{"pageNumber":"148","pageRowStart":"3675","pageSize":"25","recordCount":41054,"records":[{"id":70241176,"text":"70241176 - 2023 - Changes in suspended-sediment yields under divergent land-cover disturbance histories: A comparison of two large watersheds, Olympic Mountains, USA","interactions":[],"lastModifiedDate":"2023-06-27T16:41:52.717587","indexId":"70241176","displayToPublicDate":"2023-01-30T07:02:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Changes in suspended-sediment yields under divergent land-cover disturbance histories: A comparison of two large watersheds, Olympic Mountains, USA","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Improvements in timber harvest practices and reductions in harvest volumes over the past half&nbsp;century are commonly presumed to have reduced sediment loads in many western US rivers. However, direct assessments in larger watersheds are relatively sparse. Here, we compare 2019–21 sediment concentrations against those of the late 1970s in the Bogachiel and Calawah &nbsp;River watersheds, adjacent and similarly sized (~300 km<sup>2</sup>) basins in the western Olympic Mountains of Washington State. The Calawah River&nbsp;watershed has experienced significant land-cover disturbance, including a large 1951 fire, extensive post-fire salvage logging, and relatively high rates of timber harvest through the 1990s. In contrast, the Bogachiel&nbsp;River watershed did not burn, and experienced only modest timber harvest that largely post-dated 1970s sediment monitoring. Channel-width trends suggest the Calawah River was still recovering from 1950s disturbances in the late 1970s. We found that 2019–21 suspended-sediment loads in the Calawah River were 2.3–2.6 times lower than would have been expected based on 1970s sediment rating curves, while recent loads in the Bogachiel River were a factor of 1.4 ± 1.0 lower. We consider the plausibility and possible explanations of declining concentrations in the less-disturbed Bogachiel River. Suspended-sediment yields in the Bogachiel River were two times higher than yields in the Calawah River, which is attributed to a combination of modestly higher precipitation, more efficient runoff generation, and more extensive and erodible Quaternary valley fills in the Bogachiel River. Regional shifts in flood hydrology have also influenced suspended-sediment loads in both watersheds. Our results then document a significant decline in suspended-sediment concentrations in the Calawah River over the past half&nbsp;century. Reduced land-cover disturbance provides the simplest and most likely explanation for this decline, though the wide range of possible concentration changes in the Bogachiel River leaves open possibilities that other processes (human, natural, or methodologic) could be a factor.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5556","usgsCitation":"Jaeger, K.L., Anderson, S.W., and Dunn, S., 2023, Changes in suspended-sediment yields under divergent land-cover disturbance histories: A comparison of two large watersheds, Olympic Mountains, USA: Earth Surface Processes and Landforms, v. 48, no. 7, p. 1398-1413, https://doi.org/10.1002/esp.5556.","productDescription":"16 p.","startPage":"1398","endPage":"1413","ipdsId":"IP-144931","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":444679,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5556","text":"Publisher Index Page"},{"id":435479,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95L5ADD","text":"USGS data release","linkHelpText":"Supporting Spatial Data for Sediment Studies in the Bogachiel and Calawah River Watersheds, Washington"},{"id":414086,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.35640085378517,\n              48.1377522152041\n            ],\n            [\n              -124.35640085378517,\n              47.1761943193718\n            ],\n            [\n              -122.80798616934896,\n              47.1761943193718\n            ],\n            [\n              -122.80798616934896,\n              48.1377522152041\n            ],\n            [\n              -124.35640085378517,\n              48.1377522152041\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-02-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Jaeger, Kristin L. 0000-0002-1209-8506","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":206935,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866348,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Sarah B. 0000-0003-4463-0074","orcid":"https://orcid.org/0000-0003-4463-0074","contributorId":291768,"corporation":false,"usgs":false,"family":"Dunn","given":"Sarah B.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":866350,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242920,"text":"70242920 - 2023 - Peat decomposition and erosion contribute to pond deepening in a temperate salt marsh","interactions":[],"lastModifiedDate":"2023-04-24T11:45:32.606708","indexId":"70242920","displayToPublicDate":"2023-01-30T06:41:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Peat decomposition and erosion contribute to pond deepening in a temperate salt marsh","docAbstract":"<div class=\"article-section__content en main\"><p>Salt marsh ponds expand and deepen over time, potentially reducing ecosystem carbon storage and resilience. The water&nbsp;filled volumes of ponds represent missing carbon due to prevented soil accumulation and removal by erosion and decomposition. Removal mechanisms have different implications as eroded carbon can be redistributed while decomposition results in loss. We constrained ponding effects on carbon dynamics in a New England marsh and determined whether expansion and deepening impact nearby soils by conducting geochemical characterizations of cores from three ponds and surrounding high marshes and models of wind-driven erosion. Radioisotope profiles demonstrate that ponds are not depositional environments and that contemporaneous marsh accretion represents prevented accumulation accounting for 32%–42% of the missing carbon. Erosion accounted for 0%–38% and was bracketed using radioisotope inventories and wind-driven resuspension models. Decomposition, calculated by difference, removes 22%–68%, and when normalized over pond lifespans, produces rates that agree with previous metabolism measurements. Pond surface soils contain new contributions from submerged primary producers and evidence of microbial alteration of underlying peat, as higher levels of detrital biomarkers and thermal stability indices, compared to the marsh. Below pond surface horizons, soil properties and organic matter composition were similar to the marsh, indicating that ponding effects are shallow. Soil bulk density, elemental content, and accretion rates were similar between marsh sites but different from ponds, suggesting that lateral effects are spatially confined. Consequently, ponds negatively impact ecosystem carbon storage but at current densities are not causing pervasive degradation of marshes in this system.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JG007063","usgsCitation":"Luk, S., Eagle, M.J., Mariotti, G., Gosselin, K., Sanderman, J., and Spivak, A.C., 2023, Peat decomposition and erosion contribute to pond deepening in a temperate salt marsh: Biogeosciences, v. 128, no. 2, e2022JG007063, 19 p., https://doi.org/10.1029/2022JG007063.","productDescription":"e2022JG007063, 19 p.","ipdsId":"IP-144333","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444682,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jg007063","text":"Publisher Index Page"},{"id":416169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -70.89116181462337,\n              42.8226718850903\n            ],\n            [\n              -70.89116181462337,\n              42.6915958038642\n            ],\n            [\n              -70.70631330997368,\n              42.6915958038642\n            ],\n            [\n              -70.70631330997368,\n              42.8226718850903\n            ],\n            [\n              -70.89116181462337,\n              42.8226718850903\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Luk, Sheron","contributorId":247610,"corporation":false,"usgs":false,"family":"Luk","given":"Sheron","email":"","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":870201,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870202,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mariotti, Giulio","contributorId":207541,"corporation":false,"usgs":false,"family":"Mariotti","given":"Giulio","email":"","affiliations":[{"id":37557,"text":"Louisiana State University, Baton Rouge LA","active":true,"usgs":false}],"preferred":false,"id":870203,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gosselin, Kelsey","contributorId":247614,"corporation":false,"usgs":false,"family":"Gosselin","given":"Kelsey","email":"","affiliations":[{"id":49592,"text":"Marine Chemistry and Geochemistry Department, Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":870204,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sanderman, Jonathan","contributorId":187477,"corporation":false,"usgs":false,"family":"Sanderman","given":"Jonathan","email":"","affiliations":[],"preferred":false,"id":870205,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spivak, Amanda C.","contributorId":191376,"corporation":false,"usgs":false,"family":"Spivak","given":"Amanda","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":870206,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240150,"text":"70240150 - 2023 - iBluff: An open-source R package for geomorphic analysis of coastal bluffs/cliffs","interactions":[],"lastModifiedDate":"2023-01-31T12:35:05.584499","indexId":"70240150","displayToPublicDate":"2023-01-30T06:32:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5923,"text":"SoftwareX","active":true,"publicationSubtype":{"id":10}},"title":"iBluff: An open-source R package for geomorphic analysis of coastal bluffs/cliffs","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"d1e104\" class=\"abstract author\"><div id=\"d1e107\"><p id=\"d1e108\">The R package<span>&nbsp;</span><strong><i>iBluff</i></strong><span>&nbsp;</span>is designed for coastal bluffs/bluffs morphological analysis and offers an automatic and reproducible alternative to identify bluff edges using a bare earth digital elevation model (DEM) instead of hand digitizing. This package extracts elevation profiles along automatically identified transects on the bluff-face, bluff top, toe, secondary inflections, relative concavity/convexity of bluff-face, and beach dunes (crests and troughs). The package requires at a minimum a bare earth DEM as a raster and a generalized line shapefile (shoreline) approximately parallel with the bluff-face. Both files should be in the same projected coordinate system. The<span>&nbsp;</span><strong><i>iBluff</i></strong><span>&nbsp;</span>package was developed to expand and generalize studies of high-relief coastal areas, investigate erosion and seasonality, and could be extended to use three-dimensional (3D) point-cloud data instead of a DEM.</p></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.softx.2023.101325","usgsCitation":"Palaseanu-Lovejoy, M., 2023, iBluff: An open-source R package for geomorphic analysis of coastal bluffs/cliffs: SoftwareX, v. 21, 101325, 8 p., https://doi.org/10.1016/j.softx.2023.101325.","productDescription":"101325, 8 p.","ipdsId":"IP-147257","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":444684,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.softx.2023.101325","text":"Publisher Index Page"},{"id":412490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":862773,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70264031,"text":"70264031 - 2023 - Assimilating ecological theory with empiricism: Using constrained generalized additive models to enhance survival analyses","interactions":[],"lastModifiedDate":"2025-03-05T15:18:51.590688","indexId":"70264031","displayToPublicDate":"2023-01-30T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Assimilating ecological theory with empiricism: Using constrained generalized additive models to enhance survival analyses","docAbstract":"<p>1. Integrating ecological theory with empirical methods is ubiquitous in ecology using hierarchical Bayesian models. However, there has been little development focused on integration of ecological theory into models for survival analysis. Survival is a fundamental process, linking individual fitness with population dynamics, but incorporating life history strategies to inform survival estimation can be challenging because mortality processes occur at multiple scales.</p><p>2. We develop an approach to survival analysis, incorporating model constraints based on a species' life history strategy using functional analytical tools. Specifically, we structurally separate intrinsic patterns of mortality that arise from age-specific processes (e.g. increasing survival during early life stages due to growth or maturation, versus senescence) from extrinsic mortality patterns that arise over different periods of time (e.g. seasonal temporal shifts). We use shape constrained generalized additive models (CGAMs) to obtain age-specific hazard functions that incorporate theoretical information based on classical survivorship curves into the age component of the model and capture extrinsic factors in the time component.</p><p>3. We compare the performance of our modelling approach to standard survival modelling tools that do not explicitly incorporate species life history strategy in the model structure, using metrics of predictive power, accuracy, efficiency and computation time. We applied these models to two case studies that reflect different functional shapes for the underlying survivorship curves, examining age-period survival for white-tailed deer <i>Odocoileus virginianus</i> in Wisconsin, USA and Columbian sharp-tailed grouse T<i>ympanuchus phasianellus columbianus</i> in Colorado, USA.</p>","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210x.14057","usgsCitation":"Ketz, A., Storm, D., Barker, R., Apa, A.D., Oliva-Aviles, C., and Walsh, D.P., 2023, Assimilating ecological theory with empiricism: Using constrained generalized additive models to enhance survival analyses: Methods in Ecology and Evolution, v. 14, no. 3, p. 952-967, https://doi.org/10.1111/2041-210x.14057.","productDescription":"16 p.","startPage":"952","endPage":"967","ipdsId":"IP-141205","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487398,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Wisconsin","active":true,"usgs":false}],"preferred":false,"id":929534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Apa, Anthony D.","contributorId":272966,"corporation":false,"usgs":false,"family":"Apa","given":"Anthony","email":"","middleInitial":"D.","affiliations":[{"id":40103,"text":"cdpw","active":true,"usgs":false}],"preferred":false,"id":929535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oliva-Aviles, Cristian","contributorId":301099,"corporation":false,"usgs":false,"family":"Oliva-Aviles","given":"Cristian","affiliations":[{"id":65304,"text":"Genentech","active":true,"usgs":false}],"preferred":false,"id":929536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":929537,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70247102,"text":"70247102 - 2023 - Estimating parasite infrapopulation size given imperfect detection: Proof-of-concept with ectoparasitic fleas on prairie dogs","interactions":[],"lastModifiedDate":"2023-07-25T15:05:03.23572","indexId":"70247102","displayToPublicDate":"2023-01-27T09:54:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2025,"text":"International Journal for Parasitology: Parasites and Wildlife","active":true,"publicationSubtype":{"id":10}},"title":"Estimating parasite infrapopulation size given imperfect detection: Proof-of-concept with ectoparasitic fleas on prairie dogs","docAbstract":"<p><span>Parasite infrapopulation size - the population of parasites affecting a single host - is a central metric in parasitology. However, parasites are small and elusive such that imperfect detection is expected. Repeated sampling of parasites during primary sampling occasions (e.g., each host capture) informs the detection process. Here, we estimate flea (Siphonaptera) infrapopulation size on black-tailed&nbsp;prairie dogs&nbsp;(</span><i>Cynomys ludovicianus</i><span>, BTPDs) as a proof-of-concept for estimating parasite infrapopulations given imperfect detection. From Jun–Aug 2011, we live-trapped 299 BTPDs for a total of 573 captures on 20 plots distributed among 13 colonies at the Vermejo Park Ranch, New Mexico, USA. During each capture, an anesthetized BTPD was combed 3 times consecutively, 15&nbsp;s each, to remove and count fleas. Each flea (</span><i>n</i><span>&nbsp;=&nbsp;4846) was linked to the BTPD from which it was collected and assigned an encounter history (’100’, ‘010’, ‘001’). We analyzed the encounter histories using Huggins closed captures models, setting recapture probabilities to 0, thereby accounting for flea removal from hosts. The probability of detecting an individual flea (</span><i>p</i><span>) increased with Julian date; field personnel may have become more efficient at combing fleas as the field season progressed. Combined&nbsp;</span><i>p</i><span>&nbsp;across 3 combings equaled 0.99. Estimates of flea infrapopulation size were reasonable and followed the negative&nbsp;binomial distribution. Our general approach may be broadly applicable to estimating infrapopulation sizes for parasites. The utility of this approach increases as&nbsp;</span><i>p</i><span>&nbsp;declines but, if&nbsp;</span><i>p</i><span>&nbsp;is very low, inference is likely limited.