{"pageNumber":"146","pageRowStart":"3625","pageSize":"25","recordCount":41054,"records":[{"id":70241164,"text":"70241164 - 2023 - Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA","interactions":[],"lastModifiedDate":"2023-03-14T11:41:46.391597","indexId":"70241164","displayToPublicDate":"2023-02-10T06:39:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the predicted burn probabilities with decadal housing density. We then compared the predicted burn probabilities and risk across the study area with observed values and quantified trends. Finally, we evaluated how housing growth and changes in burn probability influenced risk individually and combined. Fires burned 9055 km<sup>2</sup><span>&nbsp;</span>and exposed more than 8500 homes from 1990 to 2019. Observed burned area increased 632% from the 1990s to the 2000s, which combined with housing growth, resulted in a 1342% increase in homes exposed. Increases continued in the 2010s but at lower rates; burned area by 65% and exposure by 32%. The random forests model had excellent fit and high correlation with observations (AUC = 0.88 and<span>&nbsp;</span><i>r</i> = 0.9). Observed values were within the 95% uncertainty interval for all years except 2016 (burned area) and 2000 (exposure). However, our model overpredicted in years with low observed burned area and underpredicted in years with high observed burned area. Overpredictions in risk resulted in lower rates of change in predicted risk compared with change in observed exposure. Increases in risk between the 1990s and 2000s were primarily due to warmer and drier weather conditions and secondarily because of housing growth. However, increases between the 2000s and 2010s were primarily due to housing growth. Our modeling approach identifies spatial and temporal patterns of wildfire potential and risk, which is critical information to guide decision-making. Because the drivers behind risk shift over time, strategies to mitigate risk may need to account for multiple drivers simultaneously.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4403","usgsCitation":"Hawbaker, T., Henne, P., Vanderhoof, M.K., Carlson, A., Mockrin, M.H., and Radeloff, V., 2023, Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA: Ecosphere, v. 14, no. 2, e4403, 21 p., https://doi.org/10.1002/ecs2.4403.","productDescription":"e4403, 21 p.","ipdsId":"IP-135971","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":444510,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4403","text":"Publisher Index Page"},{"id":435460,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9237EQ3","text":"USGS data release","linkHelpText":"Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains, USA (data release)"},{"id":414083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Wyoming","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -109.2317128626994,\n              35.58851540437456\n            ],\n            [\n              -104.39978051410459,\n              35.58851540437456\n            ],\n            [\n              -104.39978051410459,\n              41.88580422682267\n            ],\n            [\n              -109.2317128626994,\n              41.88580422682267\n            ],\n            [\n              -109.2317128626994,\n              35.58851540437456\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":866324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":866325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":866326,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson, Amanda R. 0000-0002-0450-2636","orcid":"https://orcid.org/0000-0002-0450-2636","contributorId":195661,"corporation":false,"usgs":false,"family":"Carlson","given":"Amanda R.","affiliations":[],"preferred":false,"id":866327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mockrin, Miranda H.","contributorId":211622,"corporation":false,"usgs":false,"family":"Mockrin","given":"Miranda","email":"","middleInitial":"H.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":866328,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Radeloff, Volker C.","contributorId":294405,"corporation":false,"usgs":false,"family":"Radeloff","given":"Volker C.","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":866329,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70240715,"text":"70240715 - 2023 - High winds and melting sea ice trigger landward movement in a polar bear population of concern","interactions":[],"lastModifiedDate":"2023-02-16T12:38:31.852988","indexId":"70240715","displayToPublicDate":"2023-02-10T06:35:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"High winds and melting sea ice trigger landward movement in a polar bear population of concern","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Some animal species are responding to climate change by altering the timing of events like mating and migration. Such behavioral plasticity can be adaptive, but it is not always. Polar bears (<i>Ursus maritimus</i>) from the southern Beaufort Sea subpopulation have mostly remained on ice year-round, but as the climate warms and summer sea ice declines, a growing proportion of the subpopulation is summering ashore. The triggers of this novel behavior are not well understood. Our study uses a parametric time-to-event model to test whether biological and/or time-varying environmental variables thought to influence polar bear movement and habitat selection also drive decisions to swim ashore. We quantified the time polar bears spent occupying offshore sea ice of varying ice concentrations. We evaluated variations in the ordinal date bears moved to land with respect to local environmental conditions such as sea ice concentration and wind across 10 years (2005–2015). Results from our study suggest that storm events (i.e., sustained high wind speeds) may force polar bears from severely degraded ice habitat and catalyze seasonal movements to land. Unlike polar bears long adapted to complete summer ice melt, southern Beaufort Sea bears that summer ashore appear more tolerant of poor-quality sea ice habitat and are less willing to abandon it. Our findings provide a window into emergent, climatically mediated behavior in an Arctic marine mammal vulnerable to rapid habitat decline.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4420","usgsCitation":"Kellner, A., Atwood, T.C., Douglas, D.C., Breck, S., and Wittemyer, G., 2023, High winds and melting sea ice trigger landward movement in a polar bear population of concern: Ecosphere, v. 14, no. 2, e4420, 16 p., https://doi.org/10.1002/ecs2.4420.","productDescription":"e4420, 16 p.","ipdsId":"IP-136818","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":444513,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4420","text":"Publisher Index Page"},{"id":413124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -156.78503805536766,\n              71.01233260482948\n            ],\n            [\n              -150.7656435404558,\n              69.43088703799009\n            ],\n            [\n              -145.27965163875427,\n              69.0464450592834\n            ],\n            [\n              -140.87264284738143,\n              69.52036239243833\n            ],\n            [\n              -141.1898528331863,\n              70.60450287797403\n            ],\n            [\n              -146.26625965461366,\n              70.68683273008907\n            ],\n            [\n              -151.032794691366,\n              71.13547502010817\n            ],\n            [\n              -155.69745862420342,\n              71.45995688648216\n            ],\n            [\n              -156.78503805536766,\n              71.01233260482948\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Kellner, Annie","contributorId":302415,"corporation":false,"usgs":false,"family":"Kellner","given":"Annie","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":864408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":864409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":864410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Breck, Stewart","contributorId":199403,"corporation":false,"usgs":false,"family":"Breck","given":"Stewart","affiliations":[],"preferred":false,"id":864411,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wittemyer, George","contributorId":198621,"corporation":false,"usgs":false,"family":"Wittemyer","given":"George","email":"","affiliations":[],"preferred":false,"id":864412,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240442,"text":"sir20225127 - 2023 - Status and understanding of groundwater quality in the Redding–Red Bluff shallow aquifer study unit, 2019—California GAMA priority basin project","interactions":[],"lastModifiedDate":"2026-02-24T17:54:15.206636","indexId":"sir20225127","displayToPublicDate":"2023-02-09T13:32:20","publicationYear":"2023","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":"2022-5127","displayTitle":"Status and Understanding of Groundwater Quality in the Redding–Red Bluff Shallow Aquifer Study Unit, 2019: California GAMA Priority Basin Project","title":"Status and understanding of groundwater quality in the Redding–Red Bluff shallow aquifer study unit, 2019—California GAMA priority basin project","docAbstract":"<p>Groundwater quality in the north Sacramento Valley (NSV) was studied in the Redding–Red Bluff shallow aquifer study unit (referred to as the NSV shallow aquifer or NSV-SA) as part of the Priority Basin Project (PBP) of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is in Shasta and Tehama Counties and included two physiographic study areas: (1) the Redding area to the north and (2) the Red Bluff area to the south. The study was focused on groundwater resources used for domestic drinking-water supply, which are mostly drawn from shallower parts of aquifer systems than those of groundwater resources used for public drinking-water supply in the same area. This assessment characterized the quality of ambient groundwater in the aquifer before filtration or treatment, rather than the quality of drinking water delivered to the tap.<br>The water-quality evaluation in this study has three components: (1) a status assessment, which characterized the quality of the groundwater resources used for domestic supply for 2018–19, in reference to state and national benchmarks; (2) an understanding assessment, which evaluated the natural and human factors potentially affecting water quality in those resources; and (3) a comparison between the groundwater resources used for domestic supply and those used for public supply in the region.<br>The status assessment was based on data collected from 50 sites sampled by the U.S. Geological Survey for the GAMA-PBP in 2018–19. To provide context for the measured concentrations of groundwater constituents compared to U.S. Environmental Protection Agency and California State Water Resources Control Board Division of Drinking Water regulatory and non-regulatory benchmarks for drinking-water quality, relative concentrations (RCs) of groundwater constituents were calculated as the concentration in a sample divided by the respective benchmark. Health-based benchmarks include regulatory and non-regulatory human-health benchmarks such as a maximum contaminant level, notification level, or health-based screening level. Aesthetic-based benchmarks are regulatory or non-regulatory non-health-based benchmarks that can affect the color or taste of water. A grid-based method was used to estimate the proportions of the groundwater resources used for domestic drinking wells that have water-quality constituents below (low), approaching (moderate, greater than half the benchmark), or above (high) benchmark concentrations. This method provides statistically unbiased results at the study-area scale and permits comparisons to other GAMA-PBP study areas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225127","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","usgsCitation":"Harkness, J.S., 2023, Status and understanding of groundwater quality in the Redding–Red Bluff shallow aquifer study unit, 2019—California GAMA priority basin project: U.S. Geological Survey Scientific Investigations Report 2022–5127, 76 p., https://doi.org/10.3133/sir20225127.","productDescription":"Report: xii, 76 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-127139","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":412847,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9XQIWRU","text":"USGS data release","linkHelpText":"Potential explanatory variables for groundwater quality in the Redding–Red Bluff shallow aquifer assessment study unit, 2018–2019—California GAMA Priority Basin Project"},{"id":412842,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5127/coverthb.jpg"},{"id":412843,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5127/sir20225127.