized and precipitated alongside varying amounts of Fe into Mn and ferromanganese (FeMn) mineral deposits that occur extensively in the deep ocean wherever sediment accumulation is low and substrate is available. FeMn crusts grow as pavements on rock outcrops throughout the global ocean whereas nodules form as individual FeMn-encrusted particles on the sediment-covered abyssal plains. Both crusts and nodules are composed predominantly of Fe and Mn oxide minerals that precipitate from seawater and for some nodules also from porewaters of deep-sea sediment. In contrast, hydrothermal oxide deposits consist predominantly of Mn or Fe oxide. FeMn crusts and nodules exhibit very high specific surface areas that allow them to scavenge abundant metals and other elements, recording the history of the source waters. Crusts especially serve as an important record of paleoceanographic conditions over the past 70 + million years. Critical metals essential to many computer, military, and green technologies are enriched in crust and nodule deposits to concentrations high enough to compare with, or exceed, typical terrestrial deposits, and they can be considered as potential resources for mining in the near future. Twenty-three contracts pertaining to exploration for nodules and crusts have been signed with the International Seabed Authority, and resource/reserve, baseline, and environmental impact assessments are underway. Many challenges remain to be addressed before full-scale mining of marine FeMn deposits will occur. However, their unique genesis and the growing worldwide need for rare and critical metals keep these deep-ocean deposits relevant to industry, scientists, and governments.
Soils are naturally occurring bodies that form in the interface between the geosphere, biosphere, hydrosphere, and atmosphere. They are the medium for much of the Earth's plant and animal growth. Soil morphology and how it evolves are functions of the soil-forming factors of climate, organisms, relief, parent material, and time. The expression of soil morphology takes the form of layers, called horizons, that differ in their color, particle size distribution, structure, chemistry, and organic matter content from the parent material. A fundamental soil mapping unit in the USA is the soil order and 12 soil orders have been defined on the basis of soil morphology, physical and chemical properties, and climate. Soil geography in the USA is explained by an examination of how these 12 soil orders are found in particular climates, under specific vegetation communities, how they develop from compositionally distinct parent materials, or how they are a result of the age of soil parent material. Paleosols are ancient soils, those that formed in the past. Three types of paleosols are recognized, buried soils (those covered by a younger sediment or rock), exhumed paleosols (formerly buried soils that are now exposed at the surface due to erosion of overlying materials), and relict paleosols (soils that occur at the land surface, but which formed in an environment, such as a climate or biome, very different from that at the present time). Paleosols can help define geologic contacts and can aid in elucidating past climates or vegetation regimes. Although there are rich geologic records of paleosols in the Quaternary, there is an increasing recognition of the importance of all these features in the longer, pre-Quaternary geologic record.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-409548-9.12002-0","usgsCitation":"Muhs, D.R., 2021, Soils and paleosols, chap. of Encyclopedia of geology, p. 370-384, https://doi.org/10.1016/B978-0-12-409548-9.12002-0.","productDescription":"15 p.","startPage":"370","endPage":"384","ipdsId":"IP-109564","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":396903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":1857,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":true,"id":837628,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70229501,"text":"70229501 - 2021 - Eolian sediments","interactions":[],"lastModifiedDate":"2022-03-09T14:20:27.61191","indexId":"70229501","displayToPublicDate":"2020-12-02T08:17:11","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Eolian sediments","docAbstract":"The origin and nature of eolian (wind-blown) sediments are reviewed, with an emphasis on the occurrence of these features in the Quaternary. Eolian sediments consist of windblown sand, loess, and long-range-transported (LRT) dust, in order of decreasing particle size. Eolian sand forms some of the most dramatic landscapes in the world, particularly when these sediments are deposited as dunes in sand seas. The largest eolian sand seas are found in subtropical deserts and in mid-latitude basins that are arid because of rainshadow effects. Dunes can be helpful in interpreting past climates, both for understanding past moisture balance and paleowinds (past wind directions). Loess is windblown silt that can be recognized in the field and mapped as a geologic body. It can be many tens of meters thick, but usually decreases systematically with distance from its source or sources. Much loess is glaciogenic, the result of glacial grinding of bedrock into “rock flour” that is easily entrained by the wind, but some loess owes its origins to nonglacial processes or is simply inherited from silt-rich rocks. The geologic record shows that both glacial loess and non-glacial loess accumulated mostly during glacial periods, suggesting that particular environmental conditions are favorable for loess accumulation. These conditions include increased source sediments, a dry, windy environment with minimal vegetation cover, and a decreased intensity of the hydrological cycle. The same conditions apparently enhance the production of LRT dust, which consists of particles generally less than 10 μm. At present, most dust sources are in the same regions where the largest eolian sand seas occur, although sandy sediments are not the only sources of finer-grained dust. LRT dust can be transported across oceans, from continent to continent, and may play important roles in the overall planetary radiation balance, as fertilizer to the world's primary producers in the oceans, and as a soil parent material. Geologic records of LRT dust transport can be found in deep-sea sediments, ice caps, lakes, distal loess deposits, and soils. These records indicate that, like loess, the flux of dust was greater during glacial periods. Although eolian sand, loess, and LRT dust all have rich geologic records in the Quaternary, there is an increasing recognition of the importance of all these features in the longer, pre-Quaternary geologic record.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-409548-9.12491-1","usgsCitation":"Muhs, D.R., 2021, Eolian sediments, chap. of Encyclopedia of Geology, p. 348-369, https://doi.org/10.1016/B978-0-12-409548-9.12491-1.","productDescription":"22 p.","startPage":"348","endPage":"369","ipdsId":"IP-108752","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":396901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd editionE","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":1857,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":true,"id":837629,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70237317,"text":"70237317 - 2021 - Dating by cosmogenic nuclides","interactions":[],"lastModifiedDate":"2022-10-07T13:16:49.440633","indexId":"70237317","displayToPublicDate":"2020-12-02T08:13:08","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Dating by cosmogenic nuclides","docAbstract":"Since the 1990s, cosmogenic nuclides have revolutionized the study of Earth surface processes, particularly the understanding of rates and dates. These nuclides, including 3He, 10Be, 14C, 21Ne, 26Al, and 36Cl, enable dating of landforms and the measurement of erosion rates both at the scale of drainage basins and at specific locations on Earth's surface. Cosmogenic nuclides are produced at low rates (several to hundreds of atoms per gram per year) by the interaction of cosmic rays with elements both in the atmosphere and in surficial materials, including in rock and soil. Measuring nuclide concentrations requires elemental separation from source geologic material followed by counting of atoms using sensitive accelerator mass spectrometers. Because nuclide production rates have been quantified, the measured concentration of these nuclides can be interpreted as a near-surface residence time. Here, we review the systematics of commonly used cosmogenic nuclides, describe how they are extracted and measured, and then present case studies focusing on the most commonly measured cosmogenic nuclide, 10Be. We present common applications such as dating surface features, including moraines and outcrops shaped by glaciation, the use of cosmogenic nuclides for inferring tectonic and erosion processes in drainage basins, and the use of these nuclides to trace sediment sources in drainage basins. When multiple nuclides are measured in one sample, they can be used to model burial and exposure histories in stratigraphic sections. We conclude by exploring what the future might bring in terms of measurements and applications.