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijppaw.2023.01.002","usgsCitation":"Eads, D.A., Huyvaert, K.P., and Biggins, D.E., 2023, Estimating parasite infrapopulation size given imperfect detection: Proof-of-concept with ectoparasitic fleas on prairie dogs: International Journal for Parasitology: Parasites and Wildlife, v. 20, p. 117-121, https://doi.org/10.1016/j.ijppaw.2023.01.002.","productDescription":"5 p.","startPage":"117","endPage":"121","ipdsId":"IP-146545","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":444692,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijppaw.2023.01.002","text":"Publisher Index Page"},{"id":419306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Vermejo Park Ranch","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.8,\n              36.6\n            ],\n            [\n              -104.8,\n              36.5\n            ],\n            [\n              -104.7,\n              36.5\n            ],\n            [\n              -104.7,\n              36.6\n            ],\n            [\n              -104.8,\n              36.6\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"20","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":878902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huyvaert, Kathryn P.","contributorId":202514,"corporation":false,"usgs":false,"family":"Huyvaert","given":"Kathryn","email":"","middleInitial":"P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":878903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biggins, Dean E. 0000-0003-2078-671X bigginsd@usgs.gov","orcid":"https://orcid.org/0000-0003-2078-671X","contributorId":2522,"corporation":false,"usgs":true,"family":"Biggins","given":"Dean","email":"bigginsd@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":878904,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70256545,"text":"70256545 - 2023 - Viability of side-scan sonar to enumerate Paddlefish, a large pelagic freshwater fish, in rivers and reservoirs","interactions":[],"lastModifiedDate":"2024-08-22T14:59:53.775057","indexId":"70256545","displayToPublicDate":"2023-01-27T09:42:10","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Viability of side-scan sonar to enumerate Paddlefish, a large pelagic freshwater fish, in rivers and reservoirs","docAbstract":"<p><span>Recreational-grade side-scan sonar (SSS) has become an invaluable tool for&nbsp;inland fisheries, particularly when characterizing underwater habitat, but it is being increasingly used for enumerating large-bodied (&gt; 1&nbsp;m total length [TL]) aquatic fauna. We used SSS in river and reservoir environments to evaluate methods for identifying and counting&nbsp;Paddlefish&nbsp;</span><span><i>Polyodon spathula</i></span><span>, a large pelagic&nbsp;planktivore&nbsp;of recreational and economic importance that can exceed 2&nbsp;m in length and weigh over 70&nbsp;kg. We assessed accuracy and precision among readers to identify Paddlefish by assigning confidence scores (1–3; with 3 being more confident) to sonar images of a ballistics-gel filled fiberglass replica Paddlefish. Readers varied in their confidence scores for the replica Paddlefish and no reader could identify the target beyond 25&nbsp;m from the transducer. Afterwards, we used SSS to survey several kilometers of a reservoir during summer residency and a large river during springtime spawning migrations. Two readers counted Paddlefish images in the SSS recordings and we estimated&nbsp;population size&nbsp;in the surveyed area with distance sampling. In the reservoir, the number of Paddlefish counted ranged from 172 to 184. In the river, the number of Paddlefish counted ranged from 165 to 617. The exponential model of distance was most-supported for detection in both environments, except there was support for a half-norm distribution for one reader in the river. In the reservoir, abundance estimates were statistically similar between readers at approximately 1500 (7/ha) in the total scanned area. In the river, similar abundance estimates were obtained with the half-norm model from one reader compared to the exponential model of the other reader, resulting in approximately 1500 individuals (30/ha) in the surveyed area. The application of SSS to count Paddlefish has some clear advantages to traditional methods, such as gill netting, and can be done at multiple times of the year. Distance sampling methods compensated for differences in counts among readers, indicating distance sampling can produce similar abundance estimates even when variation in counts exists among readers.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2023.106639","usgsCitation":"Wolfenkoehler, W., Long, J.M., Gary, R., Snow, R., Schooley, J.D., Bruckerhoff, L.A., and Lonsinger, R.C., 2023, Viability of side-scan sonar to enumerate Paddlefish, a large pelagic freshwater fish, in rivers and reservoirs: Fisheries Research, v. 261, 106639, 9 p., https://doi.org/10.1016/j.fishres.2023.106639.","productDescription":"106639, 9 p.","ipdsId":"IP-142414","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Keystone Lake, Lake Carl Blackwell, Verdigris River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -97.32079029272471,\n              36.18635094806682\n            ],\n            [\n              -97.32079029272471,\n              36.089827328506544\n            ],\n            [\n              -97.1696333849386,\n              36.089827328506544\n            ],\n            [\n              -97.1696333849386,\n              36.18635094806682\n            ],\n            [\n              -97.32079029272471,\n              36.18635094806682\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -96.2644501788143,\n              36.125328208556084\n         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\"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -95.52086370103724,\n              36.84221290357827\n            ],\n            [\n              -95.63789552781877,\n              36.84221290357827\n            ],\n            [\n              -95.63789552781877,\n              36.6881372389295\n            ],\n            [\n              -95.52086370103724,\n              36.6881372389295\n            ],\n            [\n              -95.52086370103724,\n              36.84221290357827\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"261","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wolfenkoehler, Wyatt","contributorId":341077,"corporation":false,"usgs":false,"family":"Wolfenkoehler","given":"Wyatt","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gary, Ryan","contributorId":341078,"corporation":false,"usgs":false,"family":"Gary","given":"Ryan","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snow, Richard A.","contributorId":341079,"corporation":false,"usgs":false,"family":"Snow","given":"Richard A.","affiliations":[{"id":81697,"text":"Oklahoma Fishery Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":907911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schooley, Jason D.","contributorId":341080,"corporation":false,"usgs":false,"family":"Schooley","given":"Jason","email":"","middleInitial":"D.","affiliations":[{"id":81698,"text":"Paddlefish Research Center","active":true,"usgs":false}],"preferred":false,"id":907912,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bruckerhoff, Lindsey Ann 0000-0002-9523-4808","orcid":"https://orcid.org/0000-0002-9523-4808","contributorId":292594,"corporation":false,"usgs":true,"family":"Bruckerhoff","given":"Lindsey","email":"","middleInitial":"Ann","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907913,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lonsinger, Robert Charles 0000-0002-1040-7299","orcid":"https://orcid.org/0000-0002-1040-7299","contributorId":340524,"corporation":false,"usgs":true,"family":"Lonsinger","given":"Robert","email":"","middleInitial":"Charles","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907914,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70247865,"text":"70247865 - 2023 - Decompression and degassing, repressurization, and regassing during cyclic eruptions at Guagua Pichincha volcano, Ecuador, 1999–2001","interactions":[],"lastModifiedDate":"2023-08-22T13:39:04.295519","indexId":"70247865","displayToPublicDate":"2023-01-27T08:32:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Decompression and degassing, repressurization, and regassing during cyclic eruptions at Guagua Pichincha volcano, Ecuador, 1999–2001","docAbstract":"<p><span>In 1999–2001, Guagua Pichincha volcano, Ecuador, produced a series of cyclic explosive and effusive eruptions. Rock samples, including dense blocks and pumiceous clasts collected during the eruption sequence, and ballistic bombs later collected from the crater floor, provide information about magma storage, ascent, decompression, degassing, repressurization, and regassing prior to eruption. Pairs of Fe-Ti oxides indicate equilibrium within 1.2–1.5 log units above the NNO oxidation buffer and equilibrium temperatures from 805 to 905 °C. Melt inclusions record H</span><sub>2</sub><span>O contents of 2.7–4.6 wt% and CO</span><sub>2</sub><span>&nbsp;contents (uncorrected for CO</span><sub>2</sub><span>&nbsp;segregation into bubbles) from 19 to 310 ppm. Minimum melt inclusion saturation pressures fall between 69 and 168 MPa, or equilibration depths of 2.8 and 6.8 km, the lower end of which is coincident with the maximum inferred equilibration depths for the most vesicular breadcrust bombs sampled. Amphibole phenocrysts lack breakdown rims (except for one sample) and plagioclase phenocrysts have abundant oscillatory compositional zones. Plagioclase areal microlite number densities (</span><i>N</i><sub><i>a</i></sub><span>) range over less than one order of magnitude (8.9×10</span><sup>3</sup><span>–8.7×10</span><sup>4</sup><span>&nbsp;mm</span><sup>-2</sup><span>) among all samples, with the exception of a dense, low crystallinity sample (</span><i>N</i><sub><i>a</i></sub><span>&nbsp;= 3.0×10</span><sup>3</sup><span>&nbsp;mm</span><sup>−2</sup><span>) and a pumiceous sample erupted on 17 December 1999 (</span><i>N</i><sub><i>a</i></sub><span>&nbsp;= 1.7×10</span><sup>3</sup><span>&nbsp;mm</span><sup>−2</sup><span>). Plagioclase microlite shapes include tabular, hopper, and swallowtail forms. Taken together, the relatively high plagioclase microlite number densities, the high number of oscillatory zones in plagioclase phenocrysts, the presence of CO</span><sub>2</sub><span>&nbsp;in groundmass glass, seismicity, and time-varying tilt cycles provide a picture of sudden evacuation of magma residing at different levels in the shallow conduit. Explosive eruptions punctuate inter-eruptive repose periods marked by time-varying rates of degassing (volatile fluxing) and re-pressurization. Shallow residence time in the conduit was sufficient to allow precipitation of silica-phase in the groundmass, but insufficient to allow breakdown of hornblende phenocrysts, with the one exception of the final dome sample from 2000, which has the longest preceding repose time. These results support a model of cyclic pressure cycling, volatile exsolution and regassing, and magma decompression decoupled from ascent.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-023-01626-3","usgsCitation":"Wright, H.M., Cioni, R., Cashman, K.V., Mothes, P., and Rosi, M., 2023, Decompression and degassing, repressurization, and regassing during cyclic eruptions at Guagua Pichincha volcano, Ecuador, 1999–2001: Bulletin of Volcanology, v. 85, 12, 24 p., https://doi.org/10.1007/s00445-023-01626-3.","productDescription":"12, 24 p.","ipdsId":"IP-143035","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444695,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-023-01626-3","text":"Publisher Index Page"},{"id":420012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","otherGeospatial":"Guagua Pichincha Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -78.64295621873246,\n              -0.14110488224878281\n            ],\n            [\n              -78.64295621873246,\n              -0.201181738857926\n            ],\n            [\n              -78.58224335456136,\n              -0.201181738857926\n            ],\n            [\n              -78.58224335456136,\n              -0.14110488224878281\n            ],\n            [\n              -78.64295621873246,\n              -0.14110488224878281\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"85","noUsgsAuthors":false,"publicationDate":"2023-01-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":880787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cioni, Raffaello 0000-0002-2526-9095","orcid":"https://orcid.org/0000-0002-2526-9095","contributorId":328622,"corporation":false,"usgs":false,"family":"Cioni","given":"Raffaello","email":"","affiliations":[{"id":78424,"text":"Universita degli Studi di Firenzi","active":true,"usgs":false}],"preferred":false,"id":880788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cashman, Katharine V.","contributorId":199542,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine","email":"","middleInitial":"V.","affiliations":[{"id":13025,"text":"Department of Geological Sciences, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":880789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mothes, Patricia","contributorId":178532,"corporation":false,"usgs":false,"family":"Mothes","given":"Patricia","affiliations":[],"preferred":false,"id":880790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosi, Mauro","contributorId":206499,"corporation":false,"usgs":false,"family":"Rosi","given":"Mauro","email":"","affiliations":[],"preferred":false,"id":880791,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240144,"text":"70240144 - 2023 - New maps of conductive heat flow in the Great Basin, USA: Separating conductive and convective influences","interactions":[],"lastModifiedDate":"2023-01-30T12:51:57.454932","indexId":"70240144","displayToPublicDate":"2023-01-27T06:50:11","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"New maps of conductive heat flow in the Great Basin, USA: Separating conductive and convective influences","docAbstract":"Geothermal well data from Southern Methodist University and the U.S. Geological Survey (USGS) were used to create maps of estimated background conductive heat flow across the Great Basin region of the western United States. These heat flow maps were generated as part of the USGS hydrothermal and Enhanced Geothermal Systems resource assessment process, and the creation process seeks to remove the influence of hydrothermal convection from the predictions of the background conductive heat flow. The heat flow maps were constructed using a custom-developed iterative process using weighted regression, in which convectively influenced outliers were de-emphasized by assigning lower weights to measurements with heat flow values further from the estimated local trend (e.g., local convective influence). The local linear weighted regression algorithm is two-dimensional locally estimated scatterplot smoothing where smoothness was controlled by varying the number of nearby wells used for each local interpolation.