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5127"},{"id":412844,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225127/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5127"},{"id":500482,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114339.htm","linkFileType":{"id":5,"text":"html"}},{"id":412846,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5127/sir20225127.XML"},{"id":412845,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5127/images"}],"country":"United States","state":"California","otherGeospatial":"Redding, Red Bluff","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.22608060888808,\n              40.66915109279353\n            ],\n            [\n              -123.22608060888808,\n              38.91419987326245\n            ],\n            [\n              -120.94189440773403,\n              38.91419987326245\n            ],\n            [\n              -120.94189440773403,\n              40.66915109279353\n            ],\n            [\n              -123.22608060888808,\n              40.66915109279353\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"gs-w_opp_nawqa_science_team@usgs.gov\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"gs-w_opp_nawqa_science_team@usgs.gov\">NAWQA Science Team</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive, MS 413<br>Reston, VA 20192–0002</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeologic Setting</li><li>Methods</li><li>Potential Explanatory Variables</li><li>Status and Understanding of Groundwater Quality in the Shallow Aquifer System</li><li>Comparison of Domestic and Public-Supply Aquifer Systems</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Attribution of Potential Explanatory Variables</li></ul>","publishedDate":"2023-02-09","noUsgsAuthors":false,"publicationDate":"2023-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Harkness, Jennifer S. 0000-0001-9050-2570 jharkness@usgs.gov","orcid":"https://orcid.org/0000-0001-9050-2570","contributorId":224299,"corporation":false,"usgs":true,"family":"Harkness","given":"Jennifer","email":"jharkness@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863811,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70240476,"text":"ofr20231006 - 2023 - Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm","interactions":[],"lastModifiedDate":"2026-02-10T21:32:15.228526","indexId":"ofr20231006","displayToPublicDate":"2023-02-08T13:48:38","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1006","displayTitle":"Improving Temporal Frequency of Landsat Surface Temperature Products Using the Gap-Filling Algorithm","title":"Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm","docAbstract":"<p>Remotely sensed surface temperature (ST) has been widely used to monitor and assess landscape thermal conditions, hydrologic modeling, and surface energy balance. Landsat thermal sensors have continuously measured the Earth surface thermal radiance since August 1982. The thermal radiance measurements are atmospherically compensated and converted to Landsat STs and delivered as part of the U.S. Geological Survey Landsat Collection 1 U.S. Analysis Ready Data; however, the low satellite revisit cycles combined with the presence of clouds and cloud shadows reduce the number of valid retrievals. This reduction can limit the ability to monitor annual or seasonal variations in the surface thermal budget. These factors reduce the ability to use the temperature data to fit time series for historical trend analysis to match background climate variations. In this study, we implemented an approach that uses linear harmonic least absolute shrinkage and selection operator regression models to fill gaps because of clouds, shadows, and coarse temporal resolution. The gap-filled data provide increased temporal density of Landsat ST records. The gap-filled Landsat ST, therefore, can allow for an improved monitoring of annual, seasonal, or even monthly landscape thermal conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231006","usgsCitation":"Xian, G., Shi, H., Arab, S., Mueller, C., Hussain, R., Sayler, K., and Howard, D., 2023, Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm: U.S. Geological Survey Open-File Report 2023–1006, 15 p., https://doi.org/10.3133/ofr20231006.","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-144337","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":412873,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1006/images"},{"id":412872,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1006/ofr20231006.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":412871,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1006/ofr20231006.pdf","text":"Report","size":"41.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1006"},{"id":412880,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231006/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412870,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1006/coverthb.jpg"},{"id":499732,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114340.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Atlanta","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.9318883744094,\n              34.338976979151155\n            ],\n            [\n              -84.9318883744094,\n              33.376859208686255\n            ],\n            [\n              -83.70224614831253,\n              33.376859208686255\n            ],\n            [\n              -83.70224614831253,\n              34.338976979151155\n            ],\n            [\n              -84.9318883744094,\n              34.338976979151155\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a><br>U.S. Geological Survey<br>47914 252nd Street<br>Sioux Falls, SD 57198</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Enhancement of Temporal Density of Landsat Surface Temperature Data</li><li>Results for Gap-Filled Surface Temperature Data</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-02-08","noUsgsAuthors":false,"publicationDate":"2023-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":863892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shi, Hua 0000-0001-7013-1565","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":300281,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":863893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arab, Saeed 0000-0003-1602-8801","orcid":"https://orcid.org/0000-0003-1602-8801","contributorId":299964,"corporation":false,"usgs":false,"family":"Arab","given":"Saeed","email":"","affiliations":[{"id":61731,"text":"KBR","active":true,"usgs":false}],"preferred":false,"id":863894,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mueller, Chase 0000-0002-9948-1304","orcid":"https://orcid.org/0000-0002-9948-1304","contributorId":302266,"corporation":false,"usgs":false,"family":"Mueller","given":"Chase","affiliations":[],"preferred":false,"id":863895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hussain, Reza 0000-0002-5445-3027","orcid":"https://orcid.org/0000-0002-5445-3027","contributorId":301245,"corporation":false,"usgs":false,"family":"Hussain","given":"Reza","affiliations":[{"id":65343,"text":"KBR, Contractor to U.S. Geological Survey, Earth Resources Observation and Science (EROS) Center","active":true,"usgs":false}],"preferred":false,"id":863896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sayler, Kristi L. 0000-0003-2514-242X sayler@usgs.gov","orcid":"https://orcid.org/0000-0003-2514-242X","contributorId":2988,"corporation":false,"usgs":true,"family":"Sayler","given":"Kristi","email":"sayler@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":863897,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Howard, Danny 0000-0002-7563-7538 danny.howard.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":176973,"corporation":false,"usgs":true,"family":"Howard","given":"Danny","email":"danny.howard.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":863898,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70262055,"text":"70262055 - 2023 - Perception and trust influence acceptance for black bears more than bear density or conflicts","interactions":[],"lastModifiedDate":"2025-01-10T17:00:40.529559","indexId":"70262055","displayToPublicDate":"2023-02-08T10:37:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9319,"text":"Frontiers in Conservation Science","active":true,"publicationSubtype":{"id":10}},"title":"Perception and trust influence acceptance for black bears more than bear density or conflicts","docAbstract":"<p><strong>Introduction:</strong><span>&nbsp;</span>To sustain black bear (Ursus americanus) populations, wildlife managers should understand the coupled socio-ecological systems that influence acceptance capacity for bears.</p><p><strong>Method:</strong><span>&nbsp;</span>In a study area encompassing a portion of New York State, we spatially matched datasets from three sources: human-bear conflict reports between 2006 and 2018, estimates of local bear density in 2017–2018, and responses to a 2018 property owner survey (n=1,772). We used structural equation modeling to test hypothesized relationships between local human-bear conflict, local bear density, and psychological variables.</p><p><strong>Results:</strong><span>&nbsp;</span>The final model explained 57% of the variance in acceptance. The effect of bear population density on acceptance capacity for bears was relatively small and was mediated by a third variable: perception of proximity to the effects of human-bear interactions. The variables that exerted a direct effect on acceptance were perception of bear-related benefits, perception of bear-related risks, perceived proximity to effects of human-bear interactions, and being a hunter. Perception of bear-related benefits had a greater effect on acceptance than perception of bear-related risks. Perceived proximity to effects of human-bear interactions was affected by local bear density, but also was affected by social trust. Increased social trust had nearly the same effect on perceived proximity as decreased bear density. Social trust had the greatest indirect effect on acceptance of any variable in the model.</p><p><strong>Discussion:</strong><span>&nbsp;</span>Findings suggest wildlife agencies could maintain public acceptance for bears through an integrated approach that combines actions to address bear-related perceptions and social trust along with active management of bear populations.</p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fcosc.2023.1041393","usgsCitation":"Siemer, W., Lauber, T., Stedman, R., Hurst, J., Sun, C., Fuller, A.K., Hollingshead, N., Belant, J., and Kellner, K., 2023, Perception and trust influence acceptance for black bears more than bear density or conflicts: Frontiers in Conservation Science, v. 4, 1041393, 13 p., https://doi.org/10.3389/fcosc.2023.1041393.","productDescription":"1041393, 13 p.","ipdsId":"IP-147449","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467120,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fcosc.2023.1041393","text":"Publisher Index Page"},{"id":466002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.92499168267652,\n              40.760363749644455\n            ],\n            [\n              -73.65063699090229,\n              40.98264101294393\n            ],\n            [\n              -73.6996393039949,\n              41.10089280193728\n            ],\n            [\n              -73.49391688239375,\n              41.2484207881225\n            ],\n            [\n              -73.56250536378525,\n              41.3073292248944\n            ],\n            [\n              -73.48423008439727,\n              42.05372989136586\n            ],\n            [\n              -73.5233960109858,\n              42.126434934459525\n            ],\n            [\n              -73.41562767810787,\n              42.34405165012723\n            ],\n            [\n              -73.83681626701608,\n              42.54652252735795\n            ],\n            [\n              -74.44841929328119,\n              42.6495653802757\n            ],\n            [\n              -75.7909273246029,\n              43.03044245093176\n            ],\n            [\n              -76.43773682001827,\n              43.50144007856014\n            ],\n            [\n              -77.04532365530125,\n              43.25213523900416\n            ],\n            [\n              -78.07429641881241,\n              43.3804649394846\n            ],\n            [\n              -79.06407311309604,\n              43.2521232638133\n            ],\n            [\n              -79.02485730522619,\n              42.98027715144707\n            ],\n            [\n              -78.90726018672747,\n              42.90136300879922\n            ],\n            [\n              -79.08365221595503,\n              42.69283803617958\n            ],\n            [\n              -79.75001378472541,\n              42.331662242956355\n            ],\n            [\n              -79.76953018691533,\n              42.01940417603805\n            ],\n            [\n              -75.3404244202763,\n              41.98299557666223\n            ],\n            [\n              -75.07586228888928,\n              41.75679559693819\n            ],\n            [\n              -75.0464736918644,\n              41.515116258185316\n            ],\n            [\n              -74.78190029599845,\n              41.44169802010788\n            ],\n            [\n              -74.66431063355593,\n              41.3681952398467\n            ],\n            [\n              -73.93913471760371,\n              41.02160483993919\n            ],\n            [\n              -73.92499168267652,\n              40.760363749644455\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"4","noUsgsAuthors":false,"publicationDate":"2023-02-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Siemer, William F.","contributorId":348063,"corporation":false,"usgs":false,"family":"Siemer","given":"William F.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lauber, T. Bruce","contributorId":348064,"corporation":false,"usgs":false,"family":"Lauber","given":"T. Bruce","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stedman, Richard C.","contributorId":348065,"corporation":false,"usgs":false,"family":"Stedman","given":"Richard C.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hurst, Jeremy E.","contributorId":348066,"corporation":false,"usgs":false,"family":"Hurst","given":"Jeremy E.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":922916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Catherine C.","contributorId":348067,"corporation":false,"usgs":false,"family":"Sun","given":"Catherine C.","affiliations":[{"id":36972,"text":"University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":922917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuller, Angela K. 0000-0002-9247-7468 afuller@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-7468","contributorId":3984,"corporation":false,"usgs":true,"family":"Fuller","given":"Angela","email":"afuller@usgs.gov","middleInitial":"K.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":922918,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hollingshead, Nicholas A.","contributorId":348068,"corporation":false,"usgs":false,"family":"Hollingshead","given":"Nicholas A.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":922919,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Belant, Jerrold L.","contributorId":348069,"corporation":false,"usgs":false,"family":"Belant","given":"Jerrold L.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922920,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kellner, Kenneth III","contributorId":348070,"corporation":false,"usgs":false,"family":"Kellner","given":"Kenneth","suffix":"III","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":922921,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70241144,"text":"70241144 - 2023 - Decoupling of species and plant communities of the U.S. Southwest: A CCSM4 climate scenario example","interactions":[],"lastModifiedDate":"2023-03-13T12:14:35.489863","indexId":"70241144","displayToPublicDate":"2023-02-08T07:10:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Decoupling of species and plant communities of the U.S. Southwest: A CCSM4 climate scenario example","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Climate change is predicted to alter the current climate suitability under which plant species and communities occur. Predictions of change have focused on individual species or entire communities, but theory indicates plants will not respond uniformly to climate change within or between communities. We developed models of the current climate suitability (the baseline) of 66 plant species characteristic of 29 plant communities of the arid Southwest, made predictions of climate suitability for the species under two climate change scenarios for the years 2041–2060 (Community Climate System Model version 1.4 [CCSM4] global climate model [GCM], Representative Concentration Pathway [RCP] 4.5 and 8.5 scenarios), and calculated changes in suitability between the future scenarios and baseline for each species. Climate change exposure for the entire community was then evaluated as the composite change of the predicted future climate suitability of the communities' characteristic species. Loss of 25% or more of favorable climate suitability was predicted for 39 (RCP4.5) and 51 (RCP8.5) species within their communities. The proportion of the study area with all species in a community having unfavorable suitability was 17.9% (RCP4.5) and 21.3% (RCP8.5) compared to 6.2% for baseline. We show that suitable climates for species within a plant community are not expected to be a single community-wide trajectory, but rather changes in climate suitability will be unique to the species and not experienced uniformly across the extant communities. This decoupling of plant species within their traditional plant communities may lead to a cascade of unanticipated ecological responses and unprecedented challenges to resource management. Our study results can inform hypotheses of the future successional track of plant communities, characteristic species, and the decisions resource managers must make for management.