{"pageNumber":"518","pageRowStart":"12925","pageSize":"25","recordCount":165384,"records":[{"id":70223858,"text":"70223858 - 2021 - Implications of aggregating and smoothing daily production data on estimates of the transition time between flow regimes in horizontal hydraulically fractured Bakken oil wells","interactions":[],"lastModifiedDate":"2021-09-10T16:10:38.075312","indexId":"70223858","displayToPublicDate":"2021-01-29T10:04:40","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2701,"text":"Mathematical Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Implications of aggregating and smoothing daily production data on estimates of the transition time between flow regimes in horizontal hydraulically fractured Bakken oil wells","docAbstract":"<p><span>The level to which data are aggregated or smoothed can impact analytical and predictive modeling results. This paper discusses findings regarding such impacts on estimating change points in production flow regimes of horizontal hydraulically fractured shale oil wells producing from the middle member of the Bakken Formation. Change points that signal transitions in flow regimes are important because they subsequently affect estimates of ultimate recovery from wells producing from shale plays. Extending our earlier work, we employ two different statistical approaches, Bacon–Watts Bayesian regression and nonlinear constrained least squares regression, and a designed computational experiment to estimate the time of transition from the transient to the boundary-dominated flow regime for 14 different wells using daily production data rather than aggregated monthly data, as previously considered. The daily data were also smoothed to reduce noise. Computational experiments suggest that both statistical approaches can lead to plausible estimates of the transition point under different data aggregation or smoothing regimes, but that daily data are likely too granular to produce credible estimates. Although the expected value of transition points using smoothed daily data and monthly disaggregated data are generally comparable, the confidence intervals bounding the estimates based on smoothed daily data are generally wider. Our results not only inform the operational practices of oil producers engaged in economic evaluation of their shale resources and additional play development activities, but also the activities of petroleum research groups, government agencies, and financial organizations seeking to improve the trustworthiness of resource projections.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s11004-020-09909-7","usgsCitation":"Coburn, T.C., and Attanasi, E., 2021, Implications of aggregating and smoothing daily production data on estimates of the transition time between flow regimes in horizontal hydraulically fractured Bakken oil wells: Mathematical Geosciences, v. 53, p. 1261-1292, https://doi.org/10.1007/s11004-020-09909-7.","productDescription":"32 p.","startPage":"1261","endPage":"1292","ipdsId":"IP-114030","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":389064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","noUsgsAuthors":false,"publicationDate":"2021-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Coburn, T. C.","contributorId":219832,"corporation":false,"usgs":false,"family":"Coburn","given":"T.","email":"","middleInitial":"C.","affiliations":[{"id":40076,"text":"1 University of Tulsa, School of Energy Economics, Policy and Commerce, USA,","active":true,"usgs":false}],"preferred":false,"id":823008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":823009,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70229002,"text":"70229002 - 2021 - Ensemble species distribution model identifies survey opportunities for at-risk bearded beaksedge (Rhynchospora crinipes) in the southeastern United States","interactions":[],"lastModifiedDate":"2022-02-25T15:39:57.320263","indexId":"70229002","displayToPublicDate":"2021-01-29T09:33:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2821,"text":"Natural Areas Journal","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ensemble species distribution model identifies survey opportunities for at-risk bearded beaksedge (<i>Rhynchospora crinipes</i>) in the southeastern United States","title":"Ensemble species distribution model identifies survey opportunities for at-risk bearded beaksedge (Rhynchospora crinipes) in the southeastern United States","docAbstract":"<p><span>Locating additional occurrences of at-risk species can inform assessments of their status and conservation needs (including potential legal protections). The perennial bearded beaksedge (</span><i>Rhynchospora crinipes</i><span>) ranges from Mississippi to North Carolina, but known occurrences are limited. Because of the species' apparent rarity, a model to identify areas with suitable habitat conditions for the species will allow conservationists to effectively prioritize and allocate scarce surveying resources. We used known occurrence records, a suite of environmental datasets, and four species distribution modeling techniques (generalized additive, GAM; maximum entropy, MaxEnt; generalized boosted, GBM; and weighted ensemble) to generate maps to inform surveys for&nbsp;</span><i>R. crinipes</i><span>. The ensemble approach improved predictive performance (AUC-PR = 0.95) compared to other techniques (individual model AUC-PR ranged from 0.7 to 0.8). We also obtained quantitative insights on the species' habitat relationships, including the likelihood of&nbsp;</span><i>R. crinipes</i><span>'s presence near Atlantic white cedar (</span><i>Chamaecyparis thyoides</i><span>) habitat and floodplains, which is consistent with prior field observations. The ensemble model indicated that 3.6% of the study area could be suitable habitat, but only 0.38% had high suitability. Small stream riparian habitats and Atlantic swamp forests in Alabama, Florida, and Georgia had the highest proportion of suitable areas. Prioritizing surveys in areas with model-indicated high habitat suitability is expected to reveal additional&nbsp;</span><i>R. crinipes</i><span>&nbsp;occurrences. We suggest surveying efforts for other at-risk species may benefit from using an ensemble modeling approach to identify and prioritize survey areas and improve ecological knowledge of these species.</span></p>","language":"English","publisher":"The Natural Areas Association","doi":"10.3375/043.041.0108","usgsCitation":"Ramirez-Reyes, C., Street, G., Vilella, F., Jones-Farrand, T., Wiggers, M.S., and Evans, K., 2021, Ensemble species distribution model identifies survey opportunities for at-risk bearded beaksedge (Rhynchospora crinipes) in the southeastern United States: Natural Areas Journal, v. 41, no. 1, p. 55-63, https://doi.org/10.3375/043.041.0108.","productDescription":"9 p.","startPage":"55","endPage":"63","ipdsId":"IP-120003","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":396486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, Mississippi, North Carolina, South Carolina","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.978515625,\n              33.54139466898275\n            ],\n            [\n              -89.9560546875,\n              32.69486597787505\n            ],\n            [\n              -91.14257812499999,\n              31.50362930577303\n            ],\n            [\n              -89.47265625,\n              30.259067203213018\n            ],\n            [\n              -87.71484375,\n              29.99300228455108\n            ],\n            [\n              -86.4404296875,\n              30.221101852485987\n            ],\n            [\n              -85.0341796875,\n              29.611670115197377\n            ],\n            [\n              -83.7158203125,\n              29.6880527498568\n            ],\n            [\n              -82.8369140625,\n              28.8831596093235\n            ],\n            [\n              -80.2880859375,\n              27.449790329784214\n            ],\n            [\n              -80.6396484375,\n              29.305561325527698\n            ],\n            [\n              -81.0791015625,\n              31.052933985705163\n            ],\n            [\n              -75.1904296875,\n              35.71083783530009\n            ],\n            [\n              -78.44238281249999,\n              36.491973470593685\n            ],\n            [\n              -82.8369140625,\n              34.70549341022544\n            ],\n            [\n              -84.990234375,\n              33.32134852669881\n            ],\n            [\n              -87.978515625,\n              33.54139466898275\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"41","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ramirez-Reyes, C.","contributorId":275333,"corporation":false,"usgs":false,"family":"Ramirez-Reyes","given":"C.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":836101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Street, G.","contributorId":280202,"corporation":false,"usgs":false,"family":"Street","given":"G.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":836102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":836103,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones-Farrand, T.","contributorId":280203,"corporation":false,"usgs":false,"family":"Jones-Farrand","given":"T.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":836104,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiggers, M. S.","contributorId":280204,"corporation":false,"usgs":false,"family":"Wiggers","given":"M.","email":"","middleInitial":"S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":836105,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evans, K. O.","contributorId":280205,"corporation":false,"usgs":false,"family":"Evans","given":"K. O.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":836106,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70218787,"text":"70218787 - 2021 - American Black Bear (Ursus americanus)","interactions":[],"lastModifiedDate":"2021-03-12T14:47:21.399307","indexId":"70218787","displayToPublicDate":"2021-01-29T08:46:56","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"American Black Bear (Ursus americanus)","docAbstract":"<p>American black bears (Ursus americanus) are endemic to North America, having speciated from other ursids some 1.2 to 1.8 million years ago (Kurtn &amp; Anderson 1994). During that time, black bears came to occupy nearly all of the forested areas of the North American continent. Historically, black bears were one of the most important mammals to indigenous peoples of North America by providing food, fat, hides, and tools (Raybourne 1987). Bears also played important roles in indigenous culture as symbols of strength, hard work, and love (see Rockwell 1991). In the 18th and 19th centuries in the U.S., Canada, and Mexico, European settlers with firearms reduced black bear numbers (Williams 1930), but the axe and plow had equally negative effects on bear populations as forests gave way to agriculture and livestock. Black bears also faced intense pressure from unregulated market hunting, poaching, and predator control programs. Black bears disappeared from large portions of their North American range, being relegated to swamps, thickets, rugged mountains, and other areas deemed too inaccessible, unsuitable, or undesirable to be occupied by humans (Pelton &amp; van Manen 1994). In the early 20th century, Canadian and U.S. governments established national parks, forests, and refuges, and state and provincial legislatures created wildlife management agencies and enacted regulations to manage wildlife populations. By the late 20th century, the combination of public land infrastructure, habitat improvements, harvest regulations, law enforcement, and information-education programs resulted in significant increases in black bear numbers and range expansions in the U.S. and Canada (Pelton &amp; van Manen 1994), aided in no small part by the remarkable adaptability of this animal (Pelton 2003; Scheick &amp; McCown 2014). Today, the American black bear is one of the most iconic, abundant, and economically important bear species in the world. Unfortunately, black bear populations in Mexico have not recovered similarly to those in the U.S and Canada, and the status of the species there is uncertain.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bears of the World: Ecology, Conservation and Management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge University Press","usgsCitation":"Clark, J.D., Beckmann, J.P., Boyce, M.S., Leopold, B.D., and Pelton, M.R., 2021, American Black Bear (Ursus americanus), chap. <i>of</i> Bears of the World: Ecology, Conservation and Management, p. 122-138.","productDescription":"17 p.","startPage":"122","endPage":"138","ipdsId":"IP-107381","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":384355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":811856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beckmann, Jon P.","contributorId":210843,"corporation":false,"usgs":false,"family":"Beckmann","given":"Jon","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":811857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyce, Mark S.","contributorId":113205,"corporation":false,"usgs":false,"family":"Boyce","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":12980,"text":"Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":811858,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leopold, Bruce D","contributorId":255137,"corporation":false,"usgs":false,"family":"Leopold","given":"Bruce","email":"","middleInitial":"D","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":811859,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pelton, Michael R.","contributorId":168689,"corporation":false,"usgs":false,"family":"Pelton","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":7006,"text":"Department of Forestry, Wildlife and Fisheries, University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":811860,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223825,"text":"70223825 - 2021 - Multiple feedbacks due to biotic interactions across trophic levels can lead to persisten novel conditions that hinder restoration","interactions":[],"lastModifiedDate":"2021-09-09T13:00:52.526436","indexId":"70223825","displayToPublicDate":"2021-01-29T08:00:06","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"23","title":"Multiple feedbacks due to biotic interactions across trophic levels can lead to persisten novel conditions that hinder restoration","docAbstract":"Unlike traditional successional theory, Alternate Stable Equilibrium (ASE) theory posits that more than one community state is possible in a single environment, depending on the order that species arrive. ASE theory is often invoked in management situations where initial stressors have been removed, but native-dominated communities are not returning to degraded areas. Fundamental to this theory is the assumption that equilibria are maintained by positive feedbacks between colonizers and their environment. While ASE has been relatively well studied in aquatic ecosystems, more complex terrestrial systems offer multiple challenges, including species interactions across trophic levels that can lead to multiple feedbacks. Here, we discuss ASE theory as it applies to terrestrial, invaded ecosystems, and detail a case study from Hawaii that exemplifies how species interactions can favour the persistence of invaders, and how an understanding of interactions and feedbacks can be used to guide management. Our system includes intact native-dominated mesic forest and areas cleared for pasture, planted with non-native grasses, and later planted with a monoculture of a native nitrogen-fixing tree in an effort to restore forests. We discuss interactions between birds, understorey fruiting native species, understorey non-native grasses, soils and bryophytes in separate feedback mechanisms, and explain our efforts to identify which of these feedbacks is most important to address in a management context. Finally, we suggest that using models can help overcome some of the challenges that terrestrial ecosystems pose when studying ASE.