{"pageNumber":"195","pageRowStart":"4850","pageSize":"25","recordCount":41062,"records":[{"id":70240948,"text":"70240948 - 2022 - Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds","interactions":[],"lastModifiedDate":"2023-03-02T13:08:41.273057","indexId":"70240948","displayToPublicDate":"2022-02-16T07:06:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1023,"text":"Biological Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds","docAbstract":"

Mercury contamination is a major threat to the global environment, and is still increasing in some regions despite international regulations. The methylated form of mercury is hazardous to biota, yet its sublethal effects are difficult to detect in wildlife. Body condition can vary in response to stressors, but previous studies have shown mixed effects of mercury on body condition in wildlife. Using birds as study organisms, we provide the first quantitative synthesis of the effect of mercury on body condition in animals. In addition, we explored the influence of intrinsic, extrinsic and methodological factors potentially explaining cross-study heterogeneity in results. We considered experimental and correlative studies carried out in adult birds and chicks, and mercury exposure inferred from blood and feathers. Most experimental investigations (90%) showed a significant relationship between mercury concentrations and body condition. Experimental exposure to mercury disrupted nutrient (fat) metabolism, metabolic rates, and food intake, resulting in either positive or negative associations with body condition. Correlative studies also showed either positive or negative associations, of which only 14% were statistically significant. Therefore, the overall effect of mercury concentrations on body condition was null in both experimental (estimate ± SE = 0.262 ± 0.309, 20 effect sizes, five species) and correlative studies (−0.011 ± 0.020, 315 effect sizes, 145 species). The single and interactive effects of age class and tissue type were accounted for in meta-analytic models of the correlative data set, since chicks and adults, as well as blood and feathers, are known to behave differently in terms of mercury accumulation and health effects. Of the 15 moderators tested, only wintering status explained cross-study heterogeneity in the correlative data set: free-ranging wintering birds were more likely to show a negative association between mercury and body condition. However, wintering effect sizes were limited to passerines, further studies should thus confirm this trend in other taxa. Collectively, our results suggest that (i) effects of mercury on body condition are weak and mostly detectable under controlled conditions, and (ii) body condition indices are unreliable indicators of mercury sublethal effects in the wild. Food availability, feeding rates and other sources of variation that are challenging to quantify likely confound the association between mercury and body condition in natura. Future studies could explore the metabolic effects of mercury further using designs that allow for the estimation and/or manipulation of food intake in both wild and captive birds, especially in under-represented life-history stages such as migration and overwintering.

","language":"English","publisher":"Wiley","doi":"10.1111/brv.12840","usgsCitation":"Carravieri, A., Vincze, O., Bustamante, P., Ackerman, J.T., Adams, E.M., Angelier, F., Chastel, O., Cherel, Y., Gilg, O., Golubova, E., Kitaysky, A., Luff, K., Seewagen, C.L., Strom, H., Will, A.P., Yannic, G., Giraudeau, M., and Fort, J., 2022, Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds: Biological Reviews, v. 97, no. 4, p. 1253-1271, https://doi.org/10.1111/brv.12840.","productDescription":"19 p.","startPage":"1253","endPage":"1271","ipdsId":"IP-131356","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":448781,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/brv.12840","text":"Publisher Index Page"},{"id":413610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Carravieri, Alice 0000-0002-7740-843X","orcid":"https://orcid.org/0000-0002-7740-843X","contributorId":302760,"corporation":false,"usgs":false,"family":"Carravieri","given":"Alice","email":"","affiliations":[{"id":65546,"text":"Littoral Environnement et Sociétés","active":true,"usgs":false}],"preferred":false,"id":865390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vincze, Orsolya 0000-0001-5789-2124","orcid":"https://orcid.org/0000-0001-5789-2124","contributorId":302761,"corporation":false,"usgs":false,"family":"Vincze","given":"Orsolya","email":"","affiliations":[{"id":65547,"text":"Hungarian Department of Biology and Ecology","active":true,"usgs":false}],"preferred":false,"id":865391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bustamante, Paco","contributorId":201551,"corporation":false,"usgs":false,"family":"Bustamante","given":"Paco","email":"","affiliations":[{"id":36199,"text":"La Rochelle University","active":true,"usgs":false}],"preferred":false,"id":865392,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":865393,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Evan M.","contributorId":139994,"corporation":false,"usgs":false,"family":"Adams","given":"Evan","email":"","middleInitial":"M.","affiliations":[{"id":6928,"text":"BioDiversity Research Institute, Gorham, ME 04038","active":true,"usgs":false}],"preferred":false,"id":865394,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Angelier, Frederic","contributorId":293655,"corporation":false,"usgs":false,"family":"Angelier","given":"Frederic","email":"","affiliations":[{"id":63358,"text":"Centre d'Etudes Biologiques de Chizé (CEBC), UMR 7372 CNRS- La Rochelle Université, 79360 Villiers-en-Bois, France","active":true,"usgs":false}],"preferred":false,"id":865395,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chastel, Olivier","contributorId":293653,"corporation":false,"usgs":false,"family":"Chastel","given":"Olivier","email":"","affiliations":[{"id":63355,"text":"Centre d'Etudes Biologiques de Chizé (CEBC), UMR 7372 CNRS- La Rochelle Université, 79360 Villiers-en-Bois, France.","active":true,"usgs":false}],"preferred":false,"id":865396,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cherel, Yves 0000-0001-9469-9489","orcid":"https://orcid.org/0000-0001-9469-9489","contributorId":267388,"corporation":false,"usgs":false,"family":"Cherel","given":"Yves","email":"","affiliations":[{"id":55487,"text":"La Rochelle University, Villiers-en-Bois, France","active":true,"usgs":false}],"preferred":false,"id":865397,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gilg, Olivier","contributorId":169342,"corporation":false,"usgs":false,"family":"Gilg","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":865398,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Golubova, Elena","contributorId":293663,"corporation":false,"usgs":false,"family":"Golubova","given":"Elena","email":"","affiliations":[{"id":63366,"text":"Laboratory of Ornithology, Institute of Biological Problems of the North, RU-685000 Magadan, Portovaya Str., 18, Russia","active":true,"usgs":false}],"preferred":false,"id":865399,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kitaysky, Alexander","contributorId":221846,"corporation":false,"usgs":false,"family":"Kitaysky","given":"Alexander","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":865400,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Luff, Katelyn 0000-0002-8897-5325","orcid":"https://orcid.org/0000-0002-8897-5325","contributorId":302762,"corporation":false,"usgs":false,"family":"Luff","given":"Katelyn","email":"","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":865401,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Seewagen, Chad L.","contributorId":302763,"corporation":false,"usgs":false,"family":"Seewagen","given":"Chad","email":"","middleInitial":"L.","affiliations":[{"id":65548,"text":"Great Hollow Nature Preserve and Ecological Research Center","active":true,"usgs":false}],"preferred":false,"id":865402,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Strom, Hallvard","contributorId":293678,"corporation":false,"usgs":false,"family":"Strom","given":"Hallvard","email":"","affiliations":[{"id":63362,"text":"Norwegian Polar Institute, Fram center, 9296 Tromsø, Norway","active":true,"usgs":false}],"preferred":false,"id":865403,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Will, Alexis P.","contributorId":302764,"corporation":false,"usgs":false,"family":"Will","given":"Alexis","email":"","middleInitial":"P.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":865404,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Yannic, Glenn","contributorId":293683,"corporation":false,"usgs":false,"family":"Yannic","given":"Glenn","email":"","affiliations":[{"id":63378,"text":"Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, 38000 Grenoble, France","active":true,"usgs":false}],"preferred":false,"id":865405,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Giraudeau, Mathieu","contributorId":302765,"corporation":false,"usgs":false,"family":"Giraudeau","given":"Mathieu","email":"","affiliations":[{"id":65546,"text":"Littoral Environnement et Sociétés","active":true,"usgs":false}],"preferred":false,"id":865406,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Fort, Jerome","contributorId":23344,"corporation":false,"usgs":false,"family":"Fort","given":"Jerome","email":"","affiliations":[],"preferred":false,"id":865407,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70230279,"text":"70230279 - 2022 - Hydrologic modification and channel evolution degrades connectivity on the Atchafalaya River floodplain","interactions":[],"lastModifiedDate":"2022-06-16T15:25:44.019773","indexId":"70230279","displayToPublicDate":"2022-02-15T08:55:12","publicationYear":"2022","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":"Hydrologic modification and channel evolution degrades connectivity on the Atchafalaya River floodplain","docAbstract":"

The Atchafalaya River Basin is the largest remaining forested wetland in the contiguous United States. Since 1960, dredging and channel erosion in the Basin have resulted in changes to the hydrologic connectivity that have not been quantified. Analyses were conducted to determine the hydraulic and geomorphic factors that have changed since discharge became controlled that may have decreased river/floodplain connectivity. We examined: (1) stage/discharge relationships from 1960 to 2014; (2) hydroperiods across the floodplain; (3) discharge distribution to the floodplain by comparing discharge measurements from 1959–1968 to 2005–2012; and (4) channel cross-sections and floodplain elevations. Our results indicate that much of the floodplain no longer receives headwater discharge (upstream to downstream, > 200 km2) or receives too little discharge to alleviate stagnancy and hypoxia in the forested wetland at lower stages. Large portions of the Basin (400 km2) have low water levels controlled by channel geomorphology and sea-level rise that inundate the forested floodplain for more than 50% of the calendar year. This extended duration of inundation contributes to hypoxia and likely reduces nutrient retention. The confinement of discharge to a large efficient channel compromises the ability of this system to respond to sea-level rise and subsidence. This study provides insight to the effects of flood management projects along Coastal Plain rivers and deltas.

","language":"English","publisher":"Wiley","doi":"10.1002/esp.5347","usgsCitation":"Kroes, D., Demas, C.R., Allen, Y., Day, R., Roberts, S.W., and Varisco, J., 2022, Hydrologic modification and channel evolution degrades connectivity on the Atchafalaya River floodplain: Earth Surface Processes and Landforms, v. 47, no. 7, p. 1790-1807, https://doi.org/10.1002/esp.5347.","productDescription":"18 p.","startPage":"1790","endPage":"1807","ipdsId":"IP-094587","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":448787,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5347","text":"Publisher Index Page"},{"id":435966,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94GULXE","text":"USGS data release","linkHelpText":"Mean bed elevations of waterbodies on the Atchafalaya River floodplain"},{"id":398209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Atchafalaya River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.09814453125,\n 29.36302703778376\n ],\n [\n -90.977783203125,\n 29.36302703778376\n ],\n [\n -90.977783203125,\n 31.956823015897207\n ],\n [\n -93.09814453125,\n 31.956823015897207\n ],\n [\n -93.09814453125,\n 29.36302703778376\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"7","noUsgsAuthors":false,"publicationDate":"2022-03-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":839850,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demas, Charles R","contributorId":289813,"corporation":false,"usgs":false,"family":"Demas","given":"Charles","email":"","middleInitial":"R","affiliations":[{"id":38437,"text":"Retired, U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":839851,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Yvonne A.","contributorId":289815,"corporation":false,"usgs":false,"family":"Allen","given":"Yvonne A.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":839852,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Day, Richard 0000-0002-5959-7054","orcid":"https://orcid.org/0000-0002-5959-7054","contributorId":222817,"corporation":false,"usgs":true,"family":"Day","given":"Richard","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":839853,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Steve W","contributorId":289819,"corporation":false,"usgs":false,"family":"Roberts","given":"Steve","email":"","middleInitial":"W","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":839854,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Varisco, Jeff","contributorId":289821,"corporation":false,"usgs":false,"family":"Varisco","given":"Jeff","email":"","affiliations":[{"id":12537,"text":"USACE","active":true,"usgs":false}],"preferred":false,"id":839855,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70241842,"text":"70241842 - 2022 - Molecular mechanisms of solid bitumen and vitrinite reflectance suppression explored using hydrous pyrolysis of artificial source rock","interactions":[],"lastModifiedDate":"2023-03-29T12:05:04.630383","indexId":"70241842","displayToPublicDate":"2022-02-15T07:01:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Molecular mechanisms of solid bitumen and vitrinite reflectance suppression explored using hydrous pyrolysis of artificial source rock","docAbstract":"

The most commonly used parameter for thermal maturity calibration in basin modelling is mean random vitrinite reflectance (Ro). However, Ro suppression has been noted in samples containing a high proportion of liptinite macerals. This phenomenon has been demonstrated empirically using hydrous pyrolysis of artificial source rock containing various proportions of thermally immature Wyodak-Anderson coal and liptinite-rich kerogen from the Parachute Creek Member of the Green River Formation. Analysis of samples pyrolyzed at 330 °C for 72 h demonstrates that Ro values of both vitrinite and solid bitumen are suppressed in rocks containing liptinite-rich kerogen. Raman and micro-Fourier transform infrared (µ-FTIR) analyses were performed to investigate the mechanisms of suppression. Raman maturity proxies show decreased aromaticity in samples with suppressed Ro, particularly in solid bitumen, with aromaticity decreasing as the proportion of liptinite increases. The µ-FTIR proxy for aliphatic chain length and/or branching ratio is static in solid bitumen, yet increases slightly in vitrinite as the liptinite proportion increases. These spectroscopic results suggest slightly different suppression mechanisms for vitrinite and solid bitumen, with reduced C\"singleC bond cleavage and marginally reduced aromaticity in vitrinite with suppressed Ro, and strongly reduced aromaticity and C\"singleC bond cleavage in solid bitumen with suppressed Ro. These results support the hypothesis that the generation of free radicals during maturation slows aromatization and highlight the disadvantages of using solid bitumen Ro for maturity calibration in liptinite-rich samples. Furthermore, our results indicate that use of Raman data obtained from liptinite-rich samples may also result in suppressed maturity indicators, particularly if the macerals are not identified prior to analysis.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2022.104371","usgsCitation":"Sanders, M.M., Jubb, A., Hackley, P.C., and Peters, K., 2022, Molecular mechanisms of solid bitumen and vitrinite reflectance suppression explored using hydrous pyrolysis of artificial source rock: Organic Geochemistry, v. 165, 104371, 12 p., https://doi.org/10.1016/j.orggeochem.2022.104371.","productDescription":"104371, 12 p.","ipdsId":"IP-134667","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":506102,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.orggeochem.2022.104371","text":"Publisher Index Page"},{"id":414885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sanders, Margaret M. 0000-0003-3505-874X","orcid":"https://orcid.org/0000-0003-3505-874X","contributorId":248709,"corporation":false,"usgs":true,"family":"Sanders","given":"Margaret","email":"","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":867904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":867905,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":867906,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Kenneth E.","contributorId":10897,"corporation":false,"usgs":true,"family":"Peters","given":"Kenneth E.","affiliations":[],"preferred":false,"id":867907,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230491,"text":"70230491 - 2022 - Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas","interactions":[],"lastModifiedDate":"2022-04-14T11:49:12.307184","indexId":"70230491","displayToPublicDate":"2022-02-15T06:48:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10551,"text":"Vegetation Classification and Survey","active":true,"publicationSubtype":{"id":10}},"title":"Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas","docAbstract":"

