The effects of season, location, species, and sex on body weight and a comprehensive array of blood chemistry and hematology analytes were compared for free-ranging western (Aechmophorus occidentalis) and Clark's (Aechmophorus clarkii) grebes. Birds (n = 56) were collected from Puget Sound, WA, and Monterey Bay and San Francisco Bay, CA, from February 2007 to March 2011. The data supported generalization of observed ranges for most analytes across Aechmophorus grebe metapopulations wintering on the Pacific coast. Notable seasonal and location effects were observed for packed cell volume (winter 6% greater than fall; winter California [CA] 5% greater than Washington [WA]), total white blood cell count (CA 3.57 × 103 cells/µL greater than WA), heterophils (WA 10% greater than CA), lymphocytes (winter 19% greater than fall), heterophil to lymphocyte ratio (fall 5.7 greater than winter), basophils (CA greater than WA), plasma protein (WA about 10 g/L [1.0 g/dL] greater than CA), plasma protein to fibrinogen ratio (winter about 15 greater than fall), potassium (CA 2 mmol/L greater than WA), and liver enzymes (alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase: WA greater than CA). Within California, season had a greater effect on body mass than sex (mean winter weights about 200 g greater than fall), whereas within a season, males weighed only about 80 g more than females, on average. These data give biologists and veterinarians quantitative reference values to better assess health at the individual and metapopulation level.
","language":"English","publisher":"Association of Avian Veterinarians","doi":"10.1647/2019-473","usgsCitation":"Anderson, N., De La Cruz, S.E., Gaydos, J., Ziccardi, M.H., and Harvey, D.J., 2021, Effects of season, location, species, and sex on hematologic and plasma biochemical values and body mass in free-ranging Grebes (Aechmophorus species): Journal of Avian Medicine and Surgery, v. 35, no. 2, p. 135-154, https://doi.org/10.1647/2019-473.","productDescription":"20 p.","startPage":"135","endPage":"154","ipdsId":"IP-110043","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451615,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/0q5221wf","text":"External Repository"},{"id":387454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington, California","otherGeospatial":"Puget Sound, San Francisco Bay, Monterery Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.45312499999999,\n 47.07012182383309\n ],\n [\n -121.37695312499999,\n 47.07012182383309\n ],\n [\n -121.37695312499999,\n 48.8936153614802\n ],\n [\n -124.45312499999999,\n 48.8936153614802\n ],\n [\n -124.45312499999999,\n 47.07012182383309\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.00292968749999,\n 37.055177106660814\n ],\n [\n -121.46484375,\n 37.055177106660814\n ],\n [\n -121.46484375,\n 38.58252615935333\n ],\n [\n -123.00292968749999,\n 38.58252615935333\n ],\n [\n -123.00292968749999,\n 37.055177106660814\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.20916748046876,\n 36.56260003738545\n ],\n [\n -121.70654296874999,\n 36.56260003738545\n ],\n [\n -121.70654296874999,\n 36.96086580957587\n ],\n [\n -122.20916748046876,\n 36.96086580957587\n ],\n [\n -122.20916748046876,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Nancy L","contributorId":261393,"corporation":false,"usgs":false,"family":"Anderson","given":"Nancy L","affiliations":[{"id":52834,"text":"University of California, Oiled Wildlife Care Network, Wildlife Health Center, School of Veterinary Medicine, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":819952,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":819953,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaydos, Joseph K","contributorId":261394,"corporation":false,"usgs":false,"family":"Gaydos","given":"Joseph K","affiliations":[{"id":52835,"text":"Wildlife Health Center, Orcas Island Office, Eastsound, WA 98245, USA","active":true,"usgs":false}],"preferred":false,"id":819954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ziccardi, Michael H.","contributorId":74617,"corporation":false,"usgs":false,"family":"Ziccardi","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":819955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harvey, Danielle J","contributorId":261395,"corporation":false,"usgs":false,"family":"Harvey","given":"Danielle","email":"","middleInitial":"J","affiliations":[{"id":52836,"text":"Department of Public Health Sciences, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":819956,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70222412,"text":"70222412 - 2021 - Temperature variation and host immunity regulate viral persistence in a salmonid host","interactions":[],"lastModifiedDate":"2021-07-27T11:59:37.309609","indexId":"70222412","displayToPublicDate":"2021-07-07T06:33:08","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9113,"text":"Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"Temperature variation and host immunity regulate viral persistence in a salmonid host","docAbstract":"Environmental variation has important effects on host–pathogen interactions, affecting large-scale ecological processes such as the severity and frequency of epidemics. However, less is known about how the environment interacts with host immunity to modulate virus fitness within hosts. Here, we studied the interaction between host immune responses and water temperature on the long-term persistence of a model vertebrate virus, infectious hematopoietic necrosis virus (IHNV) in steelhead trout (Oncorhynchus mykiss). We first used cell culture methods to factor out strong host immune responses, allowing us to test the effect of temperature on viral replication. We found that 15
The Chesapeake Bay ecosystem is a national treasure that provides almost $100 billion annually of goods and services. The Chesapeake Bay Program (CBP), is one of the largest federal-state restoration partnerships in the United States and is underpinned by rigorous science. The U.S. Geological Survey (USGS) has a pivotal role as a science provider for assessing ecosystem condition and response in the Chesapeake watershed. Despite significant CBP accomplishments, the pressures of climate change and competing demands on land use and change require an acceleration of progress towards the 10 goals in the Chesapeake Bay Watershed Agreement. USGS Chesapeake studies are increasing efforts to provide integrated science and are engaging stakeholders to inform the multi-faceted restoration and conservation decisions to improve habitat for fish and waterfowl, and socio-economic benefits to the 18 million people living in the watershed.
