{"pageNumber":"613","pageRowStart":"15300","pageSize":"25","recordCount":165296,"records":[{"id":70209418,"text":"70209418 - 2020 - Economic valuation of health benefits from using geologic data to communicate radon risk potential","interactions":[],"lastModifiedDate":"2023-12-01T21:15:36.519346","indexId":"70209418","displayToPublicDate":"2020-03-20T09:45:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5522,"text":"Environmental Health","onlineIssn":"1476-069X","active":true,"publicationSubtype":{"id":10}},"title":"Economic valuation of health benefits from using geologic data to communicate radon risk potential","docAbstract":"<p>Background: Radon exposure is the second leading cause of lung cancer worldwide and represents a major health concern within and outside the United States. Mitigating exposure to radon is especially critical in places with high rates of tobacco smoking (e.g., Kentucky, USA), as radon-induced lung cancer is markedly greater among people exposed to tobacco smoke. Despite homes being a common source of radon exposure, convincing homeowners to test and mitigate for radon remains a challenge. A new communication strategy to increase radon testing among Kentucky homeowners utilizes fine-scale geologic map data to create detailed radon risk potential maps. We assessed the health benefits of this strategy via avoided lung cancer and associated premature mortality and quantified the economic value of these benefits to indicate the potential utility of using geologic map data in radon communication strategies. Methods: We estimated the change in radon testing among all 120 counties in Kentucky following a new communication strategy reliant on geologic maps. We approximated the resultant potential change in radon mitigation rates and subsequent expected lung cancer cases and mortality avoided among smokers and non-smokers exposed to ≥4 pCi/L of radon in the home. We then applied the value of a statistical life to derive the economic value of the expected avoided mortality. Results: The new communication strategy is estimated to help 75 Kentucky residents in one year avoid exposure to harmful radon levels via increased testing and mitigation rates. This equated to the potential avoidance of approximately one premature death due to lung cancer, with a net present value of \\$3.4 to \\$8.5 million (2016 USD). Conclusions: Our analysis illustrates the potential economic value of health benefits associated with geologic map data used as part of a communication strategy conveying radon risk to the public. Geologic map data are freely available in varying resolutions throughout the United States, suggesting Kentucky’s radon communication strategy using geologic maps can be employed in other states to educate the public about radon. As this is only a single application, in a single state, the economic and health benefits of geologic map data in educating the public about radon are likely to exceed our estimates.</p>","language":"English","publisher":"Springer","doi":"10.1186/s12940-020-00589-8","usgsCitation":"Chiavacci, S.J., Shapiro, C.D., Pindilli, E., Casey, C.F., Rayens, M.K., Wiggins, A.T., Andrews, W.M., and Hahn, E.J., 2020, Economic valuation of health benefits from using geologic data to communicate radon risk potential: Environmental Health, v. 19, 36, 9 p., https://doi.org/10.1186/s12940-020-00589-8.","productDescription":"36, 9 p.","ipdsId":"IP-110968","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":457301,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12940-020-00589-8","text":"Publisher Index Page"},{"id":373860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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epindilli@usgs.gov","orcid":"https://orcid.org/0000-0002-5101-1266","contributorId":140262,"corporation":false,"usgs":true,"family":"Pindilli","given":"Emily","email":"epindilli@usgs.gov","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":786436,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casey, Clyde F. 0000-0001-6960-5129","orcid":"https://orcid.org/0000-0001-6960-5129","contributorId":223854,"corporation":false,"usgs":true,"family":"Casey","given":"Clyde","email":"","middleInitial":"F.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":786434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rayens, Mary Kay 0000-0001-8465-8763","orcid":"https://orcid.org/0000-0001-8465-8763","contributorId":223855,"corporation":false,"usgs":false,"family":"Rayens","given":"Mary","email":"","middleInitial":"Kay","affiliations":[{"id":40779,"text":"University of Kentucky College of Nursing","active":true,"usgs":false}],"preferred":false,"id":786435,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiggins, Amanda T.","contributorId":223881,"corporation":false,"usgs":false,"family":"Wiggins","given":"Amanda","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":786543,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Andrews, William M. Jr.","contributorId":51406,"corporation":false,"usgs":true,"family":"Andrews","given":"William","suffix":"Jr.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":786544,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hahn, Ellen J.","contributorId":223882,"corporation":false,"usgs":false,"family":"Hahn","given":"Ellen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":786545,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70228430,"text":"70228430 - 2020 - Electrofishing encounter probability, survival, and dispersal of stocked age-0 Muskellunge in Wisconsin lakes","interactions":[],"lastModifiedDate":"2022-02-10T15:05:58.812086","indexId":"70228430","displayToPublicDate":"2020-03-20T08:58:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Electrofishing encounter probability, survival, and dispersal of stocked age-0 Muskellunge in Wisconsin lakes","docAbstract":"<p><span>Boat electrofishing is often used to sample age-0 Muskellunge&nbsp;</span><i>Esox masquinongy</i><span>&nbsp;for indexing recruitment or evaluating stocking success. However, electrofishing samples typically result in low CPUE, prompting concerns regarding whether catch rates reflect actual abundance or whether boat electrofishing is generally ineffective for capturing age-0 Muskellunge (i.e., if fish are not being encountered by the gear). To address these concerns, we used radiotelemetry to evaluate the probability of encountering stocked age-0 Muskellunge (230–350&nbsp;mm TL) during standardized fall electrofishing surveys in three Wisconsin lakes. Our approach also allowed us to evaluate short-term survival and dispersal from stocking locations. Despite limited dispersal (&lt;2.5&nbsp;km) from the stocking locations and relatively high short-term survival (75–94%) of radio-tagged fish, few age-0 Muskellunge were located within the path of the electrofishing boat (7–30%). Furthermore, the probability of encounter by boat electrofishing varied by as much as 6.3 times among lakes. Differences in encounter probability among lakes appeared to be related to lake basin and habitat characteristics. Overlays of electrofishing sampling effort and fish locations revealed that traditional shoreline electrofishing may not be an effective way of estimating age-0 Muskellunge CPUE. Modifications to electrofishing protocols, including increased effort in offshore areas and consideration of basin characteristics and habitat, may be needed to increase encounter probabilities and the utility of boat electrofishing for sampling age-0 Muskellunge.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10418","usgsCitation":"Dembkowski, D., Kerns, J.A., Easterly, E.G., and Isermann, D.A., 2020, Electrofishing encounter probability, survival, and dispersal of stocked age-0 Muskellunge in Wisconsin lakes: North American Journal of Fisheries Management, v. 40, no. 2, p. 383-393, https://doi.org/10.1002/nafm.10418.","productDescription":"11 p.","startPage":"383","endPage":"393","ipdsId":"IP-111289","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Stella Lake, Twin Valley Lake, Upper Gresham Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.21207427978516,\n              45.70557989372282\n            ],\n            [\n              -89.17963027954102,\n              45.70557989372282\n            ],\n            [\n              -89.17963027954102,\n              45.72236042939562\n            ],\n            [\n              -89.21207427978516,\n              45.72236042939562\n            ],\n            [\n              -89.21207427978516,\n              45.70557989372282\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -89.75199222564697,\n              46.06087385306044\n            ],\n            [\n              -89.723,\n              46.06087385306044\n            ],\n            [\n              -89.723,\n              46.07721993221842\n            ],\n            [\n              -89.75199222564697,\n              46.07721993221842\n            ],\n            [\n              -89.75199222564697,\n              46.06087385306044\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -90.10273933410645,\n              43.01569327500512\n            ],\n            [\n              -90.08136749267578,\n              43.01569327500512\n            ],\n            [\n              -90.08136749267578,\n              43.03708953184211\n            ],\n            [\n              -90.10273933410645,\n              43.03708953184211\n            ],\n            [\n              -90.10273933410645,\n              43.01569327500512\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"40","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Dembkowski, Daniel J.","contributorId":275781,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":834283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kerns, Janice A.","contributorId":275782,"corporation":false,"usgs":false,"family":"Kerns","given":"Janice","email":"","middleInitial":"A.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":834284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Easterly, Emma G.","contributorId":275785,"corporation":false,"usgs":false,"family":"Easterly","given":"Emma","email":"","middleInitial":"G.","affiliations":[{"id":33303,"text":"University of Wisconsin Stevens Point","active":true,"usgs":false}],"preferred":false,"id":834285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":834282,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70210265,"text":"70210265 - 2020 - 40Ar/39Ar and U-Pb SIMS zircon ages of Ediacaran dikes from the Arabian-Nubian Shield of south Jordan","interactions":[],"lastModifiedDate":"2020-05-27T13:53:26.508555","indexId":"70210265","displayToPublicDate":"2020-03-20T08:50:13","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"40Ar/39Ar and U-Pb SIMS zircon ages of Ediacaran dikes from the Arabian-Nubian Shield of south Jordan","docAbstract":"A spectacular feature of the Arabian-Nubian Shield (ANS) is the abundance of well-exposed and extensive Neoproterozoic dike swarms of multiple generations. These dikes are generally categorized into metamorphosed and unmetamorphosed post-orogenic dike swarms. The unmetamorphosed dikes in the northern ANS can be grouped into an old and young generations. We dated three dikes from the old generation of the unmetamorphosed dikes: a composite dike with latite margins and rhyolite core (607 ± 6 Ma, U-Pb), a biotite rhyolite dike (600 ± 4 Ma, 40Ar/39Ar age of biotite) and an andesite dike (594 ± 3, 40Ar/39Ar age of amphibole). We propose that these dikes representing the old generation were emplaced at different episodes extending approximately between 607 and 590 Ma. Time and composition equivalent plutonic rocks are common in Jordan and the northern ANS. These dikes crosscut the late to post-collisional granitoids and display a subduction-related character as evidenced from the Nb-Ta anomaly, suggesting a transitional magmatic activity from the orogenic to extensional environment. This generation of dikes is absent in the alkali feldspar A-type granite dated at 586 ± 5 Ma in Jordan and equivalent rocks in the northern ANS, which are crosscut only by the dolerite dikes which has an approximate crystallization age of ~579 Ma (40Ar/39Ar whole rock total gas age). Their within-plate character is supported by the absence of the Nb-Ta anomaly and the high field strength elements tectonic discrimination plots. We propose that these dolerite dikes represent the last Neoproterozoic igneous activity in the northern ANS, i.e. the magmatic activity was terminated ~50 m.y. before the estimated age of the Ram Unconformity at ~530 Ma. This age is in agreement with a previously suggested model of mantle lithosphere delamination from below the northern ANS after a significant crust-mantle thickening caused by the East African Orogeny. The thickening triggered exceptionally rapid uplift, followed by erosional unroofing of the ANS rocks, some lateral extension, and post-orogenic magmatic activity. This was followed by thermal relaxation and subsidence and the gradual denudation, erosion, and peneplanation that gradually developed until the approximate age of the unconformity at ~530 Ma.","language":"English","publisher":"Elsevier","doi":"10.1016/j.precamres.2020.105714","usgsCitation":"Ghanem, H., McAleer, R.J., Jarrar, G.H., Al Hseinat, M., and Whitehouse, M., 2020, 40Ar/39Ar and U-Pb SIMS zircon ages of Ediacaran dikes from the Arabian-Nubian Shield of south Jordan: Precambrian Research, v. 434, 105714, 21 p., https://doi.org/10.1016/j.precamres.2020.105714.","productDescription":"105714, 21 p.","ipdsId":"IP-112209","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":375071,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Red Sea, Sinai Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              34.541015625,\n              29.99300228455108\n            ],\n            [\n              34.27734375,\n              31.12819929911196\n            ],\n            [\n              31.289062500000004,\n              31.57853542647338\n            ],\n            [\n              30.41015625,\n              28.07198030177986\n            ],\n            [\n              32.16796875,\n              16.88865978738161\n            ],\n            [\n              42.1875,\n              9.709057068618208\n            ],\n            [\n              48.427734375,\n              8.494104537551882\n            ],\n            [\n              48.515625,\n              14.349547837185362\n            ],\n            [\n              41.484375,\n              24.686952411999155\n            ],\n            [\n              34.541015625,\n              29.99300228455108\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"434","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ghanem, Hind","contributorId":189107,"corporation":false,"usgs":false,"family":"Ghanem","given":"Hind","email":"","affiliations":[],"preferred":false,"id":789842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":789843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarrar, Ghaleb H. 0000-0003-3424-3337","orcid":"https://orcid.org/0000-0003-3424-3337","contributorId":224974,"corporation":false,"usgs":false,"family":"Jarrar","given":"Ghaleb","middleInitial":"H.","affiliations":[{"id":35514,"text":"University of Jordan","active":true,"usgs":false}],"preferred":false,"id":789844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Al Hseinat, Mu’ayyad 0000-0003-3269-1144","orcid":"https://orcid.org/0000-0003-3269-1144","contributorId":224975,"corporation":false,"usgs":false,"family":"Al Hseinat","given":"Mu’ayyad","email":"","affiliations":[{"id":35514,"text":"University of Jordan","active":true,"usgs":false}],"preferred":false,"id":789845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whitehouse, Martin 0000-0003-2227-577X","orcid":"https://orcid.org/0000-0003-2227-577X","contributorId":224976,"corporation":false,"usgs":false,"family":"Whitehouse","given":"Martin","email":"","affiliations":[{"id":39794,"text":"Swedish Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":789846,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70213189,"text":"70213189 - 2020 - Altered climate leads to positive density‐dependent feedbacks in a tropical wet forest","interactions":[],"lastModifiedDate":"2020-09-15T15:58:10.209633","indexId":"70213189","displayToPublicDate":"2020-03-20T08:45:59","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Altered climate leads to positive density‐dependent feedbacks in a tropical wet forest","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Climate change is predicted to result in warmer and drier Neotropical forests relative to current conditions. Negative density‐dependent feedbacks, mediated by natural enemies, are key to maintaining the high diversity of tree species found in the tropics, yet we have little understanding of how projected changes in climate are likely to affect these critical controls. Over 3&nbsp;years, we evaluated the effects of a natural drought and in situ experimental warming on density‐dependent feedbacks on seedling demography in a wet tropical forest in Puerto Rico. In the +4°C warming treatment, we found that seedling survival increased with increasing density of the same species (conspecific). These positive density‐dependent feedbacks were not associated with a decrease in aboveground natural enemy pressure. If positive density‐dependent feedbacks are not transient, the diversity of tropical wet forests, which may rely on negative density dependence to drive diversity, could decline in a future warmer, drier world.