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Plant Invasions: The role of biotic interactions","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CABI","usgsCitation":"Yelenik, S.G., D’Antonio, C.M., Rehm, E.M., and Caldwell, I., 2021, Multiple feedbacks due to biotic interactions across trophic levels can lead to persisten novel conditions that hinder restoration, chap. 23 <i>of</i> Plant Invasions: The role of biotic interactions, p. 402-420.","productDescription":"19 p.","startPage":"402","endPage":"420","ipdsId":"IP-116356","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":388998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769 syelenik@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":5251,"corporation":false,"usgs":true,"family":"Yelenik","given":"Stephanie","email":"syelenik@usgs.gov","middleInitial":"G.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":822803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Antonio, Carla M.","contributorId":196690,"corporation":false,"usgs":false,"family":"D’Antonio","given":"Carla","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":822804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rehm, Evan M","contributorId":216487,"corporation":false,"usgs":false,"family":"Rehm","given":"Evan","email":"","middleInitial":"M","affiliations":[{"id":39457,"text":"University of California at Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":822805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caldwell, Iain","contributorId":265492,"corporation":false,"usgs":false,"family":"Caldwell","given":"Iain","email":"","affiliations":[{"id":35992,"text":"James Cook University, Australia","active":true,"usgs":false}],"preferred":false,"id":822806,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70217720,"text":"70217720 - 2021 - Tectonic and magmatic controls on the metallogenesis of porphyry deposits in Alaska","interactions":[],"lastModifiedDate":"2021-02-01T14:12:59.353933","indexId":"70217720","displayToPublicDate":"2021-01-29T07:47:46","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Tectonic and magmatic controls on the metallogenesis of porphyry deposits in Alaska","docAbstract":"Porphyry Cu and Mo deposits and occurrences are found throughout Alaska; they formed episodically during repeated subduction and arc-continent collisions spanning the Silurian to Quaternary. Porphyry systems occur in continental-margin and island arcs, which are broadly grouped into pre-accretionary or post-accretionary arcs. Pre-Mesozoic occurrences formed in continental or island arcs prior to accretion onto the margin of North America, whereas Mesozoic and younger systems formed in arcs that developed after terrane fragments were accreted to the margin of North America. As a result, older porphyry systems are typically in the interior and northern metallogenic belts, whereas the younger porphyry systems are predominantly found in the southern third of the state, closer to the modern continental margin.\nAlaska porphyry formation peaked in the mid-Cretaceous and continued through the Late Cretaceous to Tertiary, in association with continental-margin arcs extending from the eastern interior, into southwest Alaska and along the Alaska Peninsula and Aleutian Islands. Porphyry system formation is not generally recognized in the Early Cretaceous, Triassic, or early Paleozoic – time periods that coincide with continental collisional events or extension. Relatively few pre-accretionary porphyry systems are documented in more deeply exhumed arc segments due to low preservation potential in areas of rapid or repeated bedrock uplift and associated erosion that occurred during later tectonic events.\nSignificant diversity is observed in porphyry occurrences across the state and even within the same region. Occurrences form in association with arc-related intrusions or intrusive complexes, that range in composition from diorite to syenite, but are commonly monzonitic to granitic. Some porphyry occurrences are associated with alkaline intrusive belts that exhibit a stronger crustal contribution to magmatic sources. Intrusions associated with porphyry formation in Alaska are commonly moderately oxidized, however, a distinct group of porphyry systems are associated with more-reduced magmas.\nHydrothermal alteration described at many occurrences exhibits zoning from proximal potassic alteration to typically peripheral and(or) later sericitic alteration, that is flanked by large zones of propylitic alteration. Diversity in alteration is observed where sodic and sodic-calcic alteration is present, commonly in more-enigmatic deposits, such as Island Mountain and Chicken Mountain. Advanced argillic alteration is rare, but present in notable examples, such as the Pebble porphyry Cu(-Au-Mo) deposit. Sulfide mineralization is characterized by pyrite, chalcopyrite, molybdenite, and rare bornite hosted in veinlets, veins and disseminations in wallrocks and causative intrusions. Some porphyry systems contain abundant pyrrhotite and(or) arsenopyrite in the mineral assemblages. Systems that exhibit bornite-bearing assemblages containing abundant molybdenite are commonly arsenic- and gold-poor and tend to be associated with more oxidized arc magmas. In contrast, those systems that are pyrrhotite and(or) arsenopyrite dominant tend to be gold, arsenic, and bismuth bearing, and are commonly associated with more-reduced magmas. \nExploration for porphyry occurrences in Alaska has experienced a resurgence and currently constitutes about 20% of exploration dollars in the state. Many systems lack complete descriptions, and coupled with the cost of exploration, remain incompletely explored. Additional understanding of known occurrences combined with a framework geologic understanding of porphyry-bearing metallogenic belts will likely result in new discoveries in the future.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Porphyry deposits of the northwestern Cordillera of North America: A 25-year update","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Canadian Institute of Mining, Metallurgy and Petroleum","usgsCitation":"Kreiner, D.C., Jones, J.V., Kelley, K.D., and Graham, G.E., 2021, Tectonic and magmatic controls on the metallogenesis of porphyry deposits in Alaska, chap. <i>of</i> Porphyry deposits of the northwestern Cordillera of North America: A 25-year update, v. 57, p. 134-175.","productDescription":"42 p.","startPage":"134","endPage":"175","ipdsId":"IP-113700","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":382786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382778,"type":{"id":15,"text":"Index Page"},"url":"https://store.cim.org/en/porphyry-deposits-of-the-northwestern-cordillera-of-north-america-a-25-year-update-2"}],"country":"United 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,{"id":70220287,"text":"70220287 - 2021 - Quarterly wildlife mortality report January 2021","interactions":[],"lastModifiedDate":"2023-10-13T13:37:56.075106","indexId":"70220287","displayToPublicDate":"2021-01-29T07:45:42","publicationYear":"2021","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":9359,"text":"Wildlife Disease Association Newsletter","active":true,"publicationSubtype":{"id":30}},"title":"Quarterly wildlife mortality report January 2021","docAbstract":"The USGS National Wildlife Health Center (NWHC) Quarterly Mortality Report provides brief summaries of epizootic mortality and morbidity events by quarter. The write-ups, highlighting epizootic events and other wildlife disease topics of interest, are published in the Wildlife Disease Association quarterly newsletter. A link is provided in this WDA newsletter to the Wildlife Health Information Sharing Partnership event reporting system (WHISPers) so readers can view associated data.","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Richards, B.J., Bodenstein, B., Grear, D.A., Ip, H., Ballmann, A., Lankton, J.S., and Shearn-Bochsler, V.I., 2021, Quarterly wildlife mortality report January 2021: Wildlife Disease Association Newsletter, p. 15-17.","productDescription":"3 p.","startPage":"15","endPage":"17","ipdsId":"IP-125495","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":385398,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive","linkFileType":{"id":5,"text":"html"}},{"id":385413,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Richards, Bryan J. 0000-0001-9955-2523","orcid":"https://orcid.org/0000-0001-9955-2523","contributorId":219535,"corporation":false,"usgs":true,"family":"Richards","given":"Bryan","email":"","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":189820,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara","email":"bbodenstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ip, Hon S. 0000-0003-4844-7533","orcid":"https://orcid.org/0000-0003-4844-7533","contributorId":126815,"corporation":false,"usgs":true,"family":"Ip","given":"Hon S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815017,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815018,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shearn-Bochsler, Valerie I. 0000-0002-5590-6518 vbochsler@usgs.gov","orcid":"https://orcid.org/0000-0002-5590-6518","contributorId":3234,"corporation":false,"usgs":true,"family":"Shearn-Bochsler","given":"Valerie","email":"vbochsler@usgs.gov","middleInitial":"I.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":815019,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70217863,"text":"70217863 - 2021 - Non-native Asian swamp eel, Monopterus albus/javanensis (Zuiew, 1973/Lacepede, 1800), responses to low temperatures","interactions":[],"lastModifiedDate":"2023-07-07T14:11:49.37828","indexId":"70217863","displayToPublicDate":"2021-01-29T07:42:09","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1651,"text":"Fish Physiology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Non-native Asian swamp eel, <i>Monopterus albus/javanensis</i> (Zuiew, 1973/Lacepede, 1800), responses to low temperatures","title":"Non-native Asian swamp eel, Monopterus albus/javanensis (Zuiew, 1973/Lacepede, 1800), responses to low temperatures","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Asian swamp eel,<span>&nbsp;</span><i>Monopterus albus/javanensis</i><span>&nbsp;</span>[Zuiew, 1973/Lacepede 1800], has been established in the southeastern USA since at least 1994, yet little is known about its ability to survive low winter temperatures. We use standard thermal methodologies to quantify low temperature responses and provide a detailed description of swamp eel reactions to cold temperatures. When exposed to chronic temperature decreases of 1.0 °C day<sup>−1</sup>, swamp eel ceased foraging at 15.0 °C, markedly diminished movements below 11.0 °C, and became incapacitated near 9.6 °C. During critical thermal minima trials, swamp eel exposed to acute temperature drops (0.25 °C min<sup>−1</sup>) tolerated temperatures as low as 6.2 °C. Swamp eel exhibited a moderate cold acclimation response, gaining 0.23 °C in cold tolerance for every 1 °C drop in acclimation temperature. Progressive time-series critical thermal minimum temperatures (CTmin) estimates for eel acclimated to 20.5 °C followed by an acute temperature decrease to 16.0 °C, revealed that cold acclimation may occur in only 8 days. Fringe populations of swamp eel in their native range periodically experience colder winter temperatures, which may explain the ability of introduced populations to survive winter cold fronts in Florida. Understanding Asian swamp eel acute and chronic thermal limits may be useful in assessing dispersal risk and range expansion in the southeastern USA.</p></div></div><div id=\"cobranding-and-download-availability-text\" class=\"note test-pdf-link\"><br></div>","language":"English","publisher":"Springer","doi":"10.1007/s10695-021-00925-w","usgsCitation":"Saylor, R.K., Schofield, P., and Bennett, W., 2021, Non-native Asian swamp eel, Monopterus albus/javanensis (Zuiew, 1973/Lacepede, 1800), responses to low temperatures: Fish Physiology and Biochemistry, v. 47, p. 465-476, https://doi.org/10.1007/s10695-021-00925-w.","productDescription":"12 p.; Data Release","startPage":"465","endPage":"476","ipdsId":"IP-120529","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":383089,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418749,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NFFZTV","text":"Non-native Asian swamp eel, Monopterus albus/javanensis (Zuiew, 1973/Lacepede, 1800), responses to low temperatures","linkFileType":{"id":5,"text":"html"}}],"volume":"47","noUsgsAuthors":false,"publicationDate":"2021-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Saylor, Ryan K.","contributorId":248815,"corporation":false,"usgs":false,"family":"Saylor","given":"Ryan","email":"","middleInitial":"K.","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":809965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schofield, Pam 0000-0002-8752-2797","orcid":"https://orcid.org/0000-0002-8752-2797","contributorId":213749,"corporation":false,"usgs":true,"family":"Schofield","given":"Pam","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":809966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Wayne A","contributorId":248816,"corporation":false,"usgs":false,"family":"Bennett","given":"Wayne A","affiliations":[{"id":16703,"text":"University of West Florida","active":true,"usgs":false}],"preferred":false,"id":809967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70220471,"text":"70220471 - 2021 - Reconstructing population dynamics of a threatened marine mammal using multiple data sets","interactions":[],"lastModifiedDate":"2021-05-14T12:48:58.278944","indexId":"70220471","displayToPublicDate":"2021-01-29T07:38:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing population dynamics of a threatened marine mammal using multiple data sets","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Models of marine mammal population dynamics have been used extensively to predict abundance. A less common application of these models is to reconstruct historical population dynamics, filling in gaps in observation data by integrating information from multiple sources. We developed an integrated population model for the Florida manatee (<i>Trichechus manatus latirostris</i>) to reconstruct its population dynamics in the southwest region of the state over the past 20&nbsp;years. Our model improved precision of key parameter estimates and permitted inference on poorly known parameters. Population growth was slow (averaging 1.02; 95% credible interval 1.01–1.03) but not steady, and an unusual mortality event in 2013 led to an estimated net loss of 332 (217–466) manatees. Our analyses showed that precise estimates of abundance could be derived from estimates of vital rates and a few input estimates of abundance, which may mean costly surveys to estimate abundance don’t need to be conducted as frequently. Our study also shows that retrospective analyses can be useful to: (1) model the transient dynamics of age distribution; (2) assess and communicate the conservation status of wild populations; and (3) improve our understanding of environmental effects on population dynamics and thus enhance our ability to forecast.