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U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Edwin B. Forsythe National Wildlife Refuge in New Jersey. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of 23 marsh management units within the refuge and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to about \\$980,000, but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than \\$980,000 included applying sediment to the marsh surface to increase elevation in five marsh management units, digging runnels on the marsh surface to improve drainage in five marsh management units, and breaching roads and berms to improve tidal flow in five marsh management units. The potential management benefits were derived from expected reduction in the duration of surface flooding, improved capacity for marsh elevation to keep pace with sea-level rise and increases in numbers of spiders (as an indicator of trophic health), tidal marsh obligate birds, and wintering American black ducks. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Edwin B. Forsythe National Wildlife Refuge that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211037","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Castelli, P.M., and Rettig, V., 2021, Optimization of salt marsh management at the Edwin B. Forsythe National Wildlife Refuge, New Jersey, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1037, 41 p., https://doi.org/10.3133/ofr20211037.","productDescription":"vi, 41 p.","ipdsId":"IP-120822","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":386007,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1037/coverthb.jpg"},{"id":386008,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1037/ofr20211037.pdf","text":"Report","size":"7.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1037"},{"id":386009,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1037/images"}],"country":"United States","state":"New Jersey","otherGeospatial":"Edwin B. Forsythe National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.41967010498045,\n 39.388182633584485\n ],\n [\n -74.36851501464844,\n 39.40967202224426\n ],\n [\n -74.36817169189453,\n 39.433011014927224\n ],\n [\n -74.33040618896484,\n 39.45395640766923\n ],\n [\n -74.31255340576172,\n 39.48125549646666\n ],\n [\n -74.3276596069336,\n 39.50059690888215\n ],\n [\n -74.4107437133789,\n 39.51807903374736\n ],\n [\n -74.43305969238281,\n 39.519138415094176\n ],\n [\n -74.4601821899414,\n 39.51198727745152\n ],\n [\n -74.4275665283203,\n 39.49397374330326\n ],\n [\n -74.45743560791016,\n 39.46959506012395\n ],\n [\n -74.44267272949219,\n 39.45766759232811\n ],\n [\n -74.41967010498045,\n 39.388182633584485\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Batrachochytrium salamandrivorans (Bsal) is a fungal pathogen that can cause the emerging infectious disease Bsal chytridiomycosis in some amphibians and is currently causing dramatic declines in European urodeles. To date, Bsal has not been detected in North America but has the potential to cause severe declines in naïve hosts if introduced. Therefore, it is critical that wildlife managers are prepared with effective management actions to combat the fungus. Research has been initiated to identify strategies; however, managers need guidance to prepare for an outbreak until results are available. We conducted a workshop at the Joint Meeting of The Wildlife Society and American Fisheries Society on 30 September 2019 with participants of a Bsal symposium. Our goals were to describe the expected effects of 11 management actions that could be implemented for Bsal in salamander communities in the northwestern, northeastern, and southeastern United States. Participants expected a variety of proposed management actions to decrease pathogen transmission and increase host survival, but also that the selection of a management action may depend on the specific membership of the amphibian community. Collectively, our assessment will help refine research and modeling priorities in an effort to mitigate the risk of Bsal to native U.S. amphibians.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.1198","usgsCitation":"Bernard, R.F., and Campbell Grant, E.H., 2021, Rapid assessment indicates context-dependent mitigation for amphibian disease risk: Wildlife Society Bulletin, v. 45, no. 23-24, p. 290-299, https://doi.org/10.1002/wsb.1198.","productDescription":"10 p.","startPage":"290","endPage":"299","ipdsId":"IP-118442","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451621,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/wsb.1198","text":"Publisher Index Page"},{"id":387134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"23-24","noUsgsAuthors":false,"publicationDate":"2021-07-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Bernard, Riley F 0000-0002-1321-3625","orcid":"https://orcid.org/0000-0002-1321-3625","contributorId":238925,"corporation":false,"usgs":false,"family":"Bernard","given":"Riley","email":"","middleInitial":"F","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":819007,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819008,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221863,"text":"70221863 - 2021 - Coastal Tree-Ring Records for Paleoclimate and Paleoenvironmental Applications in North America","interactions":[],"lastModifiedDate":"2021-07-13T09:57:05.983187","indexId":"70221863","displayToPublicDate":"2021-07-06T12:00:53","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Coastal Tree-Ring Records for Paleoclimate and Paleoenvironmental Applications in North America","docAbstract":"For more than a century, tree-ring research has identified relationships between climatic and ecological conditions and tree growth to describe past environments and constrain future ecosystem vulnerabilities. Tree-ring records are frequently used as environmental proxies that extend knowledge of past climate and ecology on millennial scales. Many of the most pressing global change questions facing North America concern the rate of climate change and vulnerability of ecosystems and society along the coast. The opportunities and applications in dendrochronology continue to grow with advancing methodologies, faster computational ability, and the cost-reduction of many chemical and anatomical analyses. Here, we propose that many pressing global change questions that affect coastal communities can be addressed using dendrochronological techniques. We review coastal tree-ring studies that demonstrate the utility and potential for future tree-ring studies in the northeastern, southeastern, northwestern, and southwestern North American coasts. Additionally, we show that tree-ring chronologies along the coast give insight into local and regional climate phenomena that are distinct from nearby, inland tree-ring chronologies of the same species. Lastly, we identify opportunities for coastal dendrochronology and encourage the collection of more tree-ring records that are directly impacted by coastal phenomena.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2021.107044","usgsCitation":"Tucker, C., and Pearl, J.K., 2021, Coastal Tree-Ring Records for Paleoclimate and Paleoenvironmental Applications in North America: Quaternary Science Reviews, v. 265, 107044, 14 p., https://doi.org/10.1016/j.quascirev.2021.107044.","productDescription":"107044, 14 p.","ipdsId":"IP-123038","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":387125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North American Pacific, Atlantic Coastal Rings","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.45703125,\n 42.032974332441405\n ],\n [\n -123.3984375,\n 42.032974332441405\n ],\n [\n -123.3984375,\n 60.06484046010452\n ],\n [\n -153.45703125,\n 60.06484046010452\n ],\n [\n -153.45703125,\n 42.032974332441405\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.16796875,\n 27.68352808378776\n ],\n [\n -62.05078125,\n 27.68352808378776\n ],\n [\n -62.05078125,\n 45.213003555993964\n ],\n [\n -77.16796875,\n 45.213003555993964\n ],\n [\n -77.16796875,\n 27.68352808378776\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"265","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tucker, Clay","contributorId":257674,"corporation":false,"usgs":false,"family":"Tucker","given":"Clay","email":"","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":819054,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearl, Jessie K. 0000-0002-1556-2159","orcid":"https://orcid.org/0000-0002-1556-2159","contributorId":242893,"corporation":false,"usgs":true,"family":"Pearl","given":"Jessie","email":"","middleInitial":"K.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":819055,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221784,"text":"ofr20211053 - 2021 - Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey flood risk management project area in San Diego County, California—Breeding activities and habitat use—2020 annual report","interactions":[],"lastModifiedDate":"2021-08-03T12:41:56.22042","indexId":"ofr20211053","displayToPublicDate":"2021-07-06T09:36:49","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1053","displayTitle":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey Flood Risk Management Project Area in San Diego County, California: Breeding Activities and Habitat Use—2020 Annual Report","title":"Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey flood risk management project area in San Diego County, California—Breeding activities and habitat use—2020 annual report","docAbstract":"To investigate whether the cumulative years of treatment had an impact on vireo reproductive effort, we looked at the effects of the Treatment Index on reproductive parameters. Results from generalized linear models indicated that treatment did not have an effect on vireo nesting effort or the number of vireo fledglings per pair produced in 2020.
Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Damaging ground motions from the 2011
Natural perchlorate (ClO4−) exists in many places on Earth, in lunar regolith, meteorites, and on the surface of Mars. Terrestrial natural ClO4− has widely variable Cl and O stable isotopic compositions (δ37Cl, δ18O, Δ17O). The δ18O and Δ17O values of ClO4− from the most hyper-arid locations co-vary. ClO4− from less arid areas has relatively little 17O excess and poor Δ17O-δ18O correlation. ClO4− from the Atacama Desert has unusually low δ37Cl (<−10‰) and exhibits a positive correlation between δ37Cl and δ18O, while the δ37Cl of ClO4− from all other locations varies between −5 and +7‰ with no δ37Cl-δ18O covariation. To evaluate the impact of different precursors (ClOx) and reaction pathways on the isotopic composition of ClO4−, we measured the isotopic composition of ClO4− produced in the laboratory by UV or O3 mediated aqueous oxidation of Cl−, OCl−, ClO2−, and ClO2° as well as O3 mediated oxidation of dry NaCl. ClOx oxidation in aqueous or dry systems enriched in O3 produced ClO4− with Δ17O values that generally increased with the number of O atoms required and included evidence that the site-specific 17O anomaly in O3 was preferentially transferred to ClO4−. Based on the inferred number of O atoms sourced from O3, and known Cl and O reaction pathways, it appears that ClO2° and ClO3* were required intermediates in the production of ClO4− in the O3 experiments. ClOx aqueous oxidation by UV irradiation produced ClO4− with a large range of δ18O values and little or no 17O anomaly. ClO3− was produced to a much greater extent than ClO4− in all experiments except dry oxidation of NaCl by O3. The isotopic composition of ClO3− was distinct from that of ClO4− produced from the same initial reactants. Combined results of O3 and UV mediated reactions largely bracketed the range of natural ClO4− δ18O and Δ17O values as well as δ37Cl values of non-Atacama natural samples, but no conditions produced the low δ37Cl values of Atacama ClO4−. Our results indicate that variation in production mechanisms, possibly combined with isotopically variable precursors, could be responsible for much of the observed isotopic variation in natural ClO4− and ClO3−.