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15087","usgsCitation":"Barreto-Muñoz, A., Alonso-Rodriguez, A.M., Aldrich-Wolfe, L., Cavaleri, M.A., Reed, S.C., and Wood, T.E., 2020, Altered climate leads to positive density‐dependent feedbacks in a tropical wet forest: Global Change Biology, v. 26, no. 6, p. 3417-3428, https://doi.org/10.1111/gcb.15087.","productDescription":"12 p.","startPage":"3417","endPage":"3428","ipdsId":"IP-114129","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":490067,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1608727","text":"External Repository"},{"id":378353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -67.3736572265625,\n              17.916022703877665\n            ],\n            [\n              -65.6268310546875,\n              17.916022703877665\n            ],\n            [\n              -65.6268310546875,\n              18.531700307384043\n            ],\n            [\n              -67.3736572265625,\n              18.531700307384043\n            ],\n            [\n              -67.3736572265625,\n              17.916022703877665\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"6","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Barreto-Muñoz, Armando","contributorId":239891,"corporation":false,"usgs":false,"family":"Barreto-Muñoz","given":"Armando","affiliations":[{"id":48028,"text":"University of Arizona, Biosystems Engineering, Tucson, AZ, 85721 USA","active":true,"usgs":false}],"preferred":false,"id":798557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alonso-Rodriguez, Aura M.","contributorId":206281,"corporation":false,"usgs":false,"family":"Alonso-Rodriguez","given":"Aura","email":"","middleInitial":"M.","affiliations":[{"id":37300,"text":"International Institute of Tropical Forestry, USDA Forest Service, Sabana Field Research Station, Luquillo, Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":798568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldrich-Wolfe, Laura","contributorId":49263,"corporation":false,"usgs":true,"family":"Aldrich-Wolfe","given":"Laura","email":"","affiliations":[],"preferred":false,"id":798569,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cavaleri, Molly A.","contributorId":206282,"corporation":false,"usgs":false,"family":"Cavaleri","given":"Molly","email":"","middleInitial":"A.","affiliations":[{"id":34284,"text":"School of Forest Resources and Environmental Science, Michigan Technological University","active":true,"usgs":false}],"preferred":false,"id":798570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":798571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wood, Tana E.","contributorId":197805,"corporation":false,"usgs":false,"family":"Wood","given":"Tana","middleInitial":"E.","affiliations":[],"preferred":false,"id":798572,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70223302,"text":"70223302 - 2020 - Thermal diversity of salmon streams in the Matanuska-Susitna Basin, Alaska","interactions":[],"lastModifiedDate":"2021-08-20T13:25:13.949874","indexId":"70223302","displayToPublicDate":"2020-03-20T08:15:14","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2126,"text":"JAWRA","active":true,"publicationSubtype":{"id":10}},"title":"Thermal diversity of salmon streams in the Matanuska-Susitna Basin, Alaska","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>We present the first description of summer stream thermal regimes in Alaska using metrics that represent the magnitude, variability, frequency, duration, and timing of temperature events related to salmon life histories. We used cluster analysis to characterize thermal regimes present in the Matanuska-Susitna (Mat-Su) Basin based on 10 nonredundant temperature metrics and identified the most important drivers of our thermal regimes using random forests. Our results indicated four distinct thermal regimes among the 248 site-years in the Mat-Su Basin. Over 41% of site-years had cold-stable temperatures. An additional 22% of site-years had cold-variable temperatures and the latest timing of maximum stream temperatures. Twenty-eight percent of site-years had warm-variable temperatures that remained above 13°C for approximately two months. The remaining 9% of site-years had the warmest and most variable daily maximum temperatures, exceeding 18°C for almost one month, indicating potential impacts to spawning and rearing salmon. Climate and landscape drivers differentiating thermal regimes included spring and summer air temperatures, spring snowpack, summer precipitation, wetlands, and lakes. Climate change projections for 2050–2069 indicated a future shift toward warm thermal regimes and a reduced portfolio of thermal diversity. These results portend negative impacts to some salmon populations and stress the importance of prioritizing actions that maintain thermal regime diversity.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12839","usgsCitation":"Shaftel, R., Mauger, S., Falke, J.A., Rinella, D., Davis, J., and Jones, L., 2020, Thermal diversity of salmon streams in the Matanuska-Susitna Basin, Alaska: JAWRA, v. 56, no. 4, p. 630-646, https://doi.org/10.1111/1752-1688.12839.","productDescription":"17 p.","startPage":"630","endPage":"646","ipdsId":"IP-101713","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":388225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Matanuska-Susitna Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -158.81835937499997,\n              59.06315402462662\n            ],\n            [\n              -141.1962890625,\n              59.06315402462662\n            ],\n            [\n              -141.1962890625,\n              65.69447579373418\n            ],\n            [\n              -158.81835937499997,\n              65.69447579373418\n            ],\n            [\n              -158.81835937499997,\n              59.06315402462662\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"56","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaftel, Rebecca","contributorId":264540,"corporation":false,"usgs":false,"family":"Shaftel","given":"Rebecca","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mauger, Sue","contributorId":264546,"corporation":false,"usgs":false,"family":"Mauger","given":"Sue","email":"","affiliations":[{"id":54494,"text":"ak","active":true,"usgs":false}],"preferred":false,"id":821656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":821657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rinella, Daniel","contributorId":264541,"corporation":false,"usgs":false,"family":"Rinella","given":"Daniel","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":821653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Jeff","contributorId":264544,"corporation":false,"usgs":false,"family":"Davis","given":"Jeff","email":"","affiliations":[{"id":54492,"text":"arri","active":true,"usgs":false}],"preferred":false,"id":821654,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Leslie","contributorId":264545,"corporation":false,"usgs":false,"family":"Jones","given":"Leslie","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":821655,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70211822,"text":"70211822 - 2020 - Genetic family reconstruction characterizes Lake Sturgeon use of newly constructed spawning habitat and larval dispersal","interactions":[],"lastModifiedDate":"2020-08-10T13:10:20.527958","indexId":"70211822","displayToPublicDate":"2020-03-20T08:04:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Genetic family reconstruction characterizes Lake Sturgeon use of newly constructed spawning habitat and larval dispersal","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Since 2004, seven spawning reefs have been constructed in the St. Clair–Detroit River system to remediate lost spawning habitat and increase recruitment of Lake Sturgeon<span>&nbsp;</span><i>Acipenser fulvescens<span>&nbsp;</span></i>. Assessment of management actions by collecting and enumerating eggs and larvae provided evidence of spawning Lake Sturgeon and survival of eggs until larval dispersal at constructed reef sites. However, the number of spawners contributing sampled offspring (<i>N<span>&nbsp;</span></i><sub><i>s<span>&nbsp;</span></i></sub>), effective number of breeders (<i>N<span>&nbsp;</span></i><sub><i>b<span>&nbsp;</span></i></sub>), and extent of larval dispersal was unknown. Genetic reconstruction of familial relationships assigned eggs and larvae (<i>n&nbsp;<span>&nbsp;</span></i>=<i>&nbsp;<span>&nbsp;</span></i>725) collected in 2015 and 2016 to full‐ and half‐sibling groups and estimated<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>s<span>&nbsp;</span></i></sub>,<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>b<span>&nbsp;</span></i></sub>, and genetic connectivity. We used a modified COLONY simulation module to simulate and convert 18 microsatellite loci (13 disomic and 5 polysomic) to 205 dominant present/absent markers to increase marker number and familial assignment accuracy in family reconstruction analysis. We assessed COLONY's ability to accurately infer familial relationships across small (<i>n&nbsp;<span>&nbsp;</span></i>=<i>&nbsp;<span>&nbsp;</span></i>50), moderate (<i>n&nbsp;<span>&nbsp;</span></i>=<i>&nbsp;<span>&nbsp;</span></i>125), and large (<i>n&nbsp;<span>&nbsp;</span></i>=<i>&nbsp;<span>&nbsp;</span></i>750) larval sample sizes using two assumed allele frequency distributions for polysomic loci. We found that with fewer offspring sampled, COLONY underestimated<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>s<span>&nbsp;</span></i></sub>and with large sample sizes overestimated<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>s<span>&nbsp;</span></i></sub>. However, estimates were usually within 12–16% of the simulated true<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>s<span>&nbsp;</span></i></sub>. Across reefs, estimates of<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>s<span>&nbsp;</span></i></sub>were 151 in 2015 and 208 in 2016, and<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>b<span>&nbsp;</span></i></sub>was similar (158 in 2015 and 198 in 2016). Evidence of full‐ and half‐sibling larvae collected at multiple locations indicated that individual Lake Sturgeon spawned at multiple locations within years and larvae dispersed considerable distances. Estimating<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>s<span>&nbsp;</span></i></sub>,<span>&nbsp;</span><i>N<span>&nbsp;</span></i><sub><i>b<span>&nbsp;</span></i></sub>, larval dispersal, and inferred genetic connectivity between locations provides managers with population demographic parameters to assess habitat remediation projects. Continued monitoring, including genetic family reconstruction, may provide insight into the long‐term effects of constructed spawning habitat on recruitment and population‐level genetic diversity.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/tafs.10225","usgsCitation":"Hunter, R., Roseman, E., Sard, N.M., DeBruyne, R., Wang, J., and Scribner, K.T., 2020, Genetic family reconstruction characterizes Lake Sturgeon use of newly constructed spawning habitat and larval dispersal: Transactions of the American Fisheries Society, v. 149, no. 3, p. 266-283, https://doi.org/10.1002/tafs.10225.","productDescription":"18 p.","startPage":"266","endPage":"283","ipdsId":"IP-108923","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457306,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10225","text":"Publisher Index Page"},{"id":377262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"St. Clair–Detroit River system, Lake Michigan, Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -83.3038330078125,\n              41.623655390686395\n            ],\n            [\n              -82.056884765625,\n              41.623655390686395\n            ],\n            [\n              -82.056884765625,\n              43.42100882994723\n            ],\n            [\n              -83.3038330078125,\n              43.42100882994723\n            ],\n            [\n              -83.3038330078125,\n              41.623655390686395\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"149","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Hunter, Robert D.","contributorId":237766,"corporation":false,"usgs":false,"family":"Hunter","given":"Robert D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":795238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roseman, Edward F. 0000-0002-5315-9838","orcid":"https://orcid.org/0000-0002-5315-9838","contributorId":217909,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":795239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sard, Nick M.","contributorId":237767,"corporation":false,"usgs":false,"family":"Sard","given":"Nick","email":"","middleInitial":"M.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":795240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeBruyne, Robin L.","contributorId":139752,"corporation":false,"usgs":false,"family":"DeBruyne","given":"Robin L.","affiliations":[{"id":12902,"text":"MI State UNiversity","active":true,"usgs":false}],"preferred":false,"id":795241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Jinliang","contributorId":237768,"corporation":false,"usgs":false,"family":"Wang","given":"Jinliang","email":"","affiliations":[{"id":34772,"text":"Institute of Zoology, Zoological Society of London","active":true,"usgs":false}],"preferred":false,"id":795242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scribner, Kim T.","contributorId":95434,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","email":"","middleInitial":"T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":795243,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70228610,"text":"70228610 - 2020 - Gametogenesis and assessment of nonlethal tools to assign sex and reproductive condition in Burbot","interactions":[],"lastModifiedDate":"2022-02-14T13:30:20.258521","indexId":"70228610","displayToPublicDate":"2020-03-20T07:27:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Gametogenesis and assessment of nonlethal tools to assign sex and reproductive condition in Burbot","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Nonlethal tools (plasma sex steroid concentrations and ultrasound) for assigning sex and reproductive condition in Burbot<span>&nbsp;</span><i>Lota lota</i><span>&nbsp;</span>from Lake Roosevelt, Washington, were assessed. Gonadal tissue, blood plasma, and gonadal sonograms were collected monthly from November 2016 to March 2018. Gametogenesis was described by gonadal histology during an entire reproductive cycle to confirm sex and reproductive condition. Plasma testosterone (T) and estradiol-17β (E2) concentrations were measured by radioimmunoassay. Plasma 11-ketotestosterone (11-KT) concentrations were measured by liquid chromatography–mass spectrometry. Plasma sex steroid profiles, gonadosomatic index, and ovarian follicle diameter were also described during an entire reproductive cycle. Plasma 11-KT concentration was used to assign sex with 82% accuracy during the entire reproductive cycle, and plasma 11-KT and E2 concentrations were used to assign sex with 98% accuracy when fish were reproductive (i.e., November–March in Lake Roosevelt). Plasma T and E2 concentrations were used to assign reproductive condition in females with 98% accuracy, and plasma T concentration was used to assign reproductive condition in males with 90% accuracy. Ultrasound was used to assign sex with 96% accuracy but was not useful for assigning reproductive condition. Nonlethal tools to assign sex and reproductive condition will enable fisheries biologists to assess reproductive indices of the Burbot population in Lake Roosevelt to inform management decisions.