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4414","usgsCitation":"Thomas, K.A., Stauffer, B.A., and Jarchow, C., 2023, Decoupling of species and plant communities of the U.S. Southwest: A CCSM4 climate scenario example: Ecosphere, v. 14, no. 2, e4414, 17 p., https://doi.org/10.1002/ecs2.4414.","productDescription":"e4414, 17 p.","ipdsId":"IP-129707","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":444527,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4414","text":"Publisher Index Page"},{"id":414011,"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              -104.19194718597245,\n              31.626430047866663\n            ],\n            [\n              -104.19194718597245,\n              42.71940226417041\n            ],\n            [\n              -121.499050325485,\n              42.71940226417041\n            ],\n            [\n              -121.499050325485,\n              31.626430047866663\n            ],\n            [\n              -104.19194718597245,\n              31.626430047866663\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":866261,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stauffer, Brett A. 0000-0003-0028-5731","orcid":"https://orcid.org/0000-0003-0028-5731","contributorId":299753,"corporation":false,"usgs":false,"family":"Stauffer","given":"Brett","email":"","middleInitial":"A.","affiliations":[{"id":64942,"text":"formerly: USGS Southwest Biolgoical Science Center, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":866262,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":866263,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70240691,"text":"70240691 - 2023 - Effect of thermal and mechanical processes on hydraulic transmissivity evolution","interactions":[],"lastModifiedDate":"2023-02-15T13:06:28.62152","indexId":"70240691","displayToPublicDate":"2023-02-08T07:05:10","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Effect of thermal and mechanical processes on hydraulic transmissivity evolution","docAbstract":"Fracture healing is a critical component of enhanced geothermal systems, the earthquake cycle, and induced seismicity. Accordingly, there is significant interest in understanding the process of healing and its effects on fluid transport. The creation, reactivation, and sustainability of fracture networks depend on complex coupling among thermal, hydraulic, mechanical, and chemical processes. We use laboratory slide-hold-slide experiments, at temperatures from 22 to 200 ˚C, to examine effects of fracture reactivation and quasi-static loading on the evolution of fluid transport properties of simulated fractures in Westerly granite. At all temperatures, the in-plane hydraulic transmissivity consistently decays during hold periods resulting in an overall reduction in transmissivity. During the first three to fifteen hours of an experiment, transmissivity decreases rapidly due to the generation of wear products, development of a sliding surface, and compaction of the resulting gouge. Once the sliding surface has developed, the long-term transmissivity decay rate at 22 and 100 ˚C is significantly lower than the transmissivity decay rate during the initial 3 to 15 hours of the experiment. However, at 200 °C, the decay of hydraulic transmissivity remains high throughout the experiment. The long-term decay of hydraulic transmissivity can be fitted with a power law model with more rapid reduction of hydraulic transmissivity at higher temperature. Periods of sliding on the fracture surface result in transient increases in the transmissivity, due to shear dilation, as is expected for Coulomb materials. These transients are superimposed on the long-term decay. When sliding ceases and a new hold period commences, there is a rapid reduction in transmissivity and return to the long-term rate of transmissivity decay. The rate of decay of the transmissivity transients is inversely proportional to temperature, in contrast to the long-term decay and the expected behavior for processes like subcritical crack growth and indentation creep. The higher decay rates that are observed during the initial 3-15 hours of the tests and following sliding, are associated with times that the porosity of the gouge is expected to be high. The difference in decay rates suggests that when the gouge is driven far from equilibrium by active shearing, densification may be dominated by a different mechanism from long-term compaction.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings, 48th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 6-8, 2023","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"48th Workshop on Geothermal Reservoir Engineering Stanford University","conferenceDate":"February 6-8, 2023","conferenceLocation":"Stanford, California","language":"English","publisher":"Sanford University","usgsCitation":"Jeppson, T.N., Lockner, D., Taron, J.M., Moore, D.E., Kilgore, B.D., Beeler, N.M., and Hickman, S.H., 2023, Effect of thermal and mechanical processes on hydraulic transmissivity evolution, <i>in</i> Proceedings, 48th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California, February 6-8, 2023, Stanford, California, February 6-8, 2023, 9 p.","productDescription":"9 p.","ipdsId":"IP-148253","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":413102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413101,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2023/Jeppson.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jeppson, Tamara Nicole 0000-0001-5526-5530","orcid":"https://orcid.org/0000-0001-5526-5530","contributorId":248768,"corporation":false,"usgs":true,"family":"Jeppson","given":"Tamara","email":"","middleInitial":"Nicole","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":864316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockner, David A. 0000-0001-8630-6833","orcid":"https://orcid.org/0000-0001-8630-6833","contributorId":261920,"corporation":false,"usgs":true,"family":"Lockner","given":"David A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":864317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taron, Joshua M. 0000-0003-2719-3917","orcid":"https://orcid.org/0000-0003-2719-3917","contributorId":248769,"corporation":false,"usgs":true,"family":"Taron","given":"Joshua","email":"","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":864318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":864319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kilgore, Brian D. 0000-0003-0530-7979 bkilgore@usgs.gov","orcid":"https://orcid.org/0000-0003-0530-7979","contributorId":3887,"corporation":false,"usgs":true,"family":"Kilgore","given":"Brian","email":"bkilgore@usgs.gov","middleInitial":"D.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":864320,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beeler, Nicholas M. 0000-0002-3397-8481 nbeeler@usgs.gov","orcid":"https://orcid.org/0000-0002-3397-8481","contributorId":2682,"corporation":false,"usgs":true,"family":"Beeler","given":"Nicholas","email":"nbeeler@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":864321,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":864322,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70243870,"text":"70243870 - 2023 - Applications of nonergodic site response models to ShakeAlert case studies in the Los Angeles area","interactions":[],"lastModifiedDate":"2023-05-24T18:23:58.93677","indexId":"70243870","displayToPublicDate":"2023-02-07T13:15:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Applications of nonergodic site response models to ShakeAlert case studies in the Los Angeles area","docAbstract":"<p><span>In this study, we explore whether the&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf29\">Parker and Baltay (2022)</a><span>&nbsp;site response models for the Los Angeles (LA) basin region can improve ground‐motion forecasts in the U.S. Geological Survey ShakeAlert earthquake early warning system (hereafter ShakeAlert). We implement the peak ground acceleration and peak ground velocity site response models of&nbsp;</span><a class=\"link link-ref xref-bibr\" data-modal-source-id=\"rf29\">Parker and Baltay (2022)</a><span>&nbsp;in ShakeAlert via the earthquake information to ground‐motion (hereafter eqinfo2GM) module, which predicts ground motions from the estimated earthquake parameters of magnitude, rupture length, and location. The nonergodic site response models for the greater LA area were developed using ground motions from 414&nbsp;</span><strong>M</strong><span>&nbsp;3–7.3 earthquakes in southern California. We test nonergodic ground‐motion forecasts for five earthquakes in the LA area: the 1994&nbsp;</span><strong>M</strong><span>&nbsp;6.7 Northridge earthquake, the 2008&nbsp;</span><strong>M</strong><span>&nbsp;5.4 Chino Hills earthquake, the 2019&nbsp;</span><strong>M</strong><span>&nbsp;7.1 Ridgecrest earthquake, the 2020&nbsp;</span><strong>M</strong><span>&nbsp;4.5 South El Monte earthquake, and a synthetic&nbsp;</span><strong>M</strong><span>&nbsp;7.8 earthquake on the southern San Andreas fault from the ShakeOut scenario, which was the basis of a statewide emergency response exercise. From the test results, we find that with the nonergodic site response applied, ShakeAlert not only alerts larger areas but can also result in longer warning times in LA region. In addition, the modified Mercalli intensity (MMI) ground‐motion predictions generated by the ShakeAlert eqinfo2GM module are improved in accuracy when compared with the corresponding ShakeMap ground‐truth MMI when the nonergodic site response model is applied.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220145","usgsCitation":"Lin, R., Parker, G.A., McGuire, J., and Baltay Sundstrom, A.S., 2023, Applications of nonergodic site response models to ShakeAlert case studies in the Los Angeles area: Bulletin of the Seismological Society of America, v. 113, no. 3, p. 1324-1343, https://doi.org/10.1785/0120220145.","productDescription":"20 p.","startPage":"1324","endPage":"1343","ipdsId":"IP-142361","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":417403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Los Angeles","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.38078299074152,\n              34.43090673360663\n            ],\n            [\n              -119.38078299074152,\n              33.385811767084306\n            ],\n            [\n              -116.79288709511383,\n              33.385811767084306\n            ],\n            [\n              -116.79288709511383,\n              34.43090673360663\n            ],\n            [\n              -119.38078299074152,\n              34.43090673360663\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"113","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Rongrong 0000-0002-6234-2183","orcid":"https://orcid.org/0000-0002-6234-2183","contributorId":305696,"corporation":false,"usgs":true,"family":"Lin","given":"Rongrong","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":873570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parker, Grace Alexandra 0000-0002-9445-2571","orcid":"https://orcid.org/0000-0002-9445-2571","contributorId":237091,"corporation":false,"usgs":true,"family":"Parker","given":"Grace","email":"","middleInitial":"Alexandra","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":873571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":873572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baltay, Annemarie S. 0000-0002-6514-852X abaltay@usgs.gov","orcid":"https://orcid.org/0000-0002-6514-852X","contributorId":4932,"corporation":false,"usgs":true,"family":"Baltay","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":873573,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70240218,"text":"sim3501 - 2023 - Colored shaded-relief bathymetric map and orthomosaic from structure-from-motion quantitative underwater imaging device with five cameras of the Lake Tahoe floor, California","interactions":[],"lastModifiedDate":"2026-02-19T17:50:10.38879","indexId":"sim3501","displayToPublicDate":"2023-02-07T12:49:09","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3501","displayTitle":"Colored Shaded-Relief Bathymetric Map and Orthomosaic from Structure-from-Motion Quantitative Underwater Imaging Device with Five Cameras of the Lake Tahoe Floor, California","title":"Colored shaded-relief bathymetric map and orthomosaic from structure-from-motion quantitative underwater imaging device with five cameras of the Lake Tahoe floor, California","docAbstract":"<p>This two-sheet publication displays a high-resolution colored shaded-relief bathymetric map (sheet 1) and orthomosaic (sheet 2) of part of the Lake Tahoe floor in California generated from a U.S. Geological Survey towed surface vehicle with multiple downward-looking underwater cameras. The system is named the Structure-from-Motion Quantitative Underwater Imaging Device with Five Cameras (SQUID-5). The cameras were synchronized with each other and with a survey-grade Global Navigation Satellite System. A total of 42,939 photographs were collected with nearly complete overlapping coverage of an area approximately 250 meters by 250 meters. A digital terrain model and an orthomosaic were generated from the overlapping photographs using Structure-from-Motion and photogrammetry techniques. Gaps are present in the bathymetry data owing to data-collection or -processing artifacts. These two sheets display the very fine details of the lake floor mapped using SQUID-5.