Geobiology explores how Earth's system has changed over the course of geologic history and how living organisms on this planet are impacted by or are indeed causing these changes. For decades, geologists, paleontologists, and geochemists have generated data to investigate these topics. Foundational efforts in sedimentary geochemistry utilized spreadsheets for data storage and analysis, suitable for several thousand samples, but not practical or scalable for larger, more complex datasets. As results have accumulated, researchers have increasingly gravitated toward larger compilations and statistical tools. New data frameworks have become necessary to handle larger sample sets and encourage more sophisticated or even standardized statistical analyses.
","language":"English","publisher":"Wiley","doi":"10.1111/gbi.12462","usgsCitation":"Farrell, U., Samawi, R., Anjanappa, S., Klykov, R., Adeboye, O., Agic, H., Ahm, A., Boag, T., Bowyer, F., Brocks, J.J., Brunoir, T., Canfield, D., Chen, X., Cheng, M., Clarkson, M., Cole, D.B., Cordie, D., Crockford, P.W., Cui, H., Dahl, T., Del Mouro, L., Dewing, K., Dornbos, S., Drabon, N., Dumoulin, J.A., Emmings, J., Endringa, C.R., Fraser, T.A., Gaines, R.R., Gaschnig, R.M., Gibson, T.M., Gilleaudeau, G.J., Gill, B.C., Goldberg, K., Guilbaud, R., Halverson, G.P., Hammarlund, E.U., Hantsoo, K.G., Henderson, M.A., Hodgskiss, M.S., Horner, T., Husson, J.M., Johnson, B., Kabanov, P., Keller, C.B., Kimmig, J., Kipp, M.A., Knoll, A.H., Kreitsmann, T., Kunzmann, M., Kurzweil, F., LeRoy, M.A., Li, C., Lipp, A., Loydell, D.K., Lu, X., Macdonald, F.A., Magnall, J.M., Mand, K., Mehra, A., Melchin, M.J., Miller, A.J., Mwinde, C.N., O’Connell, B., Och, L.M., Ossa Ossa, F., Pages, A., Paiste, K., Partin, C.A., Peters, S., Petrov, P., Playter, T.L., Plaza-Torres, S., Porter, S.M., Poulton, S.W., Pruss, S.B., Richoz, S., Ritzer, S.R., Rooney, A.D., Sahoo, S.K., Schoepfer, S.D., Sclafani, J.A., Shen, Y., Shorttle, O., Slotznick, S.P., Smith, E.F., Spinks, S., Stockey, R.G., Strauss, J.V., Stueken, E.E., Tecklenburg, S., Thomson, D., Tosca, N.J., Uhlein, G.J., Vizcaino, M.N., Wang, H., White, T., Wilby, P.R., Woltz, C.R., Wood, R., Xiang, L., Yurchenko, I.A., Zhang, T., Planavsky, N.J., Lau, K.V., Johnston, D.T., and Sperling, E.A., 2021, The Sedimentary Geochemistry and Paleoenvironments Project: Geobiology, v. 19, no. 6, p. 545-556, https://doi.org/10.1111/gbi.12462.","productDescription":"22 p.","startPage":"545","endPage":"556","ipdsId":"IP-128698","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":451634,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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The theory of migratory coupling postulates that aggregations of migrant prey can induce large-scale synchronized movements in predators, and this coupling is consequential for the dynamics of ecological communities. The degree to which humans influence these interactions remains largely unknown. We tested whether creation of large resource pulses by humans such as seasonal herding of reindeer Rangifer tarandus and hunting of moose, Alces alces, can induce migratory coupling with Golden Eagles, Aquila chrysaetos, and whether these lead to demographic consequences for the eagles.
Fennoscandia.
We used movement data from 32 tracked Golden Eagles spanning 125 annual migratory cycles over 8 years. We obtained reindeer distribution data through collaboration with reindeer herders based on satellite tracking of reindeer, and moose harvest data from the national hunting statistics for Sweden. We assessed demographic consequences for eagles from ingesting lead from ammunition fragments in moose carcasses through survival estimates and their links with lead concentrations in eagles' blood.
In spring, eagles migrated hundreds of kilometres to be spatially and temporally coupled with calving reindeer, whereas in autumn, eagles matched their distribution with the location and timing of moose hunt. Juveniles were more likely to couple with reindeer calving, whereas adults were particularly drawn to areas of higher moose harvest. Due to this coupling, eagles ingested lead from spent ammunition in moose offal and carcasses and the resulting lead toxicity increased the risk of mortality by 3.4 times.
We show how migratory coupling connects landscape processes and that human actions can influence migratory coupling over large spatial scales and increase demographic risks for predators. We provide vital knowledge towards resolving human–wildlife conflicts and the conservation of protected species over a large spatial and temporal scale.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.13373","usgsCitation":"Singh, N.J., Ecke, F., Katzner, T., Bagchi, S., Sandstrom, P., and Hornfeldt, B., 2021, Consequences of migratory coupling of predators and prey when mediated by human actions: Diversity and Distributions, v. 27, no. 9, p. 1848-1860, https://doi.org/10.1111/ddi.13373.","productDescription":"13 p.","startPage":"1848","endPage":"1860","ipdsId":"IP-074750","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":451636,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.13373","text":"Publisher Index Page"},{"id":432753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sweden","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[22.18317,65.72374],[21.21352,65.02601],[21.36963,64.41359],[19.77888,63.60955],[17.84778,62.7494],[17.11955,61.34117],[17.83135,60.63658],[18.78772,60.08191],[17.86922,58.95377],[16.82919,58.71983],[16.44771,57.04112],[15.87979,56.1043],[14.66668,56.20089],[14.10072,55.40778],[12.94291,55.36174],[12.6251,56.30708],[11.78794,57.44182],[11.02737,58.85615],[11.46827,59.43239],[12.30037,60.11793],[12.63115,61.29357],[11.99206,61.80036],[11.93057,63.12832],[12.57994,64.06622],[13.57192,64.04911],[13.91991,64.44542],[13.55569,64.78703],[15.10841,66.19387],[16.10871,67.30246],[16.76888,68.01394],[17.72918,68.01055],[17.99387,68.56739],[19.87856,68.40719],[20.02527,69.06514],[20.64559,69.10625],[21.97853,68.61685],[23.53947,67.93601],[23.56588,66.39605],[23.90338,66.00693],[22.18317,65.72374]]]},\"properties\":{\"name\":\"Sweden\"}}]}","volume":"27","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-07-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Navinder J.","contributorId":342307,"corporation":false,"usgs":false,"family":"Singh","given":"Navinder","email":"","middleInitial":"J.","affiliations":[{"id":81856,"text":"Department of Wildlife, Fish, and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden","active":true,"usgs":false}],"preferred":false,"id":909987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ecke, Fraucke","contributorId":342308,"corporation":false,"usgs":false,"family":"Ecke","given":"Fraucke","email":"","affiliations":[{"id":81856,"text":"Department of Wildlife, Fish, and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden","active":true,"usgs":false}],"preferred":false,"id":909988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":191353,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":909989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagchi, Sumanta","contributorId":210387,"corporation":false,"usgs":false,"family":"Bagchi","given":"Sumanta","email":"","affiliations":[],"preferred":false,"id":909990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandstrom, Per","contributorId":342309,"corporation":false,"usgs":false,"family":"Sandstrom","given":"Per","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":909991,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hornfeldt, Birger","contributorId":342310,"corporation":false,"usgs":false,"family":"Hornfeldt","given":"Birger","email":"","affiliations":[{"id":12666,"text":"Swedish University of Agricultural Sciences","active":true,"usgs":false}],"preferred":false,"id":909992,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70238936,"text":"70238936 - 2021 - Translational invasion ecology: Bridging research and practice to address one of the greatest threats to biodiversity","interactions":[],"lastModifiedDate":"2022-12-19T12:47:57.9032","indexId":"70238936","displayToPublicDate":"2021-07-05T06:41:14","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Translational invasion ecology: Bridging research and practice to address one of the greatest threats to biodiversity","docAbstract":"Effective natural resource management and policy is contingent on information generated by research. Conversely, the applicability of research depends on whether it is responsive to the needs and constraints of resource managers and policy makers. However, many scientific fields including invasion ecology suffer from a disconnect between research and practice. Despite strong socio-political imperatives, evidenced by extensive funding dedicated to addressing invasive species, the pairing of invasion ecology with stakeholder needs to support effective management and policy is lacking. As a potential solution, we propose translational invasion ecology (TIE). As an extension of translational ecology, as a framework to increase collaboration among scientists, practitioners, and policy makers to reduce negative impacts of invasive species. As an extension of translational ecology, TIE is an approach that embodies an intentional and inclusive process in which researchers, stakeholders, and decision makers collaborate to develop and implement ecological research via joint consideration of the ecological, sociological, economic, and/or political contexts in order to improve invasive species management. TIE ideally results in improved outcomes as well as shared benefits between researchers and managers. We delineate the steps of our proposed TIE approach and describe successful examples of ongoing TIE projects from the US and internationally. We suggest practical ways to begin incorporating TIE into research and management practices, including supporting boundary-spanning organizations and activities, expanding networks, sharing translational experiences, and measuring outcomes. We find that there is a need for strengthened boundary spanning, as well as funding and recognition for advancing translational approaches. As climate change and globalization exacerbate invasive species impacts, TIE provides a promising approach to generate actionable ecological research while improving outcomes of invasive species management and policy decisions.