\nThree maps resulting from conductive heat flow models are detailed in this paper, highlighting the influence of measurement confidence. The three maps use either: measurements from all wells with equal weight (no confidence weights), or one of two different published categorization methods to de-emphasize low-quality measurements; one categorization method graded thermal gradient quality, the other categorization method graded thermal conductivity quality. Each map is an estimate of background conductive heat flow as a function of reported data quality, and a point coverage is also provided for all wells in the compiled dataset. The point coverage includes an important new attribute for geothermal wells: the residual, which can be interpreted as the departure of a well from the estimated background heat flow conditions, and the value of the residual may be useful in identifying the influence of fluids (hydrothermal or groundwater) on conductive heat flow. Of the three maps presented, the map that de-emphasized the impact of wells with low-quality thermal gradient measurements appears to perform best because it did not incorporate many of the wells in the Snake River Plain that do not penetrate the aquifer and are therefore very unlikely to reflect true conductive conditions.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, 48th Workshop on Geothermal Reservoir Engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"48th Workshop on Geothermal Reservoir Engineering","conferenceDate":"February 6-8, 2023","conferenceLocation":"Stanford, California","language":"English","publisher":"Stanford Geothermal Workshop","usgsCitation":"DeAngelo, J., Burns, E., Gentry, E., Batir, J.F., Lindsey, C.R., and Mordensky, S.P., 2023, New maps of conductive heat flow in the Great Basin, USA: Separating conductive and convective influences, <i>in</i> Proceedings, 48th Workshop on Geothermal Reservoir Engineering, Stanford, California, February 6-8, 2023, 13 p.","productDescription":"13 p.","ipdsId":"IP-149016","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":412439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412435,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2023/Deangelo.pdf?t=1674862190"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.94931681460088,\n              43.31269307515126\n            ],\n            [\n              -121.94931681460088,\n              34.37043992080774\n            ],\n            [\n              -110.40572044760874,\n              34.37043992080774\n            ],\n            [\n              -110.40572044760874,\n              43.31269307515126\n            ],\n            [\n              -121.94931681460088,\n              43.31269307515126\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":862754,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":862755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gentry, Emilie","contributorId":293494,"corporation":false,"usgs":false,"family":"Gentry","given":"Emilie","email":"","affiliations":[{"id":63314,"text":"Petrolern","active":true,"usgs":false}],"preferred":false,"id":862756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batir, Joseph F.","contributorId":293495,"corporation":false,"usgs":false,"family":"Batir","given":"Joseph","email":"","middleInitial":"F.","affiliations":[{"id":63314,"text":"Petrolern","active":true,"usgs":false}],"preferred":false,"id":862757,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Cary Ruth 0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":292016,"corporation":false,"usgs":true,"family":"Lindsey","given":"Cary","email":"","middleInitial":"Ruth","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":862758,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":862759,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240125,"text":"70240125 - 2023 - Revising supraglacial rock avalanche magnitudes and frequencies in Glacier Bay National Park, Alaska","interactions":[],"lastModifiedDate":"2023-01-30T12:36:58.473885","indexId":"70240125","displayToPublicDate":"2023-01-27T06:33:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Revising supraglacial rock avalanche magnitudes and frequencies in Glacier Bay National Park, Alaska","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><p id=\"sp0060\">The frequency of large supraglacial landslides (rock avalanches) occurring in glacial environments is thought to be increasing due to feedbacks with climate warming and permafrost degradation. However, it is difficult to (i) test this; (ii) establish cause–effect relationships; and (iii) determine associated lag-times, due to both temporal and spatial biases in detection rates. Here we applied the Google Earth Engine supraglacial debris input detector (GERALDINE) to Glacier Bay National Park &amp; Preserve (GLBA), Alaska. We find that the number of rock avalanches (RAs) has previously been underestimated by 53&nbsp;%, with a bias in past detections towards large area RAs. In total, GLBA experienced 69 RAs during 1984–2020, with the highest frequency in the last three years. Of these, 58&nbsp;% were deposited into the accumulation zone and then sequestered into the ice within two years. RA sources clustered spatially at high elevations and around certain peaks and ridges, predominantly at the boundary of modelled permafrost likelihood. They also clustered temporally, occurring mainly between May and September when air temperatures were high enough to initiate rock-permafrost degradation mechanisms. There was a chronic background debris supply from RAs, with at least one RA occurring in all but nine years; however, a debris rich period during 2012–2016 was driven by three large RAs delivering 44&nbsp;% of all (1984–2020) debris (by area). Comparable investigation of slope-failures in other remote currently glaciated regions is lacking. If RA rates are similar elsewhere, especially the bias towards emplacement onto/into accumulation zones, their contribution to glacial sediment budgets has been globally underestimated.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2023.108591","usgsCitation":"Smith, W., Dunning, S.A., Ross, N., Telling, J., Bessette-Kirton, E., Shugar, D., Coe, J.A., and Geertsema, M., 2023, Revising supraglacial rock avalanche magnitudes and frequencies in Glacier Bay National Park, Alaska: Geomorphology, v. 425, 108591, 15 p., https://doi.org/10.1016/j.geomorph.2023.108591.","productDescription":"108591, 15 p.","ipdsId":"IP-135862","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":444700,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1016/j.geomorph.2023.108591","text":"Publisher Index Page"},{"id":412436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -138.03863703041065,\n              59.29498993664896\n            ],\n            [\n              -138.03863703041065,\n              58.044630678420305\n            ],\n            [\n              -134.97475265482453,\n              58.044630678420305\n            ],\n            [\n              -134.97475265482453,\n              59.29498993664896\n            ],\n            [\n              -138.03863703041065,\n              59.29498993664896\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"425","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, William 0000-0002-7134-7592","orcid":"https://orcid.org/0000-0002-7134-7592","contributorId":301834,"corporation":false,"usgs":false,"family":"Smith","given":"William","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":862693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunning, Stuart A. 0000-0002-2310-7367","orcid":"https://orcid.org/0000-0002-2310-7367","contributorId":301835,"corporation":false,"usgs":false,"family":"Dunning","given":"Stuart","email":"","middleInitial":"A.","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":862694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ross, Neil 0000-0002-8338-4905","orcid":"https://orcid.org/0000-0002-8338-4905","contributorId":301836,"corporation":false,"usgs":false,"family":"Ross","given":"Neil","email":"","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":862695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Telling, Jon 0000-0002-8180-0979","orcid":"https://orcid.org/0000-0002-8180-0979","contributorId":301837,"corporation":false,"usgs":false,"family":"Telling","given":"Jon","email":"","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":862696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bessette-Kirton, Erin K. 0000-0002-2797-0694","orcid":"https://orcid.org/0000-0002-2797-0694","contributorId":225097,"corporation":false,"usgs":false,"family":"Bessette-Kirton","given":"Erin K.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":862697,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shugar, Dan H. 0000-0002-6279-8420","orcid":"https://orcid.org/0000-0002-6279-8420","contributorId":224588,"corporation":false,"usgs":false,"family":"Shugar","given":"Dan H.","affiliations":[{"id":40894,"text":"University of Calgary, Calgary, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":862698,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":862699,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Geertsema, M. 0000-0002-4650-8251","orcid":"https://orcid.org/0000-0002-4650-8251","contributorId":167412,"corporation":false,"usgs":false,"family":"Geertsema","given":"M.","affiliations":[],"preferred":false,"id":862700,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70239897,"text":"ofr20221111 - 2023 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2021","interactions":[],"lastModifiedDate":"2023-03-01T13:59:05.52129","indexId":"ofr20221111","displayToPublicDate":"2023-01-26T14:05:46","publicationYear":"2023","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":"2022-1111","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2021","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2021","docAbstract":"<p><span>The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, by 7 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries. </span></p><p><span>This is the sixth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. Prior reports in this series documented data collected from October 2015 to September 2020. This report contains information pertinent to data collection during the 2021 water year, from October 2020 to September 2021. There were no modifications this year to the previously installed monitoring network. Data at each station were compared for the length of the project and on a yearly basis to show the annual variability of discharge and salinity in the project area. </span></p><p><span>Discharge and salinity varied widely during the 2021 water year data collection period, which included above-average rainfall for four of the five counties in the study area. Total annual rainfall for all counties ranked third among the annual totals computed for the 6 years considered for this study. Annual mean discharge at Durbin Creek was highest among the tributaries, followed by Trout River, Clapboard Creek, Ortega River, Pottsburg Creek at U.S. 90, Julington Creek, Pottsburg Creek near South Jacksonville, Dunn Creek, Cedar River, and Broward River, whose annual mean discharge was lowest. Annual mean discharge at 7 of the 10 tributary monitoring sites was higher for the 2021 water year than for the 2020 water year, and the computed annual mean flow at Clapboard Creek was the highest over the 6 years considered for this study. The annual mean discharge for each of the main-stem sites was higher for the 2021 water year than for the 2020 water year and ranked second among the annual totals computed for the 6 years considered for this study. </span></p><p><span>Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which was expected. Relative to annual mean salinity calculated for the 2020 water year, annual mean salinity at all monitoring locations was lower for the 2021 water year except at the tributary site of Durbin Creek, which remained the same. The 2021 annual mean salinity at all sites ranked second lowest since the beginning of the study in 2016 except at Julington Creek and Racy Point, which tied for lowest, and Durbin Creek, which had the same value for each year.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221111","issn":"ISSN 2331-1258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2023, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2021: U.S. Geological Survey Open-File Report 2022–1111, 48 p., https://doi.org/10.3133/ofr20221111.","productDescription":"Report: x, 48 p.; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-139675","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":413532,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221111/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412288,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1111/ofr20221111.XML","linkFileType":{"id":8,"text":"xml"}},{"id":412285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1111/coverthb.jpg"},{"id":412286,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1111/ofr20221111.pdf","text":"Report","size":"16.3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":412287,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1111/images"},{"id":412289,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation—U.S. Geological Survey National Water Information System database"}],"country":"United States","state":"Florida","otherGeospatial":"St. Johns River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.31115628870195,\n              30.583300030597925\n            ],\n            [\n              -82.31115628870195,\n              29.490035998849976\n            ],\n            [\n              -81.03179238276725,\n              29.490035998849976\n            ],\n            [\n              -81.03179238276725,\n              30.583300030597925\n            ],\n            [\n              -82.31115628870195,\n              30.583300030597925\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/car-fl-water\" href=\"https://www.usgs.gov/centers/car-fl-water\">Caribbean-Florida Water Science Center</a> <br>U.S. Geological Survey&nbsp;<br><span class=\"HQEo7\" role=\"link\" data-markjs=\"true\" data-mce-tabindex=\"0\">4446 Pet Lane, Suite 108 <br>Lutz, FL 33559</span>&nbsp;</p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-01-25","noUsgsAuthors":false,"publicationDate":"2023-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ryan, Patrick J. 0000-0002-1490-4938 pryan@usgs.gov","orcid":"https://orcid.org/0000-0002-1490-4938","contributorId":203974,"corporation":false,"usgs":true,"family":"Ryan","given":"Patrick","email":"pryan@usgs.gov","middleInitial":"J.