Aims: Natural resource management and biodiversity conservation rely on inventories of vegetation that span multiple management or political jurisdictions. However, while remote sensing data and analytical tools have enabled production of maps at increasing spatial resolution and reliability, there are limited examples where national or continental-scaled maps are produced to represent vegetation at high thematic detail. We illustrate two examples that have bridged the gap between traditional land cover mapping and modern vegetation classification. Study area: Our two case studies include national (USA) and continental (North and South America) vegetation and land cover mapping. These studies span conditions from subpolar to tropical latitudes of the Americas. Methods: Both case studies used a supervised modeling approach with the International Vegetation Classification (IVC) to produce maps that provide for greater thematic detail. Georeferenced locations for these vegetation types are used by machine learning algorithms to train a predictive model and generate a distribution map. Results: The USA LANDFIRE (Landscape Fire and Resource Management Planning Tools Project) case study illustrates how a history of vegetation-based classification and availability of key inputs can come together to generate standard map products covering more than 9.8 million km2 that are unsurpassed anywhere in the world in terms of spatial and thematic resolution. That being said, it also remains clear that mapping at the thematic resolution of the IVC Group and finer resolution require very large and spatially balanced inputs of georeferenced samples. Even with extensive prior data collection efforts, these remain a key limitation. The NatureServe effort for the Americas - encompassing 22% of the global land surface - demonstrates methods and outputs suitable for worldwide application at continental scales. Conclusions: Continued collection of input data used in the case studies could enable mapping at these spatial and thematic resolutions around the globe.

","language":"English","publisher":"Pensoft","doi":"10.3897/VCS.67537","usgsCitation":"Comer, P.J., Hak, J.C., Dockter, D., and Smith, J., 2022, Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas: Vegetation Classification and Survey, p. 29-43, https://doi.org/10.3897/VCS.67537.","productDescription":"15 p.","startPage":"29","endPage":"43","ipdsId":"IP-128344","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":448793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3897/vcs.67537","text":"Publisher Index Page"},{"id":398727,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2022-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Comer, Patrick J. 0000-0002-5869-2105","orcid":"https://orcid.org/0000-0002-5869-2105","contributorId":258190,"corporation":false,"usgs":false,"family":"Comer","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":840550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hak, Jon C","contributorId":290233,"corporation":false,"usgs":false,"family":"Hak","given":"Jon","email":"","middleInitial":"C","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":840551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dockter, Daryn 0000-0003-1914-8657","orcid":"https://orcid.org/0000-0003-1914-8657","contributorId":216392,"corporation":false,"usgs":false,"family":"Dockter","given":"Daryn","affiliations":[],"preferred":false,"id":840552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Jim","contributorId":191054,"corporation":false,"usgs":false,"family":"Smith","given":"Jim","email":"","affiliations":[],"preferred":false,"id":840553,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237179,"text":"70237179 - 2022 - High abundance of a single taxon (amphipods) predicts aquatic macrophyte biodiversity in prairie wetlands","interactions":[],"lastModifiedDate":"2022-10-04T11:36:17.269282","indexId":"70237179","displayToPublicDate":"2022-02-15T06:33:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"High abundance of a single taxon (amphipods) predicts aquatic macrophyte biodiversity in prairie wetlands","docAbstract":"

Conservation programs often aim to protect the abundance of individual species and biodiversity simultaneously. We quantified relations between amphipod densities and aquatic macrophyte (large plants and algae) diversity to test a hypothesis that biodiversity can support high abundance of a single taxonomic group. Amphipods (Gammarus lacustris and Hyalella azteca) are key forage for waterfowl and are declining in the Prairie Pothole Region of North America. We sampled a large gradient of amphipod densities (0–7050 amphipods/m3) in 49 semi-permanent wetlands, and 50% of the study wetlands had high amphipod densities (> 500 amphipods/m3). Generalized linear models revealed G. lacustris and H. azteca densities increased exponentially with macrophyte diversity indices. Further, H. azteca densities were greatest at moderate levels of submersed vegetation biomass. Community analyses showed both amphipod species were positively associated with diverse macrophyte assemblages and negatively associated with high coverage of cattails (Typha spp.), a taxon that creates monotypic stands, as well as bladderwort (Utricularia spp.), a carnivorous plant. Our results indicate that amphipods could be used as an umbrella species for protecting diverse macrophyte communities in semi-permanent and permanent wetlands of North America’s Prairie Pothole Region.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1007/s10531-022-02379-9","usgsCitation":"Larson, D.M., DeJong, D., Anteau, M.J., Fitzpatrick, M.J., Keith, B.R., Schilling, E.G., and Thoele, B., 2022, High abundance of a single taxon (amphipods) predicts aquatic macrophyte biodiversity in prairie wetlands: Conservation Biology, v. 31, p. 1073-1093, https://doi.org/10.1007/s10531-022-02379-9.","productDescription":"21 p.","startPage":"1073","endPage":"1093","ipdsId":"IP-125387","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":448796,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10531-022-02379-9","text":"Publisher Index Page"},{"id":435968,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9INBET3","text":"USGS data release","linkHelpText":"Macrophyte and amphipod surveys in prairie wetlands of Minnesota in year 2019"},{"id":407850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","noUsgsAuthors":false,"publicationDate":"2022-02-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Danelle M. 0000-0001-6349-6267","orcid":"https://orcid.org/0000-0001-6349-6267","contributorId":228838,"corporation":false,"usgs":true,"family":"Larson","given":"Danelle","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":853568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeJong, Demmey","contributorId":297160,"corporation":false,"usgs":false,"family":"DeJong","given":"Demmey","email":"","affiliations":[{"id":64304,"text":"Augsburg University","active":true,"usgs":false}],"preferred":false,"id":853569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":853570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fitzpatrick, Megan J.","contributorId":290649,"corporation":false,"usgs":false,"family":"Fitzpatrick","given":"Megan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":853571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keith, Breanna R.","contributorId":290647,"corporation":false,"usgs":false,"family":"Keith","given":"Breanna","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":853572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schilling, Emily G. 0000-0001-9920-4908","orcid":"https://orcid.org/0000-0001-9920-4908","contributorId":297161,"corporation":false,"usgs":false,"family":"Schilling","given":"Emily","email":"","middleInitial":"G.","affiliations":[{"id":64304,"text":"Augsburg University","active":true,"usgs":false}],"preferred":false,"id":853573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thoele, Barry","contributorId":297162,"corporation":false,"usgs":false,"family":"Thoele","given":"Barry","email":"","affiliations":[{"id":64306,"text":"Lincoln Bait LCC","active":true,"usgs":false}],"preferred":false,"id":853574,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238946,"text":"70238946 - 2022 - Fishway Entrance Palisade","interactions":[],"lastModifiedDate":"2023-01-10T16:06:21.874488","indexId":"70238946","displayToPublicDate":"2022-02-14T10:01:03","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9958,"text":"Final Technical Report","active":true,"publicationSubtype":{"id":1}},"title":"Fishway Entrance Palisade","docAbstract":"This technical report summarizes the work that was conducted by the University of Massachusetts Amherst and the United States Geological Survey (USGS), along with other project partners, on the Fishway Entrance Palisade (EP), a projected funded through the Department of Energy’s (DOE) funding opportunity titled ‘Innovative Solutions for Fish Passage at Hydropower Dams’ (DE‐FOA‐0001662). The period of performance ranged from September 1, 2018 through September 30, 2021. \n\nThe EP is a novel fish passage engineering technology designed to provide more favorable entry conditions for fish and to reduce costs relative to conventional fishway auxiliary water systems (AWS). The EP project has four primary components.\n\nFirst, the Northeast United States Auxiliary Water Systems Database was created (Northeast Fishway Auxiliary Water Systems Database Section). The database, developed with material provided by the U.S. Fish and Wildlife Service, contains information on fishway type (e.g., lift, Denil, pool and weir) and Auxiliary Water System (AWS) details (e.g., water conveyance method, diffuser type) for 60 hydroelectric sites in the region. Findings indicate that nearly 4 out of every 10 fishway in the region is a fish lift and approximately 1 out of every 4 is a Denil ladder. The remainder are a mix of vertical slot fishways, pool and weirs, and Ice Harbor fishways. Furthermore, over half of all AWS systems use floor diffusers to discharge the auxiliary (or attraction) water into the entrance of a fishway, whereas only 14% use wall diffusers.\n\nSecond, limited experiments on a conventional AWS with live, actively migrating fish were conducted at the USGS Easter Ecological Science Center (EESC) S.O. Conte Research Laboratory (Conventional Auxiliary Water System Experiments Section). This study determined how water velocity through a wall diffuser, without turning vanes or timber baffles to distribute the flow, affects the behavior and passage of adult American shad, a conservative surrogate species for migratory fish on the East Coast. Two gross diffuser velocity treatments were examined, 0.5 ft/s and 1.0 ft/s. These wall diffuser velocities represented current (0.5 ft/s) and past (1.0 ft/s) design criteria guidelines set forth by the USFWS North Atlantic-Appalachian Region (Rojas 2020; USFWS 2019). Six trials with a total of 151 American Shad were conducted in June of 2019 for the two treatments. \n\nNo differences in American shad passage efficiency were discovered between the two treatments, while approximately 3 in every 4 attempts were successful at passing the diffuser. While these results may appear to indicate that the generally accepted gross wall diffuser velocity criteria for American shad of 0.5 ft/s could be safely increased to 1.0 ft/s, further analysis is warranted. Furthermore, it is unknown how other migratory and resident fish species that traverse these structures would be impacted by such a change. \n\nStudying the wall diffuser hydraulics led to an important AWS observation. Without turning vanes or timber baffles in this study, doubling the diffuser area was insufficient at producing the type of flow field change one may expect by halving the gross diffuser velocity. Instead, the flow fields throughout each treatments study area were similar, which led to similar results in shad performance. This not only highlights the importance of installing flow guidance devices like turning vanes, but also to the importance of properly maintaining them, which can be costly.\n\nThird, more expansive experiments on the novel EP were conducted in the spring of 2019 and 2021 (Fishway Entrance Palisade Experiments). The goal of this study was to determine how adult American shad responded to a variety of conditions at a full-scale EP. A total of six treatments were examined by changing the average auxiliary channel velocity between 1.0 and 5.0 ft/s in intervals of 1.0 ft/s and by inserting/removing an entrance gate at the opening of the fishway. Thirty trials with a total of 1,273 shad were conducted over the two years.\n\nIn all treatments, at least ~7 out of every 10 fish successfully passed the EP diffuser and swam into the entrance channel within the 3.5-hour long trial, highlighting the general effectiveness of the novel AWS technology. In both study years, lower velocities through the EP diffuser led to increased shad performance, though performance peaked for the 2 ft/s velocity treatment. This treatment condition represents an approximate six-fold increase in gross diffuser velocity relative to conventional auxiliary water systems, which in turn presents opportunities for cost savings (e.g., reduction in diffuser size).\n\nShad performance, in general, was worse in 2019 than in 2021, potentially due to the different run timing when our trials were conducted (2019 trials occurred near the end of the migration season, unlike in 2021). Treatments in 2019 had approximately a 20% reduction in entrance efficiency by the trial end, including a 16.7% drop for the 3 ft/s velocity treatment in 2019 relative to 2021 (the only carryover treatment between years). \n\nLastly, adding an entrance gate caused a significant delay to entry. The time to 25% entry raised ~20 minutes from the near instantaneous 25% entry that was reported for the other treatments conducted in the same year (2021). Though by the end of the 3.5-hour trial, the overall entrance efficiency nearly matched those of the other 2021 treatments.\n\nThe fourth and final component of the EP project was an economic analysis that focused on the cost of attraction and environmental flows (Modeling Power Generation Losses Due to Environmental and Fish Passage Attraction Flows at a Run-Of-River Hydroelectric Operation in the Northeast). The study assessed the economic impact of meeting environmental flow requirements at a representative hydroelectric facility and fish lift in the Northeast. An initial finding of the study was that there is a paucity of published data on the costs of meeting attraction and environmental flows. This is due, in part, to the proprietary nature of this data. To explore the costs associated with these flows, three types of environmental flows were assessed: upstream fishway attraction flows, downstream fishway attraction flows, and habitat maintenance minimum flows. A physics-based model was developed and calibrated with three years of hourly generation and flow data as inputs. Gage flow inputs were adjusted and used to calculate power generated. To address hydrologic variability, the model was executed to simulate 30 years of historical flows.\n\nResults indicate that both interannual and seasonal climatic factors impact the costs of meeting environmental flow requirements. Generation potential is most strongly curtailed during dry years in terms of maximizing the capacity factor (the percent of time a plant generates at capacity). Dry years, and especially dry summers, have the most significant costs associated with mitigation flows. Of the three types of flows, habitat flows are most costly in terms of power production, followed by upstream attraction flows. Downstream attraction flows are least costly. This finding is the likely result of differences in both flow rates and duration of the seasonal requirement for each flow. Overall, environmental flows represented a 2-12% loss in annual generation, but losses during a dry summer can reach over 20%.","language":"English","publisher":"U.S. Department of Energy","doi":"10.2172/1905243","usgsCitation":"Mulligan, K., Palmer, R., Towler, B., Haro, A., Lake, B., Rojas, M., and Lotter, E., 2022, Fishway Entrance Palisade: Final Technical Report, 23 p., https://doi.org/10.2172/1905243.","productDescription":"23 p.","ipdsId":"IP-138003","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":448800,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1905243","text":"External Repository"},{"id":411632,"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 -67.05182598949801,\n 44.89319311674552\n ],\n [\n -68.3175817931259,\n 47.33465807108087\n ],\n [\n -69.24621769928491,\n 47.283640086042396\n ],\n [\n -70.6255546394362,\n 45.53467504444376\n ],\n [\n -73.37060956424577,\n 44.92914333096371\n ],\n [\n -83.12438010438365,\n 34.6176223177726\n ],\n [\n -80.40129683431417,\n 31.8360293402377\n ],\n [\n -75.74355199471707,\n 35.10791041480914\n ],\n [\n -75.21833415636709,\n 38.125898555273295\n ],\n [\n -72.87164643954584,\n 40.72488283550473\n ],\n [\n -69.8736057821464,\n 41.750002105411085\n ],\n [\n -70.47472444522607,\n 43.094355406979275\n ],\n [\n -67.05182598949801,\n 44.89319311674552\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mulligan, Kevin B. 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmer, Richard","contributorId":202903,"corporation":false,"usgs":false,"family":"Palmer","given":"Richard","affiliations":[],"preferred":false,"id":859309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Towler, Brett","contributorId":141164,"corporation":false,"usgs":false,"family":"Towler","given":"Brett","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":859310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haro, Alexander 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":139198,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lake, Bjorn","contributorId":300039,"corporation":false,"usgs":false,"family":"Lake","given":"Bjorn","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":859312,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rojas, Marcia","contributorId":300040,"corporation":false,"usgs":false,"family":"Rojas","given":"Marcia","email":"","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":859313,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lotter, Elizabeth","contributorId":300041,"corporation":false,"usgs":false,"family":"Lotter","given":"Elizabeth","email":"","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":859314,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228674,"text":"70228674 - 2022 - A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level","interactions":[],"lastModifiedDate":"2022-02-16T15:22:51.655089","indexId":"70228674","displayToPublicDate":"2022-02-14T09:19:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5542,"text":"Advances in Statistical Climatology, Meteorology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level","docAbstract":"