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3501","usgsCitation":"Hatcher, G.A., Warrick, J.A., and Dartnell, P., 2022, Colored shaded-relief bathymetric map and orthomosaic from structure-from-motion quantitative underwater imaging device with five cameras of the Lake Tahoe floor, California: U.S. Geological Survey Scientific Investigations Map 3501, 2 sheets, scale 1:700, https://doi.org/10.3133/sim3501.","productDescription":"2 Sheets: 35.00 × 34.00 inches; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-139653","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":412576,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9934I6U","text":"USGS data release","description":"USGS data release","linkHelpText":"Point clouds, bathymetric maps, and orthoimagery generated from overlapping lakebed images acquired with the SQUID-5 system near Dollar Point, Lake Tahoe, CA, March 2021"},{"id":412577,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V44ZYS","text":"USGS data release","description":"USGS data release","linkHelpText":"Overlapping lakebed images and associated GNSS locations acquired near Dollar Point, Lake Tahoe, CA, March 2021"},{"id":412573,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3501/coverthb.jpg"},{"id":412574,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3501/sim3501_sheet1.pdf","text":"Sheet 1","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3501 Sheet 1"},{"id":412575,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3501/sim3501_sheet2.pdf","text":"Sheet 2","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3501 Sheet 2"},{"id":500207,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114342.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Lake Tahoe","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.23690229714447,\n              39.300192154621016\n            ],\n            [\n              -120.23690229714447,\n              38.87400239989947\n            ],\n            [\n              -119.8635257065711,\n              38.87400239989947\n            ],\n            [\n              -119.8635257065711,\n              39.300192154621016\n            ],\n            [\n              -120.23690229714447,\n              39.300192154621016\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/pcmsc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/pcmsc\">Pacific Coastal and Marine Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>2885 Mission St.<br>Santa Cruz, CA 95060</p>","publishedDate":"2023-02-07","noUsgsAuthors":false,"publicationDate":"2023-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hatcher, Gerald A. 0000-0001-7705-1509","orcid":"https://orcid.org/0000-0001-7705-1509","contributorId":67586,"corporation":false,"usgs":true,"family":"Hatcher","given":"Gerald A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":862995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warrick, Jonathan A. 0000-0002-0205-3814 jwarrick@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-3814","contributorId":139314,"corporation":false,"usgs":true,"family":"Warrick","given":"Jonathan A.","email":"jwarrick@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":862996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":862997,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70256508,"text":"70256508 - 2023 - Bluegill population demographics as related to abiotic and biotic factors in Florida lakes","interactions":[],"lastModifiedDate":"2024-08-20T16:53:45.611917","indexId":"70256508","displayToPublicDate":"2023-02-07T11:50:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6476,"text":"Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Bluegill population demographics as related to abiotic and biotic factors in Florida lakes","docAbstract":"<p><span>Research on Bluegills,&nbsp;</span><i><span class=\"html-italic\">Lepomis macrochirus</span></i><span>&nbsp;R., is abundant but typically focuses on water bodies with similar environmental conditions. We assessed Bluegill density, relative abundance (catch per unit effort [CPUE] by electrofishing), growth, and size structure in 60 lakes with wide-ranging surface areas (2–12,412 ha), trophic states (oligotrophic–hypereutrophic), and macrophyte abundances (0.3–100 percent of lake volume inhabited [PVI]) across Florida, USA. Bluegill density and CPUE increased with lake productivity and decreased with macrophyte abundance. Bluegill growth increased with lake productivity and CPUE of stock-length Florida Bass,&nbsp;</span><span class=\"html-italic\">Micropterus floridanus</span><span>&nbsp;L., a Bluegill predator. Bluegill size structure increased with lake productivity and decreased with Bluegill density. Results indicate that Bluegill fisheries with abundant individuals of quality size (≥150 mm) require productive (&gt;25 μg/L chlorophyll-</span><span class=\"html-italic\">a</span><span>&nbsp;concentration) lakes with moderate to high macrophyte coverage (PVI 50–100), abundant stock-length Florida Bass (&gt;40 fish/h of electrofishing), and Bluegill densities &lt;300 fish/ha. This study provides an approach to predict Bluegill population demographics based on abiotic and biotic factors, establish fisheries management expectations, and develop regional and lake-specific management tools.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/fishes8020100","usgsCitation":"Carlson, A.K., and Hoyer, M.V., 2023, Bluegill population demographics as related to abiotic and biotic factors in Florida lakes: Fishes, v. 8, no. 2, 100, 19 p., https://doi.org/10.3390/fishes8020100.","productDescription":"100, 19 p.","ipdsId":"IP-139048","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":444546,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes8020100","text":"Publisher Index Page"},{"id":432951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoyer, Mark V.","contributorId":340952,"corporation":false,"usgs":false,"family":"Hoyer","given":"Mark","email":"","middleInitial":"V.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907727,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70254881,"text":"70254881 - 2023 - An evaluation of multistate occupancy models for estimating relative abundance and population trends","interactions":[],"lastModifiedDate":"2024-06-11T16:40:06.367815","indexId":"70254881","displayToPublicDate":"2023-02-07T11:37:06","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of multistate occupancy models for estimating relative abundance and population trends","docAbstract":"<p><span>Detecting spatiotemporal changes in the abundances of organisms is key to effectively conserving species. While indices of abundance have long been used, there has been a shift toward model-based estimators that account for the detection process. Popular approaches including traditional occupancy models and N-mixture models entail tradeoffs. The traditional occupancy approach requires the researcher coarsen the characterization of abundance to the probability that a site is occupied or unoccupied. Conversely, N-mixture models make use of variation in counts, but perform poorly when individuals have low detectability or move into or out of sites between visits. Multistate occupancy models that differentiate relatively abundant from non-abundant states have the potential to fill this gap but have been underexplored. We conducted a simulation study to test whether multistate occupancy models could capture spatial abundance patterns and detect population declines in the face of low individual detection probability (</span><i>p</i><span>&nbsp;≤&nbsp;0.3) and unmodeled heterogeneity (e.g., that arising from individual movement). We considered 10,773 scenarios to examine the effects of differing amounts of heterogeneity as well as alternative study designs, population parameters, and modeling choices. We tracked bias in the proportion of sites estimated to be in the abundant state for single-season models, and power to detect a declining trend across multiple years. We also evaluated data diagnostic metrics to provide guidance to users. Multistate occupancy models were able to differentiate sites with higher abundances from sites with lower abundances when there were at least medium levels of spatial heterogeneity in true abundances. If different sites were randomly selected each year, power to detect even large population declines (65%) was poor (power&nbsp;&lt;&nbsp;0.8). However, if the same sites were surveyed each year, and a dynamic multistate occupancy was used, multistate occupancy models could detect (power&nbsp;≥&nbsp;0.8) relatively small declines (5-40%) in 20% of scenarios, and frequently detect large declines of 45-60% (mean power&nbsp;=&nbsp;0.92). Conservation decisions rely on detecting change reliably, rarely needing absolute abundance information. Multistate occupancy models can improve our ability to detect changing abundance while accommodating low individual detection probability and heterogeneity in count monitoring data.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2023.110303","usgsCitation":"Steen, V., Duarte, A., and Peterson, J., 2023, An evaluation of multistate occupancy models for estimating relative abundance and population trends: Ecological Modelling, v. 478, 110303, 9 p., https://doi.org/10.1016/j.ecolmodel.2023.110303.","productDescription":"110303, 9 p.","ipdsId":"IP-144901","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444548,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2023.110303","text":"Publisher Index Page"},{"id":429891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"478","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Steen, Valerie A. 0000-0002-1417-8139","orcid":"https://orcid.org/0000-0002-1417-8139","contributorId":205994,"corporation":false,"usgs":false,"family":"Steen","given":"Valerie A.","affiliations":[{"id":36710,"text":"University of Connecticut","active":true,"usgs":false}],"preferred":false,"id":902764,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duarte, Adam","contributorId":337608,"corporation":false,"usgs":false,"family":"Duarte","given":"Adam","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":902765,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902766,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70256625,"text":"70256625 - 2023 - Support for the fasting endurance hypothesis of partial migration in a nearshore seabird","interactions":[],"lastModifiedDate":"2024-08-27T15:38:26.036411","indexId":"70256625","displayToPublicDate":"2023-02-07T10:30:25","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Support for the fasting endurance hypothesis of partial migration in a nearshore seabird","docAbstract":"<p><span>Partial migration occurs when only a fraction of a population migrates instead of all individuals. Considered an evolutionary precursor to full migration, understanding why some individuals choose to undertake migration while others do not may serve to inform general migratory theory. While several hypotheses currently exist for explaining the maintenance of partial migration, empirical support for many is limited. To address this gap, we analyzed GPS data acquired from brown pelicans (</span><i>Pelecanus occidentalis</i><span>;&nbsp;</span><i>n</i><span> = 74), a partially migratory seabird, nesting on six colonies in the South Atlantic Bight over the course of four autumn migrations. We estimated that approximately 74% of pelicans nesting within the study area may be migratory on an annual basis, with the remainder staying within the surrounding marine ecoregion year-round. Mean date of migration initiation was 9 November, although movements occurred from September to December. Results from Cox's proportional hazards modeling indicated significant positive and negative effects of sea surface temperatures and body condition on migration rate, respectively. We suggest that the ontogenetic migration of the primary forage species of brown pelicans from estuarine to pelagic environments causes a seasonal reduction in prey and that pelicans in poor body condition are unable to meet the energetic demands potentially associated with this decrease in prey availability (i.e., the fasting endurance hypothesis of partial migration). Although we did not find evidence for a density-dependent migratory response, the effects of intraspecific competition on migration in pelicans also appear to warrant consideration.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4365","usgsCitation":"Wilkinson, B., and Jodice, P.G., 2023, Support for the fasting endurance hypothesis of partial migration in a nearshore seabird: Ecosphere, v. 14, no. 2, e4365, 14 p., https://doi.org/10.1002/ecs2.4365.","productDescription":"e4365, 14 p.","ipdsId":"IP-138118","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":489176,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4365","text":"Publisher Index Page"},{"id":433202,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, South Carolina","otherGeospatial":"Southern Atlantic Bight","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -79.05297920929696,\n              34.03073611807265\n            ],\n            [\n              -81.51071034327317,\n              31.670634225271414\n            ],\n            [\n              -81.44326290770108,\n              30.745131881151735\n            ],\n            [\n              -78.41498319817921,\n              33.68781001381117\n            ],\n            [\n              -79.05297920929696,\n              34.03073611807265\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Wilkinson, Bradley P.","contributorId":341414,"corporation":false,"usgs":false,"family":"Wilkinson","given":"Bradley P.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908374,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70240397,"text":"70240397 - 2023 - A review of common natural disasters as analogs for asteroid impact effects and cascading hazards","interactions":[],"lastModifiedDate":"2023-04-12T13:40:53.119991","indexId":"70240397","displayToPublicDate":"2023-02-07T08:30:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"A review of common natural disasters as analogs for asteroid impact effects and cascading hazards","docAbstract":"<p><span>Modern civilization has no collective experience with possible wide-ranging effects from a medium-sized asteroid impactor. Currently, modeling efforts that predict initial effects from a meteor impact or airburst provide needed information for initial preparation and evacuation plans, but longer-term cascading hazards are not typically considered. However, more common natural disasters, such as volcanic eruptions, earthquakes, wildfires, dust storms, and hurricanes, are likely analogs that can provide the scope and scale of these potential effects. These events, especially the larger events with cascading effects, are key for understanding the scope and complexity of mitigation, relief, and recovery efforts for a medium-sized asteroid impact event. This paper reviews the initial and cascading effects of these natural hazards, describes the state of the art for modeling these hazards, and discusses the relevance of these hazards to expected long-term effects of an asteroid impact. Emergency managers, resource managers and planners, and research scientists involved in mitigation and recovery efforts would likely derive significant benefit from a framework linking multiple hazard models to provide a seamless sequence of related forecasts.