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true},{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":862297,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70239871,"text":"ofr20231001 - 2023 - Assessment of habitat use by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, 2020–21","interactions":[],"lastModifiedDate":"2023-01-27T11:53:34.04232","indexId":"ofr20231001","displayToPublicDate":"2023-01-26T12:01:59","publicationYear":"2023","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":"2023-1001","displayTitle":"Assessment of Habitat Use by Juvenile Chinook Salmon (<em>Oncorhynchus tshawytscha</em>) in the Willamette River Basin, Oregon, 2020–21","title":"Assessment of habitat use by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, 2020–21","docAbstract":"<p>We conducted a field study during 2020–21 to describe habitat use patterns of juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>) in the mainstem Willamette, McKenzie, and Santiam Rivers and to evaluate how habitat suitability criteria affected the predictive accuracy of a hydraulic habitat model. Two approaches were used to collect habitat use data: a stratified sampling design was used to ensure that a representative sample of available habitats was included in our sampling; and a targeted sampling design was used to collect additional data in habitat cells where juvenile Chinook salmon were observed. Habitat attributes and fish presence data were collected in habitat cells that were approximately 2 square meters during April, June, and July. A total of 632 cells were sampled during the study and included habitat located in the main channel (373 cells), side channels (228 cells), and in alcoves (31 cells). Juvenile Chinook salmon were observed in 42 percent of the cells located in the main channel, 38 percent of the cells located in side channels, and 7 percent of the cells located in alcoves. We used logistic regression to develop resource selection functions for April, June, and July, which produced probability-based predictions of habitat use for juvenile Chinook salmon based on water velocity and water depth. The resource selection functions revealed a habitat shift by juvenile Chinook salmon to locations with higher water velocities and greater water depths from April to July as juvenile Chinook salmon size increased. The resource selection functions that we developed are an important addition to habitat modeling in the Willamette River basin because they were developed from in-basin data, capture seasonal differences in habitat use, and facilitate probability-based estimates of habitat use for juvenile Chinook salmon. These advancements will improve habitat modeling efforts for juvenile Chinook salmon during spring and summer months within the Willamette River.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231001","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansen, G.S., Perry, R.W., Kock, T.J., White, J.S., Haner, P.V., Plumb, J.M., and Wallick, J.R., 2023, Assessment of habitat use by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, 2020–21: U.S. Geological Survey Open-File Report 2023–1001, 20 p., https://doi.org/10.3133/ofr20231001.","productDescription":"vii, 20 p.","onlineOnly":"Y","ipdsId":"IP-141847","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":412251,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1001/coverthb.jpg"},{"id":412252,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1001/ofr20231001.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1001"},{"id":412254,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1001/images"},{"id":412255,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1001/ofr20231001.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.70681047535611,\n              46.26773381073258\n            ],\n            [\n              -124.70681047535611,\n              42.583539358952294\n            ],\n            [\n              -121.08286121390995,\n              42.583539358952294\n            ],\n            [\n              -121.08286121390995,\n              46.26773381073258\n            ],\n            [\n              -124.70681047535611,\n              46.26773381073258\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/western-fisheries-research-center\" data-mce-href=\"https://www.usgs.gov/centers/western-fisheries-research-center\">Western Fisheries Research Center</a><br>U.S. Geological Survey<br>6505 NE 65th Street<br>Seattle, Washington 98115-5016</p>","tableOfContents":"<ul><li>Acknowledgements</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results</li><li>Discussion</li><li>References Cited</li></ul>","publishedDate":"2023-01-26","noUsgsAuthors":false,"publicationDate":"2023-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Hansen, Gabriel S. 0000-0001-6272-3632 ghansen@usgs.gov","orcid":"https://orcid.org/0000-0001-6272-3632","contributorId":3422,"corporation":false,"usgs":true,"family":"Hansen","given":"Gabriel","email":"ghansen@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":862212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":862213,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":862214,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, James S. 0000-0002-7255-3785 jameswhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7255-3785","contributorId":290253,"corporation":false,"usgs":false,"family":"White","given":"James","email":"jameswhite@usgs.gov","middleInitial":"S.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":862215,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haner, Philip V. 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Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":862218,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70239819,"text":"ofr20221112 - 2023 - Simulation of regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018","interactions":[],"lastModifiedDate":"2026-02-10T21:14:02.219453","indexId":"ofr20221112","displayToPublicDate":"2023-01-26T10:05:00","publicationYear":"2023","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":"2022-1112","displayTitle":"Simulation of Regional Groundwater Flow and Advective Transport of Per- and Polyfluoroalkyl Substances, Joint Base McGuire-Dix-Lakehurst and Vicinity, New Jersey, 2018","title":"Simulation of regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018","docAbstract":"<p>A three-dimensional numerical model of groundwater flow was developed and calibrated for the unconsolidated New Jersey Coastal Plain aquifers underlying Joint Base McGuire-Dix-Lakehurst (JBMDL) and vicinity, New Jersey, to evaluate groundwater flow pathways of per- and polyfluoroalkyl substances (PFAS) contamination associated with use of aqueous film forming foam (AFFF) at the base. The regional subsurface flow model spans an area of approximately 518 square miles around JBMDL and is based on a previously developed hydrogeologic framework of the area. Steady-state flow in the unconsolidated aquifers was simulated using the MODFLOW 6 groundwater flow model, which is able to account for hydrostratigraphic pinchouts and discontinuities in the Coastal Plain aquifers underlying JBMDL. To account for local patterns of fluid flow driving advective subsurface migration of PFAS, the grid was refined using quadtree meshes spanning 21 areas where historical AFFF use was identified, five off-site reconnaissance areas identified by AFCEC as areas in which the occurrence of PFAS is most likely to pose a potential danger to local drinking water supplies, and along streams that behave as drains in the base-flow-dominated Coastal Plain.</p><p>Following grid refinement, four physical processes known to govern subsurface flow were introduced to the model. These included effective precipitation recharge, discharge to streams and stream-connected wetlands, regional inflows and outflows along the model bottom, and withdrawals from wells, each of which were incorporated into the model as either external or internal boundary conditions. To account for effective precipitation recharge, a specified-flow boundary was assigned along the top of the model. Similarly, regional flows predicted using the modified U.S Geological Survey’s New Jersey Coastal Plain Regional Aquifer System Analysis model were treated as specified-flow boundary conditions along the bottom of the model. Base-flow losses were treated as drains along streams delineated using a 10-foot LiDAR dataset. Drains were also assigned to cells falling within stream-connected National Hydrologic Database wetlands. Finally, well-pumpage data mined from the New Jersey Water Transfer database were added to the model to account for extraction of groundwater through pumping from industrial-supply and drinking-water-supply wells. Along model edges established at groundwater divides, where the net flux of water across the boundary is equal to zero, natural no-flow boundary conditions were imposed.</p><p>The refined flow model was calibrated using the parameter-estimation (PEST) program, which adjusts model parameters by performing a gradient search over the sum-of-squared-error objective function until the parameter set that produces simulated water levels and base flows most closely matches 544 water levels and 20 estimated base flows and closely adheres to initial parameter estimates. Based on the analysis of calibration residuals, the model did not appear to be affected by significant model structural error.</p><p>The MODPATH particle-tracking algorithm was used to estimate advective transport paths of PFAS in the vicinity of JBMDL. Forward tracking was used to determine paths of PFAS away from AFFF source areas to streams, wetlands, pumping wells, and geographic areas that PFAS may contaminate. Additionally, reverse tracking was used to determine particle pathlines away from off-site PFAS reconnaissance areas, or areas within which all sources of PFAS might be advectively transported into subsurface drinking-water supplies, to locations at land surface that may indicate a source of PFAS.</p><p>The coupled and calibrated groundwater flow and particle-tracking transport model provide valuable tools for predicting the relative extent of PFAS contamination from onsite legacy source areas. The calibrated model also provides measures of water-level and base-flow observation influence that can help guide future data-collection efforts related to groundwater and surface water sampling for PFAS.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221112","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Fiore, A.R., and Colarullo, S.J., 2023, Simulation of regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018: U.S. Geological Survey Open-File Report 2022–1112, 41 p., 2 pls., https://doi.org/10.3133/ofr20221112.","productDescription":"Report: ix, 41 p.; 2 Plates: 35.00 x 45.00 inches and 45.00 x 30.00 inches; Data Release","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-129806","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":412124,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EK4CZS","text":"USGS data release","linkHelpText":"MODFLOW6 and MODPATH7 used to simulate regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":412125,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112.XML"},{"id":412123,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221112/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1112"},{"id":412121,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1112/coverthb.jpg"},{"id":412126,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1112/images/"},{"id":412129,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112_plate1.pdf","text":"Plate 1","size":"212 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Forward particle tracks from aqueous film-forming foam source areas 1 to 15 and reverse particle tracks from per- and polyfluoroalkyl substances reconnaissance areas 4 and 14, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":412122,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112.pdf","text":"Report","size":"7.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1112"},{"id":412130,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112_plate2.pdf","text":"Plate 2","size":"200 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Forward particle tracks from aqueous film-forming foam source areas 16 to 21 and reverse particle tracks from per- and polyfluoroalkyl substances reconnaissance areas 16 to 19, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":499723,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114286.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.77016941849112,\n              40.156458843115274\n            ],\n            [\n              -74.77016941849112,\n              39.93505011875061\n            ],\n            [\n              -74.17559168378837,\n              39.93505011875061\n            ],\n            [\n              -74.17559168378837,\n              40.156458843115274\n            ],\n            [\n              -74.77016941849112,\n              40.156458843115274\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\">New Jersey Water Science Center</a><br>U.S. Geological Survey<br>3450 Princeton Pike, Suite 110<br>Lawrenceville, NJ 08648</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Description of Study Area</li><li>Data Sources</li><li>Simulation of Regional Groundwater Flow</li><li>Model Calibration</li><li>Regional Groundwater Flow Paths and Advective Transport of Per- and Polyfluoroalkyl Substances</li><li>Limitations of the Regional Model</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Description of Model Layers and Their Thicknesses</li><li>Appendix 2. 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,{"id":70239931,"text":"fs20233004 - 2023 - Rangeland Condition Monitoring Assessment and Projection, 1985–2021","interactions":[],"lastModifiedDate":"2026-02-04T20:33:36.72143","indexId":"fs20233004","displayToPublicDate":"2023-01-26T09:48:28","publicationYear":"2023","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":"2023-3004","displayTitle":"Rangeland Condition Monitoring Assessment and Projection, 1985–2021","title":"Rangeland Condition Monitoring Assessment and Projection, 1985–2021","docAbstract":"<p>The Rangeland Condition Monitoring Assessment and Projection (RCMAP) project quantifies the percentage cover of rangeland components across the western United States using Landsat imagery from 1985 to 2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, nonsagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013 to 2018 and additional field data; for example, Bureau of Land Management Assessment, Inventory, and Monitoring instead of using the 2016 “base” map as an intermediary. This removes one level of model error and allows the direct association of high-resolution derived training data to the corresponding year of Landsat imagery. Neural network models have replaced Cubist models as our classifier. Continuous Change Detection and Classification synthetic Landsat images were obtained for six monthly periods for each region and were added as predictors. These data enhance the phenologic detail of imagery, improving discrimination among components. Postprocessing has been improved with updated fire recovery equations stratified by ecosystem resistance and resilience classes. Additionally, postprocessing has been enhanced through a revised noise detection model, based on third order polynomial models for each component and each pixel. These data can be used to answer critical questions regarding the effect of climate change and the suitability of management practices. Component products can be downloaded from the Multi-Resolution Land Characteristics Consortium website at <a data-mce-href=\"https://www.mrlc.gov/data\" href=\"https://www.mrlc.gov/data\">https://www.mrlc.gov/data</a>.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/fs20233004","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Rigge, M.B., 2023, Rangeland Condition Monitoring Assessment and Projection, 1985–2021: U.S. Geological Survey Fact Sheet 2023–3004, 6 p., https://doi.org/10.3133/fs20233004.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","ipdsId":"IP-148071","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":499564,"rank":6,"type":{"id":36,"text":"NGMDB Index 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Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":862550,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70239898,"text":"pp1842Z - 2023 - The effects of management practices on grassland birds—Clay-colored Sparrow (<i>Spizella pallida</i>)","interactions":[{"subject":{"id":70239898,"text":"pp1842Z - 2023 - The effects of management practices on grassland birds—Clay-colored Sparrow (<i>Spizella pallida</i>)","indexId":"pp1842Z","publicationYear":"2023","noYear":false,"chapter":"Z","displayTitle":"The Effects of Management Practices on Grassland Birds—Clay-Colored Sparrow (<i>Spizella pallida</i>)","title":"The effects of management practices on grassland birds—Clay-colored Sparrow (<i>Spizella pallida</i>)"},"predicate":"IS_PART_OF","object":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"id":1}],"isPartOf":{"id":70203022,"text":"pp1842 - 2019 - The effects of management practices on grassland birds","indexId":"pp1842","publicationYear":"2019","noYear":false,"title":"The effects of management practices on grassland birds"},"lastModifiedDate":"2023-12-20T21:26:31.022182","indexId":"pp1842Z","displayToPublicDate":"2023-01-25T11:27:27","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1842","chapter":"Z","displayTitle":"The Effects of Management Practices on Grassland Birds—Clay-Colored Sparrow (<i>Spizella pallida</i>)","title":"The effects of management practices on grassland birds—Clay-colored Sparrow (<i>Spizella pallida</i>)","docAbstract":"<p>Keys to Clay-colored Sparrow (<i>Spizella pallida</i>) management include providing grasslands with a shrub or forb component or shrub-dominated edge habitat, which includes dense grass and moderately high litter cover, and avoiding disturbances that completely eliminate woody vegetation. Clay-colored Sparrows have been reported to use habitats with 20–186 centimeters (cm) average vegetation height, 3–50 cm visual obstruction reading, 15–74 percent grass cover, 5–23 percent forb cover, less than 30 percent shrub cover, 1–20 percent bare ground, 10–63 percent litter cover, and less than or equal to 5 cm litter depth.