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41598-021-81478-z","usgsCitation":"Hostetler, J., Martin, J., Kosempa, M., Edwards, H., Rood, K., Barton, S., and Runge, M.C., 2021, Reconstructing population dynamics of a threatened marine mammal using multiple data sets: Scientific Reports, v. 11, 2702 , 15 p., https://doi.org/10.1038/s41598-021-81478-z.","productDescription":"2702 , 15 p.","ipdsId":"IP-117972","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":453658,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-021-81478-z","text":"Publisher Index Page"},{"id":436529,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98835OJ","text":"USGS data release","linkHelpText":"Data from: Reconstructing population dynamics of a threatened marine mammal using multiple data sets"},{"id":385637,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Florida","otherGeospatial":"Southwest Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.232421875,\n              25.16517336866393\n            ],\n            [\n              -80.419921875,\n              25.16517336866393\n            ],\n            [\n              -80.419921875,\n              28.65203063036226\n            ],\n            [\n              -83.232421875,\n              28.65203063036226\n            ],\n            [\n              -83.232421875,\n              25.16517336866393\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2021-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Hostetler, J. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":258049,"corporation":false,"usgs":false,"family":"Hostetler","given":"J.","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":815612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":216734,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":815613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kosempa, M.","contributorId":258050,"corporation":false,"usgs":false,"family":"Kosempa","given":"M.","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":815614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edwards, H.","contributorId":258052,"corporation":false,"usgs":false,"family":"Edwards","given":"H.","email":"","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":815615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rood, K.","contributorId":258054,"corporation":false,"usgs":false,"family":"Rood","given":"K.","email":"","affiliations":[{"id":35758,"text":"FWC","active":true,"usgs":false}],"preferred":false,"id":815616,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barton, S.","contributorId":258057,"corporation":false,"usgs":false,"family":"Barton","given":"S.","email":"","affiliations":[{"id":52219,"text":"Mote","active":true,"usgs":false}],"preferred":false,"id":815617,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":815618,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70223118,"text":"70223118 - 2021 - Knowledge inventory of foundational data products in planetary science","interactions":[],"lastModifiedDate":"2021-08-11T12:27:54.283197","indexId":"70223118","displayToPublicDate":"2021-01-29T07:26:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":8607,"text":"The Planetary Science Journal","active":true,"publicationSubtype":{"id":10}},"title":"Knowledge inventory of foundational data products in planetary science","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Some of the key components of any Planetary Spatial Data Infrastructure (PDSI) are the data products that end-users wish to discover, access, and interrogate. One precursor to the implementation of a PSDI is a knowledge inventory that catalogs what products are available, from which data producers, and at what initially understood data qualities. We present a knowledge inventory of foundational PSDI data products: geodetic coordinate reference frames, elevation or topography, and orthoimages or orthomosaics. Additionally, we catalog the available gravity models that serve as critical data for the assessment of spatial location, spatial accuracy, and ultimately spatial efficacy. We strengthen our previously published definitions of foundational data products to assist in solidifying a common vocabulary that will improve communication about these essential data products.</p></div>","language":"English","publisher":"IOP Science","doi":"10.3847/psj/abcb94","usgsCitation":"Laura, J., and Beyer, R.A., 2021, Knowledge inventory of foundational data products in planetary science: The Planetary Science Journal, v. 2, no. 1, 18, 28 p., https://doi.org/10.3847/psj/abcb94.","productDescription":"18, 28 p.","ipdsId":"IP-115047","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":453661,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/abcb94","text":"Publisher Index Page"},{"id":387838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Laura, Jason 0000-0002-1377-8159","orcid":"https://orcid.org/0000-0002-1377-8159","contributorId":222124,"corporation":false,"usgs":true,"family":"Laura","given":"Jason","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":821035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beyer, Ross A.","contributorId":264165,"corporation":false,"usgs":false,"family":"Beyer","given":"Ross","email":"","middleInitial":"A.","affiliations":[{"id":37319,"text":"SETI Institute","active":true,"usgs":false}],"preferred":false,"id":821036,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70219570,"text":"70219570 - 2021 - Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures","interactions":[],"lastModifiedDate":"2021-05-27T13:23:08.289537","indexId":"70219570","displayToPublicDate":"2021-01-29T07:04:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3517,"text":"Talanta","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Spike- and blank-based procedures were applied to estimate the detection limits (DLs) for example analytes from inorganic and organic methods for water samples to compare with the U.S. Environmental Protection Agency's (EPA) Method Detection Limit (MDL) procedures (revisions 1.11 and 2.0). The multi-concentration spike-based procedures ASTM Within-laboratory Critical Level (DQCALC) and EPA's Lowest Concentration Minimum Reporting Level were compared in one application, with DQCALC further applied to many methods. The blank-based DLs, MDL<sub>b99</sub><span>&nbsp;</span>(99th percentile) or MDL<sub>bY</sub><span>&nbsp;</span>(= mean blank concentration&nbsp;+&nbsp;<i>s</i>&nbsp;×&nbsp;<i>t</i>), estimated using large numbers (&gt;100) of blank samples often provide DLs that better approach or achieve the desired ≤1% false positive risk level compared to spike-based DLs. For primarily organic methods that do not provide many uncensored blank results, spike-based DQCALC or MDL rev. 2.0 are needed to simulate the blank distribution and estimate the DL. DQCALC is especially useful for estimating DLs for multi-analyte methods having very different analyte response characteristics. Time series plots of DLs estimated using different procedures reveal that DLs are dependent on the applied procedure, should not be expected to be static over time, and seem best viewed as falling over a range versus being a single value. Use of both blank- and spike-based DL procedures help inform this DL range. Data reporting conventions that censor data at a threshold and report “less than” that threshold concentration as the reporting level have unknown and potentially high false negative risk. The U.S. Geological Survey National Water Quality Laboratory's Laboratory Reporting Level (LRL) convention (applied primarily to organic methods) attempts to simultaneously minimize both the false positive and false negative risk when&nbsp;&lt;LRL is reported and data between DL and the higher LRL are allowed to be reported.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.talanta.2021.122139","usgsCitation":"Foreman, W.T., Williams, T.L., Furlong, E., Hemmerle, D., Stetson, S., Jha, V.K., Noriega, M., Decess, J.A., Reed-Parker, C., and Sandstrom, M.W., 2021, Comparison of detection limits estimated using single- and multi-concentration spike-based and blank-based procedures: Talanta, v. 228, 122139, 15 p., https://doi.org/10.1016/j.talanta.2021.122139.","productDescription":"122139, 15 p.","ipdsId":"IP-121087","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":436530,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MUSPFI","text":"USGS data release","linkHelpText":"Data from USGS National Water Quality Laboratory methods used to calculate and compare detection limits estimated using single- and multi-concentration spike-based and blank-based procedures"},{"id":385078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"228","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":190786,"corporation":false,"usgs":true,"family":"Foreman","given":"William","email":"wforeman@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Teresa Lynne 0000-0002-9507-9350","orcid":"https://orcid.org/0000-0002-9507-9350","contributorId":257407,"corporation":false,"usgs":true,"family":"Williams","given":"Teresa","email":"","middleInitial":"Lynne","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814197,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Furlong, Edward 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":213730,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814198,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hemmerle, Dawn 0000-0002-9495-6681","orcid":"https://orcid.org/0000-0002-9495-6681","contributorId":257409,"corporation":false,"usgs":true,"family":"Hemmerle","given":"Dawn","email":"","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814199,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stetson, Sarah 0000-0002-4930-4748 sstetson@usgs.gov","orcid":"https://orcid.org/0000-0002-4930-4748","contributorId":216528,"corporation":false,"usgs":true,"family":"Stetson","given":"Sarah","email":"sstetson@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814200,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jha, Virendra K. 0000-0002-1076-0738 vkjha@usgs.gov","orcid":"https://orcid.org/0000-0002-1076-0738","contributorId":257416,"corporation":false,"usgs":true,"family":"Jha","given":"Virendra","email":"vkjha@usgs.gov","middleInitial":"K.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":814205,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Noriega, Mary C 0000-0002-4426-3553","orcid":"https://orcid.org/0000-0002-4426-3553","contributorId":257413,"corporation":false,"usgs":false,"family":"Noriega","given":"Mary C","affiliations":[{"id":52011,"text":"USGS, National Water Quality Laboratory, retired","active":true,"usgs":false}],"preferred":false,"id":814201,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Decess, Jessica A 0000-0002-4202-3265","orcid":"https://orcid.org/0000-0002-4202-3265","contributorId":257414,"corporation":false,"usgs":false,"family":"Decess","given":"Jessica","email":"","middleInitial":"A","affiliations":[{"id":52014,"text":"Formerly: Cherokee Nation Technology Solutions, Denver, CO; Currently: The Medical Center of Aurora, Aurora, CO","active":true,"usgs":false}],"preferred":false,"id":814202,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reed-Parker, Carmen 0000-0001-9579-578X","orcid":"https://orcid.org/0000-0001-9579-578X","contributorId":257415,"corporation":false,"usgs":false,"family":"Reed-Parker","given":"Carmen","email":"","affiliations":[{"id":52011,"text":"USGS, National Water Quality Laboratory, retired","active":true,"usgs":false}],"preferred":false,"id":814203,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":true,"id":814204,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70229334,"text":"70229334 - 2021 - Detecting resource limitation in a large herbivore population is enhanced with measures of nutritional condition","interactions":[],"lastModifiedDate":"2022-03-03T23:56:22.478536","indexId":"70229334","displayToPublicDate":"2021-01-28T17:46:41","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3910,"text":"Frontiers in Ecology and Evolution","onlineIssn":"2296-701X","active":true,"publicationSubtype":{"id":10}},"title":"Detecting resource limitation in a large herbivore population is enhanced with measures of nutritional condition","docAbstract":"<p><span>Resource limitation at the population level is a function of forage quality and its abundance relative to its per capita availability, which in turn, determines nutritional condition of individuals. Effects of resource limitation on population dynamics in ungulates often occur through predictable and sequential changes in vital rates, which can enable assessments of how resource limitation influences population growth. We tested theoretical predictions of bottom-up (i.e., resource limitation) forcing on moose (</span><i>Alces alces</i><span>) through the lens of vital rates by quantifying the relative influence of intrinsic measures of nutritional condition and extrinsic measures of remotely sensed environmental data on demographic rates. We measured rates of pregnancy, parturition, juvenile, and adult survival for 82 adult females in a population where predators largely were absent. Life stage simulation analyses (LSAs) indicated that interannual fluctuations in adult survival contributed to most of the variability in λ. We then extended the LSA to estimate vital rates as a function of bottom-up covariates to evaluate their influence on λ. We detected weak signatures of effects from environmental covariates that were remotely sensed and spatially explicit to each seasonal range. Instead, nutritional condition strongly influenced rates of pregnancy, parturition, and overwinter survival of adults, clearly implicating resource limitation on λ. Our findings depart from the classic life-history paradigm of population dynamics in ungulates in that adult survival was highly variable and generated most of the variability in population growth rates. At the surface, lack of variation explained by environmental covariates may suggest weak evidence of resource limitation in the population, when nutritional condition actually underpinned most demographics. We suggest that variability in vital rates and effects of resource limitation may depend on context more than previously appreciated, and density dependence can obfuscate the relationships between remotely sensed data and demographic rates.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2020.522174","usgsCitation":"Oates, B.A., Monteith, K., Goheen, J., Merkle, J., Fralick, G., and Kauffman, M., 2021, Detecting resource limitation in a large herbivore population is enhanced with measures of nutritional condition: Frontiers in Ecology and Evolution, v. 8, 522174, 15 p., https://doi.org/10.3389/fevo.2020.522174.","productDescription":"522174, 15 p.","ipdsId":"IP-085031","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2020.522174","text":"Publisher Index Page"},{"id":396736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Upper Green River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.61035156249999,\n              42.85985981506279\n            ],\n            [\n              -110.01708984374999,\n              42.85985981506279\n            ],\n            [\n              -110.01708984374999,\n              43.45291889355465\n            ],\n            [\n              -110.61035156249999,\n              43.45291889355465\n            ],\n            [\n              -110.61035156249999,\n              42.85985981506279\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Oates, Brendan A.","contributorId":275241,"corporation":false,"usgs":false,"family":"Oates","given":"Brendan","email":"","middleInitial":"A.","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":837074,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Monteith, Kevin L.","contributorId":287798,"corporation":false,"usgs":false,"family":"Monteith","given":"Kevin L.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837071,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goheen, Jacob R.","contributorId":287799,"corporation":false,"usgs":false,"family":"Goheen","given":"Jacob R.