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11069-022-05722-z","usgsCitation":"Titus, T.N., Robertson, D., Sankey, J., Mastin, L.G., and Rengers, F.K., 2023, A review of common natural disasters as analogs for asteroid impact effects and cascading hazards: Natural Hazards, v. 116, p. 1355-1402, https://doi.org/10.1007/s11069-022-05722-z.","productDescription":"48 p.","startPage":"1355","endPage":"1402","ipdsId":"IP-134192","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444554,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11069-022-05722-z","text":"Publisher Index Page"},{"id":412812,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"116","noUsgsAuthors":false,"publicationDate":"2023-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":863656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robertson, D. G.","contributorId":178727,"corporation":false,"usgs":false,"family":"Robertson","given":"D. G.","affiliations":[],"preferred":false,"id":863657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Joel B. 0000-0003-3150-4992","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":261248,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":863658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":863659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":863660,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240420,"text":"70240420 - 2023 - From bottom-up to top-down control of invertebrate herbivores in a retrogressive chronosequence","interactions":[],"lastModifiedDate":"2023-03-01T17:24:15.482344","indexId":"70240420","displayToPublicDate":"2023-02-07T08:19:26","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"From bottom-up to top-down control of invertebrate herbivores in a retrogressive chronosequence","docAbstract":"In the long-term absence of disturbance, ecosystems often enter a decline or retrogressive phase which leads to reductions in primary productivity, plant biomass, nutrient cycling and foliar quality. However, the consequences of ecosystem retrogression for higher trophic levels such as herbivores and predators, are less clear. Using a post-fire forested island-chronosequence across which retrogression occurs, we provide evidence that nutrient availability strongly controls invertebrate herbivore biomass when predators are few, but that there is a switch from bottom-up to top-down control when predators are common. This trophic flip in herbivore control probably arises because invertebrate predators respond to alternative energy channels from the adjacent aquatic matrix, which were independent of terrestrial plant biomass. Our results suggest that effects of nutrient limitation resulting from ecosystem retrogression on trophic cascades are modified by nutrient-independent variation in predator abundance, and this calls for a more holistic approach to trophic ecology to better understand herbivore effects on plant communities.","language":"English","publisher":"Wiley","doi":"10.1111/ele.14161","usgsCitation":"Kempel, A., Allan, E., Gossner, M.M., Jochum, M., Grace, J., and Wardle, D., 2023, From bottom-up to top-down control of invertebrate herbivores in a retrogressive chronosequence: Ecology Letters, v. 26, no. 3, p. 411-424, https://doi.org/10.1111/ele.14161.","productDescription":"14 p.","startPage":"411","endPage":"424","ipdsId":"IP-145201","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444558,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ele.14161","text":"Publisher Index Page"},{"id":412811,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sweden","otherGeospatial":"Lake Hornavan, Lake Uddjaure","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              17.753317254270684,\n              65.82375868539958\n            ],\n            [\n              17.84395446130219,\n              65.82938231209414\n            ],\n            [\n              17.89613951989537,\n              65.89116109990525\n            ],\n            [\n              17.967550652708383,\n              65.86871328240625\n            ],\n            [\n              18.04170836755182,\n              65.86422136141547\n            ],\n            [\n              18.033468621457757,\n              65.89789161557204\n            ],\n         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Sciences","active":true,"usgs":false}],"preferred":false,"id":863728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allan, Eric","contributorId":302203,"corporation":false,"usgs":false,"family":"Allan","given":"Eric","email":"","affiliations":[{"id":38843,"text":"University of Bern, Switzerland","active":true,"usgs":false}],"preferred":false,"id":863729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gossner, Martin M.","contributorId":302205,"corporation":false,"usgs":false,"family":"Gossner","given":"Martin","email":"","middleInitial":"M.","affiliations":[{"id":65437,"text":"WSL Swiss Federal Research Institute, Switzerland","active":true,"usgs":false}],"preferred":false,"id":863730,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jochum, Malte","contributorId":302207,"corporation":false,"usgs":false,"family":"Jochum","given":"Malte","email":"","affiliations":[{"id":40802,"text":"German Centre for Integrative Biodiversity Research","active":true,"usgs":false}],"preferred":false,"id":863731,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, James 0000-0001-6374-4726","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":220737,"corporation":false,"usgs":true,"family":"Grace","given":"James","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":863732,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wardle, David A.","contributorId":266150,"corporation":false,"usgs":false,"family":"Wardle","given":"David A.","affiliations":[{"id":54930,"text":"Asian School of the Environment, Nanyang Technological University, 50 Nanyang avenue, Singapore 639798","active":true,"usgs":false}],"preferred":false,"id":863733,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70242017,"text":"70242017 - 2023 - Six years of fluvial response to a large dam removal on the Carmel River, California, USA","interactions":[],"lastModifiedDate":"2023-06-27T16:51:13.29324","indexId":"70242017","displayToPublicDate":"2023-02-07T08:17:40","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Six years of fluvial response to a large dam removal on the Carmel River, California, USA","docAbstract":"<p><span>Measuring river response to dam removal affords a rare, important opportunity to study fluvial response to sediment pulses on a large field scale. We present a before–after/control–impact study of the Carmel River, California, measuring fluvial geomorphic and grain-size evolution over 8 years, six of which postdated removal of a 32 m-high dam (one of the largest dams removed worldwide) and included 11 flow events exceeding the 2-year flood magnitude. We find that the reservoir-sediment pulse following dam removal was relatively small (97 000 ± 24 000 t over 4 years), owing to deliberate reservoir-sediment stabilization. Scaled to the size of the Carmel River watershed and compared against long-term bedrock denudation rates, the post-dam-removal sediment release was slightly less than the annualized long-term sediment export from this basin. New sediment transited &gt;30 km to the river mouth in less than 2 years, assisted by floods 2 and 4 years after dam removal. The sediment pulse fined the downstream riverbed while causing mostly low-magnitude bed-elevation changes: commonly 0.5 to 1 m or smaller, occurring as discontinuous sediment patches or interstitial deposits, aside from the filling and subsequent partial scour of deep pools. There was no major geomorphic reset downstream from the dam site. Geomorphic changes were driven almost entirely by flow rather than by the modest increase in sediment supply, in contrast to recent examples from other large dam removals. The relatively minor disturbance caused by dam removal on the Carmel River is likely analogous to many future dam removals: a relatively small sediment pulse after deliberate limitation of reservoir-sediment erosion, and with an upstream dam remaining in place. Thus, a large dam removal need not lead to major downstream impacts.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.5561","usgsCitation":"East, A.E., Harrison, L.R., Smith, D.P., Logan, J.B., and Bond, R., 2023, Six years of fluvial response to a large dam removal on the Carmel River, California, USA: Earth Surface Processes and Landforms, v. 48, no. 8, p. 1487-1501, https://doi.org/10.1002/esp.5561.","productDescription":"15 p.","startPage":"1487","endPage":"1501","ipdsId":"IP-146182","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444561,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5561","text":"Publisher Index Page"},{"id":415160,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Carmel River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.62577522165773,\n              36.36105374788829\n            ],\n            [\n              -121.58724434610056,\n              36.40905968854021\n            ],\n            [\n              -121.61843600726598,\n              36.46293870830412\n            ],\n            [\n              -121.750541866319,\n              36.53594773620604\n            ],\n            [\n              -121.8532908678046,\n              36.61551540625254\n            ],\n            [\n              -121.90741757394426,\n              36.588265345279865\n            ],\n            [\n              -121.93261880515863,\n              36.54806169091083\n            ],\n            [\n              -121.88413981443409,\n              36.520771377870034\n            ],\n            [\n              -121.79850327393265,\n              36.50047233869989\n            ],\n            [\n              -121.7839886060512,\n              36.469663631874326\n            ],\n            [\n              -121.74712134963194,\n              36.40894399256348\n            ],\n            [\n              -121.68209557572075,\n              36.36804816657221\n            ],\n            [\n              -121.62606895769773,\n              36.3610353099688\n            ],\n            [\n              -121.62577522165773,\n              36.36105374788829\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":868544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrison, Lee R.","contributorId":174322,"corporation":false,"usgs":false,"family":"Harrison","given":"Lee","email":"","middleInitial":"R.","affiliations":[{"id":6710,"text":"University of California, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":868545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Douglas P.","contributorId":201716,"corporation":false,"usgs":false,"family":"Smith","given":"Douglas","email":"","middleInitial":"P.","affiliations":[{"id":35924,"text":"California State University, Monterey Bay","active":true,"usgs":false}],"preferred":false,"id":868546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":868547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bond, Rosealea","contributorId":201717,"corporation":false,"usgs":false,"family":"Bond","given":"Rosealea","affiliations":[{"id":12520,"text":"NOAA National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":868548,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70246694,"text":"70246694 - 2023 - Upwelling, climate change, and the shifting geography of coral reef development","interactions":[],"lastModifiedDate":"2023-07-17T12:20:56.213839","indexId":"70246694","displayToPublicDate":"2023-02-07T07:18:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Upwelling, climate change, and the shifting geography of coral reef development","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The eastern tropical Pacific is oceanographically unfavorable for coral-reef development. Nevertheless, reefs have persisted there for the last 7000&nbsp;years. Rates of vertical accretion during the Holocene have been similar in the strong-upwelling Gulf of Panamá (GoP) and the adjacent, weak-upwelling Gulf of Chiriquí (GoC); however, seasonal upwelling in the GoP exacerbated a climate-driven hiatus in reef development in the late Holocene. The situation is now reversed and seasonal upwelling in the GoP currently buffers thermal stress, creating a refuge for coral growth. We developed carbonate budget models to project the capacity of reefs in both gulfs to keep up with future sea-level rise. On average, the GoP had significantly higher net carbonate production rates than the GoC. With an estimated contemporary reef-accretion potential (RAP) of 5.5&nbsp;mm&nbsp;year<sup>−1</sup>, reefs in the GoP are projected to be able to keep up with sea-level rise if CO<sub>2</sub><span>&nbsp;</span>emissions are reduced, but not under current emissions trajectories. With an estimated RAP of just 0.3&nbsp;mm&nbsp;year<sup>−1</sup>, reefs in the GoC are likely already unable to keep up with contemporary sea-level rise in Panamá (1.4&nbsp;mm&nbsp;year<sup>−1</sup>). Whereas the GoP has the potential to support functional reefs in the near-term, our study indicates that their long-term persistence will depend on reduction of greenhouse gases.