</p></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10226","usgsCitation":"McGarvey, L., Halvorson, L.J., Ilgen, J., Guy, C.S., McLellan, J., and Webb, M., 2020, Gametogenesis and assessment of nonlethal tools to assign sex and reproductive condition in Burbot: Transactions of the American Fisheries Society, v. 149, no. 2, p. 225-240, https://doi.org/10.1002/tafs.10226.","productDescription":"16 p.","startPage":"225","endPage":"240","ipdsId":"IP-112124","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Lake Roosevelt","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.4271240234375,\n              48.04136507445029\n            ],\n            [\n              -117.90527343750001,\n              48.04136507445029\n            ],\n            [\n              -117.90527343750001,\n              48.76705193388751\n            ],\n            [\n              -118.4271240234375,\n              48.76705193388751\n            ],\n            [\n              -118.4271240234375,\n              48.04136507445029\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"149","issue":"2","noUsgsAuthors":false,"publicationDate":"2020-03-09","publicationStatus":"PW","contributors":{"authors":[{"text":"McGarvey, Lauren M.","contributorId":276359,"corporation":false,"usgs":false,"family":"McGarvey","given":"Lauren M.","affiliations":[{"id":36244,"text":"MSU","active":true,"usgs":false}],"preferred":false,"id":834789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halvorson, Leif J.","contributorId":276360,"corporation":false,"usgs":false,"family":"Halvorson","given":"Leif","email":"","middleInitial":"J.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":834790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ilgen, Jason E.","contributorId":276361,"corporation":false,"usgs":false,"family":"Ilgen","given":"Jason E.","affiliations":[{"id":56967,"text":"cct","active":true,"usgs":false}],"preferred":false,"id":834791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":834792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLellan, Jason G.","contributorId":276363,"corporation":false,"usgs":false,"family":"McLellan","given":"Jason G.","affiliations":[{"id":27988,"text":"Colville Confederated Tribes","active":true,"usgs":false}],"preferred":false,"id":834793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Webb, Molly A. H.","contributorId":276365,"corporation":false,"usgs":false,"family":"Webb","given":"Molly A. H.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":834794,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209464,"text":"70209464 - 2020 - The role of sand lances (Ammodytes sp.) in the Northwest Atlantic Ecosystem: A synthesis of current knowledge with implications for conservation and management","interactions":[],"lastModifiedDate":"2020-07-27T19:08:51.352171","indexId":"70209464","displayToPublicDate":"2020-03-20T07:16:42","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1652,"text":"Fish and Fisheries","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The role of sand lances (<i>Ammodytes</i> sp.) in the Northwest Atlantic Ecosystem: A synthesis of current knowledge with implications for conservation and management","title":"The role of sand lances (Ammodytes sp.) in the Northwest Atlantic Ecosystem: A synthesis of current knowledge with implications for conservation and management","docAbstract":"<p><span>The American sand lance (</span><i>Ammodytes americanus</i><span>, Ammodytidae) and the Northern sand lance (</span><i>A. dubius</i><span>, Ammodytidae) are small forage fishes that play an important functional role in the Northwest Atlantic Ocean (NWA). The NWA is a highly dynamic ecosystem currently facing increased risks from climate change, fishing and energy development. We need a better understanding of the biology, population dynamics and ecosystem role of&nbsp;</span><i>Ammodytes</i><span>&nbsp;to inform relevant management, climate adaptation and conservation efforts. To meet this need, we synthesized available data on the (a) life history, behaviour and distribution; (b) trophic ecology; (c) threats and vulnerabilities; and (d) ecosystem services role of&nbsp;</span><i>Ammodytes</i><span>&nbsp;in the NWA. Overall, 72 regional predators including 45 species of fishes, two squids, 16 seabirds and nine marine mammals were found to consume&nbsp;</span><i>Ammodytes</i><span>. Priority research needs identified during this effort include basic information on the patterns and drivers in abundance and distribution of&nbsp;</span><i>Ammodytes</i><span>, improved assessments of reproductive biology schedules and investigations of regional sensitivity and resilience to climate change, fishing and habitat disturbance. Food web studies are also needed to evaluate trophic linkages and to assess the consequences of inconsistent zooplankton prey and predator fields on energy flow within the NWA ecosystem. Synthesis results represent the first comprehensive assessment of&nbsp;</span><i>Ammodytes</i><span>&nbsp;in the NWA and are intended to inform new research and support regional ecosystem‐based management approaches.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/faf.12445","usgsCitation":"Staudinger, M., Goyert, H., Suca, J., Coleman, K., Welch, L., Llopiz, J., Wiley, D., Altman, I., Applegate, A., Auster, P., Baumann, H., Beaty, J., Boelke, D., Kaufman, L., Loring, P., Moxley, J., Paton, S., Powers, K., Richardson, D., Robbins, J., Runge, J., Smith, B., Spiegel, C., and Steinmetz, H., 2020, The role of sand lances (Ammodytes sp.) in the Northwest Atlantic Ecosystem: A synthesis of current knowledge with implications for conservation and management: Fish and Fisheries, v. 21, no. 3, p. 522-556, https://doi.org/10.1111/faf.12445.","productDescription":"35 p.","startPage":"522","endPage":"556","ipdsId":"IP-112301","costCenters":[{"id":41705,"text":"Northeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":457308,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/faf.12445","text":"Publisher Index Page"},{"id":373855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northwest Atlantic","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -65.478515625,\n              42.8115217450979\n            ],\n            [\n              -65.9619140625,\n              43.58039085560784\n            ],\n            [\n              -66.51123046875,\n              44.449467536006935\n            ],\n            [\n              -66.77490234375,\n              44.84029065139799\n            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Center","active":true,"usgs":true},{"id":484,"text":"Northwest Climate Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":786577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goyert, Holly","contributorId":223886,"corporation":false,"usgs":false,"family":"Goyert","given":"Holly","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":786578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suca, Justin","contributorId":223887,"corporation":false,"usgs":false,"family":"Suca","given":"Justin","email":"","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":786579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coleman, Kaycee","contributorId":223888,"corporation":false,"usgs":false,"family":"Coleman","given":"Kaycee","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":786580,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welch, Linda","contributorId":223889,"corporation":false,"usgs":false,"family":"Welch","given":"Linda","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":786581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Llopiz, Joel ","contributorId":223890,"corporation":false,"usgs":false,"family":"Llopiz","given":"Joel ","affiliations":[{"id":16633,"text":"WHOI","active":true,"usgs":false}],"preferred":false,"id":786582,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wiley, 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for Coastal Studies","active":true,"usgs":false}],"preferred":false,"id":786596,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Runge, Jeff","contributorId":223905,"corporation":false,"usgs":false,"family":"Runge","given":"Jeff","email":"","affiliations":[{"id":40790,"text":"University of Maine and Gulf of Maine Research Institute","active":true,"usgs":false}],"preferred":false,"id":786597,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Smith, Brian ","contributorId":223906,"corporation":false,"usgs":false,"family":"Smith","given":"Brian ","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":786598,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Spiegel, Caleb ","contributorId":223907,"corporation":false,"usgs":false,"family":"Spiegel","given":"Caleb 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,{"id":70209468,"text":"70209468 - 2020 - Climate explorer: Improved access to local climate projections","interactions":[],"lastModifiedDate":"2020-04-09T11:55:13.5498","indexId":"70209468","displayToPublicDate":"2020-03-20T06:42:47","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Climate explorer: Improved access to local climate projections","docAbstract":"The goal of the U.S. Climate Resilience Toolkit’s (CRT) Climate Explorer (CE) is to provide information at appropriate spatial and temporal scales to help practitioners gain insights into the risks posed by climate change. Ultimately, these insights can lead to groups of local stakeholders taking action to build their resilience to a changing climate. Using CE, decision-makers can visualize decade-by-decade changes in climate conditions in their county and the magnitude of changes projected for the end of this century under two plausible emissions pathways. They can also check how projected changes relate to user-defined thresholds that represent points at which valued assets may become stressed, damaged, or destroyed. By providing easy access to authoritative information in an elegant interface, the Climate Explorer can help communities recognize—and prepare to avoid or respond to—emerging climate hazards. Another important step in the evolution of CE builds on the purposeful alignment of the CRT with the U.S. Global Change Research Program’s (USGCRP) National Climate Assessment (NCA). By closely linking these two authoritative resources, we envision that users can easily transition from static maps and graphs within NCA reports to dynamic, interactive versions of the same data within CE and other resources within the CRT, which they can explore at higher spatial scales or customize for their own purposes. The provision of consistent climate data and information—a result of collaboration among USGCRP’s federal agencies—will assist decision-making by other governmental entities, nongovernmental organizations, businesses, and individuals.","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-18-0298.1","collaboration":"","usgsCitation":"Lipschultz, F., Herring, D., Ray, A.J., Alder, J.R., Dahlman, L., DeGaetano, A., Fox, J.F., Gardiner, E., Herring, J., Hicks, J., Melton, F., Morefield, P.E., and Sweet, W., 2020, Climate explorer: Improved access to local climate projections, v. 101, no. 3, p. e265-e273, https://doi.org/10.1175/BAMS-D-18-0298.1.","productDescription":"9 p.","startPage":"e265","endPage":"e273","ipdsId":"IP-091613","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":457311,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70209153,"text":"70209153 - 2020 - Implementation of a surface water extent model in Cambodia using cloud-based remote sensing","interactions":[],"lastModifiedDate":"2020-03-20T06:38:20","indexId":"70209153","displayToPublicDate":"2020-03-19T18:59:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Implementation of a surface water extent model in Cambodia using cloud-based remote sensing","docAbstract":"Mapping surface water over time provides the spatially explicit information essential for hydroclimatic research focused on droughts and flooding. Hazard risk assessments and water management planning also rely on accurate, long-term measurements describing hydrologic fluctuations. Stream gages are a common measurement tool used to better understand flow and inundation dynamics, but gage networks are incomplete or non-existent in many parts of the world. In such instances, satellite imagery may provide the only data available to monitor surface water changes over time. Here, we describe an effort to extend the applicability of the USGS Dynamic Surface Water Extent (DSWE) model to non-US regions. We leverage the multi-decadal archive of the Landsat satellite in the Google Earth Engine (GEE) cloud-based computing platform to produce and analyze 372 monthly composite maps and 31 annual maps (January 1988–December 2018) in Cambodia, a flood-prone country in Southeast Asia that lacks a comprehensive stream gage network. DSWE relies on a series of spectral water indices and elevation data to classify water into four categories of water inundation. We compared model outputs to existing surface water maps and independently assessed DSWE accuracy at discrete dates across the time series. Despite considerable cloud obstruction and missing imagery across the monthly time series, the overall accuracy exceeded 85% for all annual tests. The DSWE model consistently mapped open water with high accuracy, and areas classified as “high confidence” water correlate well to other available maps at the country scale. Results in Cambodia suggest that extending DSWE globally using a cloud computing framework may benefit scientists, managers, and planners in a wide array of applications across the globe.","language":"English","publisher":"MDPI","doi":"10.3390/rs12060984","usgsCitation":"Soulard, C.E., Walker, J.J., and Petrakis, R.E., 2020, Implementation of a surface water extent model in Cambodia using cloud-based remote sensing: Remote Sensing, v. 12, no. 6, 984, https://doi.org/10.3390/rs12060984.","productDescription":"984","ipdsId":"IP-115688","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":457313,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12060984","text":"Publisher Index Page"},{"id":437053,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LH9YYF","text":"USGS data release","linkHelpText":"Implementation of a Surface Water Extent Model using Cloud-Based Remote Sensing - Code and Maps"},{"id":373394,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cambodia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[103.49728,10.63256],[103.09069,11.15366],[102.58493,12.18659],[102.3481,13.39425],[102.98842,14.22572],[104.28142,14.41674],[105.21878,14.27321],[106.04395,13.88109],[106.49637,14.57058],[107.38273,14.20244],[107.61455,13.53553],[107.4914,12.33721],[105.81052,11.56761],[106.24967,10.96181],[105.19991,10.88931],[104.33433,10.48654],[103.49728,10.63256]]]},\"properties\":{\"name\":\"Cambodia\"}}]}","volume":"12","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Soulard, Christopher E. 0000-0002-5777-9516 csoulard@usgs.gov","orcid":"https://orcid.org/0000-0002-5777-9516","contributorId":2642,"corporation":false,"usgs":true,"family":"Soulard","given":"Christopher","email":"csoulard@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":785150,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Jessica J. 0000-0002-3225-0317 jjwalker@usgs.gov","orcid":"https://orcid.org/0000-0002-3225-0317","contributorId":169458,"corporation":false,"usgs":true,"family":"Walker","given":"Jessica","email":"jjwalker@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":785151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petrakis, Roy E. 