","largerWorkTitle":"Encyclopedia of geology","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-102908-4.00124-7","usgsCitation":"Bierman, P., Bender, A., Christ, A.J., Corbett, L.B., Halsted, C.T., Portenga, E.W., and Schmidt, A.H., 2021, Dating by cosmogenic nuclides, chap. of Encyclopedia of geology, p. 101-115, https://doi.org/10.1016/B978-0-08-102908-4.00124-7.","productDescription":"15 p.","startPage":"101","endPage":"115","ipdsId":"IP-119305","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":408085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bierman, Paul R.","contributorId":198743,"corporation":false,"usgs":false,"family":"Bierman","given":"Paul R.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":854117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bender, Adrian 0000-0001-7469-1957","orcid":"https://orcid.org/0000-0001-7469-1957","contributorId":219952,"corporation":false,"usgs":true,"family":"Bender","given":"Adrian","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":854118,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christ, Andrew J.","contributorId":297429,"corporation":false,"usgs":false,"family":"Christ","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":854119,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Corbett, Lee B.","contributorId":152123,"corporation":false,"usgs":false,"family":"Corbett","given":"Lee","email":"","middleInitial":"B.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":854120,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halsted, Christopher T.","contributorId":297431,"corporation":false,"usgs":false,"family":"Halsted","given":"Christopher","email":"","middleInitial":"T.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":854121,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Portenga, Eric W.","contributorId":297434,"corporation":false,"usgs":false,"family":"Portenga","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":55463,"text":"Eastern Michigan University","active":true,"usgs":false}],"preferred":false,"id":854122,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Amanda H.","contributorId":297436,"corporation":false,"usgs":false,"family":"Schmidt","given":"Amanda","email":"","middleInitial":"H.","affiliations":[{"id":6707,"text":"Oberlin College","active":true,"usgs":false}],"preferred":false,"id":854123,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217225,"text":"70217225 - 2021 - Forest restoration and fuels reduction: Convergent or divergent?","interactions":[],"lastModifiedDate":"2021-01-13T14:07:51.248017","indexId":"70217225","displayToPublicDate":"2020-12-02T08:01:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Forest restoration and fuels reduction: Convergent or divergent?","docAbstract":"For over 20 years, forest fuel reduction has been the dominant management action in western US forests. These same actions have also been associated with the restoration of highly altered frequent-fire forests. Perhaps the vital element in the compatibility of these treatments is that both need to incorporate the salient characteristics that frequent fire produced—variability in vegetation structure and composition across landscapes and the inability to support large patches of high-severity fire. These characteristics can be achieved with both fire and mechanical treatments. The possible key to convergence of fuel reduction and forest restoration strategies is integrated planning that permits treatment design flexibility and a longer-term focus on fire reintroduction for maintenance. With changing climate conditions, long-term forest conservation will probably need to be focused on keeping tree density low enough (i.e., in the lower range of historic variation) for forest conditions to adapt to emerging disturbance patterns and novel ecological processes.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaa134","usgsCitation":"Stephens, S.L., Battaglia, M.A., Churchill, D., Collins, B.M., Coppoletta, M., Hoffman, C.M., Lydersen, J.M., North, M.P., Parsons, R.A., Ritter, S.M., and Stevens, J., 2021, Forest restoration and fuels reduction: Convergent or divergent?: BioScience, v. 71, no. 1, p. 85-101, https://doi.org/10.1093/biosci/biaa134.","productDescription":"17 p.","startPage":"85","endPage":"101","ipdsId":"IP-118979","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":382129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, 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\"}}]}","volume":"71","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Stephens, Scott L.","contributorId":46022,"corporation":false,"usgs":false,"family":"Stephens","given":"Scott","email":"","middleInitial":"L.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":808101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Battaglia, Mike A.","contributorId":190302,"corporation":false,"usgs":false,"family":"Battaglia","given":"Mike","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":808102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Churchill, Derek J.","contributorId":247685,"corporation":false,"usgs":false,"family":"Churchill","given":"Derek J.","affiliations":[{"id":49611,"text":"3Forest Health and Resiliency Division, Washington Department of Natural Resources, Olympia, WA 98504, USA","active":true,"usgs":false}],"preferred":false,"id":808103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, Brandon M.","contributorId":127850,"corporation":false,"usgs":false,"family":"Collins","given":"Brandon","email":"","middleInitial":"M.","affiliations":[{"id":7169,"text":"USDA Forest Service, UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":808104,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coppoletta, Michelle","contributorId":247686,"corporation":false,"usgs":false,"family":"Coppoletta","given":"Michelle","email":"","affiliations":[{"id":49613,"text":"USDA Forest Service, Sierra Cascade Province Ecology Program, Quincy, CA, 95971, USA","active":true,"usgs":false}],"preferred":false,"id":808105,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoffman, Chad M. 0000-0001-8715-937X","orcid":"https://orcid.org/0000-0001-8715-937X","contributorId":247687,"corporation":false,"usgs":false,"family":"Hoffman","given":"Chad","email":"","middleInitial":"M.","affiliations":[{"id":49614,"text":"Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, CO, 80523, USA","active":true,"usgs":false}],"preferred":false,"id":808106,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lydersen, Jamie M.","contributorId":247688,"corporation":false,"usgs":false,"family":"Lydersen","given":"Jamie","email":"","middleInitial":"M.","affiliations":[{"id":49615,"text":"California