{"pageNumber":"156","pageRowStart":"3875","pageSize":"25","recordCount":40783,"records":[{"id":70239279,"text":"70239279 - 2022 - Flopy: The Python interface for MODFLOW","interactions":[],"lastModifiedDate":"2023-01-06T13:29:01.304947","indexId":"70239279","displayToPublicDate":"2022-09-26T07:27:45","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Flopy: The Python interface for MODFLOW","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"National Ground Water Association","doi":"10.1111/gwat.13259","usgsCitation":"Leaf, A.T., and Fienen, M., 2022, Flopy: The Python interface for MODFLOW: Groundwater, v. 60, no. 6, p. 710-712, https://doi.org/10.1111/gwat.13259.","productDescription":"3 p.","startPage":"710","endPage":"712","ipdsId":"IP-143798","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":435678,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EFHF9H","text":"USGS data release","linkHelpText":"Pleasant Lake worked Flopy example"},{"id":411484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-10-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":860985,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237161,"text":"70237161 - 2022 - A study on the effect of site response on California seismic hazard map assessment","interactions":[],"lastModifiedDate":"2022-10-03T11:33:59.473924","indexId":"70237161","displayToPublicDate":"2022-09-26T06:31:11","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12612,"text":"Frontiers in Earth Science: Geohazards and Georisks","active":true,"publicationSubtype":{"id":10}},"title":"A study on the effect of site response on California seismic hazard map assessment","docAbstract":"<div class=\"JournalAbstract\"><p class=\"mb15\">Prior studies have repeatedly shown that probabilistic seismic hazard maps from several different countries predict higher shaking than that observed. Previous map assessments have not, however, considered the influence of site response on hazard. Seismologists have long acknowledged the influence of near-surface geology, in particular low-impedance sediment layers, on earthquake ground-motion at frequencies of engineering concern. Although the overall effects of site response are complex, modern ground-motion models (GMMs) account for site effects using terms based on V<sub>S30</sub>, the time-averaged shear-wave velocity in the upper 30&nbsp;m of the Earth’s surface. In this study, we consider general implications of incorporating site terms from modern GMMs using site-specific V<sub>S30</sub><span>&nbsp;</span>as a proxy in probabilistic seismic hazard maps for California. At the long periods (1–5&nbsp;s) that affect tall buildings, site terms amplify the mapped hazard by factors of 1–3 at many sites relative to maps calculated for the standard reference soft-rock site condition, V<sub>S30</sub><span>&nbsp;</span>= 760 m/s. However, at the short periods of ground-motion that are the main contributors to peak ground acceleration (PGA) and thus affect smaller structures, only negligible effects occur due to nonlinear deamplification of strong ground-motion at high frequencies. Nonlinear deamplification increases as the shaking level increases. For very strong shaking, deamplification can overcome the linear amplification, yielding net deamplification. We explore the implications of these results for the evaluation of hazard maps. Because site effects do not change the maps appreciably at short periods, we can exclude site response as an explanation for why the maps overpredict historically observed shaking as captured by the California Historical Intensity Mapping Project (CHIMP) dataset. The results are expected to be generalizable to regions that are comparable to California in terms of structure and seismicity rates. In low-to-moderate-seismicity regions where the hazard reflects weaker shaking, nonlinear site response is expected to be less important for the hazard.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2022.931340","usgsCitation":"Gallahue, M.M., Salditch, L.M., Lucas, M.C., Neely, J.S., Stein, S., Abrahamson, N.A., Williams, T., and Hough, S.E., 2022, A study on the effect of site response on California seismic hazard map assessment: Frontiers in Earth Science: Geohazards and Georisks, v. 10, 931340, 11 p., https://doi.org/10.3389/feart.2022.931340.","productDescription":"931340, 11 p.","ipdsId":"IP-135357","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":446342,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2022.931340","text":"Publisher Index 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 \"}}]}","volume":"10","noUsgsAuthors":false,"publicationDate":"2022-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Gallahue, Molly M.","contributorId":263448,"corporation":false,"usgs":false,"family":"Gallahue","given":"Molly","email":"","middleInitial":"M.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":853517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Salditch, Leah Marschall 0000-0002-4478-1836","orcid":"https://orcid.org/0000-0002-4478-1836","contributorId":297144,"corporation":false,"usgs":true,"family":"Salditch","given":"Leah","email":"","middleInitial":"Marschall","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":853518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Madeleine C.","contributorId":263451,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","email":"","middleInitial":"C.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":853519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":853520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":853521,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Abrahamson, Norman A.","contributorId":115451,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":853522,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williams, Tessa","contributorId":297145,"corporation":false,"usgs":false,"family":"Williams","given":"Tessa","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":853523,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":853524,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70239833,"text":"70239833 - 2022 - Wind turbine wakes can impact down-wind vegetation greenness","interactions":[],"lastModifiedDate":"2023-01-23T12:18:53.782104","indexId":"70239833","displayToPublicDate":"2022-09-26T06:16:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Wind turbine wakes can impact down-wind vegetation greenness","docAbstract":"<div class=\"article-text wd-jnl-art-abstract cf\"><p>Global wind energy has expanded 5-fold since 2010 and is predicted to expand another 8–10-fold over the next 30 years. Wakes generated by wind turbines can alter downwind microclimates and potentially downwind vegetation. However, the design of past studies has made it difficult to isolate the impact of wake effects on vegetation from land cover change. We used hourly wind data to model wake and non-wake zones