Robust, proxy-based reconstructions of relative sea-level (RSL) change are critical to distinguishing the processes that drive spatial and temporal sea-level variability. The relationships between individual proxies and RSL can be complex and are often poorly represented by traditional methods that assume Gaussian likelihood distributions. We develop a new statistical framework to estimate past RSL change based on nonparametric, empirical modern distributions of proxies in relation to RSL, applying the framework to corals and mangroves as an illustrative example. We validate our model by comparing its skill in reconstructing RSL and rates of change to two previous RSL models using synthetic time-series datasets based on Holocene sea-level data from South Florida. The new framework results in lower bias, better model fit, and greater accuracy and precision than the two previous RSL models. We also perform sensitivity tests using sea-level scenarios based on two periods of interest – meltwater pulses (MWPs) and the Holocene – to analyze the sensitivity of the statistical reconstructions to the quantity and precision of proxy data; we define high-precision indicators, such as mangroves and the reef-crest coral Acropora palmata, with 2σ vertical uncertainties within ± 3 m and lower-precision indicators, such as Orbicella spp., with 2σ vertical uncertainties within ± 10 m. For reconstructing rapid rates of change in RSL of up to ∼ 40 m kyr−1, such as those that may have characterized MWPs during deglacial periods, we find that employing the nonparametric model with 5 to 10 high-precision data points per kiloyear enables us to constrain rates to within ± 3 m kyr−1 (1σ). For reconstructing RSL with rates of up to ∼ 15 m kyr−1, as observed during the Holocene, we conclude that employing the model with 5 to 10 high-precision (or a combination of high- and low-precision) data points per kiloyear enables precise estimates of RSL within ±∼\"> 2 m (2σ) and accurate RSL reconstructions with errors ≲ 0.7 m. Employing the nonparametric model with only lower-precision indicators also produces fairly accurate estimates of RSL with errors ≲1.50 m, although with less precision, only constraining RSL to ±∼\"> 3–4 m (2σ). Although the model performs better than previous models in terms of bias, model fit, accuracy, and precision, it is computationally expensive to run because it requires inverting large matrices for every sample. The new model also provides minimal gains over similar models when a large quantity of high-precision data are available. Therefore, we recommend incorporating the nonparametric likelihood distributions when no other information (e.g., reef facies or epibionts indicative of shallow-water environments to refine coral elevational uncertainties) or no high-precision data are available at a location or during a given time period of interest.

","language":"English","publisher":"Copernicus Publications","doi":"10.5194/ascmo-8-1-2022","usgsCitation":"Ashe, E.L., Khan, N.S., Toth, L., Dutton, A., and Kopp, R.E., 2022, A statistical framework for integrating nonparametric proxy distributions into geological reconstructions of relative sea level: Advances in Statistical Climatology, Meteorology and Oceanography, v. 8, p. 1-29, https://doi.org/10.5194/ascmo-8-1-2022.","productDescription":"29 p.","startPage":"1","endPage":"29","ipdsId":"IP-130546","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/ascmo-8-1-2022","text":"Publisher Index Page"},{"id":396013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2022-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Ashe, Erica L.","contributorId":279484,"corporation":false,"usgs":false,"family":"Ashe","given":"Erica","email":"","middleInitial":"L.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":834976,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Khan, Nicole S.","contributorId":213942,"corporation":false,"usgs":false,"family":"Khan","given":"Nicole","email":"","middleInitial":"S.","affiliations":[{"id":38935,"text":"Asian School of the Environment, Nanyang Technological University, 50 Nanyang Ave., Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":834977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":834978,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dutton, Andrea","contributorId":194113,"corporation":false,"usgs":false,"family":"Dutton","given":"Andrea","email":"","affiliations":[],"preferred":false,"id":834979,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kopp, Robert E.","contributorId":194114,"corporation":false,"usgs":false,"family":"Kopp","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":834980,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228576,"text":"70228576 - 2022 - Three Mw ≥ 4.7 earthquakes within the Changning (China) shale gas field ruptured shallow faults intersecting with hydraulic fracturing wells","interactions":[],"lastModifiedDate":"2022-02-14T15:19:14.272323","indexId":"70228576","displayToPublicDate":"2022-02-14T09:06:06","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Three Mw ≥ 4.7 earthquakes within the Changning (China) shale gas field ruptured shallow faults intersecting with hydraulic fracturing wells","docAbstract":"From 2017 to 2019, three destructive earthquakes (27 January 2017 Mw 4.7, 16 December 2018 Mw 5.2, and 3 January 2019 Mw 4.8) occurred in the Changning shale gas field in the southwest Sichuan Basin, China. Previous seismological studies attributed these events to hydraulic fracturing (HF), but were unable to identify the causative seismogenic faults and their slip behaviors. Here, we use Sentinel-1 synthetic aperture radar data to measure surface deformation triggered by the three events and conduct geodetic inversions to characterize their rupture models. The resulting coseismic interferograms show prominent surface deformation with the maximum line-of-sight displacements of up to 4 cm. The inversion results show that all three earthquakes mainly ruptured sedimentary formations above the shale gas bed, in the upper 3 km of the crust, with slip magnitudes ranging from 8.5 to 15 cm, and stress drops ranging from ∼1.8 to ∼3.3 MPa. Their source faults intersect with horizontal HF wells, but do not root in the crystalline basement. Combined with the reported difficulty of increasing HF operation pressures prior to the three events, we argue that they were most likely induced by direct injection of pressurized fluids into the fault zones. Crustal deformation patterns inferred from regional topography and GPS velocities highlight that the Changning field is located within a triple junction region near the southeastern margin of the Tibetan Plateau with large deformation gradients; such conditions are not only favorable to the development of critically stressed faults, but also facilitate the occurrence of at least moderate magnitude earthquakes.","language":"English","publisher":"Wiley","doi":"10.1029/2021JB022946","usgsCitation":"Wang, S., Jiang, G., Lei, X., Barbour, A.J., Tan, X., Xu, C., and Xu, X., 2022, Three Mw ≥ 4.7 earthquakes within the Changning (China) shale gas field ruptured shallow faults intersecting with hydraulic fracturing wells: Journal of Geophysical Research B: Solid Earth, v. 127, no. 2, e2021JB022946, https://doi.org/10.1029/2021JB022946.","productDescription":"e2021JB022946","ipdsId":"IP-129647","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":395884,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"Changning shale gas field, Sichuan Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 103.5791015625,\n 27.98955087395581\n ],\n [\n 106.138916015625,\n 27.98955087395581\n ],\n [\n 106.138916015625,\n 28.9120147012556\n ],\n [\n 103.5791015625,\n 28.9120147012556\n ],\n [\n 103.5791015625,\n 27.98955087395581\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Shuai","contributorId":276197,"corporation":false,"usgs":false,"family":"Wang","given":"Shuai","email":"","affiliations":[{"id":39129,"text":"Wuhan University","active":true,"usgs":false}],"preferred":false,"id":834650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jiang, Guoyan 0000-0002-6602-7295","orcid":"https://orcid.org/0000-0002-6602-7295","contributorId":256973,"corporation":false,"usgs":false,"family":"Jiang","given":"Guoyan","email":"","affiliations":[{"id":51926,"text":"CUHK","active":true,"usgs":false}],"preferred":false,"id":834651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lei, Xinglin","contributorId":276198,"corporation":false,"usgs":false,"family":"Lei","given":"Xinglin","email":"","affiliations":[{"id":27746,"text":"Geological Survey of Japan","active":true,"usgs":false}],"preferred":false,"id":834652,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbour, Andrew J. 0000-0002-6890-2452","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":215339,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":834653,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tan, Xibin","contributorId":276199,"corporation":false,"usgs":false,"family":"Tan","given":"Xibin","email":"","affiliations":[{"id":49174,"text":"China Earthquake Administration","active":true,"usgs":false}],"preferred":false,"id":834654,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Caijun 0000-0002-3459-7824","orcid":"https://orcid.org/0000-0002-3459-7824","contributorId":278586,"corporation":false,"usgs":false,"family":"Xu","given":"Caijun","email":"","affiliations":[{"id":39129,"text":"Wuhan University","active":true,"usgs":false}],"preferred":false,"id":834813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xu, Xiwei","contributorId":276200,"corporation":false,"usgs":false,"family":"Xu","given":"Xiwei","email":"","affiliations":[{"id":56935,"text":"National Institute of Natural Hazards, Ministry of Emergency Management","active":true,"usgs":false}],"preferred":false,"id":834655,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228579,"text":"70228579 - 2022 - Fast rupture of the 2009 Mw 6.9 Canal de Ballenas earthquake in the Gulf of California dynamically triggers seismicity in California","interactions":[],"lastModifiedDate":"2022-04-11T16:57:38.241489","indexId":"70228579","displayToPublicDate":"2022-02-14T08:52:46","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Fast rupture of the 2009 Mw 6.9 Canal de Ballenas earthquake in the Gulf of California dynamically triggers seismicity in California","docAbstract":"In the Gulf of California, Mexico, the relative motion across the North America-Pacific boundary is accommodated by a series of marine transform faults and spreading centers. About 40 M>6 earthquakes have occurred in the region since 1960. On 3 August 2009, an Mw 6.9 earthquake occurred near Canal de Ballenas in the region. The earthquake was a strike-slip event with a shallow hypocenter that is likely close to the seafloor. In contrast to an adjacent M7 earthquake, this earthquake triggered a ground-motion-based earthquake early warning algorithm being tested in southern California (∼600 km away). This observation suggests that the abnormally large ground motions and dynamic strains observed for this earthquake relate to its rupture properties. To investigate this possibility, we image the rupture process and resolve the slip distribution of the event using a P-wave back-projection approach and a teleseismic, finite-fault inversion method. Results from these two independent analyses indicate a relatively simple, unilateral rupture propagation directed along-strike in the northward direction. However, the average rupture speed is estimated around 4 km/s, suggesting a possible supershear rupture. The supershear speed is also supported by a Rayleigh wave Mach cone analysis, although uncertainties in local velocity structure preclude a definitive conclusion. The Canal de Ballenas earthquake dynamically triggered seismicity at multiple sites in California, with triggering response characteristics varying from location-to-location. For instance, some of the triggered earthquakes in California occurred up to 24 hours later, suggesting that nonlinear triggering mechanisms likely have modulated their occurrence.","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggac059","usgsCitation":"Fan, W., Okuwaki, R., Barbour, A.J., Huang, Y., Lin, G., and Cochran, E.S., 2022, Fast rupture of the 2009 Mw 6.9 Canal de Ballenas earthquake in the Gulf of California dynamically triggers seismicity in California: Geophysical Journal International, v. 230, no. 1, p. 528-541, https://doi.org/10.1093/gji/ggac059.","productDescription":"14 p.","startPage":"528","endPage":"541","ipdsId":"IP-133128","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":395882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Baja California","otherGeospatial":"Canal de Ballenas, Gulf of California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.5599365234375,\n 28.23180985121183\n ],\n [\n -111.29150390625,\n 28.23180985121183\n ],\n [\n -111.29150390625,\n 30.031055426540206\n ],\n [\n -114.5599365234375,\n 30.031055426540206\n ],\n [\n -114.5599365234375,\n 28.23180985121183\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"230","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Wenyuan","contributorId":174007,"corporation":false,"usgs":false,"family":"Fan","given":"Wenyuan","email":"","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":834662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Okuwaki, Ryo","contributorId":174014,"corporation":false,"usgs":false,"family":"Okuwaki","given":"Ryo","email":"","affiliations":[{"id":27339,"text":"University of Tsukuba","active":true,"usgs":false}],"preferred":false,"id":834663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbour, Andrew J. 0000-0002-6890-2452","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":215339,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":834664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huang, Yihe","contributorId":276214,"corporation":false,"usgs":false,"family":"Huang","given":"Yihe","email":"","affiliations":[{"id":56937,"text":"Univ Michigan","active":true,"usgs":false}],"preferred":false,"id":834665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Guoqing","contributorId":168856,"corporation":false,"usgs":false,"family":"Lin","given":"Guoqing","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":834666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":834667,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70228602,"text":"70228602 - 2022 - NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings","interactions":[],"lastModifiedDate":"2022-02-14T14:29:36.859424","indexId":"70228602","displayToPublicDate":"2022-02-14T08:25:44","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings","docAbstract":"Hyperparameter optimization approaches were applied to improve performance and accuracy of groundwater flow models. Freely available new software, NWTOPT, is described that uses Tree of Parzen Estimators (TPE) and Random Search algorithms to optimize MODFLOW-NWTs solver settings. We ran 3500 trials on a steady-state and transient model. To quantify the performance of candidate solver settings, we defined a loss function based on time elapsed and mass balance error of the MODFLOW-NWT forward run. Before optimization the steady- state model ran in ~12 min and the transient model ran in ~5 h with acceptable mass balance error (<1%). After optimization runtimes were reduced to ~2.7 min (steady state) and ~48 min (transient) with errors below 0.1%. In both cases TPE found hyperparameters that resulted in faster running and lower error models than those found by Random Search. The time to complete the optimization trials was also shorter with the TPE algorithm.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2021.105250","usgsCitation":"Newcomer, M.W., and Hunt, R., 2022, NWTOPT — A hyperparameter optimization approach for selection of environmental model solver settings: Environmental Modelling and Software, v. 147, p. 1-7, https://doi.org/10.1016/j.envsoft.2021.105250.","productDescription":"105250, 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-131832","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":448809,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2021.105250","text":"Publisher Index Page"},{"id":435970,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CPBZJX","text":"USGS data release","linkHelpText":"NWTOPT"},{"id":395877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Newcomer, Max William 0000-0003-2491-546X","orcid":"https://orcid.org/0000-0003-2491-546X","contributorId":276318,"corporation":false,"usgs":true,"family":"Newcomer","given":"Max","email":"","middleInitial":"William","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834746,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239098,"text":"70239098 - 2022 - Light and flow regimes regulate the metabolism of rivers","interactions":[],"lastModifiedDate":"2022-12-27T13:52:14.349473","indexId":"70239098","displayToPublicDate":"2022-02-14T07:40:50","publicationYear":"2022","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":"Light and flow regimes regulate the metabolism of rivers","docAbstract":"