0000-0001-8932-077X","orcid":"https://orcid.org/0000-0001-8932-077X","contributorId":219707,"corporation":false,"usgs":false,"family":"Petrakis","given":"Roy","email":"","middleInitial":"E.","affiliations":[{"id":27608,"text":"Contractor to the USGS","active":true,"usgs":false}],"preferred":false,"id":785152,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70209164,"text":"70209164 - 2020 - Quantifying interregional flows of multiple ecosystem services – A case study for Germany","interactions":[],"lastModifiedDate":"2020-03-20T06:39:18","indexId":"70209164","displayToPublicDate":"2020-03-19T18:54:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1841,"text":"Global Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying interregional flows of multiple ecosystem services – A case study for Germany","docAbstract":"Despite a growing number of national-scale ecosystem service (ES) assessments, few studies consider the impacts of ES use and consumption beyond national or regional boundaries. Interregional ES flows – ecosystem services “imported” from and “exported” to other countries – are rarely analyzed and their importance for global sustainability is little known. Here, we provide a first multi-ES quantification of a nation's use of ES from abroad. We focus on ES flows that benefit the population in Germany but are supplied outside German territory. We employ a conceptual framework recently developed to systematically quantify interregional ES flows. We address four types of interregional ES flows with: (i) biophysical flows of traded goods: cocoa import for consumption; (ii) flows mediated by migratory species: migration of birds providing pest control; (iii) passive biophysical flows: flood control along transboundary watersheds; and (iv) information flows: China's giant panda loan to the Berlin Zoo. We determined that: (i) Ivory Coast and Ghana alone supply around 53% of Germany's cocoa while major negative consequences for biodiversity occurred in Cameroon and Ecuador; (ii) Africa´s humid and sub-humid climate zones are important habitats for the majority of migratory bird species that provide natural pest control services in agricultural areas in Germany; (iii) Upstream watersheds outside the country add an additional 64% flood regulation services nationally, while Germany exports 40% of flood regulation services in neighboring, downstream countries; (iv) Information flows transported by the pandas were mainly related to political aspects and - contrary to our expectations - considerably less on biological and natural aspects. We discuss the implications of these results for international resource management policy and governance.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloenvcha.2020.102051","usgsCitation":"Kleeman, J., Schroter, M., Bagstad, K.J., Kuhlicke, C., Kastner, T., Fridman, D., Schulp, C.J., Wolff, S., Martinez-Lopez, J., Koellner, T., Arnhold, S., Martin-Lopez, B., Marques, A., Lopez-Hoffman, L., Liu, J., Kissinger, M., Guerra, C., and Bonn, A., 2020, Quantifying interregional flows of multiple ecosystem services – A case study for Germany: Global Environmental Change, v. 61, 102051, https://doi.org/10.1016/j.gloenvcha.2020.102051.","productDescription":"102051","ipdsId":"IP-104288","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":457315,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gloenvcha.2020.102051","text":"Publisher Index Page"},{"id":373393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Germany","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[9.92191,54.9831],[9.93958,54.59664],[10.95011,54.36361],[10.93947,54.00869],[11.95625,54.19649],[12.51844,54.47037],[13.64747,54.07551],[14.11969,53.75703],[14.35332,53.24817],[14.07452,52.98126],[14.4376,52.62485],[14.68503,52.08995],[14.6071,51.74519],[15.017,51.10667],[14.57072,51.00234],[14.30701,51.11727],[14.05623,50.92692],[13.33813,50.73323],[12.96684,50.48408],[12.24011,50.26634],[12.41519,49.96912],[12.52102,49.54742],[13.03133,49.30707],[13.59595,48.87717],[13.24336,48.41611],[12.8841,48.28915],[13.02585,47.63758],[12.93263,47.46765],[12.62076,47.67239],[12.14136,47.70308],[11.42641,47.52377],[10.5445,47.5664],[10.40208,47.30249],[9.89607,47.5802],[9.59423,47.52506],[8.52261,47.83083],[8.3173,47.61358],[7.46676,47.62058],[7.59368,48.33302],[8.09928,49.01778],[6.65823,49.20196],[6.18632,49.4638],[6.24275,49.90223],[6.04307,50.12805],[6.15666,50.80372],[5.98866,51.85162],[6.5894,51.85203],[6.84287,52.22844],[7.09205,53.14404],[6.90514,53.48216],[7.10042,53.69393],[7.93624,53.7483],[8.12171,53.52779],[8.80073,54.02079],[8.57212,54.39565],[8.52623,54.96274],[9.28205,54.83087],[9.92191,54.9831]]]},\"properties\":{\"name\":\"Germany\"}}]}","volume":"61","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kleeman, Janina","contributorId":215954,"corporation":false,"usgs":false,"family":"Kleeman","given":"Janina","email":"","affiliations":[{"id":39336,"text":"Helmholtz Centre for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":785177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroter, Matthias 0000-0003-0207-7311","orcid":"https://orcid.org/0000-0003-0207-7311","contributorId":202612,"corporation":false,"usgs":false,"family":"Schroter","given":"Matthias","email":"","affiliations":[{"id":36494,"text":"UFZ – Helmholtz Centre for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":785178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":785179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kuhlicke, Christian 0000-0002-1193-228X","orcid":"https://orcid.org/0000-0002-1193-228X","contributorId":215955,"corporation":false,"usgs":false,"family":"Kuhlicke","given":"Christian","email":"","affiliations":[{"id":39336,"text":"Helmholtz Centre for Environmental Research","active":true,"usgs":false}],"preferred":false,"id":785180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kastner, Thomas","contributorId":202618,"corporation":false,"usgs":false,"family":"Kastner","given":"Thomas","email":"","affiliations":[{"id":27439,"text":"Senckenberg Biodiversity and Climate Research Centre","active":true,"usgs":false}],"preferred":false,"id":785181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fridman, Dor 0000-0003-3908-3571","orcid":"https://orcid.org/0000-0003-3908-3571","contributorId":223486,"corporation":false,"usgs":false,"family":"Fridman","given":"Dor","email":"","affiliations":[{"id":36498,"text":"Ben-Gurion University of the Negev","active":true,"usgs":false}],"preferred":false,"id":785182,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schulp, Catharina J. 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,{"id":70209145,"text":"70209145 - 2020 - Reconnaissance of surface water estrogenicity and the prevalence of intersex in smallmouth bass (Micropterus dolomieu) inhabiting New Jersey","interactions":[],"lastModifiedDate":"2020-03-20T06:40:39","indexId":"70209145","displayToPublicDate":"2020-03-19T18:45:08","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2041,"text":"International Journal of Environmental Research and Public Health","active":true,"publicationSubtype":{"id":10}},"title":"Reconnaissance of surface water estrogenicity and the prevalence of intersex in smallmouth bass (Micropterus dolomieu) inhabiting New Jersey","docAbstract":"The observation of testicular oocytes in male fishes has been utilized as a biomarker of estrogenic endocrine disruption. A reconnaissance project led in the Northeastern United States (US) during the period of 2008–2010 identified a high prevalence of intersex smallmouth bass on or near US Fish & Wildlife Service National Wildlife Refuges that included the observation of 100% prevalence in smallmouth bass males collected from the Wallkill River, NJ, USA. To better assess the prevalence of intersex smallmouth bass across the state of New Jersey, a tiered reconnaissance approach was initiated during the fall of 2016. Surface water samples were collected from 101 (85 river, 16 lake/reservoir) sites across the state at base-flow conditions for estrogenicity bioassay screening. Detectable estrogenicity was observed at 90% of the sites and 64% were above the US Environmental Protection Agency trigger level of 1 ng/L. Median surface water estrogenicity was 1.8 ng/L and a maximum of 6.9 ng/L E2EqBLYES was observed. Adult smallmouth bass were collected from nine sites, pre-spawn during the spring of 2017. Intersex was identified in fish at all sites, and the composite intersex prevalence was 93.8%. Prevalence across sites ranged from 70.6% to 100%. In addition to intersex, there was detectable plasma vitellogenin in males at all sites. Total estrogenicity in surface water was determined at these fish collection sites, and notable change over time was observed. Correlation analysis indicated significant positive correlations between land use (altered land; urban + agriculture) and surface water estrogenicity. There were no clear associations between land use and organismal metrics of estrogenic endocrine disruption (intersex or vitellogenin). This work establishes a baseline prevalence of intersex in male smallmouth bass in the state of New Jersey at a limited number of locations and identifies a number of waterbodies with estrogenic activity above an effects-based threshold.","language":"English","publisher":"MDPI","doi":"10.3390/ijerph17062024","usgsCitation":"Iwanowicz, L., Smalling, K., Blazer, V., Braham, R.P., Sanders, L., Boetsma, A., Procopio, N., Goodrow, S., Buchanan, G., Millemann, D., Ruppel, B., Vile, J., Henning, B., and Abatemarco, J., 2020, Reconnaissance of surface water estrogenicity and the prevalence of intersex in smallmouth bass (Micropterus dolomieu) inhabiting New Jersey: International Journal of Environmental Research and Public Health, v. 17, no. 6, 2024, https://doi.org/10.3390/ijerph17062024.","productDescription":"2024","ipdsId":"IP-110398","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":457318,"rank":0,"type":{"id":40,"text":"Open Access 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Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":785108,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buchanan, Gary","contributorId":223463,"corporation":false,"usgs":false,"family":"Buchanan","given":"Gary","email":"","affiliations":[{"id":40718,"text":"New Jersey Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":785109,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Millemann, Daniel","contributorId":223464,"corporation":false,"usgs":false,"family":"Millemann","given":"Daniel","email":"","affiliations":[{"id":40718,"text":"New Jersey Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":785110,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ruppel, Bruce","contributorId":223465,"corporation":false,"usgs":false,"family":"Ruppel","given":"Bruce","email":"","affiliations":[{"id":40718,"text":"New Jersey Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":785111,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Vile, John","contributorId":223466,"corporation":false,"usgs":false,"family":"Vile","given":"John","email":"","affiliations":[{"id":40718,"text":"New Jersey Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":785112,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Henning, Brian","contributorId":223467,"corporation":false,"usgs":false,"family":"Henning","given":"Brian","email":"","affiliations":[{"id":40718,"text":"New Jersey Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":785113,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Abatemarco, John","contributorId":223487,"corporation":false,"usgs":false,"family":"Abatemarco","given":"John","email":"","affiliations":[],"preferred":false,"id":785200,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70211978,"text":"70211978 - 2020 - A critical review on the potential impacts of neonicotinoid insecticide use: Current knowledge of environmental fate, toxicity, and implications for human health","interactions":[],"lastModifiedDate":"2020-08-12T22:51:49.456224","indexId":"70211978","displayToPublicDate":"2020-03-19T17:41:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1566,"text":"Environmental Science: Processes and Impacts","active":true,"publicationSubtype":{"id":10}},"title":"A critical review on the potential impacts of neonicotinoid insecticide use: Current knowledge of environmental fate, toxicity, and implications for human health","docAbstract":"<p><span>Neonicotinoid insecticides are widely used in both urban and agricultural settings around the world. Historically, neonicotinoid insecticides have been viewed as ideal replacements for more toxic compounds, like organophosphates, due in part to their perceived limited potential to affect the environment and human health. This critical review investigates the environmental fate and toxicity of neonicotinoids and their metabolites and the potential risks associated with exposure. Neonicotinoids are found to be ubiquitous in the environment, drinking water, and food, with low-level exposure commonly documented below acceptable daily intake standards. Available toxicological data from animal studies indicate possible genotoxicity, cytotoxicity, impaired immune function, and reduced growth and reproductive success at low concentrations, while limited data from ecological or cross-sectional epidemiological studies have identified acute and chronic health effects ranging from acute respiratory, cardiovascular, and neurological symptoms to oxidative genetic damage and birth defects. Due to the heavy use of neonicotinoids and potential for cumulative chronic exposure, these insecticides represent novel risks and necessitate further study to fully understand their risks to humans.</span></p>","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/C9EM00586B","usgsCitation":"Lehmler, H., Kolpin, D.W., Hladik, M., Vargo, J.D., Schilling, K.E., LeFevre, G.H., Peeples, T.L., Poch, M.C., LaDuca, L.E., Cwiertny, D.M., and Field, R.W., 2020, A critical review on the potential impacts of neonicotinoid insecticide use: Current knowledge of environmental fate, toxicity, and implications for human health: Environmental Science: Processes and Impacts, v. 22, p. 1315-1346, https://doi.org/10.1039/C9EM00586B.","productDescription":"32 p.","startPage":"1315","endPage":"1346","ipdsId":"IP-116942","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":487009,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11755762","text":"External Repository"},{"id":377457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lehmler, Hans-Joachim","contributorId":238108,"corporation":false,"usgs":false,"family":"Lehmler","given":"Hans-Joachim","email":"","affiliations":[],"preferred":false,"id":796064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":796065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hladik, Michelle L. 0000-0002-0891-2712 mhladik@usgs.gov","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":201293,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle L.","email":"mhladik@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":796066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vargo, John D.","contributorId":238109,"corporation":false,"usgs":false,"family":"Vargo","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":796067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schilling, Keith E.","contributorId":106429,"corporation":false,"usgs":false,"family":"Schilling","given":"Keith","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":796068,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":796069,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peeples, Tonya L.","contributorId":238110,"corporation":false,"usgs":false,"family":"Peeples","given":"Tonya","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":796070,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Poch, Matthew C.","contributorId":238111,"corporation":false,"usgs":false,"family":"Poch","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":796071,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"LaDuca, Lauren E.","contributorId":238112,"corporation":false,"usgs":false,"family":"LaDuca","given":"Lauren","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":796072,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cwiertny, David