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-28489-0","usgsCitation":"Rodriguez-Ruano, V., Toth, L., Enochs, I.C., Randall, C.J., and Aronson, R.B., 2023, Upwelling, climate change, and the shifting geography of coral reef development: Scientific Reports, v. 13, 1770, 15 p., https://doi.org/10.1038/s41598-023-28489-0.","productDescription":"1770, 15 p.","ipdsId":"IP-142612","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444566,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-28489-0","text":"Publisher Index Page"},{"id":418999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Panama","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -79.44492355404331,\n              8.765703725009672\n            ],\n            [\n              -79.44492355404331,\n              7.896453925071583\n            ],\n            [\n              -78.41265160945854,\n              7.896453925071583\n            ],\n            [\n              -78.41265160945854,\n              8.765703725009672\n            ],\n            [\n              -79.44492355404331,\n              8.765703725009672\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.40995999061637,\n              7.983464633908511\n            ],\n            [\n              -82.40995999061637,\n              7.0035723559191325\n            ],\n            [\n              -81.15805571739662,\n              7.0035723559191325\n            ],\n            [\n              -81.15805571739662,\n              7.983464633908511\n            ],\n            [\n              -82.40995999061637,\n              7.983464633908511\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2023-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Rodriguez-Ruano, Victor","contributorId":316663,"corporation":false,"usgs":false,"family":"Rodriguez-Ruano","given":"Victor","email":"","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":878013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":878014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Enochs, Ian C.","contributorId":181746,"corporation":false,"usgs":false,"family":"Enochs","given":"Ian","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":878015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Randall, Carly J. 0000-0001-8112-3552","orcid":"https://orcid.org/0000-0001-8112-3552","contributorId":212696,"corporation":false,"usgs":false,"family":"Randall","given":"Carly","email":"","middleInitial":"J.","affiliations":[{"id":32935,"text":"Australian Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":878016,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aronson, Richard B. 0000-0003-0383-3844","orcid":"https://orcid.org/0000-0003-0383-3844","contributorId":212695,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","email":"","middleInitial":"B.","affiliations":[{"id":17748,"text":"Florida Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":878017,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240733,"text":"70240733 - 2023 - Stabilising effects of karstic groundwater on stream fish communities","interactions":[],"lastModifiedDate":"2023-06-09T15:07:23.012484","indexId":"70240733","displayToPublicDate":"2023-02-07T06:52:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Stabilising effects of karstic groundwater on stream fish communities","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Although groundwater exchange processes are known to modulate atmospheric influences on stream temperature and flow, the implications for ecological stability are poorly understood. Here, we evaluated temporal change in stream fish communities across a gradient of groundwater influence defined by karst terrain (carbonate parent materials) within the Potomac River basin of eastern North America. We surveyed 12 sites in 2022 that had been sampled 29–30 years previously with similar methods. We also collected stream temperature data from each site and used the regression slope of the air-water temperature relationship to index stream thermal sensitivity and groundwater exchange processes. Sites in karst terrain exhibited strong groundwater controls on stream temperature, and fish communities were more stable over time in these locations than elsewhere. However, stream thermal sensitivity was a stronger predictor of species persistence than the spatial distribution of karst terrain in contributing areas, highlighting the ecological importance of local variation in groundwater discharge processes. The presence of calcium precipitates (marl) in stream substrates was associated with low thermal sensitivity and ecological stability over time, and we suggest such visible features may be a useful indicator of climate change refugia in stream ecosystems.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1111/eff.12705","usgsCitation":"Hitt, N.P., Rogers, K.M., Kessler, K.G., Briggs, M., and Fair, J.H., 2023, Stabilising effects of karstic groundwater on stream fish communities: Ecology of Freshwater Fish, v. 32, no. 3, p. 538-551, https://doi.org/10.1111/eff.12705.","productDescription":"14 p.","startPage":"538","endPage":"551","ipdsId":"IP-147077","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444573,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12705","text":"Publisher Index Page"},{"id":413165,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":238185,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":864580,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogers, Karli M. 0000-0002-6188-7405","orcid":"https://orcid.org/0000-0002-6188-7405","contributorId":237955,"corporation":false,"usgs":true,"family":"Rogers","given":"Karli","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":864581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kessler, Karmann G. 0000-0001-5681-4909","orcid":"https://orcid.org/0000-0001-5681-4909","contributorId":242765,"corporation":false,"usgs":true,"family":"Kessler","given":"Karmann","email":"","middleInitial":"G.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":864582,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":864583,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fair, Jennifer H. 0000-0002-9902-1893","orcid":"https://orcid.org/0000-0002-9902-1893","contributorId":245941,"corporation":false,"usgs":true,"family":"Fair","given":"Jennifer","middleInitial":"H.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":864584,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240475,"text":"70240475 - 2023 - When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates","interactions":[],"lastModifiedDate":"2023-11-08T16:48:35.179325","indexId":"70240475","displayToPublicDate":"2023-02-07T06:48:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates","docAbstract":"<p id=\"spara021\">Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates.</p><p id=\"spara022\">Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (<i>i.e.,</i><span>&nbsp;</span>weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network.</p><p id=\"spara023\">We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score &lt; 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (<i>i.e.,</i><span>&nbsp;</span>training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (<i>e.g.,</i><span>&nbsp;</span>XGBoost) perform equally well or better than more complex methods (<i>e.g.,</i><span>&nbsp;</span>artificial neural networks) and remain easier to interpret.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2023.102662","usgsCitation":"Mordensky, S.P., Lipor, J., DeAngelo, J., Burns, E., and Lindsey, C.R., 2023, When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates: Geothermics, v. 110, 102662, 22 p., https://doi.org/10.1016/j.geothermics.2023.102662.","productDescription":"102662, 22 p.","ipdsId":"IP-142531","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":444577,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2023.102662","text":"Publisher Index Page"},{"id":435466,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V1Q9XM","text":"USGS data release","linkHelpText":"Geothermal resource favorability: select features and predictions for the western United States curated for DOI 10.1016/j.geothermics.2023.102662"},{"id":412868,"rank":1,"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              -127.12518216384296,\n              49.86387644792583\n            ],\n            [\n              -127.12518216384296,\n              31.096405781605768\n            ],\n            [\n              -102.87766710543923,\n              31.096405781605768\n            ],\n            [\n              -102.87766710543923,\n              49.86387644792583\n            ],\n            [\n              -127.12518216384296,\n              49.86387644792583\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"110","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":863887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsey, Cary Ruth 0000-0001-5693-9664","orcid":"https://orcid.org/0000-0001-5693-9664","contributorId":292016,"corporation":false,"usgs":true,"family":"Lindsey","given":"Cary","email":"","middleInitial":"Ruth","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":863890,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240262,"text":"sir20225128 - 2023 - Groundwater quality near the Montebello Oil Field, Los Angeles County, California","interactions":[],"lastModifiedDate":"2023-09-18T19:56:22.528962","indexId":"sir20225128","displayToPublicDate":"2023-02-06T13:11:18","publicationYear":"2023","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":"2022-5128","displayTitle":"Groundwater Quality Near the Montebello Oil Field, Los Angeles County, California","title":"Groundwater quality near the Montebello Oil Field, Los Angeles County, California","docAbstract":"<p>Groundwater quality and potential sources and migration pathways of chemical constituents associated with hydrocarbon-bearing formations were assessed by the U.S. Geological Survey for the California State Water Resources Control Board Oil and Gas Regional Monitoring Program (RMP). Groundwater samples were collected as part of the RMP from 21 preexisting wells used for public supply, monitoring, or irrigation in and near the Montebello Oil Field and analyzed for constituents associated with hydrocarbon-bearing formations and constituents used to identify recently recharged groundwater and older groundwater. The newly collected RMP data were supplemented with historical sample data from 849 groundwater wells and analyzed with respect to explanatory factors that have the potential to influence water quality. Potential sources and migration pathways of fluids (water, gas, or oil) from hydrocarbon-bearing formations that could affect groundwater quality in the Montebello Oil Field include large volumes of recycled produced water (water withdrawn from an oil well and brought to the surface that may include oil, water, and gas from the geologic formation and water or gas injected for enhanced recovery) that have been reinjected since the 1960s to enhance oil production, oil and gas wells with well-integrity issues, and oil and gas wells with an uncemented annulus that intersects groundwater resource zones.<br>Trace amounts of dissolved petroleum hydrocarbons, thermogenic gas (propane through pentane range), or both, were detected in seven groundwater samples collected in 2014 and 2018 as part of the RMP. Five of those samples also contained manufactured volatile organic compounds and at least some modern-age groundwater (recharged during or after 1953), indicating that the hydrocarbons could have originated from surficial, or shallow, sources unrelated to oil and gas development. Two samples contained low concentrations of petroleum hydrocarbons (less than 0.1 microgram per liter) and did not contain detections of manufactured volatile organic compounds in pre-modern groundwater. These samples were collected from relatively deep wells (greater than 140 meters below land surface) with perforations completed in marine sediments that may contain water with similar compositions to produced water.<br>The RMP sample results and available historical data in and near the Montebello Oil Field did not provide conclusive evidence that oil and gas development has adversely affected groundwater resources. All samples with detectable petroleum hydrocarbons, thermogenic gases, or both, were collected from sites that also are within 500 meters of anthropogenic hydrocarbon sources not associated with oil and gas development or sources. In addition, naturally occurring sources of hydrocarbons that exist at intervals shallower than, or are in areas outside of, economically productive oil- and gas-producing zones could affect groundwater quality.<br>A definitive analysis of relations of groundwater quality to potential anthropogenic and natural explanatory factors was not possible because of the low density of new and historical sampling data, particularly in parts of the Montebello Oil Field where the largest relative risks to groundwater from hydrocarbon-bearing formations exist. Areas to consider for more detailed monitoring and analysis in the future that may present the largest relative potential risks to groundwater quality include (1) areas downgradient from historical surface ponds and sumps and (2) areas with co-located high net injection (oil reservoir injection exceeds production), old oil and gas wells that may be more likely to develop well-integrity issues than newer wells, and oil and gas wells with uncemented boreholes intersecting groundwater zones. To help fill gaps resulting from sparse groundwater wells, temperature and resistivity borehole log data could be analyzed to locate anomalies that identify potential areas where relatively warm or saline water from deeper hydrocarbon-bearing formations is present in groundwater.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225128","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Stanton, J.S., Land, M., Landon, M.K., Shimabukuro, D.H., McMahon, P.B., Davis, T.A., Hunt, A.G., and Sowers, T.A., 2023, Groundwater quality near the Montebello Oil Field, Los Angeles County, California: U.S. Geological Survey Scientific Investigations Report 2022–5128, 80 p., https://doi.org/10.3133/sir20225128.","productDescription":"Report: ix, 80 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-128118","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":412628,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FZ2SBH","text":"USGS data release","description":"USGS data release","linkHelpText":"Water chemistry data for samples collected at groundwater sites in the Montebello Oil Field study area, September 2014–October 2018, Los Angeles County, California"},{"id":412629,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5128/images"},{"id":412627,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225128/full","text":"Reports","linkFileType":{"id":5,"text":"html"},"description":"SIR 2022-5128"},{"id":412626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5128/sir20225128.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5128"},{"id":412625,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5128/coverthb.jpg"},{"id":412630,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5128/sir20225128.XML"}],"country":"United States","state":"California","otherGeospatial":"Montebello Oil Field","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.12,\n              34.04\n            ],\n            [\n              -118.12,\n              34.00\n            ],\n            [\n              -118.02,\n              34.00\n            ],\n            [\n              -118.02,\n              34.04\n            ],\n            [\n              -118.12,\n              34.04\n            ]\n          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jstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-2520-753X","contributorId":830,"corporation":false,"usgs":true,"family":"Stanton","given":"Jennifer","email":"jstanton@usgs.gov","middleInitial":"S.