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837072,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merkle, Jerod A.","contributorId":287800,"corporation":false,"usgs":false,"family":"Merkle","given":"Jerod A.","affiliations":[{"id":40829,"text":"uwy","active":true,"usgs":false}],"preferred":false,"id":837073,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fralick, Gary","contributorId":287797,"corporation":false,"usgs":false,"family":"Fralick","given":"Gary","affiliations":[{"id":56161,"text":"wygf","active":true,"usgs":false}],"preferred":false,"id":837070,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":202921,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837075,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70217705,"text":"ds1134 - 2021 - Distribution and abundance of Least Bell's Vireos and Southwestern Willow Flycatchers on the middle San Luis Rey River, San Diego County, southern California—2020 data summary","interactions":[],"lastModifiedDate":"2021-01-29T12:45:13.001068","indexId":"ds1134","displayToPublicDate":"2021-01-28T14:17:37","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1134","displayTitle":"Distribution and Abundance of Least Bell’s Vireos (<i>Vireo bellii pusillus</i>) and Southwestern Willow Flycatchers (<i>Empidonax traillii extimus</i>) on the Middle San Luis Rey River, San Diego County, Southern California—2020 Data Summary","title":"Distribution and abundance of Least Bell's Vireos and Southwestern Willow Flycatchers on the middle San Luis Rey River, San Diego County, southern California—2020 data summary","docAbstract":"<p>We surveyed for Least Bell’s Vireos (<i>Vireo bellii pusillus</i>; vireo) and Southwestern Willow Flycatchers (<i>Empidonax traillii extimus</i>; flycatcher) along the San Luis Rey River, between College Boulevard in Oceanside and Interstate 15 in Fallbrook, California (middle San Luis Rey River), in 2020. Surveys were conducted from April 13 to July 13 (vireo) and from May 14 to July 13 (flycatcher). We found 192 vireo territories, at least 150 of which were occupied by pairs. Vireo territories increased by 40 percent from 2019 to 2020 in the portion of the middle San Luis Rey River that burned as a result of a wildfire in 2017. In contrast, vireo territories decreased by 5 percent from 2019 to 2020 in the unburned portion of the middle San Luis Rey River.&nbsp;</p><p>Vireos used six different habitat types in the survey area: (1) willow-cottonwood, (2) mixed willow riparian, (3) riparian scrub, (4) upland scrub, (5) willow-sycamore, and (6) non-native. Forty-nine percent of the vireos were detected in habitat characterized as willow-cottonwood, and 93 percent of the vireos were detected in habitat with greater than 50-percent native plant cover. Of the 17 banded vireos detected in the survey area, 6 were resighted with a full color-band combination. Two other vireos with single (natal) federal bands were recaptured, identified, and color-banded in 2020. Eight vireos with a single dark blue federal band, indicating that they were banded as nestlings on the lower San Luis Rey River (LSLR), could not be recaptured for identification. One vireo with a single gold federal band, indicating that it was banded as a nestling at Marine Corps Base Camp Pendleton (MCBCP), could not be recaptured for identification. The two natal vireos that were recaptured on the middle San Luis Rey River dispersed from 2.6 to 6.2 kilometers (km) from their natal territories. Banded vireos with a known age ranged from 1 to 8 years old.&nbsp;</p><p>One resident flycatcher was observed in the survey area in 2020. The resident flycatcher (male) was detected in a territory of mixed willow habitat with greater than 50-percent native plant cover. He was detected as a single male from May 27 to July 2, 2020, and no evidence of pairing or nesting was observed. The male flycatcher was resighted with a unique color-band combination and had occupied the same territory since 2018.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1134","usgsCitation":"Allen, L.D., and Kus, B.E., 2021, Distribution and abundance of Least Bell's Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the middle San Luis Rey River, San Diego County, southern California—2020 data summary: U.S. Geological Survey Data Series 1134, 11 p., https://doi.org/10.3133/ds1134.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-124769","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":382770,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1134/ds1134.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":382769,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1134/covrthb.jpg"}],"country":"United States","state":"California","county":"San Diego County","otherGeospatial":"Middle San Luis Rey River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.33947753906249,\n              33.02248191961359\n            ],\n            [\n              -115.76293945312499,\n              33.08233672856376\n            ],\n            [\n              -116.35620117187499,\n              33.84760762988741\n            ],\n            [\n              -117.55920410156249,\n              33.394759218577995\n            ],\n            [\n              -117.33947753906249,\n              33.02248191961359\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director,<br><a href=\"https://www.usgs.gov/%20centers/%20werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/ centers/ werc\">Western Ecological Research Center</a><br><a data-mce-href=\"https://usgs.gov\" href=\"https://usgs.gov\" target=\"_blank\" rel=\"noopener\">U.S. Geological Survey</a><br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Methods</li><li>Least Bell’s Vireo</li><li>Southwestern Willow Flycatcher</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2021-01-28","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Allen, Lisa D. 0000-0002-6147-3165 ldallen@usgs.gov","orcid":"https://orcid.org/0000-0002-6147-3165","contributorId":196789,"corporation":false,"usgs":true,"family":"Allen","given":"Lisa","email":"ldallen@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":809305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":809306,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70217754,"text":"70217754 - 2021 - Integrated hierarchical models to inform management of transitional habitat and the recovery of a habitat specialist","interactions":[],"lastModifiedDate":"2021-02-01T17:12:01.757871","indexId":"70217754","displayToPublicDate":"2021-01-28T11:03:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Integrated hierarchical models to inform management of transitional habitat and the recovery of a habitat specialist","docAbstract":"<p><span>Quantifying the contribution of habitat dynamics relative to intrinsic population processes in regulating species persistence remains an ongoing challenge in ecological and applied conservation. Understanding these drivers and their relationship is essential for managing habitat‐dependent species, especially those that specialize in transitional habitats. Limitations in the ability of natural disturbance to mediate transitional habitat dynamics have resulted in a decline in early‐ and mid‐successional vegetation structure and prompted the need for aggressive habitat management to replace natural perturbations and increase habitat structural complexity. We describe a collaborative effort with a group of independent land managers to design an adaptive management program for restoring an imperiled ecosystem and recovering declining populations of an endemic habitat specialist. We developed a set of integrated, hierarchical models to estimate management‐mediated transition rates among vegetation classes in two dominant scrub communities and the species response (local colonization and extinction probabilities) as a function of habitat state. Models were fit using a long‐term data set of habitat and occupancy observations from 361 Florida scrub‐jay territories across two Florida counties. Occupancy model results correspond closely to previous approaches of estimating differential survival and reproductive success associated with habitat conditions, with highest colonization and lowest extinction rates estimated for those habitat states found to have the highest rates of survival and reproduction. In addition to offering an innovative approach for jointly modeling habitat and species population dynamics, the program we describe will also be of interest from a management perspective by providing guidance for developing collaborative, adaptive management frameworks from the ground up. We engaged land managers via workshops to specify objectives and desired state‐variable conditions, identify management alternatives, and elicit consensus opinions on model parameters. Treating expert opinions as pseudo‐observations to define Dirichlet priors allowed us to make use of existing management knowledge. Formal learning was then accumulated by updating transition probability estimates as management activities were implemented over the study period. We believe this adaptive management framework provides a useful approach for increasing our understanding of complex ecological relationships and hope that it will be adopted by others who have interest in informing management and conservation efforts.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.3306","usgsCitation":"Eaton, M.J., Breininger, D., Nichols, J.D., Paul, F., McGee, S., Smurl, M., DeMeyer, D., Baker, J., and Zondervan, M.B., 2021, Integrated hierarchical models to inform management of transitional habitat and the recovery of a habitat specialist: Ecosphere, v. 12, no. 1, e03306, 26 p., https://doi.org/10.1002/ecs2.3306.","productDescription":"e03306, 26 p.","ipdsId":"IP-115268","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":488926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3306","text":"Publisher Index Page"},{"id":382851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Brevard County, Indian River County","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -81.1285400390625,\n              27.668934069896217\n            ],\n            [\n              -80.4034423828125,\n              27.668934069896217\n            ],\n            [\n              -80.4034423828125,\n              28.64479960910591\n            ],\n            [\n              -81.1285400390625,\n              28.64479960910591\n            ],\n            [\n              -81.1285400390625,\n              27.668934069896217\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":809484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breininger, David","contributorId":248597,"corporation":false,"usgs":false,"family":"Breininger","given":"David","affiliations":[{"id":49958,"text":"NASA Ecology Program","active":true,"usgs":false}],"preferred":false,"id":809485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":809486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paul, F.","contributorId":248598,"corporation":false,"usgs":false,"family":"Paul","given":"F.","affiliations":[],"preferred":false,"id":809487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGee, Samantha","contributorId":248609,"corporation":false,"usgs":false,"family":"McGee","given":"Samantha","email":"","affiliations":[],"preferred":false,"id":809522,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smurl, Michelle","contributorId":248610,"corporation":false,"usgs":false,"family":"Smurl","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":809523,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeMeyer, David","contributorId":248611,"corporation":false,"usgs":false,"family":"DeMeyer","given":"David","email":"","affiliations":[],"preferred":false,"id":809524,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Baker, Jonny","contributorId":248612,"corporation":false,"usgs":false,"family":"Baker","given":"Jonny","email":"","affiliations":[],"preferred":false,"id":809525,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zondervan, Maria B.","contributorId":248614,"corporation":false,"usgs":false,"family":"Zondervan","given":"Maria","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":809526,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70218170,"text":"70218170 - 2021 - Joint species distribution models of Everglades wading birds to inform restoration planning","interactions":[],"lastModifiedDate":"2023-07-07T14:08:20.276686","indexId":"70218170","displayToPublicDate":"2021-01-28T10:04:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Joint species distribution models of Everglades wading birds to inform restoration planning","docAbstract":"<p><span>Restoration of the Florida Everglades, a substantial wetland ecosystem within the United States, is one of the largest ongoing restoration projects in the world. Decision-makers and managers within the Everglades ecosystem rely on ecological models forecasting indicator wildlife response to changes in the management of water flows within the system. One such indicator of ecosystem health, the presence of wading bird communities on the landscape, is currently assessed using three species distribution models that assume perfect detection and report output on different scales that are challenging to compare against one another. We sought to use current advancements in species distribution modeling to improve models of Everglades wading bird distribution. Using a joint species distribution model that accounted for imperfect detection, we modeled the presence of nine species of wading bird simultaneously in response to annual hydrologic conditions and landscape characteristics within the Everglades system. Our resulting model improved upon the previous model in three key ways: 1) the model predicts probability of occupancy for the nine species on a scale of 0–1, making the output more intuitive and easily comparable for managers and decision-makers that must consider the responses of several species simultaneously; 2) through joint species modeling, we were able to consider rarer species within the modeling that otherwise are detected in too few numbers to fit as individual models; and 3) the model explicitly allows detection probability of species to be less than 1 which can reduce bias in the site occupancy estimates. These improvements are essential as Everglades restoration continues and managers require models that consider the impacts of water management on key indicator wildlife such as the wading bird community.