M.","contributorId":190557,"corporation":false,"usgs":false,"family":"Cwiertny","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":796073,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Field, R. William","contributorId":238113,"corporation":false,"usgs":false,"family":"Field","given":"R.","email":"","middleInitial":"William","affiliations":[],"preferred":false,"id":796074,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70209339,"text":"70209339 - 2020 - Contaminant subsidies to riparian food webs in Appalachian streams impacted by mountaintop removal coal mining","interactions":[],"lastModifiedDate":"2020-05-05T17:16:53.604546","indexId":"70209339","displayToPublicDate":"2020-03-19T15:27:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Contaminant subsidies to riparian food webs in Appalachian streams impacted by mountaintop removal coal mining","docAbstract":"Selenium is highly elevated in Appalachian streams and stream organisms that receive alkaline mine drainage from mountaintop removal coal mining compared to unimpacted streams in the region. Adult aquatic insects can be important vectors of waterborne contaminants to riparian food webs, yet pathways of Se transport and exposure of riparian organisms are poorly characterized. We investigated Se concentrations in stream and riparian organisms to determine whether mining extent increased Se uptake in stream biofilms and insects and if these insects were effective Se biovectors to riparian spiders. Biofilm Se concentration increased (p = 0.006) with mining extent, reaching a maximum value of 16.5 μg/g of dw. Insect and spider Se increased with biofilm Se (p = 0.004, p = 0.003), reaching 95 and 26 μg/g of dw, respectively, in mining-impacted streams. Adult insect biomass was not related to mining extent or Se concentrations in biofilm. Even though Se concentrations in aquatic insects were significantly and positively related to mining extent, aquatic insect Se flux was not associated with mining extent because the mass of emerging insects did not change appreciably over the mining gradient. Insect and spider Se concentrations were among the highest reported in the literature, regularly exceeding the bird Se dietary risk threshold of 5 μg/g of dw. Risks of Se exposure and toxicity related to mining are thus not constrained to aquatic systems but extend to terrestrial habitats and food webs.","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b05907","usgsCitation":"Naslund, L.C., Gerson, J.R., Brooks, A.C., Walters, D., and Bernhardt, E.S., 2020, Contaminant subsidies to riparian food webs in Appalachian streams impacted by mountaintop removal coal mining: Environmental Science & Technology, v. 54, no. 7, p. 3951-3959, https://doi.org/10.1021/acs.est.9b05907.","productDescription":"9 p.","startPage":"3951","endPage":"3959","ipdsId":"IP-112482","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":457323,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.9b05907","text":"Publisher Index Page"},{"id":373727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2020-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Naslund, Laura C.","contributorId":223770,"corporation":false,"usgs":false,"family":"Naslund","given":"Laura","email":"","middleInitial":"C.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":786206,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gerson, Jacqueline R.","contributorId":198378,"corporation":false,"usgs":false,"family":"Gerson","given":"Jacqueline","email":"","middleInitial":"R.","affiliations":[{"id":27331,"text":"Duke University, Durham, NC","active":true,"usgs":false},{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":786207,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Alexander C.","contributorId":223771,"corporation":false,"usgs":false,"family":"Brooks","given":"Alexander","email":"","middleInitial":"C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":786208,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walters, David 0000-0002-4237-2158","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":205915,"corporation":false,"usgs":true,"family":"Walters","given":"David","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":786205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bernhardt, Emily S.","contributorId":173736,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily","email":"","middleInitial":"S.","affiliations":[{"id":27285,"text":"Duke Univerisity","active":true,"usgs":false}],"preferred":false,"id":786209,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70208050,"text":"sim3447 - 2020 - Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","interactions":[],"lastModifiedDate":"2022-04-22T20:02:50.44033","indexId":"sim3447","displayToPublicDate":"2020-03-19T13:23:38","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3447","displayTitle":"Geologic Map of Petroglyph National Monument and Vicinity, Bernalillo County, New Mexico","title":"Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","docAbstract":"<p>This geologic map depicts and briefly describes geologic units underlying Petroglyph National Monument and immediately adjacent areas in Bernalillo County, New Mexico. The Monument is underlain dominantly by Quaternary basalts of the Albuquerque Volcanoes volcanic field, a series of basin-filling volcanic flows and associated vents from a monogenetic volcanic highland along the eastern margin of the Llano de Albuquerque. This compilation builds on data of previously published geologic maps and reports but includes new interpretive synthesis of volcanic stratigraphy and a unified representation of Quaternary surficial deposits overlying volcanic deposits within the Monument and areas immediately adjacent. This geologic map emphasizes the distribution of Quaternary volcanic vent areas and lava flow deposits which were incompletely mapped on previous publications. Surficial deposits are simplified, but uniformly mapped and described in contrast to varying map unit distributions, names and descriptions presented in the references above. Underlying deposits of the upper Santa Fe Group are exposed in the western part of the map area and described briefly.</p><p>North-trending, syn- and post-eruption faulting is well preserved in the volcanic field and reflected in the subsurface models of aeromagnetic data. These faults are dominated by dip-slip displacement and are interpreted as extensional faults of the central Albuquerque Basin of the northern Rio Grande rift. Elongate distribution of vents for most of the volcanic deposits are spatially associated with the easternmost of these faults and are interpreted to reflect eruptions from fissures paralleling the regional extensional fault trends of the rift.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3447","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Thompson, R.A., Chan, C.F., Gilmer, A.K., and Shroba, R.R., 2020, Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico: U.S. Geological Survey Scientific Investigations Map 3447, scale 1:24,000, https://doi.org/10.3133/sim3447.","productDescription":"2 Sheets: 50.50 inches x 40.00 inches; Data Release; ReadMe","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102605","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":373216,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LW817K","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Release for Geologic Map of Petroglyph National Monument and Vicinity, Bernalillo County, New Mexico"},{"id":373215,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3447/sim3447_georeferenced.pdf","text":"Sheet—Georeferenced geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3447"},{"id":399520,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109803.htm"},{"id":373213,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3447/coverthb.jpg"},{"id":373222,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3447/ReadMe.txt","text":"Read Me","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3447 Read Me"},{"id":373214,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3447/sim3447.pdf","text":"Sheet—Geologic map of Petroglyph National Monument and vicinity, Bernalillo County, New Mexico","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3447"}],"scale":"24000","country":"United States","state":"New Mexico","county":"Bernalillo County","otherGeospatial":"Petroglyph National Monument and vicinity","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.79946899414062,\n              35.097439809364204\n            ],\n            [\n              -106.68823242187499,\n              35.097439809364204\n            ],\n            [\n              -106.68823242187499,\n              35.188961188789925\n            ],\n            [\n              -106.79946899414062,\n              35.188961188789925\n            ],\n            [\n              -106.79946899414062,\n              35.097439809364204\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Center Director, <a data-mce-href=\"https://www.usgs.gov/centers/gecsc\" href=\"https://www.usgs.gov/centers/gecsc\">Geosciences and Environmental Change Science Center</a><br>U.S. Geological Survey<br>Box 25046, Mail Stop 980<br>Denver, CO 80225</p>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-03-19","noUsgsAuthors":false,"publicationDate":"2020-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Ren A. 0000-0002-3044-3043","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":207982,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":780272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chan, Christine F. 0000-0002-4933-3258","orcid":"https://orcid.org/0000-0002-4933-3258","contributorId":221802,"corporation":false,"usgs":false,"family":"Chan","given":"Christine F.","affiliations":[{"id":6773,"text":"University of Kansas","active":true,"usgs":false}],"preferred":false,"id":780273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilmer, Amy K. 0000-0001-5038-8136","orcid":"https://orcid.org/0000-0001-5038-8136","contributorId":218307,"corporation":false,"usgs":true,"family":"Gilmer","given":"Amy","email":"","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":780275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shroba, Ralph R. 0000-0002-2664-1813 rshroba@usgs.gov","orcid":"https://orcid.org/0000-0002-2664-1813","contributorId":1266,"corporation":false,"usgs":true,"family":"Shroba","given":"Ralph","email":"rshroba@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":780274,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261319,"text":"70261319 - 2020 - Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2019","interactions":[],"lastModifiedDate":"2024-12-06T14:18:20.448582","indexId":"70261319","displayToPublicDate":"2020-03-19T10:44:33","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2019","docAbstract":"<p>Lakewide acoustic (AT) and bottom trawl (BT) surveys are conducted annually to generate indices of pelagic and benthic prey fish densities in Lake Michigan. The BT survey has been conducted each fall since 1973 using 12-m trawls at depths ranging from 9 to 110 m and include 70 fixed locations distributed across seven transects; this survey estimates densities of seven prey fish species (i.e., alewife, bloater, rainbow smelt, deepwater sculpin, slimy sculpin, round goby, ninespine stickleback) as well as for age-0 yellow perch and large burbot. The AT survey has been conducted each late summer/early fall since 2004, and the 2019 survey consisted of 26 transects [513 km total (319 miles)] covering bottom depths ranging from 15 to 235 m and 30 midwater trawl tows covering bottom depths ranging 27 to 204 m; this survey estimates densities of three prey fish species (i.e., alewife, bloater, and rainbow smelt). The data generated from these surveys are used to estimate various population parameters that are, in turn, used by state and tribal agencies in managing Lake Michigan fish stocks. </p><p>For the BT survey, total biomass density of prey fish equaled only 1.77 kg/ha, the 2nd lowest estimate of the time series and well below the long-term average total biomass of 35.7 kg/ha. For the AT survey, total biomass density of prey fish equaled 4.71 kg/ha, just above the long-term average total biomass of 4.25 kg/ha. Both surveys reported bloater to be the dominant species (by biomass) among prey fishes. Mean biomass of yearling and older (YAO) alewives in 2019 was 1.56 kg/ha in the AT survey and 0.07 kg/ha in the BT survey. Comparing the acoustic estimate to previous years, YAO alewife biomass was 76% lower than the 2018 estimate and less than the average from 2004-2019. Numeric density of age-0 alewife from the AT survey was only 35.1/ha in 2019, which is indicative of a poor year-class and only the fourth since 2004 with a density less than 100/ha. The alewife age distribution remained truncated, with age-2 fish dominating the population and only three alewife (out of 525 aged) that were older than age 3. Biomass density of YAO bloater was 3.08 kg/ha in the AT survey and 0.78 kg/ha in the BT survey- each at least an order of magnitude lower than what was estimated by the BT survey between 1981 and 1998. Numeric density of age-0 bloater was the lowest ever measured for each survey: 0/ha for the AT survey and 0.12/ha for the BT survey. Biomass density of YAO rainbow smelt was 0.03 kg/ha in the AT survey and 0.04 kg/ha in the BT survey, continuing the low rainbow smelt biomass that has been observed since 2001. Numeric density of age-0 rainbow smelt was 1.33/ha in the AT survey and 0.99 in the BT survey, indicating a weak year-class that follows three year-classes that exceeded 41/ha between 2016 and 2018. All four prey fish species sampled only by the BT survey indicated below average biomass densities. Deepwater sculpin was estimated at 0.47 kg/ha, which makes 9 of the past 10 years when biomass was &lt;1 kg/ha. Slimy sculpin was estimated at 0.02 kg/ha, the second lowest density ever measured. Round goby was estimated at 0.39 kg/ha, which was below the average biomass of 0.96 kg/ha since 2008. Ninespine stickleback were only caught in one tow, and not surprisingly was estimated at a record low biomass. Burbot biomass remained near record low levels, and no age-0 yellow perch were caught, indicating a weak yellow perch year-class in 2019.