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management.

","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2121976119","usgsCitation":"Bernhardt, E.S., Savoy, P., Vlah, M.J., Appling, A.P., Koenig, L., Hall Jr., R., Arroita, M., Blaszczak, J., Carter, A.M., Cohen, M.J., Harvey, J., Heffernan, J.B., Helton, A.M., Hosen, J., Kirk, L., McDowell, W.H., Stanley, E.H., Yackulic, C., and Grimm, N.B., 2022, Light and flow regimes regulate the metabolism of rivers: Proceedings of the National Academy of Sciences, v. 119, no. 8, e2121976119, 5 p., https://doi.org/10.1073/pnas.2121976119.","productDescription":"e2121976119, 5 p.","ipdsId":"IP-135271","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":448811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2121976119","text":"Publisher Index Page"},{"id":411062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"8","noUsgsAuthors":false,"publicationDate":"2022-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Bernhardt, Emily. S","contributorId":300289,"corporation":false,"usgs":false,"family":"Bernhardt","given":"Emily.","email":"","middleInitial":"S","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":860038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vlah, Michael J","contributorId":300353,"corporation":false,"usgs":false,"family":"Vlah","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Appling, Alison Paige 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":300354,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"Paige","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":860040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koenig, Lauren E 0000-0002-7790-330X","orcid":"https://orcid.org/0000-0002-7790-330X","contributorId":298697,"corporation":false,"usgs":false,"family":"Koenig","given":"Lauren E","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":860041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall Jr., Robert O","contributorId":292567,"corporation":false,"usgs":false,"family":"Hall Jr.","given":"Robert O","affiliations":[{"id":41061,"text":"Flathead Lake Biological Station, University of Montana, Polson, MT 59860","active":true,"usgs":false}],"preferred":false,"id":860042,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arroita, Maite 0000-0001-8754-7604","orcid":"https://orcid.org/0000-0001-8754-7604","contributorId":203307,"corporation":false,"usgs":false,"family":"Arroita","given":"Maite","email":"","affiliations":[{"id":36597,"text":"Flathead Lake Biological Station, University of Montana; University of the Basque Country","active":true,"usgs":false}],"preferred":false,"id":860043,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blaszczak, Joanna 0000-0001-5122-0829","orcid":"https://orcid.org/0000-0001-5122-0829","contributorId":225159,"corporation":false,"usgs":false,"family":"Blaszczak","given":"Joanna","email":"","affiliations":[{"id":41055,"text":"Natural Resources and Environmental Science, University of Nevada, Reno, NV 89557, USA","active":true,"usgs":false}],"preferred":false,"id":860044,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Carter, Alice M. 0000-0002-7225-7249","orcid":"https://orcid.org/0000-0002-7225-7249","contributorId":298702,"corporation":false,"usgs":false,"family":"Carter","given":"Alice","email":"","middleInitial":"M.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860045,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cohen, Matthew J.","contributorId":138990,"corporation":false,"usgs":false,"family":"Cohen","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":860046,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":860047,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Heffernan, James B. 0000-0001-7641-9949","orcid":"https://orcid.org/0000-0001-7641-9949","contributorId":211189,"corporation":false,"usgs":false,"family":"Heffernan","given":"James","email":"","middleInitial":"B.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":860048,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Helton, Ashley M. 0000-0001-6928-2104","orcid":"https://orcid.org/0000-0001-6928-2104","contributorId":298703,"corporation":false,"usgs":false,"family":"Helton","given":"Ashley","email":"","middleInitial":"M.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":860049,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hosen, J.D. 0000-0003-2559-0687","orcid":"https://orcid.org/0000-0003-2559-0687","contributorId":210149,"corporation":false,"usgs":false,"family":"Hosen","given":"J.D.","affiliations":[{"id":38085,"text":"Yale Univ.","active":true,"usgs":false}],"preferred":false,"id":860050,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kirk, Lily","contributorId":300290,"corporation":false,"usgs":false,"family":"Kirk","given":"Lily","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":860051,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"McDowell, William H.","contributorId":198684,"corporation":false,"usgs":false,"family":"McDowell","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":18105,"text":"University of New Hampshire, Durham","active":true,"usgs":false}],"preferred":false,"id":860052,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Stanley, Emily H.","contributorId":55725,"corporation":false,"usgs":false,"family":"Stanley","given":"Emily","email":"","middleInitial":"H.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":860053,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":860054,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Grimm, Nancy B.","contributorId":44058,"corporation":false,"usgs":false,"family":"Grimm","given":"Nancy","email":"","middleInitial":"B.","affiliations":[{"id":24511,"text":"Arizona State University, Tempe AZ USA 85287","active":true,"usgs":false}],"preferred":false,"id":860055,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70230406,"text":"70230406 - 2022 - Smoothed Particle Hydrodynamics simulations of reef surf zone processes driven by plunging irregular waves","interactions":[],"lastModifiedDate":"2022-04-12T12:20:14.982267","indexId":"70230406","displayToPublicDate":"2022-02-14T07:19:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Smoothed Particle Hydrodynamics simulations of reef surf zone processes driven by plunging irregular waves","docAbstract":"

As waves interact with the slopes of coral reefs and other steep bathymetry profiles, plunging breaking usually occurs where the free surface overturns and violent water motion is triggered. Resolving these surf zone processes pose significant challenges for conventional mesh-based hydrodynamic models, due to the rapidly-deforming nature of the free surface and associated flows. Yet the accurate prediction of these surf zone hydrodynamics is critical for predicting a wide range of nearshore processes driven by wave breaking (e.g., wave dissipation and energy transfers; mean water levels and currents; and wave runup). In this study we assess the ability of the mesh-free, Lagrangian particle-based numerical modelling approach Smoothed Particle Hydrodynamics (SPH) based on DualSPHysics, to simulate the fine-scale hydrodynamic processes driven by irregular wave transformation over a fringing reef profile, by comparing results against detailed experimental observations from a physical modelling study. To greatly improve the computational efficiency, the SPH model was coupled to the mesh-based multi-layer nonhydrostatic wave-flow model SWASH. With this coupled approach, SWASH was used to efficiently simulate the evolution of non-breaking waves from the wavemaker up to the fore reef slope, with the SPH model then used to simulate the detailed hydrodynamic processes over the reef from just offshore of the breakpoint to the shoreline. The SPH model was able to accurately reproduce the complex free surface deformations during plunging breaking, the spectral evolution of waves across the reef flat (including nonlinear wave shape), the mean water levels and currents, and wave runup at the shoreline. Using the long duration simulations (>400 wave periods), the model was able to reproduce the full range of wave motions over the reef (from sea-swell to infragravity frequencies), including the increasing dominance of low frequency waves towards the shoreline and the large cross-reef standing wave motions excited by the reef geometry.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2022.101945","usgsCitation":"Lowe, R.J., Altomare, C., Buckley, M.L., da Silva, R.F., Hansen, J.E., Rijnsdorp, D.P., Dominguez, J., and Crespo, A., 2022, Smoothed Particle Hydrodynamics simulations of reef surf zone processes driven by plunging irregular waves: Ocean Modelling, v. 171, 101945, 20 p., https://doi.org/10.1016/j.ocemod.2022.101945.","productDescription":"101945, 20 p.","ipdsId":"IP-131129","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448813,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2117/387691","text":"External Repository"},{"id":398535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"171","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":840332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Altomare, C.","contributorId":290134,"corporation":false,"usgs":false,"family":"Altomare","given":"C.","email":"","affiliations":[{"id":62343,"text":"Universitat Politecnica de Catalunya - BarcelonaTech (UPC)","active":true,"usgs":false}],"preferred":false,"id":840333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":840334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"da Silva, Renan F.","contributorId":261462,"corporation":false,"usgs":false,"family":"da Silva","given":"Renan","email":"","middleInitial":"F.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":840335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Jeff E.","contributorId":204340,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","email":"","middleInitial":"E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":true,"id":840336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rijnsdorp, Dirk P.","contributorId":261463,"corporation":false,"usgs":false,"family":"Rijnsdorp","given":"Dirk","email":"","middleInitial":"P.","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":840337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dominguez, J.M.","contributorId":290135,"corporation":false,"usgs":false,"family":"Dominguez","given":"J.M.","email":"","affiliations":[{"id":62345,"text":"Universidade de Vigo","active":true,"usgs":false}],"preferred":false,"id":840338,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crespo, A.J.C.","contributorId":290136,"corporation":false,"usgs":false,"family":"Crespo","given":"A.J.C.","email":"","affiliations":[{"id":62345,"text":"Universidade de Vigo","active":true,"usgs":false}],"preferred":false,"id":840339,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70248454,"text":"70248454 - 2022 - Observation-constrained multicycle dynamic models of the southern San Andreas and the northern San Jacinto Faults: Addressing complexity in paleoearthquake extent and recurrence with realistic 2D fault geometry","interactions":[],"lastModifiedDate":"2023-09-14T13:37:15.595869","indexId":"70248454","displayToPublicDate":"2022-02-13T08:31:50","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Observation-constrained multicycle dynamic models of the southern San Andreas and the northern San Jacinto Faults: Addressing complexity in paleoearthquake extent and recurrence with realistic 2D fault geometry","docAbstract":"