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0245973","usgsCitation":"D’Acunto, L., Pearlstine, L.G., and Romanach, S., 2021, Joint species distribution models of Everglades wading birds to inform restoration planning: PLoS ONE, v. 16, no. 1, e0245973, 21 p.; Data Release, https://doi.org/10.1371/journal.pone.0245973.","productDescription":"e0245973, 21 p.; Data Release","ipdsId":"IP-119201","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":453665,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0245973","text":"Publisher Index Page"},{"id":383272,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418748,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P934K8T0","text":"EverWaders species distribution model development and output in the Greater Everglades from 2000-2009","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -80.419921875,\n              25.209911213827688\n            ],\n            [\n              -80.474853515625,\n              25.27450351782018\n            ],\n            [\n              -80.562744140625,\n              25.348990395713393\n            ],\n            [\n    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Service","active":true,"usgs":false}],"preferred":false,"id":810304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":223479,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":810305,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70225621,"text":"70225621 - 2021 - The 2018 update of the US National Seismic Hazard Model: Where, why, and how much probabilistic ground motion maps changed","interactions":[],"lastModifiedDate":"2021-10-28T13:21:41.798091","indexId":"70225621","displayToPublicDate":"2021-01-28T08:15:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2018 update of the US National Seismic Hazard Model: Where, why, and how much probabilistic ground motion maps changed","docAbstract":"<p><span>The 2018 US Geological Survey National Seismic Hazard Model (NSHM) incorporates new data and updated science to improve the underlying earthquake and ground motion forecasts for the conterminous United States. The NSHM considers many new data and component input models: (1) new earthquakes between 2013 and 2017 and updated earthquake magnitudes for some earlier earthquakes; (2) two updated smoothed seismicity models to forecast earthquake rates; (3) two suites of new central and eastern US (CEUS) ground motion models (GMMs) to translate ground shaking for various earthquake sizes and source-to-site distances considered in the model; (4) two CEUS GMMs for aleatory variability; (5) two CEUS site-effect models that modify ground shaking based on alternative shallow site conditions; (6) more advanced western US (WUS) lithologic and structural information to assess basin site effects for selected urban regions; and (7) a more comprehensive range of outputs (22 periods and 8 site classes) than in previous versions of the NSHMs. Each of these new datasets and models produces changes in the probabilistic ground shaking levels that are spatially and statistically analyzed. Recent earthquakes or changes to some older earthquake magnitudes and locations mostly result in probabilistic ground shaking levels that are similar to previous models, but local changes can reach up to +80% and −60% compared to the 2014 model. Newly developed CEUS models for GMMs, aleatory variability, and site effects cause overall changes up to ±64%. The addition of the WUS basin amplifications causes changes of up to +60% at longer periods for sites overlying deep soft soils. Across the conterminous United States, the hazard changes in the model are mainly caused by new GMMs in the CEUS, by sedimentary basin effects for long periods (≥1 s) in the WUS, and by seismicity changes for short (0.2 s) and long (1 s) periods for both areas.</span></p>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/8755293020988016","usgsCitation":"Petersen, M.D., Shumway, A., Powers, P.M., Mueller, C.S., Moschetti, M.P., Frankel, A.D., Rezaeian, S., McNamara, D., Luco, N., Boyd, O.S., Rukstales, K.S., Jaiswal, K.S., Thompson, E.M., Hoover, S., Clayton, B., Field, E.H., and Zeng, Y., 2021, The 2018 update of the US National Seismic Hazard Model: Where, why, and how much probabilistic ground motion maps changed: Earthquake Spectra, v. 37, no. 2, p. 959-987, https://doi.org/10.1177/8755293020988016.","productDescription":"29 p.","startPage":"959","endPage":"987","ipdsId":"IP-123826","costCenters":[{"id":237,"text":"Earthquake Science 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0000-0002-1868-9710","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":268155,"corporation":false,"usgs":false,"family":"Mueller","given":"Charles","email":"","middleInitial":"S","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":825961,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825962,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 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0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825969,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825970,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hoover, Susan M. 0000-0002-8682-6668","orcid":"https://orcid.org/0000-0002-8682-6668","contributorId":268156,"corporation":false,"usgs":false,"family":"Hoover","given":"Susan M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":825971,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Clayton, Brandon 0000-0003-0502-7184 bclayton@usgs.gov","orcid":"https://orcid.org/0000-0003-0502-7184","contributorId":197196,"corporation":false,"usgs":true,"family":"Clayton","given":"Brandon","email":"bclayton@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":825972,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Field, Edward H. 0000-0001-8172-7882 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,{"id":70217819,"text":"70217819 - 2021 - Future regulated flows of the Colorado River in Grand Canyon foretell decreased areal extent of sediment and increases in riparian vegetation","interactions":[],"lastModifiedDate":"2021-02-04T13:58:17.537836","indexId":"70217819","displayToPublicDate":"2021-01-28T07:53:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Future regulated flows of the Colorado River in Grand Canyon foretell decreased areal extent of sediment and increases in riparian vegetation","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Sediment transfer, or connectivity, by aeolian processes between channel-proximal and upland deposits in river valleys is important for the maintenance of river corridor biophysical characteristics. In regulated river systems, dams control the magnitude and duration of discharge. Alterations to the flow regime driven by dams that increase the inundation duration of sediment, or which drive the encroachment of vegetation into areas formerly composed of labile sediment and result in channel narrowing, may reduce sediment transfer from near-channel deposits to uplands via aeolian processes. Employing spatial methods developed by Kasprak<span>&nbsp;</span><i>et al</i><span>&nbsp;</span>(2018<span>&nbsp;</span><i>Prog. Phys. Geogr.</i>), here we use data describing the areal extent of bare (i.e. subaerially exposed and non-vegetated) sediment along 168 km of the Colorado River downstream from Glen Canyon Dam in Grand Canyon, USA, in conjunction with inundation extent modeling to forecast how future flows of this highly regulated river will drive changes in the areal extent of sediment available for aeolian transport. We also compare modern bare sediment area to that which presumably would have existed under pre-dam hydrographs. Over the next two decades, the planned flow regime from Glen Canyon Dam will result in slight decreases in bare sediment area (−1%) on an annual scale. This is in contrast to pre-dam years, when unregulated low flows led to marked increases in bare sediment area as compared to the current discharge regime. Our findings also indicate that ~75% of bare sediment in the study reach is inundated continuously at present, owing to increased baseflows in the post-dam flow regime; consequently, any reductions in flows below modern-day low discharges have the potential to expose large areas of bare sediment. We use vegetation modeling to quantify areas susceptible to vegetation encroachment under future flows, finding that 80% of bare sediment area is suitable for colonization by invasive tamarisk under the current flow regime. Our findings imply that the Colorado River in Grand Canyon, a system marked by widespread erosion of sediment resources and encroachment of riparian vegetation in the post-dam period, is likely to continue to see decreasing bare sediment extent over the coming decades in the absence of direct intervention through flow regime modification or widespread vegetation removal.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/abc9e4","usgsCitation":"Kasprak, A., Sankey, J.B., and Butterfield, B.J., 2021, Future regulated flows of the Colorado River in Grand Canyon foretell decreased areal extent of sediment and increases in riparian vegetation: Environmental Research Letters, v. 16, no. 1, 014029, 14 p., https://doi.org/10.1088/1748-9326/abc9e4.","productDescription":"014029, 14 p.","ipdsId":"IP-120844","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":486997,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/abc9e4","text":"Publisher Index Page"},{"id":436532,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P918E2P3","text":"USGS data release","linkHelpText":"Discharge records and sand extents along the Colorado River between Glen Canyon Dam and Phantom Ranch, Arizona"},{"id":382945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.97241210937499,\n              35.576916524038616\n            ],\n            [\n              -111.434326171875,\n              35.576916524038616\n            ],\n            [\n              -111.434326171875,\n              36.57142382346277\n            ],\n            [\n              -112.97241210937499,\n              36.57142382346277\n            ],\n            [\n              -112.97241210937499,\n              35.576916524038616\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasprak, Alan 0000-0001-8184-6128","orcid":"https://orcid.org/0000-0001-8184-6128","contributorId":245742,"corporation":false,"usgs":false,"family":"Kasprak","given":"Alan","affiliations":[{"id":49307,"text":"Current: Utah State University. Former: Southwest Biological Science Center, Grand Canyon Monitoring and Research Center, U.S. Geological Survey, Flagstaff, AZ 86001, USA","active":true,"usgs":false}],"preferred":false,"id":809824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":809825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":809826,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70217716,"text":"70217716 - 2021 - Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density","interactions":[],"lastModifiedDate":"2021-01-29T13:41:03.444159","indexId":"70217716","displayToPublicDate":"2021-01-28T07:33:38","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density","docAbstract":"<div class=\"abstract\"><p>Lyme disease is common in the northeastern United States, but rare in the southeast, even though the tick vector is found in both regions. Infection prevalence of Lyme spirochetes in host-seeking ticks, an important component to the risk of Lyme disease, is also high in the northeast and northern midwest, but declines sharply in the south. As ticks must acquire Lyme spirochetes from infected vertebrate hosts, the role of wildlife species composition on Lyme disease risk has been a topic of lively academic discussion. We compared tick–vertebrate host interactions using standardized sampling methods among 8 sites scattered throughout the eastern US. Geographical trends in diversity of tick hosts are gradual and do not match the sharp decline in prevalence at southern sites, but tick–host associations show a clear shift from mammals in the north to reptiles in the south. Tick infection prevalence declines north to south largely because of high tick infestation of efficient spirochete reservoir hosts (rodents and shrews) in the north but not in the south. Minimal infestation of small mammals in the south results from strong selective attachment to lizards such as skinks (which are inefficient reservoirs for Lyme spirochetes) in the southern states. Selective host choice, along with latitudinal differences in tick host-seeking behavior and variations in tick densities, explains the geographic pattern of Lyme disease in the eastern US.</p></div>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pbio.3001066","usgsCitation":"Ginsberg, H., Hickling, G.J., Burke, R.L., Ogden, N.H., Beati, L., LeBrun, R.A., Arsnoe, I.M., Gerhold, R., Han, S., Jackson, K., Maestas, L., Moody, T., Pang, G., Ross, B., Rulison, E.L., and Tsao, J.I., 2021, Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density: PLoS Biology, v. 19, no. 1, e3001066, 20 p., https://doi.org/10.1371/journal.pbio.3001066.","productDescription":"e3001066, 20 p.","ipdsId":"IP-117549","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":453671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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J.","contributorId":140903,"corporation":false,"usgs":false,"family":"Hickling","given":"Graham","email":"","middleInitial":"J.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":809348,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burke, Russell L.","contributorId":127374,"corporation":false,"usgs":false,"family":"Burke","given":"Russell","email":"","middleInitial":"L.","affiliations":[{"id":6921,"text":"Hofstra University","active":true,"usgs":false}],"preferred":false,"id":809349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ogden, Nicholas H.","contributorId":147667,"corporation":false,"usgs":false,"family":"Ogden","given":"Nicholas","email":"","middleInitial":"H.","affiliations":[{"id":16890,"text":"Public Health Agency of Canada","active":true,"usgs":false}],"preferred":false,"id":809350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beati, 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Lauren","contributorId":248546,"corporation":false,"usgs":false,"family":"Maestas","given":"Lauren","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":809357,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Moody, Teresa","contributorId":248547,"corporation":false,"usgs":false,"family":"Moody","given":"Teresa","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":809358,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Pang, Genevieve","contributorId":221488,"corporation":false,"usgs":false,"family":"Pang","given":"Genevieve","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":809359,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ross, Breann","contributorId":248548,"corporation":false,"usgs":false,"family":"Ross","given":"Breann","email":"","affiliations":[{"id":6921,"text":"Hofstra University","active":true,"usgs":false}],"preferred":false,"id":809360,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rulison, Eric L.","contributorId":87478,"corporation":false,"usgs":false,"family":"Rulison","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":809361,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Tsao, Jean I.","contributorId":140905,"corporation":false,"usgs":false,"family":"Tsao","given":"Jean","email":"","middleInitial":"I.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":809362,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70220311,"text":"70220311 - 2021 - The optical river bathymetry toolkit","interactions":[],"lastModifiedDate":"2021-05-04T12:12:56.975607","indexId":"70220311","displayToPublicDate":"2021-01-28T07:10:52","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"The optical river bathymetry toolkit","docAbstract":"<p><span>Spatially distributed information on water depth is essential for many applications in river research and management and, under certain circumstances, can be inferred from remotely sensed data. Although fluvial remote sensing has emerged as a rapidly developing subdiscipline of the riverine sciences, more widespread adoption of these techniques has been hindered by a lack of accessible software. The Optical River Bathymetry Toolkit (ORByT) fills this void by providing a standalone package for mapping water depth from passive optical image data. The ORByT interface enables end users to import images and field‐based depth measurements, create and refine water masks, and perform spectrally based depth retrieval via an Optimal Band Ratio Analysis algorithm. The resulting bathymetric map can be exported as an image file, point cloud, and/or cross section; a thorough accuracy assessment also is incorporated into the workflow. In addition, image‐derived depth estimates can be subtracted from water surface elevations to obtain bed elevations suitable for input to a hydrodynamic model. Potential users of ORByT must bear in mind the inherent limitations of passive optical remote sensing: reliable bathymetry can only be inferred in clear‐flowing, shallow streams; this approach is not appropriate for more turbid, deeper rivers.