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Land, Michael 0000-0001-5141-0307 mtland@usgs.gov","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":171938,"corporation":false,"usgs":true,"family":"Land","given":"Michael","email":"mtland@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863143,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shimabukuro, David H. 0000-0002-6106-5284","orcid":"https://orcid.org/0000-0002-6106-5284","contributorId":208209,"corporation":false,"usgs":false,"family":"Shimabukuro","given":"David","email":"","middleInitial":"H.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":863144,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863145,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Tracy A. 0000-0003-0253-6661 tadavis@usgs.gov","orcid":"https://orcid.org/0000-0003-0253-6661","contributorId":2715,"corporation":false,"usgs":true,"family":"Davis","given":"Tracy","email":"tadavis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":863146,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":863147,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sowers, Theron A. 0000-0002-3208-5411","orcid":"https://orcid.org/0000-0002-3208-5411","contributorId":301944,"corporation":false,"usgs":false,"family":"Sowers","given":"Theron A.","affiliations":[{"id":37762,"text":"California State University, Sacramento","active":true,"usgs":false}],"preferred":false,"id":863148,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70256526,"text":"70256526 - 2023 - Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models","interactions":[],"lastModifiedDate":"2024-08-22T11:07:08.990132","indexId":"70256526","displayToPublicDate":"2023-02-06T11:29:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18324,"text":"Hydrobiology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models","docAbstract":"<p><span>Stoneflies are a globally threatened aquatic insect order. In Arkansas, a diverse group of winter stonefly (Capniidae:&nbsp;</span><span class=\"html-italic\">Allocapnia</span><span>) have not been surveyed since the 1980s, likely because species-level identification requires the rarely-collected adult form.&nbsp;</span><i><span class=\"html-italic\">Allocapnia mohri</span></i><span>, a regional endemic, was previously commonly found in mountainous, intermittent streams from the Ouachita Mountains ecoregion north to the Ozark Highlands, but no species distributional models including land use or climate variables exist to our knowledge. We collected adults from 71 stream reaches from the historic Arkansas range from November to April 2020 and 2021. We modeled distributions using random forest (RF) models populated with landscape, climate, and both data to determine which were most predictive of species presence. Correlations between landscape or climate variables and presence were examined using multiple logistic regression. The landscape RF models performed better than the climate or landscape + climate RF models.&nbsp;</span><i><span class=\"html-italic\">A. mohri</span></i><span>&nbsp;presence sites tended to have a greater elevation, a lower mean July temperature, and a greater percentage of very slow infiltration soils in the watershed, compared to absence sites.&nbsp;</span><i><span class=\"html-italic\">A. mohri</span></i><span>&nbsp;was absent at the Ouachita Mountains sites and may be experiencing a range contraction or migration northward.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/hydrobiology2010013","usgsCitation":"Annaratone, B., Larson, C., Prater, C., Dowling, A., Magoulick, D.D., and Evans-White, M.A., 2023, Predicting habitat and distribution of an interior highlands regional endemic winter stonefly (Allocapnia mohri) in Arkansas using random forest models: Hydrobiology, v. 2, no. 1, p. 196-211, https://doi.org/10.3390/hydrobiology2010013.","productDescription":"16 p.","startPage":"196","endPage":"211","ipdsId":"IP-148164","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":444581,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrobiology2010013","text":"Publisher Index Page"},{"id":433011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.01694463644638,\n              36.49973760721201\n            ],\n            [\n              -94.64880267254001,\n              36.47406350173745\n            ],\n            [\n              -94.42836217709565,\n              35.38954127077116\n            ],\n            [\n              -94.47263609475836,\n              33.690237372303145\n            ],\n            [\n              -93.92329526083718,\n              33.50875350986783\n            ],\n            [\n              -93.15882305498532,\n              33.95704519399207\n            ],\n            [\n              -92.44070215460535,\n              34.644196725743356\n            ],\n            [\n              -91.1183522293626,\n              35.76377161713451\n            ],\n            [\n              -91.01694463644638,\n              36.49973760721201\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Annaratone, Brianna","contributorId":341024,"corporation":false,"usgs":false,"family":"Annaratone","given":"Brianna","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Camryn","contributorId":341025,"corporation":false,"usgs":false,"family":"Larson","given":"Camryn","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prater, Clay","contributorId":341026,"corporation":false,"usgs":false,"family":"Prater","given":"Clay","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dowling, Ashley","contributorId":341027,"corporation":false,"usgs":false,"family":"Dowling","given":"Ashley","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":907822,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Evans-White, Michelle A.","contributorId":341028,"corporation":false,"usgs":false,"family":"Evans-White","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":907823,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70241253,"text":"70241253 - 2023 - Ice and ocean constraints on early human migrations into North America along the Pacific Coast","interactions":[],"lastModifiedDate":"2023-03-16T13:29:11.876097","indexId":"70241253","displayToPublicDate":"2023-02-06T08:21:29","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Ice and ocean constraints on early human migrations into North America along the Pacific Coast","docAbstract":"<p><span>Founding populations of the first Americans likely occupied parts of Beringia during the Last Glacial Maximum (LGM). The timing, pathways, and modes of their southward transit remain unknown, but blockage of the interior route by North American ice sheets between ~26 and 14 cal kyr BP (ka) favors a coastal route during this period. Using models and paleoceanographic data from the North Pacific,&nbsp;we identify climatically favorable intervals when humans could have plausibly traversed the Cordilleran coastal corridor during the terminal Pleistocene. Model simulations suggest that northward coastal currents strengthened during the LGM and at times of enhanced freshwater input, making southward transit by boat more difficult. Repeated Cordilleran glacial-calving events would have further challenged coastal transit on land and at sea. Following these events, ice-free coastal areas opened and seasonal sea ice was present along the Alaskan margin until at least 15 ka. Given evidence for humans south of the ice sheets by 16 ka and possibly earlier, we posit that early people may have taken advantage of winter sea ice that connected islands and coastal refugia. Marine ice-edge habitats offer a rich food supply and traversing coastal sea ice could have mitigated the difficulty of traveling southward in watercraft or on land over glaciers.&nbsp;We identify 24.5 to 22 ka and 16.4 to 14.8 ka as environmentally favorable time periods for coastal migration, when climate conditions provided both winter sea ice and ice-free summer conditions that facilitated year-round marine resource diversity and multiple modes of mobility along the&nbsp;North Pacific coast.</span></p>","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2208738120","usgsCitation":"Praetorius, S.K., Alder, J.R., Condron, A., Mix, A., Walczak, M., Caissie, B.E., and Erlandson, J., 2023, Ice and ocean constraints on early human migrations into North America along the Pacific Coast: Proceedings of the National Academy of Sciences, v. 120, no. 7, e2208738120, 11 p., https://doi.org/10.1073/pnas.2208738120.","productDescription":"e2208738120, 11 p.","ipdsId":"IP-133916","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":444585,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://archimer.ifremer.fr/doc/00820/93170/","text":"Publisher Index Page"},{"id":435467,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95V8DP2","text":"USGS data release","linkHelpText":"Data release for Ice and ocean constraints on early human migrations into North America along the Pacific coast"},{"id":414279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Pacific Coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.72062762561171,\n              38.37875574725757\n            ],\n            [\n              -119.99459846253501,\n              39.301388384686106\n            ],\n            [\n              -122.4899431341521,\n              50.08880882681328\n            ],\n            [\n              -133.2466928684764,\n              60.77522068257534\n            ],\n            [\n              -146.986168078397,\n              63.47516560131629\n            ],\n            [\n              -159.91403683656446,\n              70.55186684208343\n            ],\n            [\n              -169.5393000094379,\n              69.74709289484804\n            ],\n            [\n              -170.83530973680112,\n              63.391879804034915\n            ],\n            [\n              -179.9,\n              50.520343621759565\n            ],\n            [\n              -156.35796682332455,\n              54.28410261306894\n            ],\n            [\n              -142.96073969458683,\n              58.298844624993336\n            ],\n            [\n              -129.39963004812796,\n              49.10107755766387\n            ],\n            [\n              -126.51878468736493,\n              43.42260588965587\n            ],\n            [\n              -123.72062762561171,\n              38.37875574725757\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"120","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-02-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Praetorius, Summer K. 0000-0003-2683-3652","orcid":"https://orcid.org/0000-0003-2683-3652","contributorId":206966,"corporation":false,"usgs":true,"family":"Praetorius","given":"Summer","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":866663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alder, Jay R. 0000-0003-2378-2853 jalder@usgs.gov","orcid":"https://orcid.org/0000-0003-2378-2853","contributorId":5118,"corporation":false,"usgs":true,"family":"Alder","given":"Jay","email":"jalder@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - 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,{"id":70242966,"text":"70242966 - 2023 - Dynamics of the wave-driven circulation in the lee of nearshore reefs","interactions":[],"lastModifiedDate":"2023-04-25T11:45:54.368684","indexId":"70242966","displayToPublicDate":"2023-02-06T06:41:33","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12811,"text":"JGR-Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of the wave-driven circulation in the lee of nearshore reefs","docAbstract":"<div class=\"article-section__content en main\"><p>Nearshore rocky reefs with scales of order 10–100&nbsp;m are common along the world's coastline and often shape wave-driven hydrodynamics and shoreline morphology in their lee. The interaction of waves with these reefs generally results in either two or four-cell mean circulation systems (2CC and 4CC, respectively), with diverging flows behind the reefs and at the shoreline in the 2CC case and flows that diverge in the lee and converge at the shoreline in the 4CC case. By applying a phase-resolving wave-flow model to conduct a&nbsp;detailed analysis of mean momentum balances for waves interacting with nearshore reefs, we develop an understanding of the drivers of 2CC and 4CC flow dynamics and how they vary for different reef geometries and wave and&nbsp;water&nbsp;level&nbsp;conditions. The 2CC or 4CC patterns were primarily driven by alongshore pressure gradients toward the exposed (nonreef fronted) or reef-fronted beach. These alongshore pressure gradients were dependent on the cross-shore setup dynamics governed by the balance between pressure (i.e., related to the setup) and radiation stress gradients, and mean bottom stresses exerted on the water column. If shoreline wave setup in the lee of the reef was less than the exposed beach, a 4CC pattern developed with convergent flow at the shoreline in the lee of the reef; otherwise, a 2CC emerged with divergent flow at the shoreline. Across the parameter space investigated, reef roughness, distance to the shoreline, and beach slope were the three parameters most likely to change the flow patterns between 2CC and 4CC.