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Va.","doi":"10.3133/pp1842Z","usgsCitation":"Shaffer, J.A., Igl, L.D., Johnson, D.H., Sondreal, M.L., Goldade, C.M., Nenneman, M.P., and Euliss, B.R., 2023, The effects of management practices on grassland birds—Clay-colored Sparrow (<i>Spizella pallida</i>), chap. Z <i>of</i> Johnson, D.H., Igl, L.D., Shaffer, J.A., and DeLong, J.P., eds., The effects of management practices on grassland birds: U.S. Geological Survey Professional Paper 1842, 27 p., https://doi.org/10.3133/pp1842Z.","productDescription":"v, 27 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-097128","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":412290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1842/z/coverthb.jpg"},{"id":412291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1842/z/pp1842z.pdf","text":"Report","size":"2.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1842Z"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/npwrc\" data-mce-href=\"https://www.usgs.gov/centers/npwrc\">Northern Prairie Wildlife Research Center</a> <br>U.S. Geological Survey<br>8711 37th Street Southeast <br>Jamestown, ND 58401</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Capsule Statement</li><li>Breeding Range</li><li>Suitable Habitat</li><li>Area Requirements and Landscape Associations</li><li>Brood Parasitism by Cowbirds and Other Species</li><li>Breeding-Season Phenology and Site Fidelity</li><li>Species’ Response to Management</li><li>Management Recommendations from the Literature</li><li>References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-01-25","noUsgsAuthors":false,"publicationDate":"2023-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Shaffer, Jill A. 0000-0003-3172-0708","orcid":"https://orcid.org/0000-0003-3172-0708","contributorId":221268,"corporation":false,"usgs":true,"family":"Shaffer","given":"Jill A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Igl, Lawrence D. 0000-0003-0530-7266","orcid":"https://orcid.org/0000-0003-0530-7266","contributorId":221768,"corporation":false,"usgs":true,"family":"Igl","given":"Lawrence D.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Douglas H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":216292,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862300,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sondreal, Marriah L.","contributorId":73532,"corporation":false,"usgs":true,"family":"Sondreal","given":"Marriah","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":862301,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldade, Christopher M.","contributorId":215632,"corporation":false,"usgs":false,"family":"Goldade","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":39297,"text":"former U.S. Geological Survey employee","active":true,"usgs":false}],"preferred":false,"id":862302,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nenneman, Melvin P.","contributorId":60572,"corporation":false,"usgs":true,"family":"Nenneman","given":"Melvin P.","affiliations":[],"preferred":false,"id":862303,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Euliss, Betty R.","contributorId":191881,"corporation":false,"usgs":false,"family":"Euliss","given":"Betty","email":"","middleInitial":"R.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":862304,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70244064,"text":"70244064 - 2023 - Advancing best practices for the analysis of the vulnerability of military installations in the Pacific Basin to coastal flooding under a changing climate – RC-2644","interactions":[],"lastModifiedDate":"2024-03-29T15:42:37.94771","indexId":"70244064","displayToPublicDate":"2023-01-25T10:37:12","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7504,"text":"Final Report","active":true,"publicationSubtype":{"id":1}},"title":"Advancing best practices for the analysis of the vulnerability of military installations in the Pacific Basin to coastal flooding under a changing climate – RC-2644","docAbstract":"Coastal flooding takes many forms, ranging from major flooding associated with storms to minor\nflooding associated with exceptionally high tides and other oceanic and atmospheric phenomena on storm-free days. A major societal challenge is to understand and predict how flood magnitude and frequency will manifest at particular places and times, now and in the future. Of particular interest here is how coastal flooding will impact Department of Defense (DoD) installations. In response to this need, this work aims to advance the practical application of statistical and other analytical techniques that can be used to assess the exposure, and ultimately the vulnerability, of built and natural environments to the impacts of coastal flooding. A variety of methods are described and applied to assess exposure. This includes tide gauge station-based diagnosis and prognosis of patterns and trends of Still Water Level, techniques to characterize the expression of ‘lesser extremes’ (e.g., sub-annual to subdecadal event probabilities), and region-wide analysis that improves upon results obtained from conventional single-tide gauge analyses. A novel hybrid statistical and dynamical modeling approach is applied to the analysis of Total Water Levels, necessary for exposure assessment along shorelines exposed to wave action. The hybrid exposure assessment modeling approach is incorporated into a broader mission-based protocol for the assessment of resilience to coastal flooding at the installation level. Demonstrated via an exemplar assessment, which takes into account functional (lost day) as well as financial impacts (lost dollars), the protocol meets the demand for an actionable characterization of how DoD installations will be affected by coastal flooding and improves DoD’s ability to make informed decisions about how to adapt to its effects. The methods described, evaluated, and applied here, including innovative approaches and proof-of-concept products developed through this work, are incorporated into and considered within an analytical framework that serves as guidance as to their relative merits with respect to coastal flood exposure assessment in various circumstances and settings, and illustrates best practices. This will provide engineers, scientists and other practitioners with an enhanced capability to generate information that can be used to support area-wide assessment related to climate adaptation planning and disaster risk reduction as well as site-specific analysis related to design and maintenance of facilities and infrastructure. While the focus is on a select set of DoD sites in\nthe Pacific Basin, the results have broad applicability nationally as well as globally.","language":"English","publisher":"U.S. Department of Defense Strategic Environmental Research and Development Program","usgsCitation":"Marra, J., Sweet, W., Leuliette, E., Kruk, M., Genz, A., Storlazzi, C.D., Ruggiero, P., Leung, M., Anderson, D.L., Merrifield, M., Becker, J., Robertson, I., Widlansky, M.J., Thompson, P., Mendez, F., Rueda, A., Antolinez, J.A., Cagigal, L., Menendez, M., Lobeto, H., Obeysekera, J., and Chiesa, C., 2023, Advancing best practices for the analysis of the vulnerability of military installations in the Pacific Basin to coastal flooding under a changing climate – RC-2644: Final Report, xxxiv, 543 p.","productDescription":"xxxiv, 543 p.","ipdsId":"IP-150451","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":427245,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427244,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://serdp-estcp.mil/projects/details/1843ce82-2c9f-431e-b17a-29680ad82bf9","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marra, John ","contributorId":221119,"corporation":false,"usgs":false,"family":"Marra","given":"John ","affiliations":[{"id":40326,"text":"NOAA, National Environmental Satellite, Data, and Information Service","active":true,"usgs":false}],"preferred":false,"id":874366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweet, William ","contributorId":223921,"corporation":false,"usgs":false,"family":"Sweet","given":"William ","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":874367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Leuliette, Eric","contributorId":305997,"corporation":false,"usgs":false,"family":"Leuliette","given":"Eric","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":874368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kruk, Michael","contributorId":305998,"corporation":false,"usgs":false,"family":"Kruk","given":"Michael","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":874369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Genz, Ayesha 0000-0002-2916-1436","orcid":"https://orcid.org/0000-0002-2916-1436","contributorId":196671,"corporation":false,"usgs":false,"family":"Genz","given":"Ayesha","email":"","affiliations":[],"preferred":false,"id":874370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":213610,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":874371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ruggiero, Peter","contributorId":15709,"corporation":false,"usgs":false,"family":"Ruggiero","given":"Peter","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":874372,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Leung, Meredith","contributorId":305379,"corporation":false,"usgs":false,"family":"Leung","given":"Meredith","email":"","affiliations":[{"id":37105,"text":"Oregon State Unversity","active":true,"usgs":false}],"preferred":false,"id":874373,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Anderson, Dylan L.","contributorId":187533,"corporation":false,"usgs":false,"family":"Anderson","given":"Dylan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":874374,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Merrifield, Mark","contributorId":305999,"corporation":false,"usgs":false,"family":"Merrifield","given":"Mark","affiliations":[{"id":16619,"text":"UCSD","active":true,"usgs":false}],"preferred":false,"id":874375,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Becker, Janet","contributorId":224305,"corporation":false,"usgs":false,"family":"Becker","given":"Janet","email":"","affiliations":[{"id":16619,"text":"UCSD","active":true,"usgs":false}],"preferred":false,"id":874376,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Robertson, Ian","contributorId":306000,"corporation":false,"usgs":false,"family":"Robertson","given":"Ian","affiliations":[{"id":25429,"text":"UH","active":true,"usgs":false}],"preferred":false,"id":874377,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Widlansky, Matthew J.","contributorId":215334,"corporation":false,"usgs":false,"family":"Widlansky","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39222,"text":"Joint Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology, University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":874378,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thompson, Philip R.","contributorId":176373,"corporation":false,"usgs":false,"family":"Thompson","given":"Philip R.","affiliations":[],"preferred":false,"id":874379,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mendez, Fernando","contributorId":264476,"corporation":false,"usgs":false,"family":"Mendez","given":"Fernando","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":874380,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Rueda, Ana","contributorId":264475,"corporation":false,"usgs":false,"family":"Rueda","given":"Ana","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":874381,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Antolinez, Jose A.A.","contributorId":177510,"corporation":false,"usgs":false,"family":"Antolinez","given":"Jose","email":"","middleInitial":"A.A.","affiliations":[],"preferred":false,"id":874382,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Cagigal, Laura","contributorId":214560,"corporation":false,"usgs":false,"family":"Cagigal","given":"Laura","affiliations":[{"id":39072,"text":"U.Cantabria","active":true,"usgs":false}],"preferred":false,"id":874383,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Menendez, Melissa","contributorId":306001,"corporation":false,"usgs":false,"family":"Menendez","given":"Melissa","email":"","affiliations":[{"id":66342,"text":"IHC","active":true,"usgs":false}],"preferred":false,"id":874384,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Lobeto, Hector","contributorId":306002,"corporation":false,"usgs":false,"family":"Lobeto","given":"Hector","email":"","affiliations":[{"id":66342,"text":"IHC","active":true,"usgs":false}],"preferred":false,"id":874385,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Obeysekera, Jayantha 0000-0002-9261-1268","orcid":"https://orcid.org/0000-0002-9261-1268","contributorId":223708,"corporation":false,"usgs":false,"family":"Obeysekera","given":"Jayantha","affiliations":[{"id":40755,"text":"South Florida WMD West Palm Beach, FL","active":true,"usgs":false}],"preferred":false,"id":874386,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Chiesa, Chris","contributorId":306003,"corporation":false,"usgs":false,"family":"Chiesa","given":"Chris","email":"","affiliations":[{"id":66343,"text":"PDC","active":true,"usgs":false}],"preferred":false,"id":874387,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}}