</p>","language":"English","publisher":"Great Lakes Fishery Commission","usgsCitation":"Bunnell, D., Warner, D., Madenjian, C.P., Turschak, B., Dieter, P., and Desorcie, T., 2020, Status and trends of pelagic and benthic prey fish populations in Lake Michigan, 2019, 15 p.","productDescription":"15 p.","ipdsId":"IP-117618","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":464795,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.glfc.org/lake-michigan-committee.php","linkFileType":{"id":5,"text":"html"}},{"id":464811,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Michigan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": 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,{"id":70210163,"text":"70210163 - 2020 - A within-season approach for detecting early crop stage of corn and soybean using high temporal and spatial resolution imagery","interactions":[],"lastModifiedDate":"2020-05-19T15:05:04.146927","indexId":"70210163","displayToPublicDate":"2020-03-19T09:58:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A within-season approach for detecting early crop stage of corn and soybean using high temporal and spatial resolution imagery","docAbstract":"Crop emergence is a critical stage for crop development and crop growth modeling. Mapping crop emergence using remote sensing data is challenging. Previous remote sensing phenology algorithms showed that crop stages could be detected around the V3-V4 (3 to 4 established leaves) vegetative stage. Traditional approaches have a strong assumption regarding the temporal evolution of plant growth and normally require a complete growth period of observations to define seasonal changes. Most approaches were not designed for the within-season mapping in the early growing season. In the current paper, we developed a new within-season emergence (WISE) approach to mapping crop green-up date using satellite observations during early growth stages. The approach was first optimized using high spatiotemporal resolution (10 m, 2 day revisit) imagery from the Vegetation and Environment monitoring New MicroSatellite (VENµS) research mission, and assessed using ground observations of early crop growth stages (emergence VE and one leaf V1 stages for corn, and emergence VE and unifoliolate VC stages for soybeans) collected over the Beltsville Agricultural Research Center (BARC) experimental fields in Beltsville, MD during the 2019 growing season. Results show that early crop growth stages can be reliably detected at sub-field scale about two weeks after crop emergence. The remote sensing green-up dates were about 4-5 days after crop emergence on average. Coefficients of determination (R2) between green-up dates and the mid-point dates of the early growth stages were above 0.90. The mean absolute differences, standard deviations, and root mean square errors comparing to the early growth stage mid-point dates were within six days. The maximum differences were within ±10 days across all fields. The WISE approach was assessed using operational Sentinel-2 data (10 m, 5 day revisit) in BARC. The detected green-up dates from Sentinel-2 were found close to VENµS results. Some fields were not detected due to the lack of observations during emergence dates. For independent evaluation, the WISE approach was applied over an agricultural watershed on the Maryland Eastern Shore using both VENµS and the harmonized Landsat and Sentinel-2 (HLS) data (30 m, 3-4 day revisit). The green-up dates were compared with crop progress reports of crop emergence dates from the National Agricultural Statistics Service (NASS) at the state-level. The WISE -detected green-up dates at the regional scale are within VE stage ranges but slightly earlier than NASS crop progress reports at the state-level. The WISE approach uses remote sensing observations during the early crop growth stages and has potential for operational application within the season using Sentinel-2 and HLS data.","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2020.111752","usgsCitation":"Gao, F., Anderson, M., Daughtry, C.S., Karnieli, A., Hively, W.D., and Kustas, W.P., 2020, A within-season approach for detecting early crop stage of corn and soybean using high temporal and spatial resolution imagery: Remote Sensing of Environment, v. 242, 111752, 19 p., https://doi.org/10.1016/j.rse.2020.111752.","productDescription":"111752, 19 p.","ipdsId":"IP-113523","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":457324,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2020.111752","text":"Publisher Index Page"},{"id":374923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Beltsville Agricultural Research Center (BARC), Choptank River watershed","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -76.94412231445312,\n              38.756225137839074\n            ],\n            [\n              -76.38381958007812,\n              38.756225137839074\n            ],\n            [\n              -76.38381958007812,\n              39.29392267616436\n            ],\n            [\n              -76.94412231445312,\n              39.29392267616436\n            ],\n            [\n              -76.94412231445312,\n              38.756225137839074\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"242","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gao, Feng","contributorId":197297,"corporation":false,"usgs":false,"family":"Gao","given":"Feng","affiliations":[],"preferred":false,"id":789358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Martha","contributorId":210925,"corporation":false,"usgs":false,"family":"Anderson","given":"Martha","affiliations":[],"preferred":false,"id":789359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":789360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karnieli, Arnon 0000-0001-8065-9793","orcid":"https://orcid.org/0000-0001-8065-9793","contributorId":224743,"corporation":false,"usgs":false,"family":"Karnieli","given":"Arnon","email":"","affiliations":[{"id":40930,"text":"Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Israel","active":true,"usgs":false}],"preferred":false,"id":789361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":789362,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kustas, William P.","contributorId":29962,"corporation":false,"usgs":false,"family":"Kustas","given":"William","email":"","middleInitial":"P.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":789363,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70211314,"text":"70211314 - 2020 - Mechanics of near-field deformation during co- and post-seismic shallow fault slip","interactions":[],"lastModifiedDate":"2020-07-23T20:28:56.833088","indexId":"70211314","displayToPublicDate":"2020-03-19T09:33:17","publicationYear":"2020","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":"Mechanics of near-field deformation during co- and post-seismic shallow fault slip","docAbstract":"Poor knowledge of how faults slip and distribute deformation in the shallow crust hinders efforts to mitigate hazards where faults increasingly intersect with the expanding global population at Earth’s surface. Here we analyze two study sites along the 2014 M 6.0 South Napa, California, earthquake rupture, each dominated by either co- or post-seismic shallow fault slip. We combine mobile laser scanning (MLS), active-source seismic tomography, and finite element modeling to investigate how deformation rate and mechanical properties of the shallow crust affect fault behavior. Despite four orders-of-magnitude difference in the rupture velocities, MLS-derived shear strain fields are remarkably similar at the two sites and suggest deceleration of the co-seismic rupture near Earth’s surface. Constrained by the MLS and seismic data, finite element models indicate shallow faulting is more sensitive to lithologic layering and plastic yielding than to the presence of fault compliant zones (i.e., regions surrounding faults with reduced stiffness). Although both elastic and elastoplastic models can reproduce the observed surface displacement fields within the uncertainty of MLS data, elastoplastic models likely provide the most reliable representations of subsurface fault behavior, as they produce geologically reasonable stress states and are consistent with field, geodetic, and seismological observations.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-020-61400-9","usgsCitation":"Nevitt, J., Brooks, B.A., Catchings, R.D., Goldman, M., Ericksen, T., and Glennie, C.L., 2020, Mechanics of near-field deformation during co- and post-seismic shallow fault slip: Scientific Reports, v. 10, 5031, 13 p., https://doi.org/10.1038/s41598-020-61400-9.","productDescription":"5031, 13 p.","ipdsId":"IP-099149","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":457326,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-020-61400-9","text":"Publisher Index Page"},{"id":376665,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Napa Fault Zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.65274047851562,\n              38.22199865889175\n            ],\n            [\n              -122.21328735351562,\n              38.22199865889175\n            ],\n            [\n              -122.21328735351562,\n              38.6897975322717\n            ],\n            [\n              -122.65274047851562,\n              38.6897975322717\n            ],\n            [\n              -122.65274047851562,\n              38.22199865889175\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2020-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Nevitt, Johanna 0000-0003-3819-1773 jnevitt@usgs.gov","orcid":"https://orcid.org/0000-0003-3819-1773","contributorId":198144,"corporation":false,"usgs":true,"family":"Nevitt","given":"Johanna","email":"jnevitt@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":793732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brooks, Benjamin A. 0000-0001-7954-6281 bbrooks@usgs.gov","orcid":"https://orcid.org/0000-0001-7954-6281","contributorId":5237,"corporation":false,"usgs":true,"family":"Brooks","given":"Benjamin","email":"bbrooks@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":793733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catchings, Rufus D. 0000-0002-5191-6102 catching@usgs.gov","orcid":"https://orcid.org/0000-0002-5191-6102","contributorId":1519,"corporation":false,"usgs":true,"family":"Catchings","given":"Rufus","email":"catching@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":793734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goldman, Mark 0000-0002-0802-829X","orcid":"https://orcid.org/0000-0002-0802-829X","contributorId":205863,"corporation":false,"usgs":true,"family":"Goldman","given":"Mark","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":793735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ericksen, Todd 0000-0001-9340-575X tericksen@usgs.gov","orcid":"https://orcid.org/0000-0001-9340-575X","contributorId":198145,"corporation":false,"usgs":true,"family":"Ericksen","given":"Todd","email":"tericksen@usgs.gov","affiliations":[],"preferred":true,"id":793749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glennie, Craig L.","contributorId":198143,"corporation":false,"usgs":false,"family":"Glennie","given":"Craig","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":793737,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70249570,"text":"70249570 - 2020 - Detecting commonality in multidimensional fish movement histories using sequence analysis","interactions":[],"lastModifiedDate":"2023-10-17T12:00:36.066173","indexId":"70249570","displayToPublicDate":"2020-03-19T06:57:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Detecting commonality in multidimensional fish movement histories using sequence analysis","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Acoustic telemetry, for tracking fish movement histories, is multidimensional capturing both spatial and temporal domains. Oftentimes, analyses of such data are limited to a single domain, one domain nested within the other, or ad hoc approaches that simultaneously consider both domains. Sequence analysis, on the other hand, offers a repeatable statistical framework that uses a sequence alignment algorithm to calculate pairwise dissimilarities among individual movement histories and then hierarchical agglomerative clustering to identify groups of fish with similar movement histories. The objective of this paper is to explore how acoustic telemetry data can be fit to this statistical framework and used to identify commonalities in the movement histories of acoustic-tagged sea lamprey during upstream migration through the St. Clair-Detroit River System.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Five significant clusters were identified among individual fish. Clusters represented differences in timing of movements (short vs long duration in the Detroit R. and Lake St. Clair); extent of upstream migration (ceased migration in Lake St. Clair, lower St. Clair R., or upper St. Clair R.), and occurrence of fallback (return to Lake St. Clair after ceasing migration in the St. Clair R.). Inferences about sea lamprey distribution and behavior from these results were similar to those reached in a previous analysis using ad-hoc analysis methods.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>The repeatable statistical framework outlined here can be used to group sea lamprey movement histories based on shared sequence characteristics (i.e., chronological order of “states” occupied). Further, this framework is flexible and allows researchers to define a priori the movement aspect (e.g., order, timing, duration) that is important for identifying both common or previously undetected movement histories. As such, we do not view sequence analysis as a panacea but as a useful complement to other modelling approaches (i.e., exploratory tool for informing hypothesis development) or a stand-alone semi-quantitative method for generating a simplified, temporally and spatially structured view of complex acoustic telemetry data and hypothesis testing when observed patterns warrant further investigation.</p>","language":"English","publisher":"Springer Nature","doi":"10.1186/s40317-020-00195-y","usgsCitation":"Lowe, M.R., Holbrook, C., and Hondorp, D.W., 2020, Detecting commonality in multidimensional fish movement histories using sequence analysis: Animal Biotelemetry, v. 8, 10, 14 p., https://doi.org/10.1186/s40317-020-00195-y.","productDescription":"10, 14 p.","ipdsId":"IP-114379","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457331,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-020-00195-y","text":"Publisher Index Page"},{"id":421938,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Michigan","otherGeospatial":"St. Clair River Detroit River system","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.33021246125514,\n              42.011299379305854\n            ],\n            [\n              -82.17664800813024,\n              42.011299379305854\n            ],\n            [\n              -82.17664800813024,\n              43.03151009761868\n            ],\n            [\n              -83.33021246125514,\n              43.03151009761868\n            ],\n            [\n              -83.33021246125514,\n              42.011299379305854\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2020-03-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Lowe, Michael R. 0000-0002-4645-9429","orcid":"https://orcid.org/0000-0002-4645-9429","contributorId":10539,"corporation":false,"usgs":true,"family":"Lowe","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":886255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":886256,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hondorp, Darryl W. 0000-0002-5182-1963 dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":886257,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208812,"text":"ofr20201021 - 2020 - Geologic map of the Paeroa Fault block and surrounding area, Taupo Volcanic Zone, New Zealand","interactions":[],"lastModifiedDate":"2020-03-20T07:07:13","indexId":"ofr20201021","displayToPublicDate":"2020-03-18T12:42:34","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1021","displayTitle":"Geologic Map of the Paeroa Fault Block and Surrounding Area, Taupo Volcanic Zone, New Zealand","title":"Geologic map of the Paeroa Fault block and surrounding area, Taupo Volcanic Zone, New Zealand","docAbstract":"<p>The Taupo Volcanic Zone (TVZ), New Zealand, is the most productive area of explosive silicic volcanism in the world. Faulted early and middle Pleistocene volcanic products are generally concealed beneath voluminous, generally unfaulted, younger volcanic products. An exception is the southeast margin of the TVZ where the two parallel, northeast-trending Paeroa and Te Weta Fault blocks expose Quaternary volcanic products consisting predominantly of caldera-related, rhyolitic ignimbrites and lacustrine sediments. The Taupo-Reporoa Basin is situated along the eastern part of the map area, and its northernmost part underwent collapse to form Reporoa Caldera.</p><p>The Paeroa Fault block is the largest exposed fault block within the TVZ, and it encompasses early and middle Pleistocene ignimbrites and sedimentary deposits that are buried throughout the Taupo-Reporoa Basin to the east. This map displays the volcanic and sedimentary geology of ~430 km<sup>2</sup> of the Paeroa Fault block and the adjacent Te Weta Fault block at a scale of 1:50,000. Volcanic and sedimentary rocks are divided into the Reporoa Group, Whakamaru Group, and Huka Group (from oldest to youngest), which are overlain by relatively unfaulted late Pleistocene and Holocene surficial volcanic and sedimentary deposits.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201021","usgsCitation":"Downs, D.T., Leonard, G.S., Wilson, C.J.N., and Rowland, J.V., 2020, Geologic map of the Paeroa Fault block and surrounding area, Taupo Volcanic Zone, New Zealand: U.S. Geological Survey Open-File Report 2020–1021, scale 1:50,000, https://doi.org/10.3133/ofr20201021.","productDescription":"1 Map: 50.22 x  34.79 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-107861","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":373326,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DYBBGX","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Database for the geologic map of the Paeroa fault block and surrounding area, Taupo Volcanic Zone, New Zealand"},{"id":373324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1021/coverthb.jpg"},{"id":373325,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2020/1021/ofr20201021.pdf","text":"Sheet","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1021"}],"country":"New Zealand ","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              165.948486328125,\n              -46.72103466129568\n            ],\n            [\n              170.7550048828125,\n              -46.72103466129568\n            ],\n            [\n              170.7550048828125,\n              -44.15462243076732\n            ],\n            [\n              165.948486328125,\n              -44.15462243076732\n            ],\n            [\n              165.948486328125,\n              -46.72103466129568\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://avo.alaska.edu/about/staff.php\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://avo.alaska.edu/about/staff.php\">Alaska Volcano Observatory staff</a><br><a href=\"https://avo.alaska.edu/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://avo.alaska.edu/\">Alaska Volcano Observatory</a><br>