Understanding mechanical conditions that lead to complexity in earthquakes is important to seismic hazard analysis. In this study, we simulate physics-based multicycle dynamic models of the San Andreas fault (Carrizo through San Bernardino sections) and the San Jacinto fault (Claremont and Clark strands). We focus on a complex fault geometry based on the Southern California Earthquake Center Community Fault Model and its effect over multiple earthquake cycles. Using geodetically derived strain rates, we validate the models against geologic slip rates and recurrence intervals at various paleoseismic sites. We find that the interactions among fault geometry, dynamic rupture and interseismic stress accumulation produce stress heterogeneities, leading to rupture segmentation and variability in earthquake recurrence. Our models produce earthquakes with rupture extents similar to a recent comprehensive paleoseismic catalog. The “earthquake gates” of the Big Bend and the Cajon Pass occasionally impede dynamic ruptures. The angle of compression, which is the subtraction of the maximum shear strain rate direction from the local fault strike, can better determine the likelihood of the impedance of restraining bends to dynamic ruptures. Because the Big Bend has an angle of compression of ∼20°, ruptures that traverse the Big Bend, like the 1857 Fort Tejon earthquake, are more frequent than expected based on empirical relations which predict the ∼40° restraining bend to terminate most ruptures. Our models indicate that large ruptures tend to initiate north of the Big Bend and propagate southwards, similar to the 1857 earthquake, providing critical information for ground shaking assessment in the region.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JB023420","usgsCitation":"Liu, D., Duan, B., Scharer, K., and Yule, D., 2022, Observation-constrained multicycle dynamic models of the southern San Andreas and the northern San Jacinto Faults: Addressing complexity in paleoearthquake extent and recurrence with realistic 2D fault geometry: JGR Solid Earth, v. 127, no. 2, e2021JB023420, 22 p., https://doi.org/10.1029/2021JB023420.","productDescription":"e2021JB023420, 22 p.","ipdsId":"IP-134346","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":420787,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas fault, San Jacinto fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.44325960160413,\n 32.16342572407258\n ],\n [\n -114.94694055365994,\n 32.602203651593555\n ],\n [\n -115.68298832504138,\n 34.35705299301095\n ],\n [\n -118.23123450540402,\n 36.17004671558314\n ],\n [\n -122.64022454058095,\n 36.13834876313085\n ],\n [\n -121.86568529506617,\n 34.953691891088454\n ],\n [\n -121.34563225647895,\n 34.47252679102584\n ],\n [\n -121.17142222603147,\n 34.2697526624934\n ],\n [\n -121.02235509801822,\n 34.13587207276275\n ],\n [\n -120.6666703621019,\n 33.96832043218005\n ],\n [\n -120.60479015432749,\n 33.80728338539414\n ],\n [\n -120.54293930018164,\n 33.558510586072956\n ],\n [\n -120.24885318454707,\n 33.2222811389733\n ],\n [\n -119.79867764478334,\n 32.6389190231105\n ],\n [\n -119.44325960160413,\n 32.16342572407258\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Dunyu","contributorId":204607,"corporation":false,"usgs":false,"family":"Liu","given":"Dunyu","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":882975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duan, Benchuan","contributorId":329691,"corporation":false,"usgs":false,"family":"Duan","given":"Benchuan","email":"","affiliations":[{"id":78687,"text":"TAMU","active":true,"usgs":false}],"preferred":false,"id":882976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scharer, Katherine M. 0000-0003-2811-2496","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":217361,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":882977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yule, Doug","contributorId":239568,"corporation":false,"usgs":false,"family":"Yule","given":"Doug","email":"","affiliations":[{"id":36305,"text":"CSU Northridge","active":true,"usgs":false}],"preferred":false,"id":882978,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247284,"text":"70247284 - 2022 - Trends in volcano seismology: 2010 to 2020 and beyond","interactions":[],"lastModifiedDate":"2023-07-26T13:36:17.77978","indexId":"70247284","displayToPublicDate":"2022-02-12T08:33:24","publicationYear":"2022","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":"Trends in volcano seismology: 2010 to 2020 and beyond","docAbstract":"

Volcano seismology has been fundamental to our current understanding of crustal magma migration and eruption. The increasing availability of portable seismic networks with the creative use of seismic sources and ambient noise has led to a better understanding of the volcanic structure of many volcanoes and is producing increasingly detailed images of the volcanic subsurface. The past decade (2010-2020) has seen advances in our understanding of seismic sources under and surrounding volcanoes through precise locations, and through analysis of source mechanisms from seismic signals that are more varied and smaller in magnitude, reaching beyond traditional techniques. In tandem with continued research on fundamental physics-based understanding of volcano-seismic sources, new advances in computational analyses including machine learning methods will push our understanding of volcanic processes into the future. Incorporation of multidisciplinary geophysical observations (especially infrasound) has become commonplace, and our understanding of infrasound propagation and sources will feed back into our ability to monitor ongoing eruptions and surficial mass movements. Open-source codes will permit widespread evaluation and adoption of new methodologies for volcano-seismic analysis and inversion. Combined with quantitative and conceptual source models using improved structural constraints, these new methodologies will better characterize the range of volcano-seismic signal evolution scenarios and hold promise for creating better short-term forecasts. Finally, permanent instrumentation is available on an expanding range of volcanoes, and open data policies are increasingly making these data available to the scientific community in near real time.

","language":"English","publisher":"Springer","doi":"10.1007/s00445-022-01530-2","usgsCitation":"Thelen, W., Matoza, R., and Hotovec-Ellis, A.J., 2022, Trends in volcano seismology: 2010 to 2020 and beyond: Bulletin of Volcanology, v. 84, 26, 10 p., https://doi.org/10.1007/s00445-022-01530-2.","productDescription":"26, 10 p.","ipdsId":"IP-133090","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467200,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/94s4g2sc","text":"External Repository"},{"id":419345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"84","noUsgsAuthors":false,"publicationDate":"2022-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":879113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Matoza, Robin","contributorId":268788,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","affiliations":[{"id":7168,"text":"UCSB","active":true,"usgs":false}],"preferred":false,"id":879114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":879115,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228474,"text":"70228474 - 2022 - Epidemiological differences between sexes affect management efficacy in simulated chronic wasting disease systems","interactions":[],"lastModifiedDate":"2022-04-11T16:55:29.843688","indexId":"70228474","displayToPublicDate":"2022-02-11T10:42:35","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Epidemiological differences between sexes affect management efficacy in simulated chronic wasting disease systems","docAbstract":"
  1. Sex-based differences in physiology, behaviour and demography commonly result in differences in disease prevalence. However, sex differences in prevalence may reflect exposure rather than transmission, which could affect disease control programmes. One potential example is chronic wasting disease (CWD), which has been observed at greater prevalence among male than female deer.
  2. We used an age- and sex-structured simulation model to explore harvest-based management of CWD under three different transmission scenarios that all generate higher male prevalence: (1) increased male susceptibility, (2) high male-to-male transmission or (3) high female-to-male transmission.
  3. Both female and male harvests were required to limit CWD epidemics across all transmission scenarios (approximated by R0), though invasion was more likely under high female-to-male transmission.
  4. In simulations, heavily male-biased harvests controlled CWD epidemics and maintained large host populations under high male-to-male transmission and increased male susceptibility scenarios. However, male-biased harvests were ineffective under high female-to-male transmission. Instead, female-biased harvests were able to limit disease transmission under high female-to-male transmission but incurred a trade-off with smaller population sizes.
  5. Synthesis and applications. Higher disease prevalence in a sex or age group may be due to higher exposure or susceptibility but does not necessarily indicate if that group is responsible for more disease transmission. We showed that multiple processes can result in the pattern of higher male prevalence, but that population-level management interventions must focus on the sex responsible for disease transmission, not just those that are most exposed.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2664.14125","usgsCitation":"Rogers, W.J., Brandell, E.E., and Cross, P., 2022, Epidemiological differences between sexes affect management efficacy in simulated chronic wasting disease systems: Journal of Applied Ecology, v. 59, no. 4, p. 1122-1133, https://doi.org/10.1111/1365-2664.14125.","productDescription":"12 p.","startPage":"1122","endPage":"1133","ipdsId":"IP-123579","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":448823,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.14125","text":"Publisher Index Page"},{"id":395849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-09","publicationStatus":"PW","contributors":{"editors":[{"text":"McCallum, Hamish","contributorId":174852,"corporation":false,"usgs":false,"family":"McCallum","given":"Hamish","affiliations":[],"preferred":false,"id":834513,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Rogers, William J.","contributorId":173588,"corporation":false,"usgs":false,"family":"Rogers","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":834384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandell, Ellen E.","contributorId":253140,"corporation":false,"usgs":false,"family":"Brandell","given":"Ellen","email":"","middleInitial":"E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":834385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":834386,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228487,"text":"70228487 - 2022 - Population structure, intergroup interaction, and human contact govern infectious disease impacts in mountain gorilla populations","interactions":[],"lastModifiedDate":"2022-06-16T15:14:55.320322","indexId":"70228487","displayToPublicDate":"2022-02-11T10:16:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":731,"text":"American Journal of Primatology","active":true,"publicationSubtype":{"id":10}},"title":"Population structure, intergroup interaction, and human contact govern infectious disease impacts in mountain gorilla populations","docAbstract":"

Infectious zoonotic diseases are a threat to wildlife conservation and global health. They are especially a concern for wild apes, which are vulnerable to many human infectious diseases. As ecotourism, deforestation, and great ape field research increase, the threat of human-sourced infections to wild populations becomes more substantial and could result in devastating population declines. The endangered mountain gorillas (Gorilla beringei beringei) of the Virunga Massif in east-central Africa suffer periodic disease outbreaks and are exposed to infections from human-sourced pathogens. It is important to understand the possible risks of disease introduction and spread in this population and how human contact may facilitate disease transmission. Here we present and evaluate an individual-based, stochastic, discrete-time disease transmission model to predict epidemic outcomes and better understand health risks to the Virunga mountain gorilla population. To model disease transmission we have derived estimates for gorilla contact, interaction, and migration rates. The model shows that the social structure of gorilla populations plays a profound role in governing disease impacts with subdivided populations experiencing less than 25% of the outbreak levels of a single homogeneous population. It predicts that gorilla group dispersal and limited group interactions are strong factors in preventing widespread population-level outbreaks of infectious disease after such diseases have been introduced into the population. However, even a moderate amount of human contact increases disease spread and can lead to population-level outbreaks.