Human-wildlife interactions (HWI) are driven fundamentally by overlapping space and resources. As competition intensifies, the likelihood of interaction and conflict increases. In turn, conflict may impede conservation efforts by lowering social tolerance of wildlife, especially when human-wildlife conflict (HWC) poses a threat to human safety and economic well-being. Thus, mitigating conflict is one of the most consequential components of a wildlife management program, particularly for large carnivores. However, unlike other large carnivores, the causative factors and conservation consequences of interactions between humans and polar bears (Ursus maritimus) are poorly understood. Historically, mitigation of human-polar bear conflict has been a low management priority with the exception of a few locations where conflict had been a chronic concern. In part, this was because of low human densities in most of the Arctic and sea ice act as a physical barrier regulating the frequency of human-polar bear interactions. However, as the Arctic has warmed, anthropogenic activities have increased, and polar bears have become more reliant on land. As a result, mitigating interaction and conflict between humans and polar bears has become a growing concern. In this chapter, we explore the nexus of polar bear and human behavior and environmental change in driving the nature and intensity of human-polar bear interaction and conflict. We first provide an overview of behaviors that contribute to the occurrence of interactions and conflicts. We then review historical and contemporary drivers of interaction and conflict and examine how climate-mediated changes to Arctic marine and terrestrial environments are likely to influence distribution and types of future incidents. We close by proposing a conceptual framework that conservationists and managers can use to mitigate the likelihood of future human-polar bear conflict in a rapidly changing Arctic.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ethology and behavioral ecology of sea otters and polar bears","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","usgsCitation":"Atwood, T.C., and Wilder, J., 2021, Human-polar bear interactions, chap. of Ethology and behavioral ecology of sea otters and polar bears, p. 325-353.","productDescription":"29 p.","startPage":"325","endPage":"353","ipdsId":"IP-112183","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":387142,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387091,"type":{"id":15,"text":"Index Page"},"url":"https://www.springer.com/gp/book/9783030667955"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Davis, Randall W.","contributorId":131160,"corporation":false,"usgs":false,"family":"Davis","given":"Randall","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":819204,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":819205,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":819056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilder, James","contributorId":152610,"corporation":false,"usgs":false,"family":"Wilder","given":"James","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":819057,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70225622,"text":"70225622 - 2021 - Sea otter foraging behavior","interactions":[],"lastModifiedDate":"2021-10-28T14:28:42.879694","indexId":"70225622","displayToPublicDate":"2021-07-04T09:24:30","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Sea otter foraging behavior","docAbstract":"Sea otters are marine specialists but diet generalists, which feed primarily on benthic mega-invertebrates (i.e., body dimension >1 cm). They locate and capture epibenthic and infaunal prey with their forepaws by relying on vision and tactile sensitivity during short-duration dives (generally <2 min) in shallow waters (routine dives <30 m and maximum dive depth ~100 m) of the littoral zone. Sea otters have an elevated resting metabolic rate and small or no energy reserves in the form of blubber, so they feed every 3–4 h. Foraging dives often occur in bouts (i.e., two or more consecutive dives), which may last several hours with 1–2 min between dives, depending on the type of prey. Sea otters consume small or soft prey entirely or use their teeth or stone tools to access the flesh of mega-invertebrates with a shell, test, or exoskeleton. The daily percentage of time that sea otters devote to foraging depends on age, sex, presence of a pup, time of year, and prey abundance, which varies geographically, seasonally, and episodically. In areas occupied by sea otters for many years, epifaunal prey generally decline first followed by infaunal species, and this may result in greater foraging effort and diet specialization associated with density-dependent competition for food. Although prey availability strongly influences sea otter carrying capacity, both intrinsic and extrinsic factors influence population equilibrium density, resulting in spatiotemporal variations in foraging behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Ethology and behavioral ecology of sea otters and polar bears","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-66796-2_4","usgsCitation":"Davis, R.W., and Bodkin, J.L., 2021, Sea otter foraging behavior, chap. of Ethology and behavioral ecology of sea otters and polar bears, p. 57-81, https://doi.org/10.1007/978-3-030-66796-2_4.","productDescription":"25 p.","startPage":"57","endPage":"81","ipdsId":"IP-122462","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":451640,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/978-3-030-66796-2_4","text":"Publisher Index Page"},{"id":391086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-07-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Randall W.","contributorId":131160,"corporation":false,"usgs":false,"family":"Davis","given":"Randall","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":825975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodkin, James L. 0000-0003-1641-4438 jbodkin@usgs.gov","orcid":"https://orcid.org/0000-0003-1641-4438","contributorId":748,"corporation":false,"usgs":true,"family":"Bodkin","given":"James","email":"jbodkin@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":825976,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221859,"text":"70221859 - 2021 - Evaluating corticosterone as a biomarker for amphibians exposed to increased salinity and ambient corticosterone","interactions":[],"lastModifiedDate":"2021-07-12T17:29:11.820999","indexId":"70221859","displayToPublicDate":"2021-07-03T12:25:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3919,"text":"Conservation Physiology","onlineIssn":"2051-1434","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating corticosterone as a biomarker for amphibians exposed to increased salinity and ambient corticosterone","docAbstract":"Physiological biomarkers are commonly used to assess the health of taxa exposed to natural and anthropogenic stressors. Glucocorticoid (GC) hormones are often used as indicators of physiological stress in wildlife because they affect growth, reproduction and survival. Increased salinity from human activities negatively influences amphibians and their corticosterone (CORT; the main amphibian GC) physiology; therefore, CORT could be a useful biomarker. We evaluated whether waterborne CORT could serve as a biomarker of salt stress for three free-living amphibian species that vary in their sensitivity to salinity: boreal chorus frogs (Pseudacris maculata), northern leopard frogs (Rana pipiens) and barred tiger salamanders (Ambystoma mavortium). Across a gradient of contamination from energy-related saline wastewaters, we tested the effects of salinity on baseline and stress-induced waterborne CORT of larvae. Stress-induced, but not baseline, CORT of leopard frogs increased with increasing salinity. Salinity was not associated with baseline or stress-induced CORT of chorus frogs or tiger salamanders. Associations between CORT and salinity were also not related to species-specific sensitivities to salinity. However, we detected background environmental CORT (ambient CORT) in all wetlands and spatial variation was high within and among wetlands. Higher ambient CORT was associated with lower waterborne CORT of larvae in wetlands. Therefore, ambient CORT likely confounded associations between waterborne CORT and salinity in our analysis and possibly influenced physiology of larvae. We hypothesize that larvae may passively take up CORT from their environment and downregulate endogenous CORT. Although effects of some hormones (e.g. oestrogen) and endocrine disruptors on aquatic organisms are well described, studies investigating the occurrence and effects of ambient CORT are limited. We provide suggestions to improve collection methods, reduce variability and avoid confounding effects of ambient CORT. By making changes to methodology, waterborne CORT could still be a promising, non-invasive conservation tool to evaluate effects of salinity on amphibians.