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.3773","usgsCitation":"Legleiter, C.J., 2021, The optical river bathymetry toolkit: River Research and Applications, v. 4, no. 37, p. 555-568, https://doi.org/10.1002/rra.3773.","productDescription":"14 p.","startPage":"555","endPage":"568","ipdsId":"IP-119553","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":453673,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3773","text":"Publisher Index Page"},{"id":385444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"37","noUsgsAuthors":false,"publicationDate":"2021-01-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":815120,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70218778,"text":"70218778 - 2021 - Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty","interactions":[],"lastModifiedDate":"2021-05-13T15:53:26.945858","indexId":"70218778","displayToPublicDate":"2021-01-28T07:10:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty","docAbstract":"<ol class=\"\"><li>Operational satellite remote sensing products are transforming rangeland management and science. Advancements in computation, data storage and processing have removed barriers that previously blocked or hindered the development and use of remote sensing products. When combined with local data and knowledge, remote sensing products can inform decision‐making at multiple scales.</li><li>We used temporal convolutional networks to produce a fractional cover product that spans western United States rangelands. We trained the model with 52,012 on‐the‐ground vegetation plots to simultaneously predict fractional cover for annual forbs and grasses, perennial forbs and grasses, shrubs, trees, litter and bare ground. To assist interpretation and to provide a measure of prediction confidence, we also produced spatiotemporal‐explicit, pixel‐level estimates of uncertainty. We evaluated the model with 5,780 on‐the‐ground vegetation plots removed from the training data.</li><li>Model evaluation averaged 6.3% mean absolute error and 9.6% root mean squared error. Evaluation with additional datasets that were not part of the training dataset, and that varied in geographic range, method of collection, scope and size, revealed similar metrics. Model performance increased across all functional groups compared to the previously produced fractional product.</li><li>The advancements achieved with the new rangeland fractional cover product expand the management toolbox with improved predictions of fractional cover and pixel‐level uncertainty. The new product is available on the Rangeland Analysis Platform (https://rangelands.app/), an interactive web application that tracks rangeland vegetation through time. This product is intended to be used alongside local on‐the‐ground data, expert knowledge, land use history, scientific literature and other sources of information when making interpretations. When being used to inform decision‐making, remotely sensed products should be evaluated and utilized according to the context of the decision and not be used in isolation.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/2041-210X.13564","usgsCitation":"Allred, B.W., Bestelmeyer, B.T., Boyd, C.S., Brown, C., Davies, K.W., Duniway, M.C., Ellsworth, L.M., Erickson, T.A., Fuhlendorf, S.D., Griffiths, T.V., Jansen, V., Jones, M.O., Karl, J.W., Knight, A.C., Maestas, J.D., Maynard, J.J., McCord, S.E., Naugle, D., Starns, H.D., Twidwell, D., and Uden, D.R., 2021, Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty: Methods in Ecology and Evolution, v. 12, no. 5, p. 841-849, https://doi.org/10.1111/2041-210X.13564.","productDescription":"9 p.","startPage":"841","endPage":"849","ipdsId":"IP-122860","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":453676,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/2041-210x.13564","text":"External Repository"},{"id":384299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Allred, Brady W.","contributorId":255105,"corporation":false,"usgs":false,"family":"Allred","given":"Brady","email":"","middleInitial":"W.","affiliations":[{"id":51432,"text":"W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, 59812, USA","active":true,"usgs":false}],"preferred":false,"id":811805,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bestelmeyer, Brandon T.","contributorId":26180,"corporation":false,"usgs":false,"family":"Bestelmeyer","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":6973,"text":"USDA-ARS Jornada Experimental Range and Jornada Basin LTER, Las Cruces, NM; New Mexico State University, Dept. of Plant and Environmental Sciences, Las Cruces, NM","active":true,"usgs":false}],"preferred":false,"id":811806,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Chad S.","contributorId":255106,"corporation":false,"usgs":false,"family":"Boyd","given":"Chad","email":"","middleInitial":"S.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":811807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Christopher","contributorId":255107,"corporation":false,"usgs":false,"family":"Brown","given":"Christopher","affiliations":[{"id":51434,"text":"Google, Inc., Mountain View, CA 94043, USA","active":true,"usgs":false}],"preferred":false,"id":811808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Kirk W.","contributorId":255108,"corporation":false,"usgs":false,"family":"Davies","given":"Kirk","email":"","middleInitial":"W.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":811809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":811810,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ellsworth, Lisa M.","contributorId":255109,"corporation":false,"usgs":false,"family":"Ellsworth","given":"Lisa","email":"","middleInitial":"M.","affiliations":[{"id":51436,"text":"Fisheries and Wildlife Department, Oregon State University, Corvallis, Oregon 97331 USA","active":true,"usgs":false}],"preferred":false,"id":811811,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Erickson, Tyler A.","contributorId":255110,"corporation":false,"usgs":false,"family":"Erickson","given":"Tyler","email":"","middleInitial":"A.","affiliations":[{"id":51434,"text":"Google, Inc., Mountain View, CA 94043, USA","active":true,"usgs":false}],"preferred":false,"id":811812,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fuhlendorf, Samuel D.","contributorId":171488,"corporation":false,"usgs":false,"family":"Fuhlendorf","given":"Samuel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":811813,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Griffiths, Timothy V.","contributorId":255111,"corporation":false,"usgs":false,"family":"Griffiths","given":"Timothy","email":"","middleInitial":"V.","affiliations":[{"id":51437,"text":"USDA Natural Resources Conservation Service, Landscape Initiatives Team, Bozeman, MT 59715, USA","active":true,"usgs":false}],"preferred":false,"id":811814,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jansen, Vincent","contributorId":255112,"corporation":false,"usgs":false,"family":"Jansen","given":"Vincent","email":"","affiliations":[{"id":51438,"text":"Department of Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, ID 83844, USA","active":true,"usgs":false}],"preferred":false,"id":811815,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jones, Matthew O.","contributorId":169805,"corporation":false,"usgs":false,"family":"Jones","given":"Matthew","email":"","middleInitial":"O.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":811816,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Karl, Jason W.","contributorId":191703,"corporation":false,"usgs":false,"family":"Karl","given":"Jason","email":"","middleInitial":"W.","affiliations":[{"id":7045,"text":"USDA-ARS Jornada Experimental Range ","active":true,"usgs":false}],"preferred":false,"id":811817,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":811818,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Maestas, Jeremy D.","contributorId":219258,"corporation":false,"usgs":false,"family":"Maestas","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":39978,"text":"USDA Natural Resources Conservation Service, Redmond, OR","active":true,"usgs":false}],"preferred":false,"id":811819,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Maynard, Jonathan J.","contributorId":216782,"corporation":false,"usgs":false,"family":"Maynard","given":"Jonathan","email":"","middleInitial":"J.","affiliations":[{"id":39514,"text":"USDA-Agricultural Resource Service, Jornada Experimental Range, Las Cruces, NM 88003, USA","active":true,"usgs":false}],"preferred":false,"id":811820,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"McCord, Sarah E.","contributorId":195931,"corporation":false,"usgs":false,"family":"McCord","given":"Sarah","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":811821,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Naugle, David E.","contributorId":255114,"corporation":false,"usgs":false,"family":"Naugle","given":"David E.","affiliations":[{"id":51432,"text":"W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT, 59812, USA","active":true,"usgs":false}],"preferred":false,"id":811822,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Starns, Heath D.","contributorId":131091,"corporation":false,"usgs":false,"family":"Starns","given":"Heath","email":"","middleInitial":"D.","affiliations":[{"id":6960,"text":"Department of Biology, Texas State University","active":true,"usgs":false}],"preferred":false,"id":811823,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Twidwell, Dirac","contributorId":187431,"corporation":false,"usgs":false,"family":"Twidwell","given":"Dirac","email":"","affiliations":[],"preferred":false,"id":811824,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Uden, Daniel R.","contributorId":219904,"corporation":false,"usgs":false,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[{"id":40095,"text":"Nebraska Cooperative Fish and Wildlife Unit, School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE","active":true,"usgs":false}],"preferred":false,"id":811825,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70219193,"text":"70219193 - 2021 - Channel response to a dam‐removal sediment pulse captured at high‐temporal resolution using routine gage data","interactions":[],"lastModifiedDate":"2021-06-01T17:29:08.413936","indexId":"70219193","displayToPublicDate":"2021-01-28T07:07:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7951,"text":"Earth Surfaces Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Channel response to a dam‐removal sediment pulse captured at high‐temporal resolution using routine gage data","docAbstract":"<p>In this study, we captured how a river channel responds to a sediment pulse originating from a dam removal using multiple lines of evidence derived from streamflow gages along the Patapsco River, Maryland, USA. Gages captured characteristics of the sediment pulse, including travel times of its leading edge (~7.8 km yr<sup>−1</sup>) and peak (~2.6 km yr<sup>−1</sup>) and suggest both translation and increasing dispersion. The pulse also changed local hydraulics and energy conditions, increasing flow velocities and Froude number, due to bed fining, homogenization and/or slope adjustment. Immediately downstream of the dam, recovery to pre‐pulse conditions occurred within the year, but farther downstream recovery was slower, with the tail of the sediment pulse working through the lower river by the end of the study 7 years later.</p><p>The patterns and timing of channel change associated with the sediment pulse were not driven by large flow or suspended sediment‐transporting events, with change mostly occurring during lower flows. This suggests pulse mobility was controlled by process‐factors largely independent of high flow.</p><p>In contrast, persistent changes occurred to out‐of‐channel flooding dynamics. Stage associated with flooding increased during the arrival of the sediment pulse, 1 to 2 years after dam removal, suggesting persistent sediment deposition at the channel margins and nearby floodplain. This resulted in National Weather Service‐indicated flood stages being attained by 3–43% smaller discharges compared to earlier in the study period.</p><p>This study captured a two‐signal response from the sediment pulse: (1) short‐ to medium‐term (weeks to months) translation and dispersion within the channel, resulting in aggradation and recovery of bed elevations and changing local hydraulics; and (2) dispersion and persistent longer‐term (years) effects of sediment deposition on overbank surfaces. This study further demonstrated the utility of US Geological Survey gage data to quantify geomorphic change, increase temporal resolution, and provide insights into trajectories of change over varying spatial and temporal scales.</p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5083","usgsCitation":"Cashman, M.J., Gellis, A.C., Boyd, E.L., Collins, M.J., Anderson, S.W., Mcfarland, B.D., and Ryan, A.M., 2021, Channel response to a dam‐removal sediment pulse captured at high‐temporal resolution using routine gage data: Earth Surfaces Processes and Landforms, v. 46, no. 6, p. 1145-1159, https://doi.org/10.1002/esp.5083.","productDescription":"15 p.","startPage":"1145","endPage":"1159","ipdsId":"IP-113441","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"links":[{"id":436533,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9REXNQ9","text":"USGS data release","linkHelpText":"Data for Specific Gage Analysis on the Patapsco River, 2010-2017"},{"id":384751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United  States","state":"Maryland","otherGeospatial":"Patapsco River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.9317626953125,\n              39.38738660316804\n            ],\n            [\n              -76.98257446289062,\n              39.35394512666976\n            ],\n            [\n              -76.88438415527344,\n              39.31198794598777\n            ],\n            [\n              -76.8218994140625,\n              39.29976783250087\n            ],\n            [\n              -76.7999267578125,\n              39.26043647112078\n            ],\n            [\n              -76.75666809082031,\n              39.216295294574024\n            ],\n            [\n              -76.68937683105469,\n              39.21097520599528\n            ],\n            [\n              -76.60697937011719,\n              39.22480659786848\n            ],\n            [\n              -76.9317626953125,\n              39.38738660316804\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"46","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-03-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":813165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Eric L. 0000-0002-1473-967X","orcid":"https://orcid.org/0000-0002-1473-967X","contributorId":256743,"corporation":false,"usgs":true,"family":"Boyd","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, Matthias J. 0000-0003-4238-2038","orcid":"https://orcid.org/0000-0003-4238-2038","contributorId":196365,"corporation":false,"usgs":false,"family":"Collins","given":"Matthias","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":813168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813169,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mcfarland, Brett Dare 0000-0002-2941-4966","orcid":"https://orcid.org/0000-0002-2941-4966","contributorId":256744,"corporation":false,"usgs":true,"family":"Mcfarland","given":"Brett","email":"","middleInitial":"Dare","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813170,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ryan, Ashley Mattie 0000-0001-5647-7447","orcid":"https://orcid.org/0000-0001-5647-7447","contributorId":256746,"corporation":false,"usgs":true,"family":"Ryan","given":"Ashley","email":"","middleInitial":"Mattie","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true}],"preferred":true,"id":813171,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70217664,"text":"sir20205121 - 2021 - Spring types and contributing aquifers from water-chemistry and multivariate statistical analyses for seeps and springs in Theodore Roosevelt National Park, North Dakota, 2018","interactions":[],"lastModifiedDate":"2021-01-28T01:29:43.632301","indexId":"sir20205121","displayToPublicDate":"2021-01-27T16:00:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5121","displayTitle":"Spring Types and Contributing Aquifers from Water-Chemistry and Multivariate Statistical Analyses for Seeps and Springs in Theodore Roosevelt National Park, North Dakota, 2018","title":"Spring types and contributing aquifers from water-chemistry and multivariate statistical analyses for seeps and springs in Theodore Roosevelt National Park, North Dakota, 2018","docAbstract":"<p>Water resources in Theodore Roosevelt National Park, North Dakota, support wildlife, visitors, and staff, and play a vital role in supporting the native ecology of the park. The U.S. Geological Survey, in cooperation with the National Park Service, completed field work in 2018 for a study to address concerns about water availability and possible sources of groundwater contamination for seeps and springs in Theodore Roosevelt National Park. The objective of the study was to improve hydrologic knowledge and determine the water composition of 11 seeps and springs in the park by collecting water-chemistry data at springs, streams, wells, and rain collectors.