","language":"English","publisher":"Wiley","doi":"10.1002/ajp.23350","usgsCitation":"Whittier, C.A., Nutter, F.B., Johnson, P.L., Cross, P., Lloyd-Smith, J., Slenning, B.D., and Stoskopf, M.K., 2022, Population structure, intergroup interaction, and human contact govern infectious disease impacts in mountain gorilla populations: American Journal of Primatology, v. 84, no. 4-5, e23350, https://doi.org/10.1002/ajp.23350.","productDescription":"e23350","ipdsId":"IP-127784","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":395847,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Democratic Republic of the Congo, Rwanda, Uganda","otherGeospatial":"Virunga Massif","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 29.344482421875,\n -1.9881263049374718\n ],\n [\n 29.344482421875,\n -2.05949288957668\n ],\n [\n 29.476318359375004,\n -2.070472083193089\n ],\n [\n 29.652099609375,\n -1.9881263049374718\n ],\n [\n 29.756469726562496,\n -1.6312493057881732\n ],\n [\n 29.838867187500004,\n -1.4610232806227417\n ],\n [\n 30.036621093749996,\n -1.2413579498795597\n ],\n [\n 29.9761962890625,\n -1.0491357039128182\n ],\n [\n 29.822387695312496,\n -0.8953492997435784\n ],\n [\n 29.652099609375,\n -0.7909904981540058\n ],\n [\n 29.7344970703125,\n -0.6426867176331666\n ],\n [\n 29.8828125,\n -0.6646579437921112\n ],\n [\n 29.94873046875,\n -0.5932511181408705\n ],\n [\n 30.113525390625,\n -0.23620538561262966\n ],\n [\n 30.2288818359375,\n -0.21423289925022543\n ],\n [\n 30.333251953124996,\n 0\n ],\n [\n 30.3387451171875,\n 0.23071226715249907\n ],\n [\n 30.173950195312504,\n 0.2966295342722323\n ],\n [\n 30.201416015625004,\n 0.45592780548689615\n ],\n [\n 30.316772460937496,\n 0.7250783020332547\n ],\n [\n 30.421142578125,\n 0.8239462091017685\n ],\n [\n 30.5694580078125,\n 0.9228116626857066\n ],\n [\n 30.5694580078125,\n 1.016182073033441\n ],\n [\n 30.454101562499996,\n 1.2248822742251262\n ],\n [\n 30.245361328125,\n 1.2413579498795726\n ],\n [\n 30.0860595703125,\n 0.9832281059656174\n ],\n [\n 29.871826171875,\n 1.043643455908483\n ],\n [\n 29.432373046874996,\n 0.6591651462894632\n ],\n [\n 29.3499755859375,\n 0.428462803418747\n ],\n [\n 29.344482421875,\n -0.07141111432402265\n ],\n [\n 29.190673828124996,\n -0.41198375451568836\n ],\n [\n 29.1192626953125,\n -0.8239462091017558\n ],\n [\n 29.20166015625,\n -1.1425024037061522\n ],\n [\n 28.992919921875004,\n -1.307259612275665\n ],\n [\n 28.992919921875004,\n -1.5763391859789206\n ],\n [\n 29.218139648437496,\n -1.6861579269987852\n ],\n [\n 29.262084960937504,\n -1.8728353512547717\n ],\n [\n 29.344482421875,\n -1.9881263049374718\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"84","issue":"4-5","noUsgsAuthors":false,"publicationDate":"2021-12-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Whittier, Christopher A. 0000-0001-9626-6513","orcid":"https://orcid.org/0000-0001-9626-6513","contributorId":275919,"corporation":false,"usgs":false,"family":"Whittier","given":"Christopher","email":"","middleInitial":"A.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":834410,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nutter, Felicia B.","contributorId":8070,"corporation":false,"usgs":false,"family":"Nutter","given":"Felicia","email":"","middleInitial":"B.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":834411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Philip L. 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F.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":834412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":834413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lloyd-Smith, James O.","contributorId":31354,"corporation":false,"usgs":true,"family":"Lloyd-Smith","given":"James O.","affiliations":[],"preferred":false,"id":834414,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Slenning, Barrett D.","contributorId":275924,"corporation":false,"usgs":false,"family":"Slenning","given":"Barrett","email":"","middleInitial":"D.","affiliations":[{"id":49830,"text":"North Carolina University","active":true,"usgs":false}],"preferred":false,"id":834415,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stoskopf, Michael K.","contributorId":83817,"corporation":false,"usgs":true,"family":"Stoskopf","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":834416,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70232514,"text":"70232514 - 2022 - Variation in foraging patterns as reflected by floral resources used by male vs female bees of selected species at Badlands National Park, SD","interactions":[],"lastModifiedDate":"2022-07-06T14:51:56.176386","indexId":"70232514","displayToPublicDate":"2022-02-11T09:45:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5819,"text":"Arthropod-Plant Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Variation in foraging patterns as reflected by floral resources used by male vs female bees of selected species at Badlands National Park, SD","docAbstract":"Female and male bees forage for different reasons: females provision nests with pollen appropriate for larval development and consume nectar for energy while males need only fuel their own energetic requirements. The expectation, therefore, is that females should visit fewer floral resource species than males, due to females’ focus on host plant species and their tie to the nest location. We used pollen collected from bees’ bodies and the flowers they were collected on to infer floral resource use in 2010-2012 at Badlands National Park, SD, USA. We collected bees on 24 1-ha plots centered on particular plant species. We compared number of floral species and families (1) associated with individual female and male bees (via generalized linear mixed models) and (2) accumulated by each sex (using rarefaction); and (3) effect of variation between sexes in plant-bee interactions via modularity analyses. Analyses were restricted to bee species with > 5 individuals per sex. Contrary to expectation, female and male bees differed infrequently in the number of floral resources they had visited, both on single foraging bouts and collectively when accumulated across all males and females of a species. When males and females did differ, males visited fewer floral species than females. Generalist and specialist bee species did not differ markedly in floral resource use by females and males. When separated by sex, seven of eleven species occupied different modules than they did when analyzed as a species; most of the bee species were connectors, thus important for stability of the network during perturbations.","language":"English","publisher":"Springer","doi":"10.1007/s11829-021-09881-x","usgsCitation":"Larson, D.L., Portman, Z.M., Larson, J., and Buhl, D.A., 2022, Variation in foraging patterns as reflected by floral resources used by male vs female bees of selected species at Badlands National Park, SD: Arthropod-Plant Interactions, v. 16, p. 145-157, https://doi.org/10.1007/s11829-021-09881-x.","productDescription":"13 p.","startPage":"145","endPage":"157","ipdsId":"IP-133064","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":448825,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11829-021-09881-x","text":"Publisher Index Page"},{"id":403066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands National Park","volume":"16","noUsgsAuthors":false,"publicationDate":"2022-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Larson, Diane L. 0000-0001-5202-0634 dlarson@usgs.gov","orcid":"https://orcid.org/0000-0001-5202-0634","contributorId":292764,"corporation":false,"usgs":true,"family":"Larson","given":"Diane","email":"dlarson@usgs.gov","middleInitial":"L.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":845742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Portman, Zachary M.","contributorId":264397,"corporation":false,"usgs":false,"family":"Portman","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":54455,"text":"Dept. of Entomology, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":845743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Larson, Jennifer 0000-0002-6259-0101","orcid":"https://orcid.org/0000-0002-6259-0101","contributorId":216120,"corporation":false,"usgs":true,"family":"Larson","given":"Jennifer","email":"","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":845744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buhl, Deborah A. 0000-0002-8563-5990 dbuhl@usgs.gov","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":146226,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah","email":"dbuhl@usgs.gov","middleInitial":"A.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":845745,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228449,"text":"sir20215118B - 2022 - Yucaipa valley integrated hydrological model","interactions":[{"subject":{"id":70228449,"text":"sir20215118B - 2022 - Yucaipa valley integrated hydrological model","indexId":"sir20215118B","publicationYear":"2022","noYear":false,"chapter":"B","displayTitle":"Yucaipa Valley Integrated Hydrological Model","title":"Yucaipa valley integrated hydrological model"},"predicate":"IS_PART_OF","object":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"id":1}],"isPartOf":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"lastModifiedDate":"2022-02-10T20:43:51.187857","indexId":"sir20215118B","displayToPublicDate":"2022-02-10T12:43:40","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5118","chapter":"B","displayTitle":"Yucaipa Valley Integrated Hydrological Model","title":"Yucaipa valley integrated hydrological model","docAbstract":"

Introduction

The hydrologic system in the Yucaipa Valley watershed (YVW) was simulated using the coupled Groundwater and Surface-water FLOW model (GSFLOW; Markstrom and others, 2008). This study uses version 2.0 of GSFLOW, which is a combination of the Precipitation-Runoff Modeling System (PRMS; Markstrom and others, 2015), and the Newton-Raphson formulation of the Modular Groundwater-Flow Model (MODFLOW-NWT; hereafter referred to as MODFLOW; Harbaugh, 2005; Niswonger and others, 2011).

GSFLOW partitions the hydrologic system into three regions (fig. B1) that are linked by the exchange of unsaturated and saturated groundwater and surface water. The properties and processes within each region influence the flow of both groundwater and surface water into, out of, and within each region. The PRMS component of GSFLOW simulates Region 1, and the MODFLOW component simulates Regions 2 and 3. In the YVW, GSFLOW was applied as the simulation code and is referred to herein as the Yucaipa Integrated Hydrologic Model (YIHM; Alzraiee and others, 2022). In the YIHM, Region 1 includes the plant canopy, snowpack, and the soil zone; Region 2 includes the stream network; and Region 3 includes the subsurface beneath Regions 1 and 2 and consists of both the saturated and unsaturated zones. Soil-moisture conditions and head relations control the flow of both groundwater and surface water between regions. The maximum lateral extents of Regions 1 and 3 were defined using the surface-water drainage divides described in the “Description of Study Area” section of chapter A of this report. The boundaries for Region 2 are the lowest elevation of the streambeds, the stream channel widths, and the horizontal extent of the stream channels in the YVW. Flow across the unsaturated part of Region 3 is assumed to be vertical and does not cross the lateral boundary.

To simulate hydrologic processes occurring within the YVW using GSFLOW, a model domain was defined to match the surface watershed such that the domain includes each surficial hydrologic unit coinciding (at least partially) with the Yucaipa groundwater subbasin (hereafter referred to as “Yucaipa subbasin”) as defined in California Bulletin 118 (California Department of Water Resources, 2016). The resulting simulated domain (fig. B2) includes the Yucaipa subbasin and intersects partially with parts of the San Bernardino and San Timoteo groundwater subbasins (fig. B2). The area of the active model domain in YIHM is about 121 square miles (mi2). The developed YIHM can be used to improve understanding of the hydrologic processes in YVW and to simulate future management scenarios with different climatic and anthropogenic changes.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215118B","collaboration":"Prepared in cooperation with San Bernardino Valley Municipal Water District","usgsCitation":"Alzraiee, A.H., Engott, J.A., Cromwell, G., and Woolfenden, L., 2022, Yucaipa valley integrated hydrological model, chap. B in Cromwell, G., and Alzraiee, A.H., eds., Hydrology of the Yucaipa groundwater subbasin—Characterization and integrated numerical model, San Bernardino and Riverside Counties, California: U.S. Geological Survey Scientific Investigations Report 2021–5118-B, 76 p., https://doi.org/10.3133/sir20215118B.","productDescription":"Report: ix, 76 p., and data release","numberOfPages":"76","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":395797,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118b.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":395800,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215118A","text":"SIR 2021-5118 Chapter A","linkHelpText":"- Hydrogeologic Characterization of the Yucaipa Groundwater Subbasin"},{"id":395798,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118b.xml"},{"id":395799,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5118/images"},{"id":395795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5118/covrthbb.jpg"},{"id":395809,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K540DV","description":"Alzraiee, A.H., Engott, J.A., Cromwell, G., and Woolfenden, L., 2022, Yucaipa valley integrated hydrological model, chap. B in Cromwell, G., and Alzraiee, A.H., eds., Hydrology of the Yucaipa groundwater subbasin—Characterization and integrated numerical model, San Bernardino and Riverside Counties, California: U.S. Geological Survey Scientific Investigations Report 2021–5118-B, 76 p., https://doi.org/10.3133/sir20215118B."}],"contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-02-10","noUsgsAuthors":false,"publicationDate":"2022-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Alzraiee, Ayman H. 0000-0001-7576-3449","orcid":"https://orcid.org/0000-0001-7576-3449","contributorId":272120,"corporation":false,"usgs":true,"family":"Alzraiee","given":"Ayman","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cromwell, Geoffrey 0000-0001-8481-405X gcromwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-405X","contributorId":5920,"corporation":false,"usgs":true,"family":"Cromwell","given":"Geoffrey","email":"gcromwell@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woolfenden, Linda R. 0000-0003-3500-4709 lrwoolfe@usgs.gov","orcid":"https://orcid.org/0000-0003-3500-4709","contributorId":1476,"corporation":false,"usgs":true,"family":"Woolfenden","given":"Linda","email":"lrwoolfe@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834328,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228448,"text":"sir20215118A - 2022 - Hydrogeologic characterization of the Yucaipa groundwater subbasin","interactions":[{"subject":{"id":70228448,"text":"sir20215118A - 2022 - Hydrogeologic characterization of the Yucaipa groundwater subbasin","indexId":"sir20215118A","publicationYear":"2022","noYear":false,"chapter":"A","displayTitle":"Hydrogeologic Characterization of the Yucaipa Groundwater Subbasin","title":"Hydrogeologic characterization of the Yucaipa groundwater subbasin"},"predicate":"IS_PART_OF","object":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"id":1}],"isPartOf":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"lastModifiedDate":"2022-02-11T16:50:35.030326","indexId":"sir20215118A","displayToPublicDate":"2022-02-10T10:29:06","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5118","chapter":"A","displayTitle":"Hydrogeologic Characterization of the Yucaipa Groundwater Subbasin","title":"Hydrogeologic characterization of the Yucaipa groundwater subbasin","docAbstract":"

Introduction

Water management in the Santa Ana River watershed in San Bernardino and Riverside Counties in southern California (fig. A1) is complex with various water purveyors navigating geographic, geologic, hydrologic, and political challenges to provide a reliable water supply to stakeholders. As the population has increased throughout southern California, so has the demand for water. The Yucaipa groundwater subbasin (hereafter referred to as “Yucaipa subbasin”), one of nine groundwater subbasins in what the California Department of Water Resources (DWR) refers to as the Upper Santa Ana Valley groundwater basin (California Department of Water Resources, 2016; fig. A1; the DWR naming convention is used within this report), is no exception; steady population growth since the 1940s and changes in water use have forced local water purveyors to regularly adapt their water infrastructure. Water demands within the Yucaipa subbasin have historically been supplied by groundwater, but water imported via the California State Water Project has augmented the total water supply through direct use and through anthropogenic recharge at the Wilson Creek and Oak Glen Creek spreading basins since 2002. Overall demand for groundwater continues to rise, and local water managers are concerned that despite the influx of imported water, groundwater levels may decline to a point where producing water will be uneconomical, severely limiting the ability of local agencies to meet water-supply demand.

To better understand the hydrogeology and water resources in the Yucaipa subbasin, the U.S. Geological Survey (USGS) initiated a study in cooperation with the San Bernardino Valley Municipal Water District (SBVMWD) to characterize and model the hydrologic system of the Yucaipa subbasin and the surrounding Yucaipa Valley watershed (YVW; fig. A2). To gain this comprehensive understanding, a three-dimensional (3D) hydrogeologic framework model (HFM; Cromwell and Matti, 2022) was constructed to quantify the structure and extent of hydrogeologic units in the YVW; the hydrologic system was conceptualized and quantified (described in chapter A); and the Yucaipa Integrated Hydrological Model (YIHM; described in chapter B) was developed to simulate the integrated surface-water and aquifer systems, including natural and anthropogenic recharge and discharge throughout the study area during 1947–2014.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215118A","collaboration":"Prepared in cooperation with San Bernardino Valley Municipal Water District","usgsCitation":"Cromwell, G., Engott, J.A., Alzraiee, A.H., Stamos, C.L., Mendez, G.O., Dick, M.C., and Bond, S., 2022, Hydrogeologic characterization of the Yucaipa groundwater subbasin, chap. A in Cromwell, G., and Alzraiee, A.H., eds., Hydrology of the Yucaipa groundwater subbasin—Characterization and integrated numerical model, San Bernardino and Riverside Counties, California: U.S. Geological Survey Scientific Investigations Report 2021–5118–A, 81 p., https://doi.org/10.3133/sir20215118A.","productDescription":"Report: vii, 81 p., and data release","numberOfPages":"81","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":395793,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F7OYQR","description":"Cromwell, G., Matti, J.C., and Roberts, S.A., 2022, Data release of hydrogeologic data of the Yucaipa groundwater subbasin, San Bernardino and Riverside Counties, California: U.S. Geological Survey Sciencebase data release, https://doi.org/ 10.5066/ P9F7OYQR.","linkHelpText":"Data release of hydrogeologic data of the Yucaipa groundwater subbasin, San Bernardino and Riverside Counties, California"},{"id":395789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5118/covrthba.jpg"},{"id":395790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118a.pdf","text":"Report","size":"60 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":395791,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118a.xml"},{"id":395792,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5118/images"},{"id":395794,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20215118B","text":"SIR 2021-5118 Chapter B","linkHelpText":"- Yucaipa valley integrated hydrological model"}],"contact":"

Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819

","tableOfContents":"
","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2022-02-10","noUsgsAuthors":false,"publicationDate":"2022-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Cromwell, Geoffrey 0000-0001-8481-405X gcromwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-405X","contributorId":5920,"corporation":false,"usgs":true,"family":"Cromwell","given":"Geoffrey","email":"gcromwell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engott, John A. 0000-0003-1889-4519 jaengott@usgs.gov","orcid":"https://orcid.org/0000-0003-1889-4519","contributorId":1142,"corporation":false,"usgs":true,"family":"Engott","given":"John","email":"jaengott@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alzraiee, Ayman H. 0000-0001-7576-3449","orcid":"https://orcid.org/0000-0001-7576-3449","contributorId":272120,"corporation":false,"usgs":true,"family":"Alzraiee","given":"Ayman","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stamos-Pfeiffer, Christina 0000-0002-1007-9352 clstamos@usgs.gov","orcid":"https://orcid.org/0000-0002-1007-9352","contributorId":169089,"corporation":false,"usgs":true,"family":"Stamos-Pfeiffer","given":"Christina","email":"clstamos@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mendez, Gregory 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":139098,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dick, Meghan C. 0000-0002-8323-3787 mdick@usgs.gov","orcid":"https://orcid.org/0000-0002-8323-3787","contributorId":200745,"corporation":false,"usgs":true,"family":"Dick","given":"Meghan","email":"mdick@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834323,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bond, Sandra 0000-0003-0522-5287 sbond@usgs.gov","orcid":"https://orcid.org/0000-0003-0522-5287","contributorId":3328,"corporation":false,"usgs":true,"family":"Bond","given":"Sandra","email":"sbond@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":834324,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70228746,"text":"70228746 - 2022 - A novel approach for directly incorporating disease into fish stock assessment: A case study with seroprevalence data","interactions":[],"lastModifiedDate":"2022-03-28T16:49:12.186131","indexId":"70228746","displayToPublicDate":"2022-02-10T06:49:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A novel approach for directly incorporating disease into fish stock assessment: A case study with seroprevalence data","docAbstract":"
When estimating mortality from disease with fish population models, common disease surveillance data such as infection prevalence are not always informative, especially for fast-acting diseases that may go unobserved in infrequently sampled populations. In these cases, seroprevalence — the proportion of fish with measurable antibody levels in their blood — may be more informative. In cases of life-long immunity, seroprevalence data require less frequent sampling intervals than infection prevalence data and can reflect the cumulative exposure history of fish. We simulation tested the usefulness of seroprevalence data in an age-structured fish stock assessment model using viral hemorrhagic septicemia virus (VHSV) in Pacific herring (Clupea pallasii) as a case study. We developed a novel epidemiological model to simulate population dynamics and seroprevalence data and fitted to these data in an integrated catch-at-age model with equations that estimate age- and time-varying mortality from disease. We found that simulated seroprevalence data can provide accurate estimates of infection history and disease-associated mortality. Importantly, even models that misspecified nonstationary processes in background or disease-associated mortality, but included seroprevalence data, accurately estimated annual infection and population abundance.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0094","usgsCitation":"Trochta, J.T., Groner, M., Hershberger, P., and Branch, T., 2022, A novel approach for directly incorporating disease into fish stock assessment: A case study with seroprevalence data: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 4, p. 611-630, https://doi.org/10.1139/cjfas-2021-0094.","productDescription":"20 p.","startPage":"611","endPage":"630","ipdsId":"IP-129096","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":448840,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2021-0094","text":"Publisher Index Page"},{"id":396090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Trochta, John T.","contributorId":279655,"corporation":false,"usgs":false,"family":"Trochta","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":57329,"text":"School of Aquatic and Fishery Sciences, Box 355020, University of Washington, Seattle WA, 98195, USA","active":true,"usgs":false}],"preferred":false,"id":835274,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Groner, Maya 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":220169,"corporation":false,"usgs":true,"family":"Groner","given":"Maya","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":835275,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":835276,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Branch, Trevor A.","contributorId":172088,"corporation":false,"usgs":false,"family":"Branch","given":"Trevor A.","affiliations":[],"preferred":false,"id":835277,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229086,"text":"70229086 - 2022 - Prospective and retrospective evaluation of the U.S. Geological Survey public aftershock forecast for the 2019-2021 Southwest Puerto Rico Earthquake and aftershocks","interactions":[],"lastModifiedDate":"2022-02-28T14:52:31.521726","indexId":"70229086","displayToPublicDate":"2022-02-09T08:47:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Prospective and retrospective evaluation of the U.S. Geological Survey public aftershock forecast for the 2019-2021 Southwest Puerto Rico Earthquake and aftershocks","docAbstract":"

The Mw\">Mw 6.4 Southwest Puerto Rico Earthquake of 7 January 2020 was accompanied by a robust fore‐ and aftershock sequence. The U.S. Geological Survey (USGS) has issued regular aftershock forecasts for more than a year since the mainshock, available on a public webpage. Forecasts were accompanied by interpretive and informational material, published in English and Spanish. Informational products included narrative “scenarios” for how the aftershock sequence could play out, infographics, and a report on the potential duration of the aftershock sequence through the next decade. Forecasts are based on the epidemic‐type aftershock sequence (ETAS) model and generated using the USGS AftershockForecaster software—an interactive graphical user interface built on the OpenSHA platform (Field et al., 2003). The initial forecast is based on past sequences in similar tectonic environments; subsequent forecasts are tuned to the ongoing sequence via Bayesian model updating. Probabilistic aftershock forecasts for the next day, week, month, and year were publicly released and archived at a daily to monthly tempo, allowing for a truly prospective test of the forecast. Here, we evaluate the forecast over the first year of the recorded aftershocks. The ETAS‐based forecast performed well overall, successfully capturing both the chance of having at least one earthquake of a given magnitude in a forecast interval as well as the non‐Poissonian distribution of the total number of aftershocks within an interval. A retrospective analysis shows that the ETAS model is a substantial improvement over the existing Reasenberg and Jones (1989) forecast model. The exercise also reveals some limitations of the current model, in particular, with respect to nonstationarities in the aftershock magnitude distribution and model parameters throughout the evolving sequence.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210222","usgsCitation":"van der Elst, N., Hardebeck, J.L., Michael, A.J., McBride, S., and Vanacore, E., 2022, Prospective and retrospective evaluation of the U.S. Geological Survey public aftershock forecast for the 2019-2021 Southwest Puerto Rico Earthquake and aftershocks: Seismological Research Letters, v. 93, no. 2A, p. 620-640, https://doi.org/10.1785/0220210222.","productDescription":"21 p.","startPage":"620","endPage":"640","ipdsId":"IP-132558","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":396546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.22259521484375,\n 17.906875582164254\n ],\n [\n -66.90811157226562,\n 17.906875582164254\n ],\n [\n -66.90811157226562,\n 18.184997171309004\n ],\n [\n -67.22259521484375,\n 18.184997171309004\n ],\n [\n -67.22259521484375,\n 17.906875582164254\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"2A","noUsgsAuthors":false,"publicationDate":"2022-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":836441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":254964,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":836442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":836443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":836444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vanacore, Elizabeth","contributorId":287037,"corporation":false,"usgs":false,"family":"Vanacore","given":"Elizabeth","affiliations":[{"id":61452,"text":"Univ. of Puerto Rico","active":true,"usgs":false}],"preferred":false,"id":836445,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70228396,"text":"70228396 - 2022 - Multi-species inference of exotic annual and native perennial grasses in rangelands of the western United States using Harmonized Landsat and Sentinel-2 data","interactions":[],"lastModifiedDate":"2022-04-04T11:13:24.753751","indexId":"70228396","displayToPublicDate":"2022-02-09T08:26:22","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Multi-species inference of exotic annual and native perennial grasses in rangelands of the western United States using Harmonized Landsat and Sentinel-2 data","docAbstract":"

The invasion of exotic annual grass (EAG), e.g., cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), into rangeland ecosystems of the western United States is a broad-scale problem that affects wildlife habitats, increases wildfire frequency, and adds to land management costs. However, identifying individual species of EAG abundance from remote sensing, particularly at early stages of invasion or growth, can be problematic because of overlapping controls and similar phenological characteristics among native and other exotic vegetation. Subsequently, refining and developing tools capable of quantifying the abundance and phenology of annual and perennial grass species would be beneficial to help inform conservation and management efforts at local to regional scales. Here, we deploy an enhanced version of the U.S. Geological Survey Rangeland Exotic Plant Monitoring System to develop timely and accurate maps of annual (2016–2020) and intra-annual (May 2021 and July 2021) abundances of exotic annual and perennial grass species throughout the rangelands of the western United States. This monitoring system leverages field observations and remote-sensing data with artificial intelligence/machine learning to rapidly produce annual and early season estimates of species abundances at a 30-m spatial resolution. We introduce a fully automated and multi-task deep-learning framework to simultaneously predict and generate weekly, near-seamless composites of Harmonized Landsat Sentinel-2 spectral data. These data, along with auxiliary datasets and time series metrics, are incorporated into an ensemble of independent XGBoost models. This study demonstrates that inclusion of the Normalized Difference Vegetation Index and Normalized Difference Wetness Index time-series data generated from our deep-learning framework enables near real-time and accurate mapping of EAG (Median Absolute Error (MdAE): 3.22, 2.72, and 0.02; and correlation coefficient (r): 0.82, 0.81, and 0.73; respectively for EAG, cheatgrass, and medusahead) and native perennial grass abundance (MdAE: 2.51, r:0.72 for Sandberg bluegrass (Poa secunda)). Our approach and the resulting data provide insights into rangeland grass dynamics, which will be useful for applications, such as fire and drought monitoring, habitat suitability mapping, as well as land-cover and land-change modelling. Spatially explicit, timely, and accurate species-specific abundance datasets provide invaluable information to land managers.

","language":"English","publisher":"MDPI","doi":"10.3390/rs14040807","usgsCitation":"Dahal, D., Pastick, N.J., Boyte, S., Parajuli, S., Oimoen, M.J., and Megard, L.J., 2022, Multi-species inference of exotic annual and native perennial grasses in rangelands of the western United States using Harmonized Landsat and Sentinel-2 data: Remote Sensing, v. 14, no. 4, Article: 807, 21 p. ; 3 Data Releases, https://doi.org/10.3390/rs14040807.","productDescription":"Article: 807, 21 p. ; 3 Data Releases","ipdsId":"IP-135991","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":504745,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13QWBFH","text":"USGS data release","linkHelpText":"Weekly Herbaceous and Exotic Annual Grass (EAG) Cover for western North America 2016 – 2026"},{"id":448849,"rank":6,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14040807","text":"Publisher Index Page"},{"id":486325,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14VQEGO","text":"USGS data release","linkHelpText":"Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2025"},{"id":435974,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1Y5TZBM","text":"USGS data release","linkHelpText":"Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, 2024"},{"id":397952,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GC5JVG","text":"USGS data release","description":"USGS data release","linkHelpText":"Fractional Estimates of Multiple Exotic Annual Grass (EAG) Species and Sandberg bluegrass in the Sagebrush Biome, USA, 2016 - 2020"},{"id":397951,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AVGRH8","text":"USGS data release","description":"USGS data release","linkHelpText":"Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, May 2021, v1"},{"id":395764,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397950,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FG6X9Q","text":"USGS data release","description":"USGS data release","linkHelpText":"Early Estimates of Exotic Annual Grass (EAG) in the Sagebrush Biome, USA, July 2021, (ver 2.0, January 2022)"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.865234375,\n 30.031055426540206\n ],\n [\n -103.3154296875,\n 32.65787573695528\n ],\n [\n -103.6669921875,\n 34.74161249883172\n ],\n [\n -100.6787109375,\n 36.63316209558658\n ],\n [\n -100.72265625,\n 36.98500309285596\n ],\n [\n -101.29394531249999,\n 37.64903402157866\n ],\n [\n -103.4033203125,\n 39.198205348894795\n ],\n [\n -104.2822265625,\n 40.713955826286046\n ],\n [\n -102.7880859375,\n 43.004647127794435\n ],\n [\n -102.3046875,\n 47.84265762816538\n ],\n [\n -103.53515625,\n 48.980216985374994\n ],\n [\n -121.201171875,\n 49.009050809382046\n ],\n [\n -121.5087890625,\n 46.92025531537451\n ],\n [\n -122.25585937500001,\n 43.96119063892024\n ],\n [\n -122.25585937500001,\n 41.27780646738183\n ],\n [\n -123.662109375,\n 39.605688178320804\n ],\n [\n -124.01367187499999,\n 38.95940879245423\n ],\n [\n -121.86035156249999,\n 36.38591277287651\n ],\n [\n -120.58593749999999,\n 34.70549341022544\n ],\n [\n -120.673828125,\n 33.97980872872457\n ],\n [\n -117.99316406249999,\n 32.91648534731439\n ],\n [\n -117.2900390625,\n 32.69486597787505\n ],\n [\n -114.9609375,\n 32.54681317351514\n ],\n [\n -110.74218749999999,\n 31.27855085894653\n ],\n [\n -108.06152343749999,\n 31.466153715024294\n ],\n [\n -108.06152343749999,\n 31.952162238024975\n ],\n [\n -105.29296874999999,\n 30.977609093348686\n ],\n [\n -104.19433593749999,\n 29.611670115197377\n ],\n [\n -102.919921875,\n 28.998531814051795\n ],\n [\n -101.865234375,\n 30.031055426540206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Dahal, Devendra 0000-0001-9594-1249","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":192023,"corporation":false,"usgs":false,"family":"Dahal","given":"Devendra","affiliations":[],"preferred":false,"id":834192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"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":834193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":205374,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":834194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parajuli, Sujan 0000-0002-1652-3063","orcid":"https://orcid.org/0000-0002-1652-3063","contributorId":275653,"corporation":false,"usgs":false,"family":"Parajuli","given":"Sujan","affiliations":[{"id":56871,"text":"KBR Inc. Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":834195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oimoen, Michael J. 0000-0003-3611-6227","orcid":"https://orcid.org/0000-0003-3611-6227","contributorId":275654,"corporation":false,"usgs":false,"family":"Oimoen","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":56871,"text":"KBR Inc. Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":834196,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Megard, Logan J. 0000-0002-0150-4521","orcid":"https://orcid.org/0000-0002-0150-4521","contributorId":275655,"corporation":false,"usgs":false,"family":"Megard","given":"Logan","email":"","middleInitial":"J.","affiliations":[{"id":56872,"text":"C2G Inc. Contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":834197,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70230388,"text":"70230388 - 2022 - Ground failure triggered by the 7 January 2020 M6.4 Puerto Rico earthquake","interactions":[],"lastModifiedDate":"2022-04-11T12:09:16.143542","indexId":"70230388","displayToPublicDate":"2022-02-09T07:07:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Ground failure triggered by the 7 January 2020 M6.4 Puerto Rico earthquake","docAbstract":"