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/conphys/coab049","usgsCitation":"Tornabene, B., Hossack, B., Crespi, E.J., and Breuner, C., 2021, Evaluating corticosterone as a biomarker for amphibians exposed to increased salinity and ambient corticosterone: Conservation Physiology, v. 9, no. 1, coab049, 15 p., https://doi.org/10.1093/conphys/coab049.","productDescription":"coab049, 15 p.","ipdsId":"IP-127959","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":451642,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coab049","text":"Publisher Index Page"},{"id":387129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Williston Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.205078125,\n 47.45780853075031\n ],\n [\n -101.162109375,\n 47.45780853075031\n ],\n [\n -101.162109375,\n 48.951366470947725\n ],\n [\n -105.205078125,\n 48.951366470947725\n ],\n [\n -105.205078125,\n 47.45780853075031\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-07-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Tornabene, Brian J.","contributorId":200041,"corporation":false,"usgs":false,"family":"Tornabene","given":"Brian J.","affiliations":[],"preferred":false,"id":819028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":819029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crespi, Erica J","contributorId":260876,"corporation":false,"usgs":false,"family":"Crespi","given":"Erica","email":"","middleInitial":"J","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":819030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Breuner, Creagh W","contributorId":241893,"corporation":false,"usgs":false,"family":"Breuner","given":"Creagh W","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":819031,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223170,"text":"70223170 - 2021 - The petrologic and degassing behavior of sulfur and other magmatic volatiles from the 2018 eruption of Kīlauea, Hawaiʻi: Melt concentrations, magma storage depths, and magma recycling","interactions":[],"lastModifiedDate":"2021-08-17T13:26:14.993263","indexId":"70223170","displayToPublicDate":"2021-07-03T08:23:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"The petrologic and degassing behavior of sulfur and other magmatic volatiles from the 2018 eruption of Kīlauea, Hawaiʻi: Melt concentrations, magma storage depths, and magma recycling","docAbstract":"Kīlauea Volcano’s 2018 lower East Rift Zone (LERZ) eruption produced exceptionally high lava effusion rates and record-setting SO2 emissions. The eruption involved a diverse range of magmas, including primitive basalts sourced from Kīlauea’s summit reservoirs. We analyzed LERZ matrix glasses, melt inclusions, and host minerals to identify melt volatile contents and magma storage depths. The LERZ glasses and melt inclusions span nearly the entire compositional range previously recognized at Kīlauea. Melt inclusions in Fo86-89 olivine from the main eruptive vent (fissure 8) underwent 70–170 °C cooling during transport in LERZ carrier melts, causing extensive post-entrapment crystallization and sulfide precipitation. Many of these melt inclusions have low sulfur (400–900 ppm) even after correction for sulfide formation. CO2 and H2O vapor saturation pressures indicate shallow melt inclusion trapping depths (1–5 km), consistent with formation within Kīlauea’s Halemaʻumaʻu and South Caldera reservoirs. Many of these inclusions also have degassed δ34S values (− 1.5 to − 0.5‰). Collectively, these results indicate that some primitive melts experienced near-surface degassing before being trapped into melt inclusions. We propose that decades-to-centuries of repeated lava lake activity and lava drain-back during eruptions (e.g., 1959 Kīlauea Iki) recycled substantial volumes of degassed magma into Kīlauea’s shallow reservoir system. Degassing and magma recycling from the 2008–2018 Halemaʻumaʻu lava lake likely reduced the volatile contents of LERZ fissure 8 magmas, resulting in lower fountain heights compared to many prior Kīlauea eruptions. The eruption’s extreme SO2 emissions were due to high lava effusion rates rather than particularly volatile-rich melts.
Mars exhibits diverse surface changes at all latitudes and all seasons. Active processes include impact cratering, aeolian sand and dust transport, a variety of slope processes, changes in polar ices, and diverse effects of seasonal CO2 frost. The extent of surface change has been surprising and indicates that the present climate is capable of reshaping the surface. Activity has important implications for the Amazonian history of Mars: understanding processes is a necessary step before we can understand their implications and variations over time.
The relentless role of invasive species in the extinction of native biota requires predictions of ecosystem vulnerability to inform proactive management strategies. The worldwide invasion and range expansion of predatory northern pike (Esox lucius) has been linked to the decline of native fishes and tools are needed to predict the vulnerability of habitats to invasion over broad geographic scales. To address this need, we coupled an intrinsic potential habitat modelling approach with a Bayesian network to evaluate the vulnerability of five culturally and economically vital species of Pacific salmon (Oncorhynchus spp.) to invasion by northern pike. This study was conducted along 22,875 stream km in the Southcentral region of Alaska, USA. Pink salmon (O. gorbuscha) were the most vulnerable species, with 15.2% (2,458 km) of their calculated extent identified as “highly” vulnerable, followed closely by chum salmon (O. keta, 14.8%; 2,557 km) and coho salmon (O. kisutch, 14.7%; 2,536 km). Moreover, all five Pacific salmon species were highly vulnerable in 1,001 stream km of shared habitat. This simple to implement, adaptable, and cost-effective framework will allow prioritizing habitats for early detection and monitoring of invading northern pike.
The strong increase of seismicity rates in the contiguous USA over the last 10 years is linked to the injection of huge amounts of wastewater from oil and gas production in unconventional hydrocarbon reservoirs. We calculated 549 moment tensors of induced earthquakes (MW ≤ 4.9) in southern Kansas to study their source mechanisms and their relation to injection activity. Seventeen percent of the events analyzed contained significant volumetric (ISO%) components, and these events mostly occurred near the two largest local earthquakes during the 4 months of largest active wastewater disposal. Mapping the local stress field, we determined that most of the region lies within a transtensional stress regime, with a maximum horizontal stress σHmax trending N75°E. In the epicentral area of the MW 4.9 Milan earthquake, the σHmax trend is rotated to about S80°E. Locally, two areas display a change in the stress field orientation with depth, from transtensional above 5.5 km depth to strike slip deeper in the basement. Relating the resolved fault geometries to the obtained local stress field orientation, we find that most of the activated fault planes were optimally oriented to the current stress field and thus small stress perturbations caused by the water injection could lead to failure.