4210 University Drive <br>Anchorage, AK 99508</p>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2020-03-18","noUsgsAuthors":false,"publicationDate":"2020-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":783479,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, Graham S.","contributorId":127469,"corporation":false,"usgs":false,"family":"Leonard","given":"Graham","email":"","middleInitial":"S.","affiliations":[{"id":5111,"text":"GNS Science, New Zealand","active":true,"usgs":false}],"preferred":false,"id":783480,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Colin J. N.","contributorId":202865,"corporation":false,"usgs":false,"family":"Wilson","given":"Colin","email":"","middleInitial":"J. N.","affiliations":[{"id":36540,"text":"Victoria University, PO Box 600, Wellington 6140, New Zealand","active":true,"usgs":false}],"preferred":false,"id":783481,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowland, Julie V 0000-0002-6578-5035","orcid":"https://orcid.org/0000-0002-6578-5035","contributorId":222909,"corporation":false,"usgs":false,"family":"Rowland","given":"Julie","email":"","middleInitial":"V","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":783482,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208116,"text":"fs20203002 - 2020 - Water resources of Union Parish, Louisiana","interactions":[],"lastModifiedDate":"2022-04-20T18:06:15.077165","indexId":"fs20203002","displayToPublicDate":"2020-03-18T12:38:43","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3002","displayTitle":"Water Resources of Union Parish, Louisiana","title":"Water resources of Union Parish, Louisiana","docAbstract":"<p>Information concerning the availability, use, and quality of water in Union Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 4.88 million gallons per day (Mgal/d) of water were withdrawn in Union Parish: 4.70 Mgal/d from groundwater sources and 0.18 Mgal/d from surface-water sources. Withdrawals for public-supply use accounted for about 89&nbsp;percent (4.36 Mgal/d) of the total water withdrawn. Other categories of use included industrial, rural domestic, livestock, rice irrigation, and general irrigation. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 2000 at about 8.89 Mgal/d.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203002","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Robinson, A.L., 2020, Water resources of Union Parish, Louisiana: U.S. Geological Survey Fact Sheet 2020–3002, 6 p., https://doi.org/10.3133/fs20203002.","productDescription":"Report: 6 p.; Data Release","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-103356","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399197,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109796.htm"},{"id":373339,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 2014–2015"},{"id":373338,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3002/fs20203002.pdf","text":"Report","size":"835 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020–3002"},{"id":373337,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3002/coverthb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Union Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.0647,33.0089],[-92.0641,33.0021],[-92.0717,32.997],[-92.0711,32.9875],[-92.0771,32.9861],[-92.082,32.9815],[-92.0754,32.9738],[-92.0759,32.9697],[-92.083,32.9692],[-92.0857,32.9651],[-92.0835,32.9619],[-92.0851,32.9569],[-92.0791,32.9565],[-92.0807,32.951],[-92.0779,32.9465],[-92.0767,32.9342],[-92.0728,32.9251],[-92.0739,32.916],[-92.0798,32.9091],[-92.0776,32.8968],[-92.0786,32.8877],[-92.084,32.8777],[-92.0751,32.8604],[-92.0663,32.85],[-92.0564,32.8446],[-92.0558,32.8378],[-92.0645,32.8341],[-92.0651,32.8313],[-92.0601,32.8277],[-92.0601,32.8241],[-92.0661,32.8213],[-92.0633,32.814],[-92.0572,32.805],[-92.0545,32.7981],[-92.0533,32.7941],[-92.0548,32.7722],[-92.0554,32.7699],[-92.0602,32.7663],[-92.0613,32.7617],[-92.0624,32.7576],[-92.0629,32.7558],[-92.0623,32.7508],[-92.0568,32.7481],[-92.0519,32.7435],[-92.054,32.7371],[-92.0589,32.7348],[-92.0605,32.7303],[-92.0654,32.723],[-92.0724,32.7161],[-92.0756,32.7088],[-92.0822,32.7042],[-92.0902,32.6878],[-92.0989,32.6836],[-92.1092,32.6827],[-92.1201,32.6735],[-92.1277,32.6762],[-92.1391,32.6757],[-92.1418,32.6702],[-92.1385,32.6611],[-92.19,32.6294],[-92.1964,32.6252],[-92.2187,32.6114],[-92.2214,32.611],[-92.2241,32.6073],[-92.224,32.6005],[-92.2266,32.5941],[-92.2288,32.5909],[-92.2342,32.5895],[-92.2402,32.5908],[-92.2451,32.5917],[-92.2506,32.5898],[-92.2566,32.5911],[-92.2625,32.5906],[-92.2647,32.587],[-92.2712,32.5828],[-92.2766,32.5814],[-92.2793,32.5837],[-92.2815,32.586],[-92.2843,32.585],[-92.2886,32.5836],[-92.2935,32.5841],[-92.2968,32.5845],[-92.3049,32.5831],[-92.3512,32.5832],[-92.4132,32.5845],[-92.4153,32.672],[-92.4736,32.6715],[-92.5188,32.6725],[-92.5195,32.7239],[-92.5233,32.723],[-92.5271,32.7202],[-92.5342,32.7224],[-92.5374,32.7206],[-92.5418,32.7187],[-92.5472,32.7205],[-92.5517,32.7268],[-92.5572,32.7331],[-92.5672,32.7453],[-92.5722,32.7489],[-92.5787,32.748],[-92.5852,32.7488],[-92.5913,32.7528],[-92.5968,32.7551],[-92.6044,32.7555],[-92.6099,32.7549],[-92.6147,32.7526],[-92.6191,32.7548],[-92.6279,32.7575],[-92.6312,32.7593],[-92.6361,32.7597],[-92.7256,32.7597],[-92.7252,32.8039],[-92.7339,32.8033],[-92.7341,32.8179],[-92.7254,32.818],[-92.7257,32.8758],[-92.7253,32.9209],[-92.7253,32.9222],[-92.7251,32.9445],[-92.725,33.0083],[-92.7246,33.0147],[-92.6255,33.0136],[-92.3864,33.0123],[-92.1457,33.0093],[-92.1194,33.0092],[-92.0647,33.0089]]]},\"properties\":{\"name\":\"Union\",\"state\":\"LA\"}}]}","contact":"<p><a href=\"mailto:gs-w-lmg_center_director@usgs.gov\" data-mce-href=\"mailto:gs-w-lmg_center_director@usgs.gov\">Director</a>, <a href=\"https://la.water.usgs.gov/\" data-mce-href=\"https://la.water.usgs.gov/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>3535 S. Sherwood Forest Blvd., Suite 120 <br>Baton Rouge, LA 70816</p>","tableOfContents":"<ul><li>Introduction</li><li>Groundwater Resources</li><li>Surface-Water Resources</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-03-18","noUsgsAuthors":false,"publicationDate":"2020-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Angela L. 0000-0001-5845-4847","orcid":"https://orcid.org/0000-0001-5845-4847","contributorId":206329,"corporation":false,"usgs":true,"family":"Robinson","given":"Angela","email":"","middleInitial":"L.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":780543,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70209081,"text":"sir20195077 - 2020 - Geochemical and mineralogical study of the Red Mountain porphyry copper-molybdenum deposit and vicinity, Santa Cruz County, Arizona","interactions":[],"lastModifiedDate":"2022-04-22T21:15:48.594847","indexId":"sir20195077","displayToPublicDate":"2020-03-18T12:15:00","publicationYear":"2020","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":"2019-5077","displayTitle":"Geochemical and Mineralogical Study of the Red Mountain Porphyry Copper-Molybdenum Deposit and Vicinity, Santa Cruz County, Arizona","title":"Geochemical and mineralogical study of the Red Mountain porphyry copper-molybdenum deposit and vicinity, Santa Cruz County, Arizona","docAbstract":"<p>The Red Mountain porphyry copper-molybdenum deposit (Cu-Mo deposit or PCD) is located in the northern part of the Patagonia Mountains, Santa Cruz County, Arizona. Extensive core drilling has delineated a large, deep-seated, structurally intact mineral system that extends from the present surface to depths of more than 1,765 meters. This system is hosted in a thick complex of predominantly felsic to andesitic volcanic rocks of the Cretaceous Period. This complex was intruded by scattered bodies of the Tertiary Period that are predominantly quartz monzonite porphyry; no major associated source intrusion&nbsp;has yet been found at depth.</p><p>A total of 818 samples of core were analyzed for as many as 44 elements. The abundances and distributions at depth of at least 17 of these elements (silver [Ag], arsenic [As], gold [Au], boron [B], bismuth [Bi], copper [Cu], mercury [Hg], potassium [K], molybdenum [Mo], lead [Pb], sulfur [S], antimony [Sb], tin [Sn], tellurium [Te], thallium [Tl], tungsten [W], and zinc [Zn]) are related mostly to events that generated the Red Mountain system. Many of these same samples were also analyzed by X-ray diffraction for a suite of minerals. The multielement and mineralogical analyses of the core samples provide important information about the concentrations, associations, and distributions of select elements and minerals, including zoning patterns that may not be apparent from visual examination of core samples. The distributions of selected elements and minerals in these samples reveal an unusually complete mineral system that extends from a typical PCD with potassic alteration at depth to peripheral zones of phyllic and advanced argillic alteration as well as a copper-rich supergene enriched zone and the remnants of a leached cap.</p><p>R-mode factor analysis was run with 34 elements for a set of samples from the deep part of the hypogene Cu-Mo deposit and another set from the part of the supergene zone with the highest copper enrichment. For the hypogene zone dataset, five factors are related to the PCD: (1) Ag, Cu, Mo, S, and Te; (2) As, B, Hg, and Sb; (3) Au and sodium (Na); (4) manganese (Mn), Pb, and Zn; and (5) K and Tl. For the supergene dataset, the deposit-related factors include (1) Cu, Mo, S, and Te;&nbsp;(2) Ag, As, Hg, Pb, Sb, and Tl; (3) Au and Na; and (4) K and rubidium (Rb). The changes in element associations between the two datasets indicate that some of these new associations are a result of formation of several suites of hypogene minerals in the deep part of the deposit and different hypogene mineral suites in the peripheral part of the deposit. Some changes may be because of the effects of supergene processes.</p><p>Zones containing deposit-related elements and minerals common to many PCDs are present at Red Mountain. These zones include a crude, inverted cup-shaped shell containing anomalous copper accompanied by high concentrations of Ag, Au, K, Mo, total S, sulfate S, Sb, Te, and Tl, as well as local concentrations of As, B, Hg, Pb, and Zn. Hydrothermal minerals spatially associated with the deep hypogene Cu-Mo deposit include chalcopyrite, molybdenite, pyrite, plagioclase, orthoclase, biotite, magnetite, calcite, quartz, and anhydrite.</p><p>Many of the hydrothermally deposited elements that are spatially related to the deposit are also concentrated in zones above the deep part of the deposit, including Ag, As, K, Pb, Sb, Te, Tl, and Zn. These elements are concentrated either (1) in generally wide, flat zones present in the upper part of the system or (2) in crudely arcuate peripheral zones found mainly in the middle part of the system and surrounding the deep part of the deposit. Near-surface, restricted hypogene anomalies are present for bismuth, mercury, tin, and tungsten.</p><p>The upper part of the deposit has been subjected to supergene&nbsp;enrichment and weathering. Deposit-related elements that remain anomalous in this area include Ag, As, Au, B, Bi, cobalt (Co), Cu,&nbsp;Hg, Mo, Pb, S, Sb, Sn, Te, Tl, uranium (U), and W. These positive&nbsp;concentrations indicate that, with the exception of copper and possibly mercury and uranium, these elements had relatively low chemical mobilities in the supergene enrichment and later&nbsp;weathering environments at Red Mountain. Most may have been&nbsp;deposited during one or more hypogene events and then redistributed locally during later events. Zinc is the only deposit-related&nbsp;element that has clearly been depleted as a result of supergene and (or) weathering events. Minerals that are common in the unweathered upper part of the system include chalcocite, pyrite,&nbsp;quartz, sericite, alunite, and pyrophyllite, as well as less common covellite, enargite, tennantite, tourmaline, barite, anglesite,&nbsp;and other sulfide or sulfate minerals.</p><p>Subsequent to formation of the Red Mountain Cu-Mo deposit and supergene enrichment, chemical weathering produced an area of pervasive hematite and other iron oxides in the near-surface part of the deposit to form a leached cap. These iron-rich minerals formed primarily as a result of the oxidation of pyrite. This event was accompanied by losses of cobalt, mercury, magnesium, and zinc, as well as destruction of sericite, plagioclase, pyrite, clay minerals, and pyrophyllite.</p><p>A total of 122 rock samples, 119 soil samples, and samples&nbsp;of three plant species (57 mesquite, 108 oak, and 68 juniper) were collected over and around Red Mountain. For the rock and soil samples, the distributions of anomalous Ag, As, Bi, Cu, Fe, Mo, Pb, Sb, Te, and Tl best delineated the exposed part of the deposit. The highest concentrations of many of these elements are centered on one or both of two main areas with exposures of quartz monzonite porphyry. The high concentrations of arsenic in the deposit area (as much as 390 parts per million (ppm) in rock and 1,500 ppm in soil) and of lead (as much as 2,370 ppm in rock and 1,490 ppm in soil) are particularly noteworthy.</p><p>The concentrations of various elements in the plant ash vary widely among the three species and are species dependent. Many of the deposit-related elements are either nonessential for plant growth or are considered toxic at certain concentration&nbsp;ranges. In spite of this, the distributions of potentially toxic Ag, As, Bi, Cd, Cu, Mo, Pb, Sb, selenium (Se), and Zn produce deposit-related anomalies for one or more of the three species.</p><p>Vegetation sampling offered no advantage over rock or soil sampling as an exploration tool. From an environmental standpoint, however, the plant analyses provide baseline data for both essential and nonessential elements that might be useful, for example, for selecting native plant species for revegetating mine waste areas.</p><p>The exposed part of the Red Mountain deposit has not been greatly disturbed as a result of mining and other activities. However, some of the rock, soil, and plant samples that were collected near the Harshaw Creek and Alum Gulch drainages, which are peripheral to Red Mountain, are also anomalous for various deposit-related elements. These anomalies are probably the result of dispersion of stream sediments contaminated with material from past mining.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195077","usgsCitation":"Chaffee, M.A., 2020, Geochemical and mineralogical study of the Red Mountain porphyry copper-molybdenum deposit and vicinity, Santa Cruz County, Arizona: U.S. Geological Survey Scientific Investigations Report 2019–5077, 164 p., https://doi.org/10.3133/sir20195077.","productDescription":"Report: x, 164 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-085267","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":373304,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BS56JZ","text":"USGS data release","linkHelpText":"Data to accompany U.S. Geological Survey Scientific Investigations Report 2019-5077: Geochemical and mineralogical study of the Red Mountain porphyry copper-molybdenum deposit and vicinity, Santa Cruz County, Arizona"},{"id":399536,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109795.htm"},{"id":373303,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5077/sir20195077.pdf","text":"Report","size":"22.