,{"id":70240182,"text":"70240182 - 2023 - Context-dependent representation of within- and between-model uncertainty: Aggregating probabilistic predictions in infectious disease epidemiology","interactions":[],"lastModifiedDate":"2023-02-01T12:52:49.671473","indexId":"70240182","displayToPublicDate":"2023-01-25T06:51:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2567,"text":"Journal of the Royal Society Interface","active":true,"publicationSubtype":{"id":10}},"title":"Context-dependent representation of within- and between-model uncertainty: Aggregating probabilistic predictions in infectious disease epidemiology","docAbstract":"<div class=\"hlFld-Abstract\"><div class=\"abstractSection abstractInFull\"><p>Probabilistic predictions support public health planning and decision making, especially in infectious disease emergencies. Aggregating outputs from multiple models yields more robust predictions of outcomes and associated uncertainty. While the selection of an aggregation method can be guided by retrospective performance evaluations, this is not always possible. For example, if predictions are conditional on assumptions about how the future will unfold (e.g. possible interventions), these assumptions may never materialize, precluding any direct comparison between predictions and observations. Here, we summarize literature on aggregating probabilistic predictions, illustrate various methods for infectious disease predictions via simulation, and present a strategy for choosing an aggregation method when empirical validation cannot be used. We focus on the linear opinion pool (LOP) and Vincent average, common methods that make different assumptions about between-prediction uncertainty. We contend that assumptions of the aggregation method should align with a hypothesis about how uncertainty is expressed within and between predictions from different sources. The LOP assumes that between-prediction uncertainty is meaningful and should be retained, while the Vincent average assumes that between-prediction uncertainty is akin to sampling error and should not be preserved. We provide an R package for implementation. Given the rising importance of multi-model infectious disease hubs, our work provides useful guidance on aggregation and a deeper understanding of the benefits and risks of different approaches.</p></div></div>","language":"English","publisher":"The Royal Society of Publishing","doi":"10.1098/rsif.2022.0659","usgsCitation":"Howerton, E., Runge, M.C., Bogich, T.L., Borchering, R.K., Inamine, H., Lessler, J., Mullany, L.C., Probert, W.J., Smith, C.P., Truelove, S., Viboud, C., and Shea, K., 2023, Context-dependent representation of within- and between-model uncertainty: Aggregating probabilistic predictions in infectious disease epidemiology: Journal of the Royal Society Interface, v. 20, 20220659, 12 p., https://doi.org/10.1098/rsif.2022.0659.","productDescription":"20220659, 12 p.","ipdsId":"IP-140843","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rsif.2022.0659","text":"Publisher Index Page"},{"id":412529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","noUsgsAuthors":false,"publicationDate":"2023-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Howerton, Emily 0000-0002-0639-3728","orcid":"https://orcid.org/0000-0002-0639-3728","contributorId":258035,"corporation":false,"usgs":false,"family":"Howerton","given":"Emily","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":862880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bogich, Tiffany L. 0000-0002-8143-5289","orcid":"https://orcid.org/0000-0002-8143-5289","contributorId":260459,"corporation":false,"usgs":false,"family":"Bogich","given":"Tiffany","email":"","middleInitial":"L.","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":862882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borchering, Rebecca K. 0000-0003-4309-2913","orcid":"https://orcid.org/0000-0003-4309-2913","contributorId":258031,"corporation":false,"usgs":false,"family":"Borchering","given":"Rebecca","email":"","middleInitial":"K.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":862883,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Inamine, Hidetoshi","contributorId":301868,"corporation":false,"usgs":false,"family":"Inamine","given":"Hidetoshi","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":862884,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lessler, Justin","contributorId":258042,"corporation":false,"usgs":false,"family":"Lessler","given":"Justin","email":"","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":862885,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mullany, Luke C","contributorId":301869,"corporation":false,"usgs":false,"family":"Mullany","given":"Luke","email":"","middleInitial":"C","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":862886,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Probert, William J.M.","contributorId":295477,"corporation":false,"usgs":false,"family":"Probert","given":"William","email":"","middleInitial":"J.M.","affiliations":[{"id":25447,"text":"University of Oxford","active":true,"usgs":false}],"preferred":false,"id":862887,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, Claire P.","contributorId":258036,"corporation":false,"usgs":false,"family":"Smith","given":"Claire","email":"","middleInitial":"P.","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":862888,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Truelove, Shaun","contributorId":258037,"corporation":false,"usgs":false,"family":"Truelove","given":"Shaun","email":"","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":862889,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Viboud, Cècile","contributorId":301870,"corporation":false,"usgs":false,"family":"Viboud","given":"Cècile","affiliations":[{"id":49979,"text":"National Institutes of Health","active":true,"usgs":false}],"preferred":false,"id":862890,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shea, Katriona 0000-0002-7607-8248","orcid":"https://orcid.org/0000-0002-7607-8248","contributorId":193646,"corporation":false,"usgs":false,"family":"Shea","given":"Katriona","email":"","affiliations":[],"preferred":false,"id":862891,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70246955,"text":"70246955 - 2023 - Improvements to estimate ADCP uncertainty sources for discharge measurements","interactions":[],"lastModifiedDate":"2023-07-20T11:46:29.773454","indexId":"70246955","displayToPublicDate":"2023-01-25T06:44:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1674,"text":"Flow Measurement and Instrumentation","active":true,"publicationSubtype":{"id":10}},"title":"Improvements to estimate ADCP uncertainty sources for discharge measurements","docAbstract":"<p id=\"abspara0010\">The use of moving boat ADCPs (Acoustic Doppler Current Profilers) for discharge measurements requires identification of the sources and magnitude of uncertainty to ensure accurate measurements. Recently, a tool known as QUant was developed to estimate the contribution to the uncertainty estimates for each transect of moving-boat ADCP discharge measurements, by varying different sampling configurations parameters through the use of Monte Carlo simulations. QUant is not only useful for estimating ADCP discharge measurement uncertainty, but also for identifying contributions of the various sources of uncertainty.</p><p id=\"abspara0015\">However, the software requires long computational times, and the method to estimate the uncertainty of multiple-transect measurements does not consider the correlation of the variables between transects. Therefore, improvements in QUant are needed to optimize its application for practical purposes by hydrographers immediately after discharge measurements.</p><p id=\"abspara0020\">This work presents four approaches for optimizing the performance of QUant to estimate the contribution to the uncertainty of different selected variables on ADCP discharge measurements and describes a new method of estimating multi-transect uncertainty with the QUant model that considers the correlation of errors in selected variables between transects. The approaches for optimization and the new multi-transect uncertainty method are evaluated using a dataset of 38 field measurements from a variety of riverine settings.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.flowmeasinst.2023.102311","usgsCitation":"Diaz Lozada, J.M., Garcia, C.M., Oberg, K., Over, T.M., and Flores Nieto, F., 2023, Improvements to estimate ADCP uncertainty sources for discharge measurements: Flow Measurement and Instrumentation, v. 90, 102311, 12 p., https://doi.org/10.1016/j.flowmeasinst.2023.102311.","productDescription":"102311, 12 p.","ipdsId":"IP-122869","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":419175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"90","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Diaz Lozada, Jose M. 0000-0002-6735-0916","orcid":"https://orcid.org/0000-0002-6735-0916","contributorId":287571,"corporation":false,"usgs":false,"family":"Diaz Lozada","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":61615,"text":"Institute for Advanced Studies for Engineering and Technology (IDIT CONICET/UNC) – FCEFyN, National University of Córdoba","active":true,"usgs":false}],"preferred":false,"id":878354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Carlos M. 0000-0002-4091-6756","orcid":"https://orcid.org/0000-0002-4091-6756","contributorId":287572,"corporation":false,"usgs":false,"family":"Garcia","given":"Carlos","email":"","middleInitial":"M.","affiliations":[{"id":61615,"text":"Institute for Advanced Studies for Engineering and Technology (IDIT CONICET/UNC) – FCEFyN, National University of Córdoba","active":true,"usgs":false}],"preferred":false,"id":878355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oberg, Kevin 0000-0002-7024-3361 kaoberg@usgs.gov","orcid":"https://orcid.org/0000-0002-7024-3361","contributorId":175229,"corporation":false,"usgs":true,"family":"Oberg","given":"Kevin","email":"kaoberg@usgs.gov","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":878356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":878357,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flores Nieto, Federico","contributorId":316794,"corporation":false,"usgs":false,"family":"Flores Nieto","given":"Federico","email":"","affiliations":[{"id":68697,"text":"Universidad Nacional de Córdoba, Argentina","active":true,"usgs":false}],"preferred":false,"id":878358,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241897,"text":"70241897 - 2023 - Stochastic watershed model ensembles for long-range planning: Verification and validation","interactions":[],"lastModifiedDate":"2023-03-30T11:38:33.672469","indexId":"70241897","displayToPublicDate":"2023-01-24T06:35:30","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":11438,"text":"Water Resource Research","active":true,"publicationSubtype":{"id":10}},"title":"Stochastic watershed model ensembles for long-range planning: Verification and validation","docAbstract":"<div class=\"article-section__content en main\"><p>Deterministic watershed models (DWMs) are used in nearly all hydrologic planning, design, and management activities, yet they cannot generate streamflow ensembles needed for hydrologic risk management (HRM). The stochastic component of DWMs is often ignored in practice, leading to a systematic bias in extreme events. Since traditional stochastic streamflow models used in HRM struggle to account for anthropogenic change, there is a need to convert DWMs into stochastic watershed models (SWMs) to generate ensembles for use in HRM. A DWM can be converted to an SWM using a post-processing (pp) approach to add error to the DWM predictions. Many pp methods advanced in the area of flood forecasting are useful in HRM and for correcting extreme event biases. Selecting a suitable error model for pp is challenging due to nonnormality, skewness, heteroscedasticity, and autocorrelation. We develop a parsimonious pp method based on an autoregressive (AR) model of the logarithm of the ratio of the observations and simulations, which leads to AR model residuals that are approximately symmetric and independent. We document the value of pp for improving flood and low flow frequency analysis and we reintroduce the concepts of verification and validation of stochastic streamflow ensembles to ensure that the SWM can reproduce both statistics it was and was not designed to reproduce, respectively. These concepts are illustrated on a Massachusetts basin using the USGS Precipitation Runoff Modeling System, with an additional analysis indicating the approach may be applicable to 1,225 other sites across the United States.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022WR032201","usgsCitation":"Shabestanipour, G., Brodeur, Z.P., Farmer, W., Steinschneider, S., Vogel, R., and Lamontagne, J., 2023, Stochastic watershed model ensembles for long-range planning: Verification and validation: Water Resource Research, v. 59, no. 2, e2022WR032201, 20 p., https://doi.org/10.1029/2022WR032201.","productDescription":"e2022WR032201, 20 p.","ipdsId":"IP-138092","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":414949,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts, New Hampshire","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -71.91821608000225,\n              42.76149650725495\n            ],\n            [\n              -71.91821608000225,\n              42.618159403372886\n            ],\n            [\n              -71.6545442050027,\n              42.618159403372886\n            ],\n            [\n              -71.6545442050027,\n              42.76149650725495\n            ],\n            [\n              -71.91821608000225,\n              42.76149650725495\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"59","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Shabestanipour, Ghazal","contributorId":303810,"corporation":false,"usgs":false,"family":"Shabestanipour","given":"Ghazal","email":"","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":868138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brodeur, Zachary P","contributorId":303811,"corporation":false,"usgs":false,"family":"Brodeur","given":"Zachary","email":"","middleInitial":"P","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":868139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farmer, William H. 0000-0002-2865-2196","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":223181,"corporation":false,"usgs":true,"family":"Farmer","given":"William H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":868140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Steinschneider, Scott 0000-0002-8882-1908","orcid":"https://orcid.org/0000-0002-8882-1908","contributorId":206359,"corporation":false,"usgs":false,"family":"Steinschneider","given":"Scott","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":868141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vogel, Richard M","contributorId":241035,"corporation":false,"usgs":false,"family":"Vogel","given":"Richard M","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":868142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lamontagne, Jonathan","contributorId":303813,"corporation":false,"usgs":false,"family":"Lamontagne","given":"Jonathan","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":868143,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70242950,"text":"70242950 - 2023 - Investigations of ambient noise velocity variations in a region of induced seismicity near Greeley, Colorado","interactions":[],"lastModifiedDate":"2023-04-24T11:20:57.423052","indexId":"70242950","displayToPublicDate":"2023-01-24T06:17:14","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Investigations of ambient noise velocity variations in a region of induced seismicity near Greeley, Colorado","docAbstract":"<div id=\"135595978\" class=\"article-section-wrapper js-article-section js-content-section  \" data-section-parent-id=\"0\"><p>Wastewater injection has induced earthquakes in Northeastern Colorado since 2014. We apply ambient noise correlation techniques to determine temporal changes in seismic velocities in the region. We find no clear correlation between seismic velocity fluctuations and either injection volumes or seismicity patterns. We do observe apparent annual variations in velocity that may be associated with hydrologic loading or thermoelastic strain. In addition, we model uniform and vertically localized velocity perturbations, and measure the velocity change with 1D synthetic seismograms. Our results indicate that our methods underestimate the known velocity change, especially at shorter station distances and when variations are restricted to a horizontal layer. If injection does cause measurable velocity changes, its effect is likely diluted in cross correlations due to its localized spatial extent around injection wells.