Tracing produced water origins from wells hydraulically fractured with freshwater-based fluids is sometimes predicated on assumptions that (1) each geological formation contains compositionally unique brine and (2) produced water from recently hydraulically fractured wells resembles fresher meteoric water more so than produced water from older wells. These assumptions are not valid in Williston Basin oil wells sampled in this study. Although distinct average 228Ra/226Ra ratios were found in water produced from the Bakken and Three Forks Formations, average δ2H, δ18O, specific gravity, and conductivity were similar but exhibited significant variability across five oil fields within each formation. Furthermore, initial produced water (“flowback”) was operationally defined based on the presence of glycol ether compounds and water from wells that had produced <56% of the amount of fluids injected and sampled within 160 days of fracturing. Flowback unexpectedly exhibited higher temperature, specific gravity, conductivity, δ2H, and δ18O, but lower oxidation–reduction potential and δ11B, relative to the wells thought to be producing formation brines (from wells with a produced-to-injected water ratio [PIWR] > 0.84 and sampled more than 316 days after fracturing). As such, establishing an overall geochemical and isotopic signature of produced water compositions based solely on chemical similarity to meteoric water and formation without the consideration of well treatments, well completion depth, or lateral location across the basin could be misleading if these signatures are assumed to be applicable across the entire basin. These findings have implications for using produced water compositions to understand the interbasin fluid flow and trace sources of hydraulic fracturing fluids.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.0c06789","usgsCitation":"Gallegos, T., Doolan, C.A., Caldwell, R.R., Engle, M.A., Varonka, M., Birdwell, J.E., Jolly, G.D., Coplen, T.B., and Oliver, T.A., 2021, Insights on geochemical, isotopic, and volumetric compositions of produced water from hydraulically fractured Williston Basin oil wells: Environmental Science and Technology, v. 55, no. 14, p. 10025-10034, https://doi.org/10.1021/acs.est.0c06789.","productDescription":"10 p.","startPage":"10025","endPage":"10034","ipdsId":"IP-118139","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":488266,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.0c06789","text":"Publisher Index Page"},{"id":386984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.18310546875,\n 47.30903424774781\n ],\n [\n -102.667236328125,\n 47.30903424774781\n ],\n [\n -102.667236328125,\n 48.31242790407178\n ],\n [\n -105.18310546875,\n 48.31242790407178\n ],\n [\n -105.18310546875,\n 47.30903424774781\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"55","issue":"14","noUsgsAuthors":false,"publicationDate":"2021-07-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gallegos, Tanya J. 0000-0003-3350-6473","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":206859,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":818717,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doolan, Colin A. 0000-0002-7595-7566 cdoolan@usgs.gov","orcid":"https://orcid.org/0000-0002-7595-7566","contributorId":3046,"corporation":false,"usgs":true,"family":"Doolan","given":"Colin","email":"cdoolan@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":818718,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Rodney R. 0000-0002-2588-715X caldwell@usgs.gov","orcid":"https://orcid.org/0000-0002-2588-715X","contributorId":2577,"corporation":false,"usgs":true,"family":"Caldwell","given":"Rodney","email":"caldwell@usgs.gov","middleInitial":"R.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":818719,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engle, Mark A 0000-0001-5258-7374","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":228981,"corporation":false,"usgs":false,"family":"Engle","given":"Mark","email":"","middleInitial":"A","affiliations":[{"id":41535,"text":"The University of Texas at El Paso, Department of Geological Sciences, El Paso, TX 79968","active":true,"usgs":false}],"preferred":false,"id":818720,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Varonka, Matthew S. 0000-0003-3620-5262","orcid":"https://orcid.org/0000-0003-3620-5262","contributorId":203231,"corporation":false,"usgs":true,"family":"Varonka","given":"Matthew S.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":818721,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":818748,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jolly, Glenn D. 0000-0001-5876-5258 gdjolly@usgs.gov","orcid":"https://orcid.org/0000-0001-5876-5258","contributorId":260780,"corporation":false,"usgs":true,"family":"Jolly","given":"Glenn","email":"gdjolly@usgs.gov","middleInitial":"D.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":818722,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":818723,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Oliver, Thomas A. 0000-0001-5994-2391 taoliver@usgs.gov","orcid":"https://orcid.org/0000-0001-5994-2391","contributorId":260781,"corporation":false,"usgs":true,"family":"Oliver","given":"Thomas","email":"taoliver@usgs.gov","middleInitial":"A.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":818724,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70222587,"text":"70222587 - 2021 - Elk monitoring in Mount Rainier and Olympic National Parks: 2008-2017 synthesis report","interactions":[],"lastModifiedDate":"2021-08-06T21:56:24.549864","indexId":"70222587","displayToPublicDate":"2021-07-01T16:45:02","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/NCCN/NRR-2021/2284","title":"Elk monitoring in Mount Rainier and Olympic National Parks: 2008-2017 synthesis report","docAbstract":"In 2008, the U.S. Geological Survey (USGS) began collaborating with the National Park Service (NPS)-North Coast and Cascades Network (NCCN), the Muckleshoot Indian Tribe (MIT), Puyallup Tribe of Indians (PTOI), and Washington Department of Fish and Wildlife (WDFW) to develop a standard survey protocol for monitoring long-term changes in the abundance, distribution, and population composition of elk on key summer ranges within Mount Rainier National Park (MORA) and Olympic National Park (OLYM). In MORA, surveys were conducted in two trend count areas (TCAs) that correspond with primary summer ranges used by the North Rainier Herd, which winters outside the park to the North, and the South Rainier Herd, which winters outside the park primarily to the South. In OLYM, we defined five TCAs including an Olympic Core TCA (hereafter, Core TCA) that encompasses summer ranges on the flanks of Mount Olympus, and four TCAs that encompass other primary summer ranges throughout the park. \nThe standard protocol allows for estimating aerial survey detection biases and adjusting raw survey counts to account for elk that were likely present but not seen during surveys. Previously, we developed a suite of aerial-bias-correction models for use in estimating aerial detection biases and adjusting raw counts of elk in MORA based on sighting conditions related to elk group size, vegetation density, lighting conditions, elk movement, as well as combinations of these and other factors. The models were based on independent sighting records of elk groups by front-seat and back-seat observer pairs in a helicopter, including detection records of some radio-collared elk groups. \nHere, we analyze results of the first 10 years of elk monitoring in MORA (2008-2017) and 8 years in OLYM (2008-2015). In a previous report covering surveys conducted from 2008-2011, data were not sufficient to model detection biases of aerial surveys conducted in OLYM; hence, analyses of elk population trends were based on counts adjusted for detection biases in MORA, whereas trends in OLYM were based on raw, unadjusted counts (Griffin et al. 2013, Jenkins et al. 2015). \nOur objectives for the current summary were to:\n(1) incorporate additional data to update aerial-bias-correction models previously developed for use in MORA to include corrections for aerial detection bias in both MORA and OLYM,\n(2) examine trends in elk abundance, distribution, and population composition estimates for subalpine summer ranges within MORA and OLYM, and\n(3) estimate effects of seasonal variation and weather on elk abundance and population composition estimates for subalpine summer ranges in both parks.","language":"English","publisher":"National Park Service","usgsCitation":"Jenkins, K., Lubow, B., Happe, P.J., Braun, K., Boetsch, J., Baccus, W., Chestnut, T., Vales, D.J., Moeller, B.J., Tirhi, M., Holman, E., and Griffin, P.C., 2021, Elk monitoring in Mount Rainier and Olympic National Parks: 2008-2017 synthesis report: Natural Resource Report NPS/NCCN/NRR-2021/2284, xiii, 77 p.","productDescription":"xiii, 77 p.","ipdsId":"IP-123180","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":387745,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":387744,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://irma.nps.gov/DataStore/DownloadFile/662550"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Ranier and Olympic National Parks","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.6680908203125,\n 46.592843997427416\n ],\n [\n -121.5582275390625,\n 46.69843486113957\n ],\n [\n -121.44287109374999,\n 46.694667307773116\n ],\n [\n -121.39892578125,\n 46.751153008636884\n ],\n [\n -121.53625488281249,\n 47.010225655683485\n ],\n [\n -121.9207763671875,\n 47.010225655683485\n ],\n [\n -121.8988037109375,\n 47.08508535995386\n ],\n [\n -122.16247558593751,\n 47.07386310181414\n ],\n [\n -122.31628417968749,\n 46.87145819560722\n ],\n [\n -122.03613281249999,\n 46.78501604269254\n ],\n [\n -121.9647216796875,\n 46.751153008636884\n ],\n [\n -121.9647216796875,\n 46.57774276255591\n ],\n [\n -121.6680908203125,\n 46.592843997427416\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.28857421875,\n 47.31648293428332\n ],\n [\n -122.904052734375,\n 47.70976154266637\n ],\n [\n -122.9754638671875,\n 47.989921667414194\n ],\n [\n -123.8818359375,\n 48.122101028190805\n ],\n [\n -124.32678222656249,\n 48.158757304569235\n ],\n [\n -124.4091796875,\n 47.912660308427654\n ],\n [\n -124.20043945312499,\n 47.76886840424207\n ],\n [\n -124.398193359375,\n 47.70606513569572\n ],\n [\n -124.112548828125,\n 47.506069781910846\n ],\n [\n -123.8323974609375,\n 47.47266286861342\n ],\n [\n -123.99719238281249,\n 47.342545069660225\n ],\n [\n -123.28857421875,\n 47.31648293428332\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jenkins, Kurt 0000-0003-1415-6607","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":221472,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":820652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lubow, B. C.","contributorId":64603,"corporation":false,"usgs":false,"family":"Lubow","given":"B. C.","affiliations":[],"preferred":false,"id":820667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Happe, P. J.","contributorId":219686,"corporation":false,"usgs":false,"family":"Happe","given":"P.","email":"","middleInitial":"J.","affiliations":[{"id":16133,"text":"National Park Service, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":820668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Braun, K.","contributorId":261796,"corporation":false,"usgs":false,"family":"Braun","given":"K.","email":"","affiliations":[],"preferred":false,"id":820669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boetsch, J.","contributorId":213934,"corporation":false,"usgs":false,"family":"Boetsch","given":"J.","email":"","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":820670,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baccus, W.","contributorId":261797,"corporation":false,"usgs":false,"family":"Baccus","given":"W.","affiliations":[],"preferred":false,"id":820671,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chestnut, T.","contributorId":261798,"corporation":false,"usgs":false,"family":"Chestnut","given":"T.","email":"","affiliations":[],"preferred":false,"id":820672,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vales, D. J.","contributorId":261799,"corporation":false,"usgs":false,"family":"Vales","given":"D.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":820673,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Moeller, B. J.","contributorId":261800,"corporation":false,"usgs":false,"family":"Moeller","given":"B.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":820674,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tirhi, M.","contributorId":261801,"corporation":false,"usgs":false,"family":"Tirhi","given":"M.","affiliations":[],"preferred":false,"id":820675,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Holman, E.","contributorId":261802,"corporation":false,"usgs":false,"family":"Holman","given":"E.","email":"","affiliations":[],"preferred":false,"id":820676,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Griffin, P. C.","contributorId":69499,"corporation":false,"usgs":false,"family":"Griffin","given":"P.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":820677,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70221862,"text":"70221862 - 2021 - What is the effect of poaching activity on wildlife species?","interactions":[],"lastModifiedDate":"2021-10-06T15:13:10.834057","indexId":"70221862","displayToPublicDate":"2021-07-01T12:04:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"What is the effect of poaching activity on wildlife species?","docAbstract":"Poaching is a pervasive threat to wildlife, yet quantifying the direct effect of poaching on wildlife is rarely possible because both wildlife and threat data are infrequently collected concurrently. In this study, we used poaching data collected through the Management Information System (MIST) and wildlife camera trap data collected by the Tropical Ecology Assessment and Monitoring (TEAM) network from 2014 to 2017 in Volcanoes National Park, Rwanda. We implemented co-occurrence multi-season occupancy models that accounted for imperfect detection to investigate the effect of poaching on initial occupancy, colonization, and extinction of 5 mammal species. Specifically, we focused on 2 species of conservation concern (mountain gorilla (Gorilla beringei beringei) and golden money (Cercopithecus mitis kandti)), and 3 species targeted by poachers (black-fronted duiker (Cephalophus nigrifrons), bushbuck (Tragelaphus scriptus), and African buffalo (Syncerus caffer)). We found that the probability of local extinction was highest in sites with poaching activity for golden monkey and bushbuck. In addition, the probability of initial occupancy for golden monkey was highest in sites without poaching activity. We only found weak evidence of effects of poaching on parameters governing the occupancy dynamics of the other species. All species showed evidence of poaching presence affecting the probability of detection of the wildlife species. This is the first study to our knowledge to combine direct threat observations from ranger-based monitoring data with camera trap wildlife observations to quantify the effect of poaching on wildlife. Given the widespread collection of ranger-based monitoring and camera trap data, our approach is broadly applicable to numerous protected areas and has the potential to significantly improve conservation management. Specifically, the relationship between poaching activity and wildlife population dynamics (this paper) can be combined with information on the relationship between ranger patrols and poaching activity (Moore et al. 2017) to develop models useful for making wise decisions about ranger patrol deployment.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2397","usgsCitation":"Moore, J.F., Uzabaho, E., Musana, A., Uwingell, P., Hines, J.E., and Nichols, J.D., 2021, What is the effect of poaching activity on wildlife species?: Ecological Applications, v. 31, no. 7, e02397, 12 p., https://doi.org/10.1002/eap.2397.","productDescription":"e02397, 12 p.","ipdsId":"IP-118381","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":387128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Rwanda","otherGeospatial":"Volcanoes National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 29.702911376953125,\n -1.3587440869100178\n ],\n [\n 29.663772583007812,\n -1.3882613601346867\n ],\n [\n 29.63081359863281,\n -1.3951257897508238\n ],\n [\n 29.59304809570312,\n -1.3882613601346867\n ],\n [\n 29.561462402343746,\n -1.384829137846475\n ],\n [\n 29.50721740722656,\n -1.4218968729661605\n ],\n [\n 29.49073791503906,\n -1.4383712317629698\n ],\n [\n 29.4927978515625,\n -1.4630825465188169\n ],\n [\n 29.480438232421875,\n -1.4692603328543323\n ],\n [\n 29.485244750976562,\n -1.4788701887242113\n ],\n [\n 29.461898803710938,\n -1.491912069367617\n ],\n [\n 29.439926147460934,\n -1.5269188384985064\n ],\n [\n 29.39804077148437,\n -1.5324100450044358\n ],\n [\n 29.442672729492188,\n -1.568788930117857\n ],\n [\n 29.481124877929688,\n -1.5660433757691457\n ],\n [\n 29.514770507812496,\n -1.5358420419244077\n ],\n [\n 29.519577026367188,\n -1.4891664166873633\n ],\n [\n 29.50996398925781,\n -1.4493540716333067\n ],\n [\n 29.540176391601562,\n -1.422583306939631\n ],\n [\n 29.54635620117188,\n -1.4184647000387454\n ],\n [\n 29.560775756835934,\n -1.408854588797322\n ],\n [\n 29.58549499511719,\n -1.4177782648419572\n ],\n [\n 29.641799926757812,\n -1.4232697407088846\n ],\n [\n 29.671325683593754,\n -1.412973212770802\n ],\n [\n 29.69467163085938,\n -1.4157189580307432\n ],\n [\n 29.70497131347656,\n -1.3875749160752702\n ],\n [\n 29.702911376953125,\n -1.3587440869100178\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Jennifer F.","contributorId":189122,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":819048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uzabaho, Eustrate","contributorId":260880,"corporation":false,"usgs":false,"family":"Uzabaho","given":"Eustrate","email":"","affiliations":[{"id":52699,"text":"Intl. Gorilla Conservation Programme, Rwanda","active":true,"usgs":false}],"preferred":false,"id":819049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musana, Abel","contributorId":260881,"corporation":false,"usgs":false,"family":"Musana","given":"Abel","email":"","affiliations":[{"id":52700,"text":"Rwanda Development Board, Rwanda","active":true,"usgs":false}],"preferred":false,"id":819050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Uwingell, Prosper","contributorId":260882,"corporation":false,"usgs":false,"family":"Uwingell","given":"Prosper","email":"","affiliations":[{"id":52700,"text":"Rwanda Development Board, Rwanda","active":true,"usgs":false}],"preferred":false,"id":819051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":200533,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":819053,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224605,"text":"70224605 - 2021 - Wetlands","interactions":[],"lastModifiedDate":"2021-09-29T17:05:36.934197","indexId":"70224605","displayToPublicDate":"2021-07-01T11:54:58","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Wetlands","docAbstract":"During the last decades, soil organic carbon (SOC) attracted the attention of a much wider array of specialists beyond agriculture and soil science, as it was proven to be one of the most crucial components of the earth’s climate system, which has a great potential to be managed by humans. Soils as a carbon pool are one of the key factors in several Sustainable Development Goals, in particular Goal 15, “Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification and halt and reverse land degradation and halt biodiversity loss” with the SOC stock being explicitly cited in Indicator 15.3.1.