Department of Forestry and Fire Protection, Fire and Resource Assessment Program, Sacramento, CA, 95814, USA","active":true,"usgs":false}],"preferred":false,"id":808107,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"North, Malcolm P.","contributorId":247689,"corporation":false,"usgs":false,"family":"North","given":"Malcolm","email":"","middleInitial":"P.","affiliations":[{"id":49616,"text":"USDA Forest Service, PSW Research Station, Mammoth Lakes, CA, 93546, USA","active":true,"usgs":false}],"preferred":false,"id":808108,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parsons, Russell A.","contributorId":247690,"corporation":false,"usgs":false,"family":"Parsons","given":"Russell","email":"","middleInitial":"A.","affiliations":[{"id":49618,"text":"USDA Forest Service, Fire Sciences Lab, Missoula, MT, 59808, USA","active":true,"usgs":false}],"preferred":false,"id":808109,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ritter, Scott M.","contributorId":150726,"corporation":false,"usgs":false,"family":"Ritter","given":"Scott","email":"","middleInitial":"M.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":808110,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stevens, Jens 0000-0002-2234-1960","orcid":"https://orcid.org/0000-0002-2234-1960","contributorId":222191,"corporation":false,"usgs":true,"family":"Stevens","given":"Jens","email":"","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808111,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70220115,"text":"70220115 - 2021 - Monitoring volcanic deformation","interactions":[],"lastModifiedDate":"2021-04-20T12:46:38.791152","indexId":"70220115","displayToPublicDate":"2020-12-02T07:42:30","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Monitoring volcanic deformation","docAbstract":"Deformation signals recorded at volcanoes have long been used to infer the processes behind subsurface magma intrusions. Monitoring strategies vary greatly depending on several factors such as the activity of the individual volcano, access, available personnel, and funding.
Certain geodetic monitoring methods, such as Electronic Distance Measurements, are inexpensive but require that scientists be dangerously close to active areas. Other techniques, such as telemetered geodetic measurements (Electronic Tiltmeters and Global Navigation Satellite System), or deformation images from Interferometric Synthetic Aperture Radar, can be collected remotely and with less risk. Observed surface deformation can be fit to the predictions of mathematical source models to obtain quantitative estimates of their parameters (e.g., location, depth, volume change and more). Combined deformation and gravity change measurements can be used to infer the density of subsurface intrusions and better constrain the source of unrest.
To be effective, geodetic monitoring must be done before, during, and after eruptions and must be integrated with other monitoring techniques (e.g., seismology, geochemistry, physical volcanology, remote sensing). It requires the long-term commitment of time and resources.
Done effectively, geodetic monitoring not only can provide timely warnings of escalating volcano hazards but may also lead to improved understanding of how volcanoes work. Even when a volcano is not active, monitoring generates baseline information against which changes in volcano behavior can be compared. Preserving the integrity and accessibility of geodetic data archives is thus essential if future volcanologists are to benefit from the decades-long records of geodetic data gathered by volcano observatories.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of geology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","doi":"10.1016/B978-0-08-102908-4.00132-6","usgsCitation":"Battaglia, M., Alpala, J., Alpala, R., Angarita, M., Arcos, D., Euillades, L., Euillades, P., Muller, C., and Narvaez, L., 2021, Monitoring volcanic deformation, chap. of Encyclopedia of geology, p. 774-804, https://doi.org/10.1016/B978-0-08-102908-4.00132-6.","productDescription":"31 p.","startPage":"774","endPage":"804","ipdsId":"IP-119768","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Battaglia, Maurizio 0000-0003-4726-5287 mbattaglia@usgs.gov","orcid":"https://orcid.org/0000-0003-4726-5287","contributorId":204742,"corporation":false,"usgs":true,"family":"Battaglia","given":"Maurizio","email":"mbattaglia@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":814512,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpala, Jorge","contributorId":139634,"corporation":false,"usgs":false,"family":"Alpala","given":"Jorge","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814513,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alpala, Rosa","contributorId":215654,"corporation":false,"usgs":false,"family":"Alpala","given":"Rosa","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814514,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Angarita, Mario","contributorId":215655,"corporation":false,"usgs":false,"family":"Angarita","given":"Mario","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":814515,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arcos, Dario","contributorId":139636,"corporation":false,"usgs":false,"family":"Arcos","given":"Dario","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Euillades, Leonardo","contributorId":225157,"corporation":false,"usgs":false,"family":"Euillades","given":"Leonardo","email":"","affiliations":[{"id":41053,"text":"Universidad Nacional de Cuyo, Facultad de Ingeniería, Instituto CEDIAC & CONICET","active":true,"usgs":false}],"preferred":false,"id":814516,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euillades, Pablo","contributorId":225156,"corporation":false,"usgs":false,"family":"Euillades","given":"Pablo","affiliations":[{"id":41053,"text":"Universidad Nacional de Cuyo, Facultad de Ingeniería, Instituto CEDIAC & CONICET","active":true,"usgs":false}],"preferred":false,"id":814517,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Muller, Cyril","contributorId":205255,"corporation":false,"usgs":false,"family":"Muller","given":"Cyril","email":"","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":814519,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Narvaez, Lourdes","contributorId":215659,"corporation":false,"usgs":false,"family":"Narvaez","given":"Lourdes","email":"","affiliations":[{"id":12810,"text":"Colombian Geological Survey","active":true,"usgs":false}],"preferred":false,"id":814520,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70217890,"text":"70217890 - 2021 - Karst geology of the Upper Midwest, USA","interactions":[],"lastModifiedDate":"2021-02-09T13:28:58.631979","indexId":"70217890","displayToPublicDate":"2020-12-02T07:27:54","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Karst geology of the Upper Midwest, USA","docAbstract":"Karst in the Upper Midwest occurs within a thick sequence of mixed carbonate and siliciclastic Cambrian through Pennsylvanian sedimentary rocks, with a minor occurrence of karst in Proterozoic sandstone. Deposition of the sediments occurred on a marine epeiric ramp that spanned much of the North American continent through most of the Paleozoic. The Upper Midwest region experienced dramatic changes in sea level over geologic time, resulting in the observed sequence of interbedded carbonate and clastic rocks. The greatest degree of karst development occurs within (1) the Lower Ordovician Prairie du Chien Group below the Sauk-Tippecanoe (Knox) unconformity, (2) the Upper Ordovician Galena Group, (3) the Middle and Upper Devonian Wapsipinicon and Cedar Valley Groups, and (4) the Middle Mississippian Mammoth Cave Group and correlative formations. Uplift and exposure of the rocks likely occurred in the Permian, with some later deposition of Cretaceous terrestrial sediments atop the marine strata. Nearly all the Cenozoic sedimentary units were removed by ice sheets during the Pleistocene; however, pockets of Cretaceous sediments persist on the margins of the Driftless Area, a region of the Upper Mississippi River Valley that remained largely free of ice during the last ice age.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Caves and Karst of the Upper Midwest, USA","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-54633-5_1","usgsCitation":"Doctor, D.H., and Alexander, E.C., 2021, Karst geology of the Upper Midwest, USA, chap. of Caves and Karst of the Upper Midwest, USA, 21 p., https://doi.org/10.1007/978-3-030-54633-5_1.","productDescription":"21 p.","ipdsId":"IP-118559","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":383150,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":810072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alexander, E. Calvin Jr.","contributorId":173840,"corporation":false,"usgs":false,"family":"Alexander","given":"E.","suffix":"Jr.","email":"","middleInitial":"Calvin","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":810073,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225626,"text":"70225626 - 2021 - USGS Illinois River Monitoring and Evaluation","interactions":[],"lastModifiedDate":"2024-03-21T16:44:51.356134","indexId":"70225626","displayToPublicDate":"2020-12-01T11:42:15","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":9543,"text":"Interim Summary Report","active":true,"publicationSubtype":{"id":3}},"title":"USGS Illinois River Monitoring and Evaluation","docAbstract":"No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2020 Interim summary report: Asian carp monitoring and response plan","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"Asian Carp Regional Coordinating Committee","usgsCitation":"Harrison, T.J., Hop, K.D., Hlavacek, E., and Knights, B.C., 2021, USGS Illinois River Monitoring and Evaluation: Interim Summary Report, 4 p.","productDescription":"4 p.","startPage":"119","endPage":"122","ipdsId":"IP-128304","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":426840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391073,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://invasivecarp.us/PlansReports.html"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.44907719485067,\n 41.985997476890276\n ],\n [\n -91.5027377363265,\n 41.985997476890276\n ],\n [\n -91.5027377363265,\n 38.48676442684382\n ],\n [\n -87.44907719485067,\n 38.48676442684382\n ],\n [\n -87.44907719485067,\n 41.985997476890276\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":825982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":825983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":825984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":897033,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219582,"text":"70219582 - 2021 - Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","interactions":[],"lastModifiedDate":"2021-04-15T12:53:09.492694","indexId":"70219582","displayToPublicDate":"2020-12-01T07:52:18","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Interactive PHREEQ-N-AMDTreat water-quality modeling tools to evaluate performance and design of treatment systems for acid mine drainage","docAbstract":"The PHREEQ-N-AMDTreat aqueous geochemical modeling tools described herein simulate changes in pH and solute concentrations resulting from passive and active treatment of acidic or alkaline mine drainage (AMD). The “user-friendly” interactive tools, which are publicly available software, utilize PHREEQC equilibrium aqueous and surface speciation models and kinetics models for O2 ingassing and CO2 outgassing, iron and manganese oxidation and precipitation, limestone dissolution, and organic carbon oxidation combined with reduction of nitrate, sulfate, and ferric iron. Reactions with synthetic caustic chemicals (CaO, Ca(OH)2, NaOH, Na2CO3) or oxidizing agents (H2O2) also may be simulated separately or combined with sequential kinetic steps. A user interface facilitates input of water chemistry data for one or two (mixed) influent AMD solutions and adjustment of kinetic variables. Graphical and tabular output indicates the changes in pH, metals and other solute concentrations, total dissolved solids, and specific conductance of treated effluent plus the cumulative quantity of precipitated solids as a function of retention time or the amount of caustic agent added. By adjusting kinetic variables or chemical dosing, the effects of independent or sequential treatment steps that have different retention time (volume/flow rate), aeration rate, quantities of reactive solids, and temperature can be simulated for the specified influent quality. The size (land area) of a treatment system can then be estimated using reaction time estimates (volume for a corresponding treatment step is the product of reaction time and flow rate; area is volume divided by depth). Given the estimated system size, the AMDTreat cost-analysis model may be used to compute approximate costs for installation (capital) and annual operations and maintenance. Thus, various passive and/or active treatment strategies can be identified that could potentially achieve the desired effluent quality, but require different land area, equipment, and costs for construction and operation.