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JC019013","usgsCitation":"da Silva, R.F., Hansen, J., Lowe, R., Rijnsdorp, D.P., and Buckley, M.L., 2023, Dynamics of the wave-driven circulation in the lee of nearshore reefs: JGR-Oceans, v. 128, no. 3, e2022JC019013, 25 p., https://doi.org/10.1029/2022JC019013.","productDescription":"e2022JC019013, 25 p.","ipdsId":"IP-139998","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":444590,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jc019013","text":"Publisher Index Page"},{"id":416227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-02-24","publicationStatus":"PW","contributors":{"authors":[{"text":"da Silva, Renan F.","contributorId":304414,"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":870367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Jeff","contributorId":304415,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":870368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowe, Ryan","contributorId":304417,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":870370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rijnsdorp, Dirk P.","contributorId":304416,"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":870369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":870371,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70262362,"text":"70262362 - 2023 - Birth rates and neonate survival in a parasite rich moose population in Vermont, USA","interactions":[],"lastModifiedDate":"2025-01-23T15:49:46.104582","indexId":"70262362","displayToPublicDate":"2023-02-05T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":693,"text":"Alces","active":true,"publicationSubtype":{"id":10}},"title":"Birth rates and neonate survival in a parasite rich moose population in Vermont, USA","docAbstract":"<p><span>Moose (</span><i>Alces alces</i><span>) populations are declining across much of their southern geographic range in North America. In Vermont and other northeastern states, measurable declines are attributed to low calf survival and reduced productivity associated with persistent winter tick (</span><i>Dermacentor albipictus</i><span>) parasitism. In 2017–2020, we studied 75 radio-collared female moose (38 calves and 37 adults) in Vermont to examine physiological, spatial, and temporal parameters relative to calf survival and adult productivity. Physiological measures included concentration of fecal glucocorticoid metabolites (fGCM) which reflects stress, and urea nitrogen:creatinine ratios in urine (UN:C) which proxy nutritional state. The pregnancy rate at capture across years was 0.67 (95% CI = 0.50 – 0.80), and was negatively related to presence of lungworm (</span><i>Dictyocaulus</i><span>&nbsp;spp.). The birth rate calculated as the average number of offspring delivered per adult female was &lt;1.0 overall (2017–2020, LCI = 0.22, UCI = 0.86), similar across years, but increased with age. Logistic exposure models indicated that daily calf survival to 60 d increased as Julian birth date and days since birth increased (log odds = 0.0819, SE = 0.0215). The per capita independence rate, or rate that adult females add independent calves to the population, was negatively related to UN:C ratios and positively with fGCM. Further, this rate was related to autumnal habitat use of adult females; it was greater in home ranges characterized by large amounts of mature (canopy) evergreen forests and wetland habitats, and small amounts of mixed forests and elevation than in ranges with abundant levels of mixed forest at high elevation. We conclude that winter ticks can negatively affect moose fecundity, and efforts to reduce host (moose) density through harvest or parasite (host) abundance through habitat manipulation may improve productivity and recruitment in local moose populations.</span></p>","language":"English","publisher":"Lakehead University","usgsCitation":"DeBow, J., Blouin, J., Rosenblatt, E., Alexander, C., Fortin, N., Gieder, K., Murdoch, J., and Donovan, T.M., 2023, Birth rates and neonate survival in a parasite rich moose population in Vermont, USA: Alces, v. 58, p. 51-73.","productDescription":"23 p.","startPage":"51","endPage":"73","ipdsId":"IP-139061","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480995,"rank":1,"type":{"id":15,"text":"Index 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James","contributorId":349022,"corporation":false,"usgs":false,"family":"Murdoch","given":"James","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":923929,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923931,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70260146,"text":"70260146 - 2023 - Dating individual zones in phenocrysts from the 2016–2017 eruption of Bogoslof volcano provides constraints on timescales of magmatic processes","interactions":[],"lastModifiedDate":"2024-10-29T14:32:35.765073","indexId":"70260146","displayToPublicDate":"2023-02-04T09:26:22","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Dating individual zones in phenocrysts from the 2016–2017 eruption of Bogoslof volcano provides constraints on timescales of magmatic processes","docAbstract":"<div id=\"preview-section-abstract\"><div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab0005\" class=\"abstract author\" lang=\"en\"><div id=\"as0005\"><div id=\"sp0065\" class=\"u-margin-s-bottom\"><span>We investigate the rates of magmatic processes using&nbsp;clinopyroxene&nbsp;diffusion chronometry on volcanic products erupted in August 2017 at the end of the 9-month eruption of Bogoslof volcano. The eruptive products contain plagioclase,&nbsp;clinopyroxene, and&nbsp;amphibole, all of which exhibit sharp chemical boundaries and are occasionally observed in multi-phase crystal clots with shared zoning boundaries across different mineral phases. At the shared boundaries in crystal clots, clinopyroxene and plagioclase continued to grow but abruptly changed composition from Mg# 81.7&nbsp;±&nbsp;5.8 to 72.9&nbsp;±&nbsp;3.0 and An</span><sub>82.5±1.4</sub><span>&nbsp;</span>to An<sub>61.3±5.7</sub><span>, respectively. Additionally, the sharp boundary marks where&nbsp;amphibole&nbsp;became unstable and began forming a reaction rim. Synthesizing these observations, we were able to determine that the shared boundaries formed as a result of rapid decompression during&nbsp;magma&nbsp;ascent, followed by storage in a shallow cryptodome, where&nbsp;magma&nbsp;accumulated prior to erupting.</span></div><div class=\"u-margin-s-bottom\"><span><br data-mce-bogus=\"1\"></span></div><div id=\"sp0070\" class=\"u-margin-s-bottom\"><span>In order to determine the timescales of magma ascent and subsequent crystal residence times, we applied diffusion chronometry on zoned clinopyroxene&nbsp;phenocrysts&nbsp;using Mg# concentrations at 1056&nbsp;°C determined from Fe</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\">Ti oxide pairs. Our diffusion modeling results show that diffusion began at the stepwise boundaries in clinopyroxenes no more than180&nbsp;days before the final explosive event.</div><div class=\"u-margin-s-bottom\"><br data-mce-bogus=\"1\"></div><div id=\"sp0075\" class=\"u-margin-s-bottom\">These results were then used to calculate crystal growth rates for shared plagioclase and amphibole rims, as shared zones in crystal clots indicate that the boundaries in all three phases formed contemporaneously. We calculate growth rates of plagioclase crystals (1.7&nbsp;±&nbsp;0.99&nbsp;×&nbsp;10<sup>−6</sup><span>&nbsp;</span>um/s) and amphibole reaction rims (2.8&nbsp;±&nbsp;0.47&nbsp;×&nbsp;10<sup>−6</sup><span>&nbsp;</span>um/s). The calculated natural growth rate of plagioclase was then used to constrain additional magmatic timescales from growth rate chronometry, results of which support our diffusion timescales.</div><div class=\"u-margin-s-bottom\"><br data-mce-bogus=\"1\"></div><div id=\"sp0080\" class=\"u-margin-s-bottom\"><span>Our results indicate that the distinct boundaries in all three mineral phases formed due to ascent-driven decompression followed by shallow emplacement of mafic magma that occurred continually throughout the course of the eruption. By subtracting diffusion timescales from the date that the samples were erupted, the oldest crystal boundaries correspond to March 2017, seemingly correlating with increases in both&nbsp;seismicity&nbsp;and SO</span><sub>2</sub><span>&nbsp;</span>emissions. These observations may suggest that our petrochronometric results are supported by interdisciplinary observations.</div></div></div></div></div><div id=\"preview-section-introduction\"><br></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2022.107741","usgsCitation":"Moshrefzadeh, J., Izbekof, P., Loewen, M.W., Larsen, J., and Regan, S., 2023, Dating individual zones in phenocrysts from the 2016–2017 eruption of Bogoslof volcano provides constraints on timescales of magmatic processes: Journal of Volcanology and Geothermal Research, v. 435, 107741, 16 p., https://doi.org/10.1016/j.jvolgeores.2022.107741.","productDescription":"107741, 16 p.","ipdsId":"IP-140665","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467121,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2022.107741","text":"Publisher Index Page"},{"id":463335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Bogoslof Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -168.04917846434188,\n              53.937993642724905\n            ],\n            [\n              -168.04917846434188,\n              53.92389191228028\n            ],\n            [\n              -168.0270096873428,\n              53.92389191228028\n            ],\n            [\n              -168.0270096873428,\n              53.937993642724905\n            ],\n            [\n              -168.04917846434188,\n              53.937993642724905\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"435","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moshrefzadeh, Jamshid 0000-0001-7333-5651","orcid":"https://orcid.org/0000-0001-7333-5651","contributorId":242807,"corporation":false,"usgs":false,"family":"Moshrefzadeh","given":"Jamshid","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbekof, Pavel 0000-0001-9052-7655","orcid":"https://orcid.org/0000-0001-9052-7655","contributorId":242806,"corporation":false,"usgs":false,"family":"Izbekof","given":"Pavel","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loewen, Matthew W. 0000-0002-5621-285X","orcid":"https://orcid.org/0000-0002-5621-285X","contributorId":213321,"corporation":false,"usgs":true,"family":"Loewen","given":"Matthew","email":"","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917194,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917195,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, Sean P.","contributorId":219815,"corporation":false,"usgs":false,"family":"Regan","given":"Sean P.","affiliations":[{"id":13599,"text":"University of Alaska - Fairbanks","active":true,"usgs":false}],"preferred":false,"id":917196,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70240729,"text":"70240729 - 2023 - A restructured Bayesian approach to estimate the abundance of a rare and invasive fish","interactions":[],"lastModifiedDate":"2023-05-25T15:45:17.03652","indexId":"70240729","displayToPublicDate":"2023-02-04T07:20:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"A restructured Bayesian approach to estimate the abundance of a rare and invasive fish","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section c-article-content-visibility\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Quantifying invasive species abundance informs management and control strategies. However, estimating abundance can be challenging, particularly when dealing with rare species early in the invasion process. Data generated from control strategies, such as removing invasive species, are usually not suited to conventional statistical modelling approaches. Hence, we developed a Bayesian model using data generated by a grass carp (<i>Ctenopharyngodon idella</i>) control program in the Sandusky River, Ohio (USA) for estimating the abundance of rare, invasive species. The model is a restructured N-mixture model modified to incorporate the data generating process (i.e., setting a trammel net to isolate a sampling area followed by boat-mounted electrofishing). Allowing the estimation of grass carp abundance from the species removal data, which had very few detections relative to the sampling effort. Our results indicated that the average number of grass carp present in the river at any one time did not change substantially from 2018 to 2020. The highest abundance estimates were in the lower and upper-middle segments of the river, suggesting possible recolonization from Lake Erie, and possibly other tributaries. Ultimately, the ability to use species-control data to estimate abundance provides important information for management, particularly for invasive ‘sleeper’ species in freshwater ecosystems.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10530-023-03006-6","usgsCitation":"Gouveia, A., Qian, S.S., Mayer, C.A., Smith, J.A., Bossenbroek, J., Hintz, W.D., Mapes, R., Weimer, E., Navarro, J., Dettmers, J.M., Young, R., Buszkiewicz, J., and Kocovsky, P.M., 2023, A restructured Bayesian approach to estimate the abundance of a rare and invasive fish: Biological Invasions, v. 25, p. 1711-1721, https://doi.org/10.1007/s10530-023-03006-6.","productDescription":"11 p.","startPage":"1711","endPage":"1721","ipdsId":"IP-131639","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":413170,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -83.17770473625303,\n              41.308643520054744\n            ],\n            [\n              -82.89527024570958,\n              41.308643520054744\n            ],\n            [\n              -82.89527024570958,\n              41.49866213865516\n            ],\n            [\n              -83.17770473625303,\n              41.49866213865516\n            ],\n            [\n              -83.17770473625303,\n              41.308643520054744\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2023-02-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Gouveia, Ana R.","contributorId":302502,"corporation":false,"usgs":false,"family":"Gouveia","given":"Ana R.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Qian, S. S.","contributorId":243524,"corporation":false,"usgs":false,"family":"Qian","given":"S.","email":"","middleInitial":"S.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayer, C. A.","contributorId":156230,"corporation":false,"usgs":false,"family":"Mayer","given":"C.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":864558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, J. A.","contributorId":219770,"corporation":false,"usgs":false,"family":"Smith","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":864559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bossenbroek, J.","contributorId":302503,"corporation":false,"usgs":false,"family":"Bossenbroek","given":"J.","email":"","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hintz, W. D.","contributorId":302504,"corporation":false,"usgs":false,"family":"Hintz","given":"W.","email":"","middleInitial":"D.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mapes, R.","contributorId":302505,"corporation":false,"usgs":false,"family":"Mapes","given":"R.","email":"","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":864562,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Weimer, E.","contributorId":302506,"corporation":false,"usgs":false,"family":"Weimer","given":"E.","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":864563,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Navarro, J.","contributorId":302507,"corporation":false,"usgs":false,"family":"Navarro","given":"J.","email":"","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":864564,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dettmers, J. M.","contributorId":302508,"corporation":false,"usgs":false,"family":"Dettmers","given":"J.","email":"","middleInitial":"M.","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":864565,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Young, R.","contributorId":241798,"corporation":false,"usgs":false,"family":"Young","given":"R.","affiliations":[{"id":48424,"text":"UAE University","active":true,"usgs":false}],"preferred":false,"id":864566,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Buszkiewicz, J. T.","contributorId":302509,"corporation":false,"usgs":false,"family":"Buszkiewicz","given":"J. 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