This technical manual is the first attempt to gather, in a standardized format, the existing data on the impacts of the main soil management practices on SOC content in a wide array of environments, including the advantages, drawbacks, and constraints. This manual presents different sustainable soil management (SSM) practices at different scales and in different contexts, supported by case studies that have been shown with quantitative data to have a positive effect on SOC stocks and successful experiences of SOC sequestration in practical field applications
Volume 2 includes a description of hot spots of SOC stocks. This manual defines hot spots of SOC as areas that represent a proportionally little of the global land surface but on which SOC storage is highly effective; bright spots as large land areas with low SOC stocks per km2 that represent a potential for further carbon sequestration.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Recarbonizing global soils – A technical manual of recommended management practices","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Food and Agriculture Organization of the United Nations","usgsCitation":"Tangen, B., and Bansal, S., 2021, Wetlands, 19 p.","productDescription":"19 p.","startPage":"36","endPage":"54","ipdsId":"IP-121703","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":389967,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fao.org/documents/card/en/c/cb6378en/"},{"id":389968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tangen, Brian 0000-0001-5157-9882 btangen@usgs.gov","orcid":"https://orcid.org/0000-0001-5157-9882","contributorId":167277,"corporation":false,"usgs":true,"family":"Tangen","given":"Brian","email":"btangen@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":824244,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70237360,"text":"70237360 - 2021 - Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning","interactions":[],"lastModifiedDate":"2022-10-11T16:24:49.683141","indexId":"70237360","displayToPublicDate":"2021-07-01T11:21:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning","docAbstract":"Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.","language":"English","publisher":"Wiley","doi":"10.1029/2021WR029579","usgsCitation":"Willard, J., Read, J., Appling, A.P., Oliver, S.K., Jia, X., and Kumar, V., 2021, Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning: Water Resources Research, v. 57, no. 7, e2021WR029579, 20 p., https://doi.org/10.1029/2021WR029579.","productDescription":"e2021WR029579, 20 p.","ipdsId":"IP-119147","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":451661,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021wr029579","text":"Publisher Index Page"},{"id":436285,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9I00WFR","text":"USGS data release","linkHelpText":"Data release: Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning (Provisional Data Release)"},{"id":408165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"57","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Willard, Jared","contributorId":237808,"corporation":false,"usgs":false,"family":"Willard","given":"Jared","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Read, Jordan 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":221385,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":854262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":854263,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":854264,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumar, Vipin","contributorId":237812,"corporation":false,"usgs":false,"family":"Kumar","given":"Vipin","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":854266,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248236,"text":"70248236 - 2021 - Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure","interactions":[],"lastModifiedDate":"2023-09-05T15:18:59.650382","indexId":"70248236","displayToPublicDate":"2021-07-01T10:09:17","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure","title":"Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure","docAbstract":"The Queen Charlotte-Fairweather Fault (QC-FF) system off the coast of British Columbia and southeast Alaska is a highly active dextral strike-slip plate boundary that accommodates ∼50 mm/yr of relative motion between the Pacific and North America plates. Nine MW ≥ 6.7 earthquakes have occurred along the QC-FF system since 1910, including a MS(G-R)8.1 event in 1949. Two recent earthquakes, the October 28, 2012 Haida Gwaii (MW7.8) and January 5, 2013 Craig, Alaska (MW7.5) events, produced postseismic transient deformation that was recorded in the motions of 25 nearby continuous Global Positioning System (cGPS) stations. Here, we use 5+ yr of cGPS measurements to characterize the underlying mechanisms of postseismic deformation and to constrain the viscosity structure of the upper mantle surrounding the QC-FF. We construct forward models of viscoelastic deformation driven by coseismic stress changes from these two earthquakes and explore a large set of laterally heterogeneous viscosity structures that incorporate a relatively weak back-arc domain; we then evaluate each model based on its fit to the postseismic signals in our cGPS data. In determining best-fit model structures, we additionally incorporate the effects of afterslip following the 2012 event. Our results indicate the occurrence of a combination of temporally decaying afterslip and vigorous viscoelastic relaxation of the mantle asthenosphere. In addition, our best-fit viscosity structure (transient viscosity of 1.4–2.0 × 1018 Pa s; steady-state viscosity of 1019 Pa s) is consistent with the range of upper mantle viscosities determined in previous studies of glacial isostatic rebound and postseismic deformation.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JB021891","usgsCitation":"Guns, K.A., Pollitz, F., Lay, T., and Yue, H., 2021, Exploring GPS observations of postseismic deformation following the 2012 MW7.8 Haida Gwaii and 2013 MW7.5 Craig, Alaska Earthquakes: Implications for viscoelastic Earth structure: Journal of Geophysical Research B: Solid Earth, v. 126, no. 7, e2021JB021891, 20 p., https://doi.org/10.1029/2021JB021891.","productDescription":"e2021JB021891, 20 p.","ipdsId":"IP-127502","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":420483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia","city":"Craig","otherGeospatial":"Haida Gwaii Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -134.04582537099918,\n 55.778120902444044\n ],\n [\n -134.04582537099918,\n 55.08543087867997\n ],\n [\n -132.168788545775,\n 55.08543087867997\n ],\n [\n -132.168788545775,\n 55.778120902444044\n ],\n [\n -134.04582537099918,\n 55.778120902444044\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -132.70446739512911,\n 53.158925565323756\n ],\n [\n -132.34949768033022,\n 52.76369069159804\n ],\n [\n -131.7793948050469,\n 52.469804491078975\n ],\n [\n -131.66107156678072,\n 52.29252484773727\n ],\n [\n -130.97264545323122,\n 51.88274035718925\n ],\n [\n -130.75751229274715,\n 51.94245878634544\n ],\n [\n -131.7471248309743,\n 53.33271351252088\n ],\n [\n -132.30647104823325,\n 53.16537474581318\n ],\n [\n -132.70446739512911,\n 53.158925565323756\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"126","issue":"7","noUsgsAuthors":false,"publicationDate":"2021-07-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Guns, Katherine A.","contributorId":329359,"corporation":false,"usgs":false,"family":"Guns","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":16619,"text":"UCSD","active":true,"usgs":false}],"preferred":false,"id":882060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":882061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lay, Thorne","contributorId":328838,"corporation":false,"usgs":false,"family":"Lay","given":"Thorne","affiliations":[{"id":6948,"text":"UC Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":882062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yue, Han","contributorId":329362,"corporation":false,"usgs":false,"family":"Yue","given":"Han","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":882063,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}