Quantifiable estimates of predator–prey interactions and relationships in aquatic habitats are difficult to obtain and rare, especially when individuals cannot be readily observed. To overcome this observational impediment, imaging sonar was used to assess the cooccurrence of predator‐size fish and juvenile salmonids, Oncorhynchus spp., at the entrance to a floating surface collector (FSC) in the forebay of North Fork Dam on the Clackamas River, Oregon (USA). Imaging sonar can be used to transform active sound waves into visual data, making it possible to obtain continuous underwater observations on the presence and interspecific interactions between predator‐size fish and prey (juvenile salmonids). Hourly counts of smolt‐size fish tracks, diel phase, water clarity and river discharge were used as covariates within a zero‐inflated Poisson model to determine how these factors may influence the number of predators in front of the FSC. Both the number of smolt‐size fish tracks and diel phase had the strongest effects on the number of predator‐size fish tracks, with more predator‐size fish tracks observed during the daytime, and as the number of smolt‐size fish tracks increased. Additionally, the presence of predator‐size fish may affect the abundance and direction of travel of juvenile salmonids, as fewer smolt‐size fish were observed when predators were present, and a greater proportion of smolt‐size fish were observed travelling away from the FSC when predator‐size fish were present. This study provides estimates of predator and prey fish abundance in the vicinity of surface collection systems at moderate‐sized hydropower projects and could help resource managers better understand mechanisms that can influence the survival and passage behaviour of juvenile salmonids using surface collection structures at dams.
","language":"English","publisher":"Wiley","doi":"10.1111/fme.12465","usgsCitation":"Smith, C.D., Plumb, J., Adams, N.S., and Wyatt, G.J., 2021, Predator and prey events at the entrance of a surface‐oriented fish collector at North Fork Dam, Oregon: Fisheries Management and Ecology, v. 28, no. 2, p. 172-182, https://doi.org/10.1111/fme.12465.","productDescription":"11 p.","startPage":"172","endPage":"182","ipdsId":"IP-097283","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":384347,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","city":"Estacada","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.38632202148438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.273920035433605\n ],\n [\n -122.27645874023438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.319323121350145\n ],\n [\n -122.38632202148438,\n 45.273920035433605\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"28","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811722,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811723,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":811724,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wyatt, Garth J","contributorId":214904,"corporation":false,"usgs":false,"family":"Wyatt","given":"Garth","email":"","middleInitial":"J","affiliations":[{"id":39135,"text":"Portland General Electric, 33831 Faraday Rd., Estacada, Oregon 97023","active":true,"usgs":false}],"preferred":false,"id":811725,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217365,"text":"70217365 - 2021 - Climate and Ecological Disturbance Analysis of Engelmann spruce and Douglas fir in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2021-01-20T13:53:14.893644","indexId":"70217365","displayToPublicDate":"2020-11-30T07:51:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7512,"text":"Trees, Forests, and People","active":true,"publicationSubtype":{"id":10}},"title":"Climate and Ecological Disturbance Analysis of Engelmann spruce and Douglas fir in the Greater Yellowstone Ecosystem","docAbstract":"The effects of anthropogenic climate change are apparent in the Greater Yellowstone Ecosystem (GYE), USA, with forest die-off, insect outbreaks, and wildfires impacting forest ecosystems. A long-term perspective would enable assessment of the historical range of variability in forest ecosystems and better determination of recent forest dynamics and historical thresholds. The objectives of this study were to (1) develop tree-ring chronologies for Engelmann spruce and Douglas fir growing at the study location, (2) correlate the annual ring widths of each species to monthly climate variables, (3) examine the instrumental climate data for regimes shifts in the mean state of variables, and (4) determine when ecological disturbances occurred through a quantification of growth releases. Finally, we discuss both climate-growth relationships and growth releases in the context of climate regime shifts and known forest disturbances. Engelmann spruce and Douglas fir showed some similar climate responses using moving correlation analysis including negative correlations between ring width and June – August current year temperature and previous growing season temperature. Regime shift analysis indicated significant (p < 0.05) shifts in minimum and maximum GYE temperature in the latter half of the 20th century. Disturbance analysis indicated that both tree species responded to wildfire and insect outbreak events with growth releases in up to 25% of the trees. Disentangling the influence of climate regime shifts and forest disturbances on the climate-growth relationships can be difficult because climate and forest disturbances are intricately linked. Our evidence indicates that regime shifts in monthly climate variables and forest disturbances as recorded by growth releases can influence the ring width response to climate over time. Trees are key to providing a long-term perspective on climate and ecological health across the GYE because they integrate both climate and ecology in their annual ring widths.
Rocky reef habitats in lacustrine systems constitute important areas for lithophilic‐spawning fishes. Interstitial spaces created by the structure of rocky reefs form microenvironments where incubating embryos and juvenile fish are potentially protected from predators and physical displacement. However, if interstitial spaces are filled or blocked by sediment or biofouling, the reef structure may lose these benefits. Common practices to restore reef habitat include augmentation of existing reef structures or construction of new reefs, though these practices can be costly. We explored an alternative approach for reef remediation. In 2018, we developed two benthic sled cleaning devices that used either propulsion or pressurized water jets and were towed behind a small vessel to clean reefs. We used the devices to clean two impaired natural rocky reefs in Saginaw Bay, Lake Huron. We indexed effectiveness of cleaning by measured changes in substrate relative hardness before and after cleaning. A biological response to reef cleaning was also measured by egg deposition of fall (Lake Whitefish Coregonus clupeaformis) and spring (Walleye Sander vitreus) lithophilic spawners. We found that our propulsion cleaning device was more effective in increasing substrate relative hardness than was the water jet device, although this was not consistent among all study locations. We also found that egg deposition on study plots was variable, but in general, egg deposition was highest on study plots that had the greatest increases in relative hardness post‐cleaning. The practicality of cleaning devices is likely related to the magnitude of site‐specific degradation. Our results indicate that the use of these or similar devices can potentially increase the quality of spawning habitat by displacing sediments that have deposited on reef structures.