</p></div>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320220033","usgsCitation":"Clifford, T., Sheehan, A., and Moschetti, M.P., 2023, Investigations of ambient noise velocity variations in a region of induced seismicity near Greeley, Colorado: The Seismic Record, v. 3, no. 2, p. 12-20, https://doi.org/10.1785/0320220033.","productDescription":"9 p.","startPage":"12","endPage":"20","ipdsId":"IP-146548","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":444720,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320220033","text":"Publisher Index Page"},{"id":416165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Greeley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.93049403298068,\n              40.56981242493987\n            ],\n            [\n              -104.93049403298068,\n              40.2769456875688\n            ],\n            [\n              -104.47541354476009,\n              40.2769456875688\n            ],\n            [\n              -104.47541354476009,\n              40.56981242493987\n            ],\n            [\n              -104.93049403298068,\n              40.56981242493987\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"3","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Clifford, Thomas","contributorId":304410,"corporation":false,"usgs":false,"family":"Clifford","given":"Thomas","email":"","affiliations":[{"id":66058,"text":"SlateGeotech, Univ. of Colorado, Boulder","active":true,"usgs":false}],"preferred":false,"id":870331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Anne","contributorId":139409,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","affiliations":[{"id":6713,"text":"University of Colorado, Boulder CO","active":true,"usgs":false}],"preferred":false,"id":870332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":870333,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250173,"text":"70250173 - 2023 - Estimating geomagnetically induced currents in southern Brazil using 3-D Earth resistivity model","interactions":[],"lastModifiedDate":"2023-11-26T14:31:28.440598","indexId":"70250173","displayToPublicDate":"2023-01-23T08:28:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"Estimating geomagnetically induced currents in southern Brazil using 3-D Earth resistivity model","docAbstract":"<div class=\"article-section__content en main\"><p>Geomagnetically induced currents (GICs) result from the interaction of the time variation of ground magnetic field during a geomagnetic disturbance with the Earth's deep electrical resistivity structure. In this study, we simulate induced GICs in a hypothetical representation of a low-latitude power transmission network located mainly over the large Paleozoic Paraná basin (PB) in southern Brazil. Two intense geomagnetic storms in June and December 2015 are chosen and geoelectric fields are calculated by convolving a three-dimensional (3-D) Earth resistivity model with recorded geomagnetic variations. The<span>&nbsp;</span><i>dB</i>/<i>dt</i><span>&nbsp;</span>proxy often used to characterize GIC activity fails during the June storm mainly due to the relationship of the instantaneous geoelectric field to previous magnetic field values. Precise resistances of network components are unknown, so assumptions are made for calculating GIC flows from the derived geoelectric field. The largest GICs are modeled in regions of low conductance in the 3-D resistivity model, concentrated in an isolated substation at the northern edge of the network and in a cluster of substations in its central part where the east-west (E-W) oriented transmission lines coincide with the orientation of the instantaneous geoelectric field. The maximum magnitude of the modeled GIC was obtained during the main phase of the June storm, modeled at a northern substation, while the lowest magnitudes were found over prominent crustal anomalies along the PB axis and bordering the continental margin. The simulation results will be used to prospect the optimal substations for installation of GIC monitoring equipment.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022SW003166","usgsCitation":"Espinosa Sarmiento, K.V., Padilha, A.L., Alves, L.R., Schultz, A., and Kelbert, A., 2023, Estimating geomagnetically induced currents in southern Brazil using 3-D Earth resistivity model: Space Weather, v. 21, no. 4, e2022SW003166, 22 p., https://doi.org/10.1029/2022SW003166.","productDescription":"e2022SW003166, 22 p.","ipdsId":"IP-150115","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":444723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022sw003166","text":"Publisher Index Page"},{"id":422952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -58.682884413719464,\n              -22.76284656134837\n            ],\n            [\n              -58.682884413719464,\n              -33.73058620408474\n            ],\n            [\n              -45.85085316371996,\n              -33.73058620408474\n            ],\n            [\n              -45.85085316371996,\n              -22.76284656134837\n            ],\n            [\n              -58.682884413719464,\n              -22.76284656134837\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"21","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Espinosa Sarmiento, Karen V.","contributorId":331738,"corporation":false,"usgs":false,"family":"Espinosa Sarmiento","given":"Karen","email":"","middleInitial":"V.","affiliations":[{"id":79276,"text":"Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, Brazil","active":true,"usgs":false}],"preferred":false,"id":888651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Padilha, Antonio L.","contributorId":331739,"corporation":false,"usgs":false,"family":"Padilha","given":"Antonio","email":"","middleInitial":"L.","affiliations":[{"id":79276,"text":"Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, Brazil","active":true,"usgs":false}],"preferred":false,"id":888652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alves, Livia R.","contributorId":331740,"corporation":false,"usgs":false,"family":"Alves","given":"Livia","email":"","middleInitial":"R.","affiliations":[{"id":79276,"text":"Instituto Nacional de Pesquisas Espaciais (INPE), Sao Jose dos Campos, Brazil","active":true,"usgs":false}],"preferred":false,"id":888653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Adam","contributorId":197380,"corporation":false,"usgs":false,"family":"Schultz","given":"Adam","affiliations":[],"preferred":false,"id":888654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":888655,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241055,"text":"70241055 - 2023 - Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides","interactions":[],"lastModifiedDate":"2023-03-08T13:17:43.875878","indexId":"70241055","displayToPublicDate":"2023-01-23T07:11:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides","docAbstract":"<div>The acute decline in global biodiversity includes not only the loss of rare species, but also the rapid collapse of common species across many different taxa. The loss of pollinating insects is of particular concern because of the ecological and economic values these species provide. The western bumble bee (<i>Bombus occidentalis</i>) was once common in western North America, but this species has become increasingly rare through much of its range. To understand potential mechanisms driving these declines, we used Bayesian occupancy models to investigate the effects of climate and land cover from 1998 to 2020, pesticide use from 2008 to 2014, and projected expected occupancy under three future scenarios. Using 14,457 surveys across 2.8 million km<sup>2</sup><span>&nbsp;</span>in the western United States, we found strong negative relationships between increasing temperature and drought on occupancy and identified neonicotinoids as the pesticides of greatest negative influence across our study region. The mean predicted occupancy declined by 57% from 1998 to 2020, ranging from 15 to 83% declines across 16 ecoregions. Even under the most optimistic scenario, we found continued declines in nearly half of the ecoregions by the 2050s and mean declines of 93% under the most severe scenario across all ecoregions. This assessment underscores the tenuous future of<span>&nbsp;</span><i>B.&nbsp;occidentalis</i><span>&nbsp;</span>and demonstrates the scale of stressors likely contributing to rapid loss of related pollinator species throughout the globe. Scaled-up, international species-monitoring schemes and improved integration of data from formal surveys and community science will substantively improve the understanding of stressors and bumble bee population trends.</div>","language":"English","publisher":"Proceedings of the National Academy of Sciences","doi":"10.1073/pnas.2211223120","usgsCitation":"Janousek, W.M., Douglas, M.R., Cannings, S., Clement, M., Delphia, C., Everett, J., Hatfield, R.G., Keinath, D.A., Koch, J.B., McCabe, L.M., Mola, J.M., Ogilvie, J., Rangwala, I., Richardson, L., Rohde, A., Strange, J.P., Tronstad, L., and Graves, T., 2023, Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides: Proceedings of the National Academy of Sciences, v. 120, no. 5, e2211223120, 9 p., https://doi.org/10.1073/pnas.2211223120.","productDescription":"e2211223120, 9 p.","ipdsId":"IP-142182","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":444728,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2211223120","text":"Publisher Index Page"},{"id":435489,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93QZRRL","text":"USGS data release","linkHelpText":"Downscaled western bumble bee predicted occupancy for 2020, western conterminous United States."},{"id":435488,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96OB96W","text":"USGS data release","linkHelpText":"Occurrence data of the western bumble bee from 1998 to 2020 across the western United States"},{"id":435487,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H45NUG","text":"USGS data release","linkHelpText":"Neonicotinoid nitroguanidine group insecticide application rates estimated across the western conterminous United States, 2008 to 2014"},{"id":435486,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UHMCV1","text":"USGS data release","linkHelpText":"Western bumble bee predicted occupancy (1998, 2020) and future projections (2050s), western conterminous United States"},{"id":413849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -126.1415510332553,\n              49.7481925327383\n            ],\n            [\n              -126.1415510332553,\n              31.243714437289896\n            ],\n            [\n              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R.","contributorId":214383,"corporation":false,"usgs":false,"family":"Douglas","given":"Margaret","email":"","middleInitial":"R.","affiliations":[{"id":39028,"text":"Dickinson College","active":true,"usgs":false}],"preferred":false,"id":865889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannings, Syd","contributorId":237985,"corporation":false,"usgs":false,"family":"Cannings","given":"Syd","email":"","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":865890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clement, Marion","contributorId":302930,"corporation":false,"usgs":false,"family":"Clement","given":"Marion","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":865891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Delphia, Casey","contributorId":302931,"corporation":false,"usgs":false,"family":"Delphia","given":"Casey","email":"","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":865892,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Everett, Jeffrey G.","contributorId":302932,"corporation":false,"usgs":false,"family":"Everett","given":"Jeffrey","middleInitial":"G.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":865893,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hatfield, Richard G.","contributorId":237986,"corporation":false,"usgs":false,"family":"Hatfield","given":"Richard","email":"","middleInitial":"G.","affiliations":[{"id":37554,"text":"Xerces Society","active":true,"usgs":false}],"preferred":false,"id":865894,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Keinath, Douglas A.","contributorId":274356,"corporation":false,"usgs":false,"family":"Keinath","given":"Douglas","email":"","middleInitial":"A.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":865895,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Koch, Jonathan B","contributorId":237988,"corporation":false,"usgs":false,"family":"Koch","given":"Jonathan","email":"","middleInitial":"B","affiliations":[{"id":47671,"text":"University of Hawai'i, Hilo","active":true,"usgs":false}],"preferred":false,"id":865896,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"McCabe, Lindsie M.","contributorId":265578,"corporation":false,"usgs":false,"family":"McCabe","given":"Lindsie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":865897,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mola, John Michael 0000-0002-5394-9071","orcid":"https://orcid.org/0000-0002-5394-9071","contributorId":224281,"corporation":false,"usgs":true,"family":"Mola","given":"John","email":"","middleInitial":"Michael","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":865898,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ogilvie, Jane","contributorId":302933,"corporation":false,"usgs":false,"family":"Ogilvie","given":"Jane","email":"","affiliations":[{"id":49195,"text":"Rocky Mountain Biological Laboratory","active":true,"usgs":false}],"preferred":false,"id":865899,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rangwala, Imtiaz","contributorId":259891,"corporation":false,"usgs":false,"family":"Rangwala","given":"Imtiaz","affiliations":[{"id":52460,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":865900,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Richardson, Leif L","contributorId":237990,"corporation":false,"usgs":false,"family":"Richardson","given":"Leif L","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":865901,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Rohde, Ashley T. 0000-0003-4939-3047","orcid":"https://orcid.org/0000-0003-4939-3047","contributorId":204143,"corporation":false,"usgs":false,"family":"Rohde","given":"Ashley T.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":865902,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Strange, James P.","contributorId":224183,"corporation":false,"usgs":false,"family":"Strange","given":"James","email":"","middleInitial":"P.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":865903,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Tronstad, Lusha M.","contributorId":224819,"corporation":false,"usgs":false,"family":"Tronstad","given":"Lusha M.","affiliations":[{"id":40947,"text":"Wyoming Natural Diversity Database, University of Wyoming, Laramie, WY, USA","active":true,"usgs":false}],"preferred":false,"id":865904,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":865905,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70241810,"text":"70241810 - 2023 - Optimization and application of non-native Phragmites australis transcriptome assemblies","interactions":[],"lastModifiedDate":"2023-03-28T11:49:17.197674","indexId":"70241810","displayToPublicDate":"2023-01-23T06:47:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Optimization and application of non-native Phragmites australis transcriptome assemblies","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p><i>Phragmites australis</i><span>&nbsp;</span>(common reed) has a cosmopolitan distribution and has been suggested as a model organism for the study of invasive plant species. In North America, the non-native subspecies (ssp.<span>&nbsp;</span><i>australis</i>) is widely distributed across the contiguous 48 states in the United States and large parts of Canada. Even though millions of dollars are spent annually on<span>&nbsp;</span><i>Phragmites</i><span>&nbsp;</span>management, insufficient knowledge of<span>&nbsp;</span><i>P</i>.<span>&nbsp;</span><i>australis</i><span>&nbsp;</span>impeded the efficiency of management. To solve this problem, transcriptomic information generated from multiple types of tissue could be a valuable resource for future studies. Here, we constructed forty-nine<span>&nbsp;</span><i>P</i>.<span>&nbsp;</span><i>australis</i><span>&nbsp;</span>transcriptomes assemblies via different assembly tools and multiple parameter settings. The optimal transcriptome assembly for functional annotation and downstream analyses was selected among these transcriptome assemblies by comprehensive assessments. For a total of 422,589 transcripts assembled in this transcriptome assembly, 319,046 transcripts (75.5%) have at least one functional annotation. Within the transcriptome assembly, we further identified 1,495 transcripts showing tissue-specific expression pattern, 10,828 putative transcription factors, and 72,165 candidates for simple sequence repeats markers. The identification and analyses of predicted transcripts related to herbicide- and salinity-resistant genes were shown as two applications of the transcriptomic information to facilitate further research on<span>&nbsp;</span><i>P</i>.