The 7 January 2020 M 6.4 Puerto Rico earthquake, the mainshock of an extended earthquake sequence, triggered significant ground failure. In this study, we detail the ground failure that occurred based largely on a postearthquake field reconnaissance campaign that we conducted. We documented more than 300 landslides, mainly rock falls that were concentrated in areas where peak ground acceleration (PGA) exceeded 30%g; sparse smaller landslides occurred in highly susceptible areas more than 50 km from the epicenter and at PGA values <10%g. Though some of the largest mass movements were in natural slopes, rock falls in road cuts had more impact because they caused widespread transportation disruption. Some structures also were damaged by landslides, but no landslide‐related fatalities were reported. Liquefaction and related lateral spreading were severe in some areas, causing damage to residential and commercial structures and a power plant. Most of the liquefaction occurred in coastal areas where shaking exceeded 50%g, though some of the most damaging instances were in Ponce, where shaking estimates were as low as 20%g. In this article, we summarize the most notable ground failures and detail the overall patterns that we observed. The observations and compiled inventory datasets presented here are valuable because no island‐wide hazard maps for earthquake‐triggered landslides or liquefaction have been developed for Puerto Rico, and postevent inventories are vital for such an effort. In general, the datasets presented here contribute to a global understanding of coseismic ground‐failure hazard by presenting detailed observations for a relatively moderate ground‐failure event with well‐constrained shaking estimates; current models and expectations are biased by the tendency to collect detailed datasets mainly for exceptional events.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220210235","usgsCitation":"Allstadt, K.E., Thompson, E.M., Bayouth Garcia, D., Irizarry Brugman, E., Hughes, K.S., and Schmitt, R.G., 2022, Ground failure triggered by the 7 January 2020 M6.4 Puerto Rico earthquake: Seismological Research Letters, v. 93, no. 2A, p. 594-608, https://doi.org/10.1785/0220210235.","productDescription":"15 p.","startPage":"594","endPage":"608","ipdsId":"IP-134674","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":398459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto 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Center","active":true,"usgs":true}],"preferred":true,"id":840154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bayouth Garcia, Desiree","contributorId":237047,"corporation":false,"usgs":false,"family":"Bayouth Garcia","given":"Desiree","email":"","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":840155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irizarry Brugman, Edwin","contributorId":237049,"corporation":false,"usgs":false,"family":"Irizarry Brugman","given":"Edwin","email":"","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":840156,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hughes, K. Stephen","contributorId":218339,"corporation":false,"usgs":false,"family":"Hughes","given":"K.","email":"","middleInitial":"Stephen","affiliations":[{"id":16585,"text":"University of Puerto Rico - Mayaguez","active":true,"usgs":false}],"preferred":false,"id":840157,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schmitt, Robert G. 0000-0001-8060-1954 rschmitt@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-1954","contributorId":5611,"corporation":false,"usgs":true,"family":"Schmitt","given":"Robert","email":"rschmitt@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":840158,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232643,"text":"70232643 - 2022 - Juvenile continental crust evolution in a modern oceanic arc setting: Petrogenesis of Cenozoic felsic plutons in Fiji, SW Pacific","interactions":[],"lastModifiedDate":"2022-07-11T11:28:14.938622","indexId":"70232643","displayToPublicDate":"2022-02-09T06:24:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Juvenile continental crust evolution in a modern oceanic arc setting: Petrogenesis of Cenozoic felsic plutons in Fiji, SW Pacific","docAbstract":"

Viti Levu, Fiji, provides one of the best exposed Phanerozoic analogues for the formation of juvenile continental crust in an intra-oceanic setting. Tonalites and trondhjemites are present in several large (75–150 km2) adjacent, mid-Cenozoic plutons. We report major and trace element data including rare earth element (REE) and high-precision high field strength element (HFSE) compositions, new Hf-Nd-Sr-Pb isotope data, and zircon U/Pb-ages, O-Hf isotopes, and trace elements, from five different plutons. The Eocene Yavuna pluton and the Miocene Colo plutons are mainly composed of tonalites and trondhjemites and represent the exposed middle crust of the former Vitiaz island arc. The plutons can be divided into three suites. One suite is light REE (LREE) depleted with some trace element ratios lower than average normal mid-ocean ridge basalts (N-MORB). A second suite has flat REE patterns similar to local island arc basalts. Both suites occur near the coast of Viti Levu, include a wide compositional spectrum from gabbro to tonalite, and can be produced mostly by fractional crystallization of mafic precursor melts. The third suite is characterized by LREE enrichments with higher LaN/YbN (2.3–4.9), higher Zr/Y (4.3–7.1), and lower Nb/Ta (9.6–12.4). They occur closer to the center of the island and are bimodal trondhjemite-gabbro intrusions. These characteristics are consistent with formation mostly by partial melting of mafic crust. Trace element modeling shows that the trace element ratios of the third suite can be produced by 10–20 % melting of the mafic crust in the presence of residual amphibole, resulting in the retention of the medium REE (MREE) and diagnostic trace element ratios including low Nb/Ta and high Zr/Y. Geochemical similarities of the LREE enriched suite to typical “low”-pressure Archean tonalites-trondhjemites-granodiorites (TTGs) imply a common petrogenetic origin and similar mechanisms for the generation of juvenile Archean and modern differentiated crust by partial melting of mafic crust with residual amphibole. In modern oceanic arcs, genetically unrelated felsic plutonic as well as volcanic rocks co-exist, and in this regard, the Fijian plutons accompany major tectonic disruptions to arc processes.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2021.11.033","usgsCitation":"Marien, C.S., Drewes-Todd, E.K., Stork, A., Todd, E., Gill, J.B., Hoffman, J.E., Tani, K., Allen, C.M., and Munker, C., 2022, Juvenile continental crust evolution in a modern oceanic arc setting: Petrogenesis of Cenozoic felsic plutons in Fiji, SW Pacific: Geochimica et Cosmochimica Acta, v. 320, p. 339-365, https://doi.org/10.1016/j.gca.2021.11.033.","productDescription":"26 p.","startPage":"339","endPage":"365","ipdsId":"IP-126025","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":403359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Fiji","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 175.25390624999997,\n -19.76670355171696\n ],\n [\n 182.109375,\n -19.76670355171696\n ],\n [\n 182.109375,\n -14.306969497825788\n ],\n [\n 175.25390624999997,\n -14.306969497825788\n ],\n [\n 175.25390624999997,\n -19.76670355171696\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"320","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Marien, Chris S.","contributorId":292913,"corporation":false,"usgs":false,"family":"Marien","given":"Chris","email":"","middleInitial":"S.","affiliations":[{"id":63070,"text":"Institut für Geologie und Mineralogie, University of Cologne, 50674 Köln, Germany","active":true,"usgs":false}],"preferred":false,"id":846163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drewes-Todd, Elizabeth Kathleen 0000-0003-0692-3714","orcid":"https://orcid.org/0000-0003-0692-3714","contributorId":243351,"corporation":false,"usgs":true,"family":"Drewes-Todd","given":"Elizabeth","email":"","middleInitial":"Kathleen","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":846162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stork, Allen","contributorId":292914,"corporation":false,"usgs":false,"family":"Stork","given":"Allen","email":"","affiliations":[{"id":63071,"text":"Department of Geology, Western Colorado University, Gunnison CO, USA","active":true,"usgs":false}],"preferred":false,"id":846164,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todd, Erin 0000-0002-4871-9730 etodd@usgs.gov","orcid":"https://orcid.org/0000-0002-4871-9730","contributorId":202811,"corporation":false,"usgs":true,"family":"Todd","given":"Erin","email":"etodd@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":846165,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gill, James B 0000-0003-2584-9687","orcid":"https://orcid.org/0000-0003-2584-9687","contributorId":248602,"corporation":false,"usgs":false,"family":"Gill","given":"James","email":"","middleInitial":"B","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":846166,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoffman, J. Elis 0000-0001-6670-1393","orcid":"https://orcid.org/0000-0001-6670-1393","contributorId":292915,"corporation":false,"usgs":false,"family":"Hoffman","given":"J.","email":"","middleInitial":"Elis","affiliations":[{"id":63072,"text":"Institut für Geologische Wissenschaften, Freie Universität Berlin, 12249 Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":846167,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tani, Kenichiro 0000-0003-3374-8608","orcid":"https://orcid.org/0000-0003-3374-8608","contributorId":292916,"corporation":false,"usgs":false,"family":"Tani","given":"Kenichiro","email":"","affiliations":[{"id":63073,"text":"Department of Geology and Palaeontology, National Museum of Nature and Science, Japan","active":true,"usgs":false}],"preferred":false,"id":846168,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Allen, Charlotte M. 0000-0002-7288-6758","orcid":"https://orcid.org/0000-0002-7288-6758","contributorId":292917,"corporation":false,"usgs":false,"family":"Allen","given":"Charlotte","email":"","middleInitial":"M.","affiliations":[{"id":63074,"text":"Research School of Earth Sciences, The Australian National University, Canberra, ACT 0200, Australia","active":true,"usgs":false}],"preferred":false,"id":846169,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Munker, Carsten 0000-0001-6406-559X","orcid":"https://orcid.org/0000-0001-6406-559X","contributorId":292918,"corporation":false,"usgs":false,"family":"Munker","given":"Carsten","email":"","affiliations":[{"id":63070,"text":"Institut für Geologie und Mineralogie, University of Cologne, 50674 Köln, Germany","active":true,"usgs":false}],"preferred":false,"id":846170,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70222925,"text":"70222925 - 2022 - Mature diffuse tectonic block boundary revealed by the 2020 southwestern Puerto Rico seismic sequence","interactions":[],"lastModifiedDate":"2022-03-23T15:27:18.978702","indexId":"70222925","displayToPublicDate":"2022-02-08T10:14:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Mature diffuse tectonic block boundary revealed by the 2020 southwestern Puerto Rico seismic sequence","docAbstract":"

Distributed faulting typically tends to coalesce into one or a few faults with repeated deformation. The progression of clustered medium-sized (≥Mw4.5) earthquakes during the 2020 seismic sequence in southwestern Puerto Rico (SWPR), modeling shoreline subsidence from InSAR, and sub-seafloor mapping by high-resolution seismic reflection profiles, suggest that the 2020 SWPR seismic sequence was distributed across several short intersecting strike-slip and normal faults beneath the insular shelf and upper slope of Guayanilla submarine canyon. Multibeam bathymetry map of the seafloor shows significant erosion and retreat of the shelf edge in the area of seismic activity as well as slope-parallel lineaments and submarine canyon meanders that typically develop over geological time. The T-axis of the moderate earthquakes further matches the extension direction previously measured on post early Pliocene (∼>3 Ma) faults. We conclude that although similar deformation has likely taken place in this area during recent geologic time, it does not appear to have coalesced during this time. The deformation may represent the southernmost part of a diffuse boundary, the Western Puerto Rico Deformation Boundary, which accommodates differential movement between the Puerto Rico and Hispaniola arc blocks. This differential movement is possibly driven by the differential seismic coupling along the Puerto Rico—Hispaniola subduction zone. We propose that the compositional heterogeneity across the island arc retards the process of focusing the deformation into a single fault. Given the evidence presented here, we should not expect a single large event in this area but similar diffuse sequences in the future.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021TC006896","usgsCitation":"ten Brink, U., Vanacore, L., Fielding, E.J., Chaytor, J., Lopez-Venegas, A., Baldwin, W.E., Foster, D.S., and Andrews, B.D., 2022, Mature diffuse tectonic block boundary revealed by the 2020 southwestern Puerto Rico seismic sequence: Tectonics, v. 41, no. 3, e2021TC006896, 18 p., https://doi.org/10.1029/2021TC006896.","productDescription":"e2021TC006896, 18 p.","ipdsId":"IP-129343","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":448860,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021tc006896","text":"External Repository"},{"id":435976,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96GY6TQ","text":"USGS data release","linkHelpText":"Multichannel seismic-reflection and navigation data collected using SIG ELC1200 and Applied Acoustics Delta Sparkers and Geometrics GeoEel digital streamers during USGS field activity 2020-014-FA."},{"id":397463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Caribbean Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.6630859375,\n 13.752724664396988\n ],\n [\n -64.4677734375,\n 13.752724664396988\n ],\n [\n -64.4677734375,\n 21.12549763660628\n ],\n [\n -74.6630859375,\n 21.12549763660628\n ],\n [\n -74.6630859375,\n 13.752724664396988\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-02-28","publicationStatus":"PW","contributors":{"authors":[{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":820819,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanacore, L","contributorId":263421,"corporation":false,"usgs":false,"family":"Vanacore","given":"L","email":"","affiliations":[{"id":53976,"text":"Dept. of Geology, U. of Puerto Rico, Mayaguez, PR","active":true,"usgs":false}],"preferred":false,"id":820820,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fielding, E. 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