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5077"},{"id":373302,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5077/coverthb.jpg"}],"country":"United States","state":"Arizona","county":"Santa Cruz County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-111.364,31.4234],[-111.3654,31.5211],[-111.2983,31.5216],[-111.2634,31.5218],[-111.1608,31.522],[-111.1595,31.5403],[-111.1616,31.5508],[-111.1612,31.6389],[-111.1614,31.7242],[-111.0036,31.7247],[-110.9557,31.7247],[-110.8906,31.7255],[-110.8712,31.7257],[-110.8518,31.7255],[-110.8523,31.731],[-110.7941,31.7309],[-110.7042,31.7308],[-110.6902,31.7306],[-110.6838,31.7305],[-110.6692,31.7308],[-110.6644,31.7303],[-110.617,31.7306],[-110.5341,31.7309],[-110.4485,31.7307],[-110.4485,31.702],[-110.4482,31.6883],[-110.4483,31.6536],[-110.448,31.6157],[-110.4561,31.6154],[-110.4558,31.6017],[-110.4555,31.5871],[-110.4562,31.4684],[-110.4561,31.3328],[-110.4611,31.3328],[-110.4888,31.3328],[-110.5574,31.3324],[-110.6259,31.3323],[-110.6645,31.3321],[-110.7229,31.3318],[-110.7915,31.3315],[-110.8238,31.3313],[-110.8261,31.3312],[-110.8351,31.3312],[-110.8659,31.3309],[-110.8787,31.3308],[-110.9721,31.3301],[-111.0496,31.3294],[-111.0664,31.3292],[-111.0728,31.3292],[-111.1604,31.3577],[-111.1676,31.3601],[-111.1705,31.361],[-111.1725,31.3617],[-111.1746,31.3624],[-111.2218,31.3778],[-111.2843,31.3978],[-111.364,31.4234]]]},\"properties\":{\"name\":\"Santa Cruz\",\"state\":\"AZ\"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/gggsc/\" data-mce-href=\"https://www.usgs.gov/centers/gggsc/\">Geology, Geophysics, and Geochemistry Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-973<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Location and Geologic Setting</li><li>Part A—Subsurface Geochemical and Mineralogical Studies of Core Sampling, Preparation, and Chemical Analysis of Core</li><li>Mineralogical Analysis</li><li>Results and Evaluation of the Core Analyses</li><li>R-Mode Factor Analysist</li><li>Distributions of Elements and Minerals in the Subsurface</li><li>Part B—Surface Geochemical Studies of Rock, Soil, and Vegetation</li><li>Sampling, Preparation, and Analysis</li><li>Results and Evaluation of the Rock Chemistry</li><li>Results and Evaluation of the Soil Chemistry</li><li>Results and Evaluation of the Vegetation Chemistry.</li><li>Distributions of Selected Elements in Rock and Soil Samples</li><li>Distribution of Percent Ash and Selected Elements in Vegetation Samples</li><li>Applications of Geochemical and Mineralogical Analyses to Geologic Mapping, Mineral Deposit Genesis and Models, Distribution and Zoning of Elements and Minerals, Exploration for Mineral Deposits, and Environmental Investigations</li><li>Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-03-18","noUsgsAuthors":false,"publicationDate":"2020-03-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Chaffee, Maurice 0000-0001-7391-1401 mchaffee@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-1401","contributorId":223366,"corporation":false,"usgs":true,"family":"Chaffee","given":"Maurice","email":"mchaffee@usgs.gov","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":784855,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70223432,"text":"70223432 - 2020 - Minnesota landowners’ trust in their department of natural resources, salient values similarity and wildlife value orientations","interactions":[],"lastModifiedDate":"2021-08-26T16:39:10.164461","indexId":"70223432","displayToPublicDate":"2020-03-18T11:36:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5016,"text":"Environment Systems and Decisions","active":true,"publicationSubtype":{"id":10}},"title":"Minnesota landowners’ trust in their department of natural resources, salient values similarity and wildlife value orientations","docAbstract":"<p><span>Due to extensive land conversion over the last century, much of the native prairie pothole ecosystem has been converted to agricultural or other human uses. The prairie pothole ecosystem is found in the northern plains of Iowa, Minnesota, South Dakota, North Dakota, and Montana. Because most of the land in this region is privately owned and used for agricultural production, most impacts to wildlife habitat are the result of decisions by individual landowners. Landowner trust in natural resource management agencies is important for agencies to effectively accomplish their mission. We measured the nature (competence and fairness) and level of trust that western Minnesota landowners have in the Minnesota Department of Natural Resources (MnDNR) and landowners’ wildlife value orientations (WVO). Landowners rated MnDNR slightly higher in competence than fairness; however, these two dimensions were strongly correlated. We developed a MnDNR trust scale (six items) and a three-cluster model dividing landowners along the MnDNR trust scale, which we named Negative (28%), Neutral (43%), and Positive (29%). We provide evidence supporting the salient values similarity (SVS) model that states people have trust in agencies holding similar values; landowners reporting greater importance for wildlife consideration when making land-use decisions also reported greater trust in the MnDNR. In addition, mutualist landowners had the highest trust in the MnDNR and utilitarian landowners the lowest level of trust, which is opposite of the trust relationship reported for the general public with state wildlife agencies. Based on the SVS model, our results suggest that mutualist landowners perceive greater congruence with MnDNR goals related to wildlife habitat compared to utilitarian landowners.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10669-020-09766-z","usgsCitation":"Gigliotti, L.M., Sweikert, L., Cornicelli, L., and Fulton, D.C., 2020, Minnesota landowners’ trust in their department of natural resources, salient values similarity and wildlife value orientations: Environment Systems and Decisions, v. 40, p. 577-587, https://doi.org/10.1007/s10669-020-09766-z.","productDescription":"11 p.","startPage":"577","endPage":"587","ipdsId":"IP-103189","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":388554,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70210858,"text":"70210858 - 2020 - Deglacial temperature controls on no-analog community establishment in the Great Lakes Region","interactions":[],"lastModifiedDate":"2020-06-30T13:37:00.272631","indexId":"70210858","displayToPublicDate":"2020-03-18T08:30:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Deglacial temperature controls on no-analog community establishment in the Great Lakes Region","docAbstract":"Understanding the drivers of vegetation dynamics and no-analog communities in eastern North America is hampered by a scarcity of independent temperature indicators. We present a new branched glycerol dialkyl glycerol tetraether (brGDGT) temperature record from Bonnet Lake, Ohio (18 to 8 ka) and report uncertainty estimates based on Bayesian linear regression and bootstrapping. We also reanalyze a previously published brGDGT record from Silver Lake, Ohio, using improved chromatographic methods. All pollen- and brGDGT-based temperature reconstructions showed qualitatively similar deglacial trends but varying magnitudes. Separating 5- and 6- methyl brGDGTs resulted in substantially lower estimates of deglacial temperature variations (6.4 °C) than inferred from earlier brGDGT methods and pollen (11.8 °C, 12.0 °C respectively). Similar trends among proxies suggest good fidelity of brGDGTs to temperature, despite calibration uncertainties. At both sites, the rise and decline of no-analog communities closely track brGDGT-inferred temperatures, with a lag of 0 to 150 years. The timing of temperature and ecological events varies between Bonnet and Silver Lakes, likely due to age model uncertainties. Climate sensitivity analyses indicate a linear sensitivity of vegetation composition to temperature variations, albeit noisy and significant only with a 500-year bin. The formation of no-analog plant communities in the upper Midwest is closely linked to late-glacial warming, but other factors, such as temperature seasonality or end-Pleistocene megafaunal extinctions, remain viable.","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2020.106245","usgsCitation":"Fastovich, D., Russell, J.M., Jackson, S., and Williams, J.W., 2020, Deglacial temperature controls on no-analog community establishment in the Great Lakes Region: Quaternary Science Reviews, v. 234, 106245, 16 p., https://doi.org/10.1016/j.quascirev.2020.106245.","productDescription":"106245, 16 p.","ipdsId":"IP-107598","costCenters":[{"id":41166,"text":"Southwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":457336,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.quascirev.2020.106245","text":"Publisher Index Page"},{"id":376014,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes Region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -85.869140625,\n              37.71859032558816\n            ],\n            [\n              -79.7607421875,\n              37.71859032558816\n            ],\n            [\n              -79.7607421875,\n              41.902277040963696\n            ],\n            [\n              -85.869140625,\n              41.902277040963696\n            ],\n            [\n              -85.869140625,\n              37.71859032558816\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"234","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fastovich, David","contributorId":225614,"corporation":false,"usgs":false,"family":"Fastovich","given":"David","email":"","affiliations":[],"preferred":false,"id":791886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, James M.","contributorId":174740,"corporation":false,"usgs":false,"family":"Russell","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":27506,"text":"Department of Earth, Environmental and Planetary Sciences, Brown University, Providence RI 02912 USA","active":true,"usgs":false}],"preferred":false,"id":791887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Stephen 0000-0002-1487-4652","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":219995,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":791749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, John W.","contributorId":16761,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":791888,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70216012,"text":"70216012 - 2020 - Relocated aftershocks and background seismicity in eastern Indonesia shed light on the 2018 Lombok and Palu earthquake sequences","interactions":[],"lastModifiedDate":"2020-11-03T13:29:28.447413","indexId":"70216012","displayToPublicDate":"2020-03-18T07:22:56","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Relocated aftershocks and background seismicity in eastern Indonesia shed light on the 2018 Lombok and Palu earthquake sequences","docAbstract":"<p>High seismicity rates in eastern Indonesia occur due to the complex interaction of several tectonic plates which resulted in two deadly, destructive earthquake sequences that occurred in Lombok Island and the city of Palu, Sulawesi in 2018. The first sequence began in July with an<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>6.4 event near Lombok, culminating in an<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>7.0 event 8 d later. This was then followed by a nearby<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>6.9 event 12 d later. Approximately 1000&nbsp;km to the northeast, a separate sequence began several weeks later near Palu where an<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>7.5 event occurred that triggered a tsunami. In this study, we present hypocentre relocations for both earthquake sequences as well as all other regional earthquakes in eastern Indonesia. The relocations were performed using a teleseismic double-difference relocation method and arrival times for<span>&nbsp;</span><i>P</i><span>&nbsp;</span>and<span>&nbsp;</span><i>S</i><span>&nbsp;</span>waves from stations at local, regional, and teleseismic distances. The catalogue and phase data were taken from the Agency for Meteorology, Climatology and Geophysics (BMKG) of Indonesia and the International Seismological Centre (ISC) for the period of April 2009 through November 2018. The relocated catalogue provides an improved view of seismicity in eastern Indonesia over the study period, sharpening locations and interpretations of seismogenic features throughout the region. In the Lombok area, the relocated earthquakes clearly show a backarc thrust to the north of the Sunda-Banda Arc transition zone. The relocated aftershocks show that the destructive<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>7.0 and<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>6.9 earthquakes of the Lombok sequence ruptured two different regions: The<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>7.0 earthquake propagated westward, whereas the<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>6.9 earthquake propagated eastward. The entire sequence of Lombok earthquakes was most likely started by the<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>6.4 event as the initial event or foreshock, which then triggered backarc thrusts on both sides. Several weeks later and far to the northeast, the<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>7.5 Palu earthquake occurred along the Palu-Koro Fault, filling a seismic gap that had not ruptured in an<span>&nbsp;</span><i>M</i><sub>w</sub><span>&nbsp;</span>6.0 event or larger since at least 1900. The distribution of aftershocks indicates that the northern part of the Palu-Koro Fault has lower relative seismicity rates than the southern part at shallow depths, and that off fault aftershocks are mostly located to the east of the Palu-Koro Fault.</p>","language":"English","publisher":"Royal Astronomical Society","doi":"10.1093/gji/ggaa118","usgsCitation":"Supendi, P., Nugraha, A.D., Widiyantoro, S., Pesicek, J.D., Thurber, C., Abdullah, C., Daryono, D., Wiyono, S., Shiddiqi, H., and Rosalia, S., 2020, Relocated aftershocks and background seismicity in eastern Indonesia shed light on the 2018 Lombok and Palu earthquake sequences: Geophysical Journal International, v. 221, no. 3, p. 1845-1855, https://doi.org/10.1093/gji/ggaa118.","productDescription":"11 p.","startPage":"1845","endPage":"1855","ipdsId":"IP-114885","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":457340,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggaa118","text":"Publisher Index Page"},{"id":380066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Lombok, Palu","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              119.14672851562499,\n              -1.4720060101903352\n            ],\n            [\n              120.574951171875,\n              -1.4720060101903352\n            ],\n            [\n              120.574951171875,\n              -0.15380840901698828\n            ],\n            [\n              119.14672851562499,\n              -0.15380840901698828\n            ],\n            [\n              119.14672851562499,\n              -1.4720060101903352\n            ]\n          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0000-0001-7964-5845","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":202042,"corporation":false,"usgs":true,"family":"Pesicek","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":803753,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thurber, C.H.","contributorId":244318,"corporation":false,"usgs":false,"family":"Thurber","given":"C.H.","affiliations":[{"id":13451,"text":"Univ. of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":803754,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abdullah, C.I.","contributorId":244319,"corporation":false,"usgs":false,"family":"Abdullah","given":"C.I.","email":"","affiliations":[{"id":48884,"text":"Bandung Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":803755,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daryono, 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