Documenting responses of biotic assemblages to coal-mining impacts is crucial to informing regulatory and reclamation actions. However, attributing biotic patterns to specific stressors is difficult given the dearth of preimpact studies and prevalence of confounding factors. Analysing species distributions and abundances, especially stratified by species traits, provides insights into how assemblage composition shifts occur. We evaluated stream habitats and fish assemblages along a mining intensity gradient in 83 headwater (2nd- and 3rd-order) streams of the upper Clinch and Powell river basins in Virginia. Our multivariate gradient (MINE.PC1) was based on percentages of watershed area covered by surface mine, underground mine and valley fill to represent spatial variance in mining intensity. MINE.PC1 was positively correlated with conductivity and percentage of substrate as cobble. Forty fish-assemblage metrics were analysed via boosted regression trees to assess assemblage responses to mining intensity, while accounting for environmental variation and spatial structure among sites. Conductivity and MINE.PC1 were strongly negatively related to occurrences of Fantail Darter (Etheostoma flabellare) and sculpin (Cottus) spp. Several taxonomic, trophic and reproductive metrics of assemblage composition responded strongly to mining intensity or its instream correlates. For example, coal mining favoured omnivore-herbivores, but inhibited invertivores, simple lithophils and nonsimple nonlithophils. We revealed distinct negative and positive responses to mining-related stressors, which suggest changes to macroinvertebrate prey availability and/or contaminant loads contribute to fish extirpations in coalfield streams. Future assessments of mining impacts on fish assemblages could be more instructive by including characterisations of physicochemical stressors and regionally calibrated biotic metrics with demonstrated sensitivity to mining.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12588","usgsCitation":"Martin, Z.P., Angermeier, P.L., Ciparis, S., and Orth, D., 2021, Coal-mining intensity influences species and trait distributions of stream fishes in two Central Appalachian watersheds: Ecology of Freshwater Fish, v. 30, no. 3, p. 347-365, https://doi.org/10.1111/eff.12588.","productDescription":"19 p.","startPage":"347","endPage":"365","ipdsId":"IP-113479","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":454189,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/eff.12588","text":"External Repository"},{"id":396022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Powell River, upper Clinch River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.71630859375,\n 37.153749608429415\n ],\n [\n -82.03765869140625,\n 37.470498470798724\n ],\n [\n -82.89459228515624,\n 36.96306042436515\n ],\n [\n -83.6444091796875,\n 36.61773216000592\n ],\n [\n -82.694091796875,\n 36.602299135790446\n ],\n [\n -81.71630859375,\n 37.153749608429415\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Zachary P. 0000-0001-5779-3548 zmartin@usgs.gov","orcid":"https://orcid.org/0000-0001-5779-3548","contributorId":279461,"corporation":false,"usgs":false,"family":"Martin","given":"Zachary","email":"zmartin@usgs.gov","middleInitial":"P.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":834958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ciparis, Serena","contributorId":279464,"corporation":false,"usgs":false,"family":"Ciparis","given":"Serena","affiliations":[{"id":12428,"text":"U. 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Today, Utah prairie dogs exist in small, isolated populations, making them less demographically stable and more susceptible to erosion of genetic variation by genetic drift. We characterized patterns of genetic structure at neutral and putatively adaptive loci in order to evaluate the relative effects of genetic drift and local adaptation on population divergence. We sampled individuals across the Utah prairie dog species range and generated 2,955 single nucleotide polymorphisms (SNPs) using double digest restriction site associated DNA sequencing (ddRAD). Genetic diversity was lower in low elevation sites compared to high elevation sites. Population divergence was high among sites and followed an isolation‐by‐distance (IBD) model. Our results indicate that genetic drift plays a substantial role in the population divergence of the Utah prairie dog, and colonies would likely benefit from translocation of individuals between recovery units, which are characterized by distinct elevations, despite the detection of environmental associations with outlier loci. By understanding the processes that shape genetic structure, better informed decisions can be made with respect to the management of threatened species to ensure that adaptation is not stymied.
Local adaptation can drive diversification of closely related species across environmental gradients and promote convergence of distantly related taxa that experience similar conditions. We examined a potential case of adaptation to novel visual environments in a species flock (Great Lakes salmonids, genus Coregonus) using a new amplicon genotyping protocol on the Oxford Nanopore Flongle and MinION. We sequenced five visual opsin genes for individuals of C. artedi, C. hoyi, C. kiyi, and C. zenithicus. Comparisons revealed species-specific differences in a key spectral tuning amino acid in rhodopsin (Tyr261Phe substitution), suggesting local adaptation of C. kiyi to the blue-shifted depths of Lake Superior. Ancestral state reconstruction demonstrates that parallel evolution and “toggling” at this amino acid residue has occurred several times across the fish tree of life, resulting in identical changes to the visual systems of distantly related taxa across replicated environmental gradients. Our results suggest that ecological differences and local adaptation to distinct visual environments are strong drivers of both evolutionary parallelism and diversification.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/gbe/evaa237","usgsCitation":"Eaton, K., Bernal, M., Backenstose, N., Yule, D., and Krabbenhoft, T.J., 2021, Nanopore amplicon sequencing reveals molecular convergence and local adaptation of rhodopsin in Great Lakes salmonids: Genome Biology and Evolution, v. 13, no. 2, evaa237, 8 p., https://doi.org/10.1093/gbe/evaa237.","productDescription":"evaa237, 8 p.","ipdsId":"IP-120367","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":454193,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gbe/evaa237","text":"Publisher Index Page"},{"id":381029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.19921875,\n 46.875213396722685\n ],\n [\n -84.92431640625,\n 48.10743118848039\n ],\n [\n -85.7373046875,\n 48.10743118848039\n ],\n [\n -86.50634765625,\n 48.93693495409401\n ],\n [\n -88.24218749999999,\n 49.06666839558117\n ],\n [\n -89.6044921875,\n 48.48748647988415\n ],\n [\n -90.06591796875,\n 47.989921667414194\n ],\n [\n -92.4169921875,\n 46.800059446787316\n ],\n [\n -91.95556640625,\n 46.649436163350245\n ],\n [\n -91.0546875,\n 46.78501604269254\n ],\n [\n -90.966796875,\n 46.51351558059737\n ],\n [\n -90.15380859375,\n 46.483264729155586\n ],\n [\n -88.06640625,\n 47.3834738721015\n ],\n [\n -88.61572265625,\n 46.9502622421856\n ],\n [\n -88.52783203125,\n 46.58906908309182\n ],\n [\n -88.11035156249999,\n 46.830133640447386\n ],\n [\n -87.25341796875,\n 46.42271253466717\n ],\n [\n -86.572265625,\n 46.28622391806706\n ],\n [\n -84.19921875,\n 46.875213396722685\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-11-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Eaton, Katherine","contributorId":245464,"corporation":false,"usgs":false,"family":"Eaton","given":"Katherine","affiliations":[{"id":40126,"text":"University of Buffalo","active":true,"usgs":false}],"preferred":false,"id":806238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bernal, Moises","contributorId":245465,"corporation":false,"usgs":false,"family":"Bernal","given":"Moises","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":806239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Backenstose, Nathan","contributorId":245466,"corporation":false,"usgs":false,"family":"Backenstose","given":"Nathan","affiliations":[{"id":40126,"text":"University of Buffalo","active":true,"usgs":false}],"preferred":false,"id":806240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yule, Daniel 0000-0002-0117-5115 dyule@usgs.gov","orcid":"https://orcid.org/0000-0002-0117-5115","contributorId":139532,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","email":"dyule@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":806241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krabbenhoft, Trevor J.","contributorId":176498,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Trevor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":806242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221833,"text":"70221833 - 2021 - Drivers and projections of ice phenology in mountain lakes in the western United States","interactions":[],"lastModifiedDate":"2021-07-09T18:35:41.337556","indexId":"70221833","displayToPublicDate":"2020-11-27T13:24:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Drivers and projections of ice phenology in mountain lakes in the western United States","docAbstract":"Climate change is causing rapid warming and altered precipitation patterns in mountain watersheds, both of which influence the timing of ice breakup in mountain lakes. To enable predictions of ice breakup in the future, we analyzed a dataset of mountain lake ice breakup dates derived from remote sensing and historical downscaled climate data. We evaluated drivers of ice breakup, constructed a predictive statistical model, and developed projections of mountain lake ice breakup date with global climate models. Using Random Forest analysis, we determined that winter and spring cumulative snow fraction (portion of precipitation falling as snow) and air temperature are the strongest predictors of ice breakup on mountain lakes. Interactions between precipitation, cumulative winter air temperature and lake surface area indicate that shifts in air temperature and precipitation affect smaller lakes (< 2 km2) more than larger lakes (> 2–10 km2). A linear mixed effects model (RMSE of 18 d), applied with an ensemble of 15 global climate models, projected that end-of-century ice breakup in mountain lakes will be earlier by 25 ± 4 and 61 ± 5 (mean ± SE) days for representative concentration pathways 4.5 and 8.5, respectively.
","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lno.11656","usgsCitation":"Caldwell, T.J., Chandra, S., Albright, T., Harpold, A., Dills, T., Greenberg, J., Sadro, S., and Dettinger, M.D., 2021, Drivers and projections of ice phenology in mountain lakes in the western United States: Limnology and Oceanography, v. 66, no. 3, p. 995-1008, https://doi.org/10.1002/lno.11656.","productDescription":"14 p.","startPage":"995","endPage":"1008","ipdsId":"IP-104573","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":454196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.11656","text":"Publisher Index Page"},{"id":387042,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Oregon, Washington","otherGeospatial":"Cascade Mountains, northern Rocky Mountains, Sierra Nevada Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.136474609375,\n 48.07807894349862\n ],\n [\n -116.378173828125,\n 49.001843917978526\n ],\n [\n -119.36645507812499,\n 49.001843917978526\n ],\n [\n -119.20166015625,\n 48.52388120259336\n ],\n [\n -117.191162109375,\n 47.66538735632654\n ],\n [\n -116.42211914062499,\n 47.65058757118734\n ],\n [\n -116.114501953125,\n 47.71715357016648\n ],\n [\n -116.136474609375,\n 48.07807894349862\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.76171875,\n 46.475699386607516\n ],\n [\n -119.84985351562499,\n 48.96579381461063\n ],\n [\n -121.78344726562499,\n 49.01625665778159\n ],\n [\n -122.1240234375,\n 47.04766864046083\n ],\n [\n -122.58544921875,\n 45.506346901083425\n ],\n [\n -123.1787109375,\n 42.73087427928485\n ],\n [\n -122.54150390625,\n 42.04113400940807\n ],\n [\n -122.27783203125,\n 41.1290213474951\n ],\n [\n -120.87158203125,\n 41.393294288784865\n ],\n [\n -120.9814453125,\n 42.08191667830631\n ],\n [\n -121.62963867187499,\n 43.98491011404692\n ],\n [\n -121.14624023437499,\n 45.18978009667531\n ],\n [\n -120.76171875,\n 46.475699386607516\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.45507812500001,\n 36.19109202182454\n ],\n [\n -119.794921875,\n 39.01064750994083\n ],\n [\n -120.498046875,\n 40.49709237269567\n ],\n [\n -120.52001953124999,\n 40.94671366508002\n ],\n [\n -121.6845703125,\n 40.56389453066509\n ],\n [\n -120.73974609374999,\n 38.47939467327645\n ],\n [\n -118.23486328125,\n 35.47856499535729\n ],\n [\n -116.87255859374999,\n 35.65729624809628\n ],\n [\n -116.45507812500001,\n 36.19109202182454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"66","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Timothy J","contributorId":146463,"corporation":false,"usgs":false,"family":"Caldwell","given":"Timothy","email":"","middleInitial":"J","affiliations":[{"id":16704,"text":"University of Nevada - Reno","active":true,"usgs":false}],"preferred":false,"id":818862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandra, Sudeep 0000-0002-9297-8211","orcid":"https://orcid.org/0000-0002-9297-8211","contributorId":224786,"corporation":false,"usgs":false,"family":"Chandra","given":"Sudeep","email":"","affiliations":[{"id":32871,"text":"University of Nevada at Reno","active":true,"usgs":false}],"preferred":false,"id":818863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Albright, Thomas","contributorId":260809,"corporation":false,"usgs":false,"family":"Albright","given":"Thomas","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harpold, Adrian","contributorId":207118,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian","affiliations":[{"id":37455,"text":"University of