<span>&nbsp;</span><i>australis</i>. Transcriptome assembly and selection would be important for the transcriptome annotation. With this optimal transcriptome assembly and all relative information from downstream analyses, we have helped to establish foundations for future studies on the mechanisms underlying the invasiveness of non-native<span>&nbsp;</span><i>P</i>.<span>&nbsp;</span><i>australis</i><span>&nbsp;</span>subspecies.</p></div></div>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0280354","usgsCitation":"Tao, F., Fan, C., Liu, Y., Sivakumar, S., Kowalski, K., and Golenberg, E.M., 2023, Optimization and application of non-native Phragmites australis transcriptome assemblies: PLoS ONE, v. 18, no. 1, e0280354, 28 p., https://doi.org/10.1371/journal.pone.0280354.","productDescription":"e0280354, 28 p.","ipdsId":"IP-132748","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":444731,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0280354","text":"Publisher Index Page"},{"id":435490,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NRU97T","text":"USGS data release","linkHelpText":"Phragmites australis Transcriptome Assembly Optimization"},{"id":414808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"1","edition":"]","noUsgsAuthors":false,"publicationDate":"2023-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Tao, Feng","contributorId":303686,"corporation":false,"usgs":false,"family":"Tao","given":"Feng","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":867786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fan, Chuanzhu","contributorId":303687,"corporation":false,"usgs":false,"family":"Fan","given":"Chuanzhu","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":867787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Yimin","contributorId":303688,"corporation":false,"usgs":false,"family":"Liu","given":"Yimin","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":867788,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sivakumar, Subashini","contributorId":303689,"corporation":false,"usgs":false,"family":"Sivakumar","given":"Subashini","email":"","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":867789,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kowalski, Kurt P. 0000-0002-8424-4701 kkowalski@usgs.gov","orcid":"https://orcid.org/0000-0002-8424-4701","contributorId":3768,"corporation":false,"usgs":true,"family":"Kowalski","given":"Kurt P.","email":"kkowalski@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":867790,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Golenberg, Edward M","contributorId":303690,"corporation":false,"usgs":false,"family":"Golenberg","given":"Edward","email":"","middleInitial":"M","affiliations":[{"id":7147,"text":"Wayne State University","active":true,"usgs":false}],"preferred":false,"id":867791,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70239880,"text":"70239880 - 2023 - Damage amplification during repetitive seismic waves in mechanically loaded rocks","interactions":[],"lastModifiedDate":"2023-01-24T12:38:52.071506","indexId":"70239880","displayToPublicDate":"2023-01-23T06:37:46","publicationYear":"2023","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":"Damage amplification during repetitive seismic waves in mechanically loaded rocks","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section c-article-content-visibility\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Cycles of stress build-up and release are inherent to tectonically active planets. Such stress oscillations impart strain and damage, prompting mechanically loaded rocks and materials to fail. Here, we investigate, under uniaxial conditions, damage accumulation and weakening caused by time-dependent creep (at 60, 65, and 70% of the rocks’ expected failure stress) and repeating stress oscillations (of ± 2.5, 5.0 or 7.5% of the creep load), simulating earthquakes at a shaking frequency of ~ 1.3&nbsp;Hz in volcanic rocks. The results show that stress oscillations impart more damage than constant loads, occasionally prompting sample failure. The magnitudes of the creep stresses and stress oscillations correlate with the mechanical responses of our porphyritic andesites, implicating progressive microcracking as the cause of permanent inelastic strain. Microstructural investigation reveals longer fractures and higher fracture density in the post-experimental rock. We deconvolve the inelastic strain signal caused by creep deformation to quantify the amount of damage imparted by each individual oscillation event, showing that the magnitude of strain is generally largest with the first few oscillations; in instances where pre-existing damage and/or the oscillations’ amplitude favour the coalescence of micro-cracks towards system scale failure, the strain signal recorded shows a sharp increase as the number of oscillations increases, regardless of the creep condition. We conclude that repetitive stress oscillations during earthquakes can amplify the amount of damage in otherwise mechanically loaded materials, thus accentuating their weakening, a process that may affect natural or engineered structures. We specifically discuss volcanic scenarios without wholesale failure, where stress oscillations may generate damage, which could, for example, alter pore fluid pathways, modify stress distribution and affect future vulnerability to rupture and associated hazards.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41598-022-26721-x","usgsCitation":"Lamur, A., Kendrick, J.E., Schaefer, L.N., Lavallee, Y., and Kennedy, B.M., 2023, Damage amplification during repetitive seismic waves in mechanically loaded rocks: Scientific Reports, v. 13, 1271, 15 p., https://doi.org/10.1038/s41598-022-26721-x.","productDescription":"1271, 15 p.","ipdsId":"IP-142549","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":444740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-26721-x","text":"Publisher Index Page"},{"id":412273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2023-01-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamur, Anthony 0000-0002-9977-0085","orcid":"https://orcid.org/0000-0002-9977-0085","contributorId":301158,"corporation":false,"usgs":false,"family":"Lamur","given":"Anthony","email":"","affiliations":[{"id":47800,"text":"Ludwig Maximilian University of Munich","active":true,"usgs":false}],"preferred":false,"id":862258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendrick, Jackie E. 0000-0001-5106-3587","orcid":"https://orcid.org/0000-0001-5106-3587","contributorId":301159,"corporation":false,"usgs":false,"family":"Kendrick","given":"Jackie","email":"","middleInitial":"E.","affiliations":[{"id":47800,"text":"Ludwig Maximilian University of Munich","active":true,"usgs":false}],"preferred":false,"id":862259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Lauren N. 0000-0003-3216-7983","orcid":"https://orcid.org/0000-0003-3216-7983","contributorId":241997,"corporation":false,"usgs":true,"family":"Schaefer","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":862260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lavallee, Yan 0000-0003-4766-5758","orcid":"https://orcid.org/0000-0003-4766-5758","contributorId":301160,"corporation":false,"usgs":false,"family":"Lavallee","given":"Yan","email":"","affiliations":[{"id":47800,"text":"Ludwig Maximilian University of Munich","active":true,"usgs":false}],"preferred":false,"id":862261,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Ben M. 0000-0001-7235-6493","orcid":"https://orcid.org/0000-0001-7235-6493","contributorId":270276,"corporation":false,"usgs":false,"family":"Kennedy","given":"Ben","email":"","middleInitial":"M.","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":862262,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70239884,"text":"70239884 - 2023 - Bioenergetics model for the nonnative Redside Shiner","interactions":[],"lastModifiedDate":"2023-03-01T17:13:23.018047","indexId":"70239884","displayToPublicDate":"2023-01-22T06:33:48","publicationYear":"2023","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":"Bioenergetics model for the nonnative Redside Shiner","docAbstract":"<h3 id=\"tafs10392-sec-0101-title\" class=\"article-section__sub-title section1\">Objective</h3><p>Redside Shiner<span>&nbsp;</span><i>Richardsonius balteatus</i><span>&nbsp;</span>has expanded from its native range in the Pacific Northwest region of North America to establish populations in six other western states. This expansion has fueled concerns regarding competition between Redside Shiner and native species, including salmonids. We developed a bioenergetic model for Redside Shiner, providing a powerful tool to quantify its trophic role in invaded ecosystems and evaluate potential impacts on native species.</p><h3 id=\"tafs10392-sec-0102-title\" class=\"article-section__sub-title section1\">Methods</h3><p>Mass- and temperature-dependent functions for consumption and respiration were fit based on controlled laboratory experiments of maximum consumption rates and routine metabolic rates using intermittent-flow respirometry, across a range of fish sizes (0.6–27.3&nbsp;g) and temperatures (5–31°C). Laboratory growth experiments were conducted to corroborate model performance across different temperatures and feeding rates.</p><h3 id=\"tafs10392-sec-0103-title\" class=\"article-section__sub-title section1\">Result</h3><p>Initial bioenergetic simulations of long-term growth experiments indicated large model error for predicted consumption and growth, and deviations from observed responses varied systematically as a function of daily consumption rate (J·g<sup>−1</sup>·d<sup>−1</sup>) and water temperature. A growth rate error correction function was developed and included in the bioenergetics model framework on a daily time step, resulting in decreased absolute model error in all experimental groups. Predicted values from the corrected model were highly correlated with observed values (�2; consumption&nbsp;=&nbsp;0.97, final weight&nbsp;=&nbsp;0.99) and unbiased. These results show that the optimal temperature for Redside Shiner growth (18°C) exceeds that of Pacific salmon<span>&nbsp;</span><i>Oncorhynchus</i><span>&nbsp;</span>spp. by 2–6°C under a scenario of high food availability and moderate food quality.</p><h3 id=\"tafs10392-sec-0104-title\" class=\"article-section__sub-title section1\">Conclusion</h3><p>Consequently, increases in water temperature associated with climate change may favor growth and expansion of Redside Shiner populations, while negatively affecting some salmonids. The bioenergetics model presented here provides the necessary first step in quantifying trophic impacts in sensitive ecosystems where Redside Shiner have invaded or in ecosystems where anadromous salmonid reintroductions are being considered.</p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10392","usgsCitation":"Johnson, R.C., Beauchamp, D., and Olden, J., 2023, Bioenergetics model for the nonnative Redside Shiner: Transactions of the American Fisheries Society, v. 152, no. 1, p. 94-113, https://doi.org/10.1002/tafs.10392.","productDescription":"20 p.","startPage":"94","endPage":"113","ipdsId":"IP-140159","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":444746,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10392","text":"Publisher Index Page"},{"id":435494,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NAIACL","text":"USGS data release","linkHelpText":"Data used to parameterize and evaluate a bioenergetics model for Redside Shiner (Richardsonius balteatus)"},{"id":412271,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"152","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Rachelle Carina 0000-0003-1480-4088","orcid":"https://orcid.org/0000-0003-1480-4088","contributorId":241962,"corporation":false,"usgs":true,"family":"Johnson","given":"Rachelle","email":"","middleInitial":"Carina","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":862274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, David 0000-0002-3592-8381","orcid":"https://orcid.org/0000-0002-3592-8381","contributorId":217816,"corporation":false,"usgs":true,"family":"Beauchamp","given":"David","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":862275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olden, Julian D.","contributorId":202893,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":862276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70266472,"text":"70266472 - 2023 - Habitat selection of a migratory freshwater fish in response to seasonal hypoxia as revealed by acoustic telemetry","interactions":[],"lastModifiedDate":"2025-05-07T18:10:32.226189","indexId":"70266472","displayToPublicDate":"2023-01-21T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Habitat selection of a migratory freshwater fish in response to seasonal hypoxia as revealed by acoustic telemetry","docAbstract":"<p>Adaptive efforts to achieve water quality objectives by modifying nutrient loading can have attendant impacts on fish habitats and fisheries. Thus, coordinating fishery and water quality management depends on knowledge of fish behavioral responses to habitat change. This study combined acoustic telemetry of fish with water quality modeling to understand how water quality management might impact fishery management. We examined habitat use of a native demersal fish, lake whitefish <i>Coregonus clupeaformis</i>, in Lake Erie. We focused on the summer stratified period when habitat was expected to be most limiting and used a forecast model to predict temperature and oxygen in the hypolimnion when fish were detected. As hypothesized, lake whitefish occupied a subset of available conditions with occupied habitats characterized by a cool, normoxic, hypolimnion. On some occasions fish were detected when the hypolimnion was predicted to be hypoxic, suggesting that fish were either displaced vertically or horizontally into marginal habitats or uncertainty in model predictions was high. Still, when hypolimnetic conditions were hypoxic, fish tended to move toward normoxia as expected, but when initial conditions were cold with high dissolved oxygen, fish movements were toward lower oxygen (but still normoxic) conditions. We also observed a high affinity for fish to remain near the southern shore in eastern Ohio, Pennsylvania, and New York. If current nutrient reduction objectives are achieved and the extent and severity of hypoxia is reduced, an expansion of lake whitefish habitat and distribution may have significance to the spatial regulation of fishing effort in Lake Erie.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.01.004","usgsCitation":"Kraus, R., Cook, H., Faust, M., Schmitt, J., Rowe, M., and Vandergoot, C., 2023, Habitat selection of a migratory freshwater fish in response to seasonal hypoxia as revealed by acoustic telemetry: Journal of Great Lakes Research, v. 49, no. 5, p. 1004-1014, https://doi.org/10.1016/j.jglr.2023.01.004.","productDescription":"11 p.","startPage":"1004","endPage":"1014","ipdsId":"IP-144704","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":485514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, New York, Ohio, Pennsylvania","otherGeospatial":"Lake Erie","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.45746247368997,\n              42.19332204270543\n            ],\n            [\n              -83.58088952321158,\n              41.37751990998936\n            ],\n            [\n              -81.36793483137687,\n              41.36610477953545\n            ],\n            [\n              -79.12723694634781,\n              42.41574902379864\n            ],\n            [\n              -78.7500162167698,\n              43.007471194229566\n            ],\n            [\n              -81.13424345938826,\n              42.76252432461877\n            ],\n            [\n              -82.2940150129951,\n              42.35073159163453\n            ],\n            [\n              -83.45746247368997,\n              42.19332204270543\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"49","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kraus, Richard 0000-0003-4494-1841","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":216548,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":936069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, H. 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