</p><p>Water samples were collected at 26 sites at springs, streams, wells, and rain collectors in the North and South Units of Theodore Roosevelt National Park. Samples in the North Unit were collected at 5 springs, 1 stream, 2 wells, and 1 rain collector. Samples in the South Unit were collected at 6 springs, 2 streams, 8 wells, and 1 rain collector. Samples from springs, streams, and wells were collected in May, July, and September 2018. Samples from rain collectors were collected when enough daily precipitation accumulated in the collectors. Sampled precipitation events during the study period were in May, June, July, August, and September 2018. Physical properties of sampled water—temperature, pH, and specific conductance—were measured in the field. Water samples were analyzed for stable isotopes of oxygen and hydrogen and for chloride concentration. Recharge rates for aquifers supplying springs were determined using precipitation volume and chloride concentrations for a 12-day period before the sample-collection date. Multivariate statistical analysis methods used on water-chemistry data included principal component analysis, cluster analysis, and end-member mixing analysis.</p><p>Water composition was used to determine the spring type and contributing aquifers for 11 springs in the North and South Units of Theodore Roosevelt National Park from analyses of water-chemistry data between May and September 2018. In the North Unit, Achenbach Spring was classified as a filtration spring with water from an unconfined part of the upper Fort Union aquifer and infiltration of precipitation. Hagen Spring, Mandal Spring, and Stevens Spring were classified as contact springs supplied by semiconfined parts of the upper Fort Union aquifer. Overlook Spring at one time may have been a natural spring or seep but now is a developed spring that behaves like a flowing artesian well completed in a confined part of the upper Fort Union aquifer. In the South Unit, six springs were classified into two spring types: filtration and contact springs. Boicourt Spring and Sheep Butte Spring were classified as filtration springs that have water supplied by unconfined parts of the upper Fort Union aquifer and infiltrated precipitation. Big Plateau Spring, Lone Tree Spring, Sheep Pasture Spring, and Southeast Corner Spring were classified as contact springs that receive waters from a semiconfined part of the upper Fort Union aquifer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20205121","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Medler, C.J., and Eldridge, W.G., 2021, Spring types and contributing aquifers from water-chemistry and multivariate statistical analyses for seeps and springs in Theodore Roosevelt National Park, North Dakota, 2018: U.S. Geological Survey Scientific Investigations Report 2020–5121, 48 p., https://doi.org/10.3133/sir20205121.","productDescription":"Report: viii, 48 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-115769","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":382693,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5121/coverthb.jpg"},{"id":382694,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5121/sir20205121.pdf","text":"Report","size":"4.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"sir2020-5121"},{"id":382695,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database"}],"country":"United States","state":"North Dakota","otherGeospatial":"Theodore Roosevelt National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.63334655761719,\n              46.87990702860922\n            ],\n            [\n              -103.29757690429686,\n              46.87990702860922\n            ],\n            [\n              -103.29757690429686,\n              47.02801434856074\n            ],\n            [\n              -103.63334655761719,\n              47.02801434856074\n            ],\n            [\n              -103.63334655761719,\n              46.87990702860922\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.48983764648438,\n              47.52832925298343\n            ],\n            [\n              -103.216552734375,\n              47.52832925298343\n            ],\n            [\n              -103.216552734375,\n              47.65428791076272\n            ],\n            [\n              -103.48983764648438,\n              47.65428791076272\n            ],\n            [\n              -103.48983764648438,\n              47.52832925298343\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.63677978515625,\n              47.22726254715105\n            ],\n            [\n              -103.60965728759764,\n              47.22726254715105\n            ],\n            [\n              -103.60965728759764,\n              47.250106104326235\n            ],\n            [\n              -103.63677978515625,\n              47.250106104326235\n            ],\n            [\n              -103.63677978515625,\n              47.22726254715105\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/dakota-water/\" data-mce-href=\"https://www.usgs.gov/centers/dakota-water/\">Dakota Water Science Center</a><br>U.S. Geological Survey<br>821 East Interstate Avenue<br>Bismarck, ND 58503<br><br>1608 Mountain View Road<br>Rapid City, SD 57702</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods for Sample Collection and Water-Chemistry Data Analysis</li><li>Water-Chemistry and Multivariate Statistical Analyses</li><li>Spring Types and Contributing Aquifers</li><li>Data and Method Limitations</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Principal Component Analysis and Cluster Analysis with Water-Chemistry Data from a 1980s National Park Service Study in Theodore Roosevelt National Park</li></ul>","publishedDate":"2021-01-27","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Medler, Colton J. 0000-0001-6119-5065","orcid":"https://orcid.org/0000-0001-6119-5065","contributorId":201463,"corporation":false,"usgs":true,"family":"Medler","given":"Colton","email":"","middleInitial":"J.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809196,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eldridge, William G. 0000-0002-3562-728X","orcid":"https://orcid.org/0000-0002-3562-728X","contributorId":208529,"corporation":false,"usgs":true,"family":"Eldridge","given":"William","email":"","middleInitial":"G.","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809197,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70217663,"text":"sir20205134 - 2021 - Groundwater flow conceptualization of the Pahute Mesa–Oasis Valley Groundwater Basin, Nevada—A synthesis of geologic, hydrologic, hydraulic-property, and tritium data","interactions":[],"lastModifiedDate":"2021-01-28T01:40:20.23064","indexId":"sir20205134","displayToPublicDate":"2021-01-27T12:05:58","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-5134","displayTitle":"Groundwater Flow Conceptualization of the Pahute Mesa–Oasis Valley Groundwater Basin, Nevada: A Synthesis of Geologic, Hydrologic, Hydraulic-Property, and Tritium Data","title":"Groundwater flow conceptualization of the Pahute Mesa–Oasis Valley Groundwater Basin, Nevada—A synthesis of geologic, hydrologic, hydraulic-property, and tritium data","docAbstract":"<p class=\"x_Pa27\"><span>This report provides a groundwater-flow conceptualization that integrates geologic, hydrologic, hydraulic-property, and radionuclide data in the Pahute Mesa–Oasis Valley (PMOV) groundwater basin, southern Nevada. Groundwater flow in the PMOV basin is of interest because 82 underground nuclear tests were detonated, most near or below the water table. A potentiometric map and nine sets of hydrostratigraphic and hydrologic cross sections supplement the conceptualization.&nbsp;</span></p><p class=\"x_Pa27\"><span>Potentiometric contours indicate that groundwater in the PMOV basin generally flows south-southwest and discharges at Oasis Valley. Groundwater encounters an alternating sequence of low- and high-transmissivity rocks, referred to as dams and pools, respectively, as it moves from east to west across eastern Pahute Mesa. Flow from all Pahute Mesa nuclear tests is to Oasis Valley and is well-constrained by water-level data. Flow converges along a corridor of high transmissivity between Pahute Mesa and Oasis Valley.&nbsp;</span></p><p class=\"x_Pa27\"><span>The location of the lateral PMOV basin boundary is well defined, and this boundary, with a few minor exceptions, represents a no-flow boundary. Some boundary uncertainty exists in the northeastern part of the basin, but potential flow-rate estimates across the northeastern boundary resulting from this uncertainty are small relative to the basin groundwater budget.&nbsp;</span></p><p class=\"x_Pa27\"><span>Recharge in the PMOV basin is derived from episodic pulses of modern water and the diffuse percolation of old water (greater than 1,000 years). Episodic recharge is a minor recharge component observed as a rise in groundwater levels that occurs 3 months to 1 year following a wet winter. Minor amounts of episodic recharge through an unsaturated zone in excess of 1,000 feet (ft) requires preferential flow through faults and fractures. The dominant recharge component is slow, steady, diffuse percolation of old water through the unsaturated zone. A large component of old water recharging the groundwater system is consistent with observations of isotopically light deuterium and oxygen 18 compositions in water from wells on Pahute Mesa and central Oasis Valley. About half the recharge in the PMOV basin is derived from the eastern Pahute Mesa area. The remaining recharge is derived primarily from other highland areas including Timber Mountain, Belted and Kawich Ranges, and Black Mountain.&nbsp;</span></p><p class=\"x_Pa27\"><span>The PMOV groundwater system is nearly steady state, where recharge is balanced by the 5,900 acre-feet per year of natural discharge at Oasis Valley. This assumption is reasonable because the basin is dominated by steady-state conditions, where long-term changes in groundwater storage are minimal. Total groundwater withdrawals from 1963 to 2018 have amounted to less than 10 percent of annual groundwater discharge and less than 0.2 percent of the basin’s groundwater storage. Therefore, present-day (2020) conditions are considered representative of predevelopment (pre-1950) conditions in nearly all areas of the basin.&nbsp;</span></p><p class=\"x_Pa27\"><span>The lower PMOV basin boundary is defined at 4,000 ft below the water table to encompass all underground nuclear tests and tritium plumes. This boundary defines the lower boundary of radionuclide migration. However, nearly all flow and tritium transport occur in the upper 1,600 ft of the saturated zone because a transmissivity-with-depth relation indicates that greater than 90 percent of the transmissivity contributing to groundwater flow occurs within 1,600 ft of the water table. Rocks at deeper depths have low transmissivity because argillic and mineralized alterations plug the fractures.&nbsp;</span></p><p class=\"x_Default\"><span>Volcanic rocks form the primary aquifers and confining units in the PMOV basin. Volcanic hydrogeologic units (HGUs) and hydrostratigraphic units (HSUs) have transmissivity distributions that span up to eight orders of magnitude with considerable overlap between distributions. Despite the large overlap between units, mean transmissivities of aquifers are one-to-two orders of magnitude greater than the confining units. However, all volcanic-rock HGUs and HSUs are composite units, meaning that they can function spatially as either an aquifer or confining unit</span><span>.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205134","collaboration":"Prepared in cooperation with the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office, Office of Environmental Management under Interagency Agreement, DE-EM0004969","usgsCitation":"Jackson, T.R., Fenelon, J.M., and Paylor, R.L., 2021, Groundwater flow conceptualization of the Pahute Mesa–Oasis Valley Groundwater Basin, Nevada—A synthesis of geologic, hydrologic, hydraulic-property, and tritium data: U.S. Geological Survey Scientific Investigations Report 2020–5134, 100 p., https://doi.org/10.3133/sir20205134.","productDescription":"Report: viii, 100 p.; 2 Plates: 26.00 x 42.00 inches and 120.01 x 36.00 inches; 7 Appendixes","onlineOnly":"Y","ipdsId":"IP-095406","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":382683,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix2.xlsx","text":"Appendix 2","size":"78 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 2"},{"id":382684,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix3.xlsm","text":"Appendix 3","size":"530 KB xlsm","description":"SIR 2020-5134 Appendix 3"},{"id":382685,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix4.xlsx","text":"Appendix 4","size":"6.1 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 4"},{"id":382681,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_plate02.pdf","text":"Plate 2","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5134 Plate 2"},{"id":382678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5134/coverthb.jpg"},{"id":382679,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134.pdf","text":"Report","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5134"},{"id":382680,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_plate01.pdf","text":"Plate 1","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5134 Plate 1"},{"id":382682,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix1.xlsx","text":"Appendix 1","size":"2.5 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 1"},{"id":382688,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix7.xlsx","text":"Appendix 7","size":"433 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 7"},{"id":382687,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix6.xlsx","text":"Appendix 6","size":"856 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 6"},{"id":382686,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5134/sir20205134_appendix5.xlsx","text":"Appendix 5","size":"799 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020-5134 Appendix 5"}],"country":"United States","state":"Nevada","otherGeospatial":"Pahute Mesa–Oasis Valley Groundwater Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.00,\n              36.65079252503471\n            ],\n            [\n              -116.00,\n              36.65079252503471\n            ],\n            [\n              -116.00,\n              38.00\n            ],\n            [\n              -117.00,\n              38.00\n            ],\n            [\n              -117.00,\n              36.65079252503471\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_nv@usgs.gov\" data-mce-href=\"mailto:dc_nv@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/nv-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/nv-water\">Nevada Water Science Center</a><br>U.S. Geological Survey<br>2730 N. Deer Run Road<br>Carson City, Nevada 95819</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Study Methods</li><li>Hydraulic-Property and Rock-Alteration Analyses</li><li>Groundwater Flow Conceptualization of the Pahute Mesa–Oasis Valley Groundwater Basin</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Appendixes 1–7</li></ul>","publishedDate":"2021-01-27","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Jackson, Tracie R. 0000-0001-8553-0323 tjackson@usgs.gov","orcid":"https://orcid.org/0000-0001-8553-0323","contributorId":150591,"corporation":false,"usgs":true,"family":"Jackson","given":"Tracie","email":"tjackson@usgs.gov","middleInitial":"R.