Nevada","active":true,"usgs":false}],"preferred":false,"id":818865,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dills, Thomas","contributorId":260810,"corporation":false,"usgs":false,"family":"Dills","given":"Thomas","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818866,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greenberg, Jonathan","contributorId":260811,"corporation":false,"usgs":false,"family":"Greenberg","given":"Jonathan","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":818867,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sadro, Steven 0000-0002-6416-3840","orcid":"https://orcid.org/0000-0002-6416-3840","contributorId":139662,"corporation":false,"usgs":false,"family":"Sadro","given":"Steven","email":"","affiliations":[{"id":12871,"text":"Marine Science Institute, University of California, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":818868,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":818869,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70226156,"text":"70226156 - 2021 - Basalt geochemistry and mantle flow during early backarc basin evolution: Havre Trough and Kermadec Arc, southwest Pacific","interactions":[],"lastModifiedDate":"2021-11-15T12:16:43.251541","indexId":"70226156","displayToPublicDate":"2020-11-27T06:14:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9540,"text":"Geochemistry Geophysics Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Basalt geochemistry and mantle flow during early backarc basin evolution: Havre Trough and Kermadec Arc, southwest Pacific","docAbstract":"The Havre Trough (HT) backarc basin in the southwest Pacific is in the rifting stage of development. We distinguish five types of basalt there based on their amount and kind of slab component: backarc basalts (BAB) with little or no slab component, modified BAB with slight amounts, reararc (RA) with more, remnants of the preexisting arc (Colville Ridge horsts), and arc front volcanoes within the HT. Previous subarc mantle is quickly removed and replaced by more fertile mantle with less slab component. The ambient mantle is “Pacific” isotopically, and more enriched in Nb/Yb and Nd and Hf isotope ratios north of the Central Kermadec Discontinuity at 32°S than to the south. The contrast may reflect inheritance in the south of mantle that was depleted during spreading that formed the southern South Fiji Basin and a higher degree of melting because of a wetter slab-derived flux. The slab component also differs along strike, more like a dry melt in the north and a supercritical fluid in the south. The mass fraction of slab component increases southward in the backarc as well as the arc front. RA volcanoes have the most slab component (1%–2%) and form indistinct ridges at high angles to, and <50 km behind, frontal volcanoes. Backarc basalts have less and occur throughout the basin. Slab components are distributed further into the backarc, and more irregularly, during the rifting than spreading stage of backarc basin development. The rifting stage is disorganized geochemically as well as spatially.
Coal mining is an anthropogenic stressor that has impacted terrestrial and semi-aquatic wildlife in the Appalachian Plateau since European settlement. Creation of grassland and early-successional habitats resulting from mining in a forested landscape has resulted in novel, non-analog habitat conditions. Depending on the taxa, the extent of mining on the landscape, and reclamation practices, effects have ranged across a gradient of negative to positive. Forest-obligate species such as woodland salamanders and forest-interior birds or those that depend on aquatic systems in their life cycle have been most impacted. Others, such as grassland and early-successional bird species have responded favorably. Some bat species, as an unintended consequence, use legacy deep mines as winter hibernacula in a region with limited karst geology. Recolonization of impacted wildlife often depends on life strategies and species’ vagility, but also on altered or arrested successional processes on the post-surface mine landscape. Many wildlife species will benefit from Forest Reclamation Approach practices going forward. In the future, managers will be faced with decisions about reforestation versus maintaining open habitats depending on the conservation need of species. Lastly, the post-mined landscape currently is the focal point for a regional effort to restore elk (Cervus canadensis) in the Appalachians.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Appalachia's coal-mined landscapes","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer Nature","doi":"10.1007/978-3-030-57780-3_6","usgsCitation":"Lituma, C.M., Cox, J., Spear, S.F., Edwards, J.W., De La Cruz, J.L., Muller, L.I., and Ford, W., 2021, Terrestrial wildlife in the post-mined Appalachian landscape: Status and opportunities, chap. of Appalachia's coal-mined landscapes, p. 135-166, https://doi.org/10.1007/978-3-030-57780-3_6.","productDescription":"32 p.","startPage":"135","endPage":"166","ipdsId":"IP-119718","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488353,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10919/104692","text":"External Repository"},{"id":393655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Appalachian Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.15625,\n 36.66841891894786\n ],\n [\n -75.05859375,\n 41.244772343082076\n ],\n [\n -73.36669921875,\n 43.004647127794435\n ],\n [\n -72.1142578125,\n 44.008620115415354\n ],\n [\n -74.44335937499999,\n 44.74673324024678\n ],\n [\n -81.9580078125,\n 38.496593518947584\n ],\n [\n -80.15625,\n 36.66841891894786\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-11-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Lituma, Christopher M.","contributorId":270668,"corporation":false,"usgs":false,"family":"Lituma","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":829720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cox, John J.","contributorId":140196,"corporation":false,"usgs":false,"family":"Cox","given":"John J.","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":829721,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spear, Stephen F.","contributorId":120450,"corporation":false,"usgs":true,"family":"Spear","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":829722,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, John W.","contributorId":270671,"corporation":false,"usgs":false,"family":"Edwards","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":829723,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"De La Cruz, Jesse L.","contributorId":270672,"corporation":false,"usgs":false,"family":"De La Cruz","given":"Jesse","email":"","middleInitial":"L.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":829724,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muller, Lisa I.","contributorId":270673,"corporation":false,"usgs":false,"family":"Muller","given":"Lisa","email":"","middleInitial":"I.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":829725,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":829719,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}