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":809193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fenelon, Joseph M. 0000-0003-4449-245X jfenelon@usgs.gov","orcid":"https://orcid.org/0000-0003-4449-245X","contributorId":2355,"corporation":false,"usgs":true,"family":"Fenelon","given":"Joseph","email":"jfenelon@usgs.gov","middleInitial":"M.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":809194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paylor, Randall L. 0000-0002-1059-6384","orcid":"https://orcid.org/0000-0002-1059-6384","contributorId":248456,"corporation":false,"usgs":true,"family":"Paylor","given":"Randall","email":"","middleInitial":"L.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":809195,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70229376,"text":"70229376 - 2021 - Estimating detection and occupancy coefficients for the Pacific Islands coral reef fish species","interactions":[],"lastModifiedDate":"2022-03-04T17:38:48.028579","indexId":"70229376","displayToPublicDate":"2021-01-27T11:23:36","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":6053,"text":"Hawaii Cooperative Studies Unit Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"HCFRU-001","title":"Estimating detection and occupancy coefficients for the Pacific Islands coral reef fish species","docAbstract":"<p><span>The data-limited stock assessment models used to monitor the status of coral reef fish species in the Western Pacific region are dependent upon accurate estimates of standing stock biomass generated from underwater visual surveys of reefs. However, the imperfect detection of and variable occupancy of habitat by reef fishes are not currently accounted for in these estimates. Therefore, the objective of this project was to estimate detection and occupancy coefficients for the species listed in the Western Pacific Regional Fishery Management Council’s Fishery Ecosystem Plans by analyzing the Pacific Island Fishery Science Center-Coral Reef Ecosystem Program Reef Fish Dataset. These detection and occupancy coefficients would then be applied to refine standing stock biomass estimates. In general, species with higher detection probabilities and/or lower occupancy rates tended to exhibit the greatest differences in the estimates of standing stock biomass calculated with and without accounting for detection and occupancy. The standing stock biomass of most reef fish species seem to be underestimated when detection and occupancy are not accounted for. However, the standing stock biomass of larger-bodied targeted species, such as jacks, snappers, and groupers, seem to be over-estimated relative to the estimates generated when accounting for occupancy and detection. While there are still issues to resolve regarding how well the current data collection methods meet the underlying assumptions of the detection and occupancy modeling approach, the inclusion of detection and occupancy coefficients seems likely to improve estimates of standing stock biomass of coral reef fish species.</span></p>","language":"English","publisher":"Hawaii Cooperative Research Studies Unit","collaboration":"Western Pacific Regional Fishery Management Council","usgsCitation":"Suarez, B., and Grabowski, T.B., 2021, Estimating detection and occupancy coefficients for the Pacific Islands coral reef fish species: Hawaii Cooperative Studies Unit Technical Report HCFRU-001, 22 p.","productDescription":"22 p.","ipdsId":"IP-124358","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":396761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396760,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dspace.lib.hawaii.edu/handle/10790/5553"}],"country":"Marianas Islands, United States","state":"Hawaii","otherGeospatial":"Pacific Remote Island Area,, Samoa","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Suarez, Bobbie","contributorId":287958,"corporation":false,"usgs":false,"family":"Suarez","given":"Bobbie","email":"","affiliations":[{"id":25429,"text":"UH","active":true,"usgs":false}],"preferred":false,"id":837231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":837230,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70218237,"text":"70218237 - 2021 - Forecasting community reassembly using climate-linked spatio-temporal ecosystem models","interactions":[],"lastModifiedDate":"2021-04-08T14:55:31.493847","indexId":"70218237","displayToPublicDate":"2021-01-27T10:55:28","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting community reassembly using climate-linked spatio-temporal ecosystem models","docAbstract":"<p><span>Ecosystems are increasingly impacted by human activities, altering linkages among physical and biological components. Spatial community reassembly occurs when these human impacts modify the spatial overlap between system components, and there is need for practical tools to forecast spatial community reassembly at landscape scales using monitoring data. To illustrate a new approach, we extend a generalization of empirical orthogonal function (EOF) analysis, which involves a spatio‐temporal ecosystem model that approximates coupled physical, biological and human dynamics. We then demonstrate its application to five trophic levels for the eastern Bering Sea by fitting to multiple, spatially unbalanced datasets measuring physical characteristics (temperature measurements and climate‐linked forecasts), primary producers (spring and fall size‐fractionated chlorophyll‐a), secondary producers (copepods), juveniles (age‐0 walleye pollock), adult consumers (five commercially important fishes), human activities (seasonal fishing effort) and mobile predators (seabirds). We identify the spatial niche for each ecosystem component, as well as dominant modes of variability that are highly correlated with a known bottom–up driver of dynamics. We then measure spatial overlap between interacting variables (using Schoener's‐D) and identify that age‐0 pollock have decreased spatial overlap with copepods and increased overlap with adult pollock during warm years, and also that adult pollock have increased overlap with arrowtooth flounder and decreased overlap with catcher–processor fishing effort during these warm years. Given the warming conditions that are projected for the coming decade, the model forecasts increased prey and competitor overlap involving adult pollock (between age‐0 pollock, adult pollock and arrowtooth flounder) and decreased overlap with the copepod forage base and with the catcher–processor fishery during future warming. We recommend that joint species distribution models be extended to incorporate ‘ecological teleconnections' (correlations between distant locations arising from known mechanisms) arising from behavioral adaptation by mobile animals as well as passive advection of nutrients and planktonic juvenile stages.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/ecog.05471","usgsCitation":"Thorson, J., Arimitsu, M.L., Barnett, L., Cheng, W., Eisner, L., Haynie, A., Hermann, A., Holsman, K., Kimmel, D., Lomas, M., Richar, J., and Siddon, E., 2021, Forecasting community reassembly using climate-linked spatio-temporal ecosystem models: Ecography, v. 44, no. 4, p. 612-625, https://doi.org/10.1111/ecog.05471.","productDescription":"14 p.","startPage":"612","endPage":"625","ipdsId":"IP-119434","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":453681,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ecog.05471","text":"Publisher Index Page"},{"id":383367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Thorson, James","contributorId":251785,"corporation":false,"usgs":false,"family":"Thorson","given":"James","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":810580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnett, Lewis","contributorId":251786,"corporation":false,"usgs":false,"family":"Barnett","given":"Lewis","affiliations":[{"id":50398,"text":"JISAO","active":true,"usgs":false}],"preferred":false,"id":810581,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheng, Wei","contributorId":251787,"corporation":false,"usgs":false,"family":"Cheng","given":"Wei","email":"","affiliations":[{"id":50399,"text":"JISAO, NOAA","active":true,"usgs":false}],"preferred":false,"id":810582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eisner, Lisa","contributorId":251788,"corporation":false,"usgs":false,"family":"Eisner","given":"Lisa","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810583,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haynie, Alan","contributorId":251789,"corporation":false,"usgs":false,"family":"Haynie","given":"Alan","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810584,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hermann, Albert","contributorId":251790,"corporation":false,"usgs":false,"family":"Hermann","given":"Albert","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810585,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Holsman, Kirsten","contributorId":251791,"corporation":false,"usgs":false,"family":"Holsman","given":"Kirsten","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810586,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kimmel, David","contributorId":251792,"corporation":false,"usgs":false,"family":"Kimmel","given":"David","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810587,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lomas, Michael","contributorId":251793,"corporation":false,"usgs":false,"family":"Lomas","given":"Michael","affiliations":[{"id":50400,"text":"Bigelow Lab for Ocean Sciences","active":true,"usgs":false}],"preferred":false,"id":810588,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Richar, Jon","contributorId":251794,"corporation":false,"usgs":false,"family":"Richar","given":"Jon","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810589,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Siddon, Elizabeth","contributorId":251795,"corporation":false,"usgs":false,"family":"Siddon","given":"Elizabeth","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":810590,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70228505,"text":"70228505 - 2021 - An inventory and typology of permanent floodplain lakes in the Mississippi alluvial valley: A first step to conservation planning","interactions":[],"lastModifiedDate":"2022-02-11T17:04:24.12061","indexId":"70228505","displayToPublicDate":"2021-01-27T10:51:06","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"An inventory and typology of permanent floodplain lakes in the Mississippi alluvial valley: A first step to conservation planning","docAbstract":"The alluvial valley of the Mississippi River is an extensive area harboring hundreds of lakes created by fluvial dynamics. These floodplain lakes are scattered throughout the valley and carved over thousands of years by shifting river courses and other hydro-fluvial processes associated with contemporary and prehistoric rivers. These lakes have significant ecological importance as they support a large component of North American biodiversity. We used remote sensing to catalog lakes, to characterize morphology, and to construct a typology via cluster analysis. We identified over 1,300 permanent lakes totaling over 100,000 ha. The lakes were classified into 12 types according to lake size, shape, depth, connectivity, inundation frequency, and surrounding landcover. We anticipate that biotic characteristics differ among the 12 types, but large-scale systematic analyses of biotic assemblages of floodplain lakes in the region are mostly absent. Our typology can provide the framework essential for organizing research to define water dynamics, water quality, and ecological conditions such as forests, mussel, fish, and avian communities to construct conservation plans. The typology encourages a large-scale view of the properties of floodplain lakes in the alluvial valley. It is a functional tool that can be used to begin identifying conservation and research needs, adapt monitoring and management programs, customize environmental programs, and use conservation resources more effectively to achieve large-scale management objectives. ","language":"English","publisher":"Springer","doi":"10.1007/s00027-020-00775-3","usgsCitation":"Miranda, L.E., Rhodes, M., Allen, Y., and Killgore, K., 2021, An inventory and typology of permanent floodplain lakes in the Mississippi alluvial valley: A first step to conservation planning: Aquatic Sciences, v. 83, 20, 11 p., https://doi.org/10.1007/s00027-020-00775-3.","productDescription":"20, 11 p.","ipdsId":"IP-117209","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395851,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.56054687499999,\n              37.09023980307208\n            ],\n            [\n              -90.19775390625,\n              36.63316209558658\n            ],\n            [\n              -91.25244140624999,\n              35.02999636902566\n            ],\n            [\n              -91.64794921875,\n              33.99802726234877\n            ],\n            [\n              -92.3291015625,\n              32.69486597787505\n            ],\n            [\n              -92.43896484375,\n              31.316101383495624\n            ],\n            [\n              -92.04345703125,\n              29.82158272057499\n            ],\n            [\n              -90.90087890624999,\n              29.11377539511439\n            ],\n            [\n              -89.7802734375,\n              28.9600886880068\n            ],\n            [\n              -89.296875,\n              29.916852233070173\n            ],\n            [\n              -89.80224609374999,\n              30.44867367928756\n            ],\n            [\n              -91.16455078125,\n              30.44867367928756\n            ],\n            [\n              -90.9228515625,\n              31.784216884487385\n            ],\n            [\n              -90.68115234375,\n              32.97180377635759\n            ],\n            [\n              -90.3515625,\n              34.14363482031264\n            ],\n            [\n              -89.18701171875,\n              36.03133177633187\n            ],\n            [\n              -88.681640625,\n              37.020098201368114\n            ],\n            [\n              -89.56054687499999,\n              37.09023980307208\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"83","noUsgsAuthors":false,"publicationDate":"2021-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rhodes, M.C.","contributorId":275997,"corporation":false,"usgs":false,"family":"Rhodes","given":"M.C.","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":834460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Y.","contributorId":275998,"corporation":false,"usgs":false,"family":"Allen","given":"Y.","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":834461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Killgore, K.J.","contributorId":200191,"corporation":false,"usgs":false,"family":"Killgore","given":"K.J.","email":"","affiliations":[{"id":33009,"text":"Engineer Research and Development Center, U. S. Army Corps of Engineers, Vicksburg, Mississippi","active":true,"usgs":false}],"preferred":false,"id":834462,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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