around 17 wind facilities across the U.S. and compared remotely-sensed vegetation greenness in wake and non-wake zones before and after construction. We located sampling sites only in the dominant vegetation type and in areas that were not disturbed before or after construction. We found evidence for wake effects on vegetation greenness at 10 of 17 facilities for portions of, or the entire growing season. Evidence included statistical significance in Before After Control Impact statistical models, differences &gt;3% between expected and observed values of vegetation greenness, and consistent spatial patterns of anomalies in vegetation greenness relative to turbine locations and wind direction. Wakes induced both increases and decreases in vegetation greenness, which may be difficult to predict prior to construction. The magnitude of wake effects depended primarily on precipitation and to a lesser degree aridity. Wake effects did not show trends over time following construction, suggesting the changes impact vegetation greenness within a growing season, but do not accrue over years. Even small changes in vegetation greenness, similar to those found in this study, have been seen to affect higher trophic levels. Given the rapid global growth of wind energy, and the importance of vegetation condition for agriculture, grazing, wildlife, and carbon storage, understanding how wakes from wind turbines impact vegetation is essential to exploit or ameliorate these effects.</p></div>","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/ac8da9","usgsCitation":"Diffendorfer, J., Vanderhoof, M.K., and Ancona, Z.H., 2022, Wind turbine wakes can impact down-wind vegetation greenness: Environmental Research Letters, v. 17, 104025, 14 p., https://doi.org/10.1088/1748-9326/ac8da9.","productDescription":"104025, 14 p.","ipdsId":"IP-136847","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":446345,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac8da9","text":"Publisher Index Page"},{"id":435679,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P3J7GR","text":"USGS data release","linkHelpText":"Wind turbine wakes can impact down-wind vegetation greenness"},{"id":412204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","noUsgsAuthors":false,"publicationDate":"2022-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":862081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":862082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ancona, Zachary H. 0000-0001-5430-0218 zancona@usgs.gov","orcid":"https://orcid.org/0000-0001-5430-0218","contributorId":5578,"corporation":false,"usgs":true,"family":"Ancona","given":"Zachary","email":"zancona@usgs.gov","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":862083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70240259,"text":"70240259 - 2022 - Insights on multistage rock avalanche behavior from runout modeling constrained by seismic inversions","interactions":[],"lastModifiedDate":"2023-02-02T13:02:32.684492","indexId":"70240259","displayToPublicDate":"2022-09-25T07:01:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7167,"text":"Journal of Geophysical Research: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Insights on multistage rock avalanche behavior from runout modeling constrained by seismic inversions","docAbstract":"<div class=\"article-section__content en main\"><p>Inversion of low-frequency regional seismic records to solve for a time series of bulk forces exerted on the earth by a landslide (a force-time function) is increasingly being used to infer volumes and dynamics of large, highly energetic landslides, such as rock avalanches and flowslides, and to provide calibration information on event dynamics and volumes for numerical landslide runout models. Much of the work to date using landslide runout modeling constrained by seismic data has focused on using single-phase models with frictional or velocity-weakening rheologies. Awareness of multistage landslide initiations is increasing, with discrete failures separated in time contributing to the final impact of an event. Our work utilizes a method for incorporating seismic data as a calibration constraint for landslide runout models, considering variable rheologies and different initiation conditions. This study presents a systematic examination of multiple rheologies and initiation conditions, and shows how these factors affect the force-time function derived from the landslide runout model. Our work confirms that, while rheology and fragmenting or initially coherent initiations affect the force-time function, multiple collapses separated by tens of seconds have the greatest impact on the shape and amplitude. We apply this method to the analysis of three real rock avalanches to better constrain plausible initiation conditions and rheology parameters using both seismic and field data. This study provides insights on how assumptions about the initiation dynamics of the source zone and the runout model definition can aid in the interpretation of seismic inversions for multistage rock avalanches.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JB023444","usgsCitation":"Mitchell, A., Allstadt, K.E., George, D.L., Aaron, J., McDougall, S., Moore, J.R., and Menounous, B., 2022, Insights on multistage rock avalanche behavior from runout modeling constrained by seismic inversions: Journal of Geophysical Research: Solid Earth, v. 127, no. 10, e2021JB023444, 29 p., https://doi.org/10.1029/2021JB023444.","productDescription":"e2021JB023444, 29 p.","ipdsId":"IP-134671","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":446348,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021jb023444","text":"External Repository"},{"id":412609,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Andrew","contributorId":225513,"corporation":false,"usgs":false,"family":"Mitchell","given":"Andrew","email":"","affiliations":[{"id":41153,"text":"Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia","active":true,"usgs":false}],"preferred":false,"id":863122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":863123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":863124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aaron, Jordan","contributorId":194904,"corporation":false,"usgs":false,"family":"Aaron","given":"Jordan","email":"","affiliations":[],"preferred":false,"id":863125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDougall, Scott","contributorId":194908,"corporation":false,"usgs":false,"family":"McDougall","given":"Scott","email":"","affiliations":[],"preferred":false,"id":863126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moore, Jeffrey R.","contributorId":194909,"corporation":false,"usgs":false,"family":"Moore","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":863127,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Menounous, Brian","contributorId":301940,"corporation":false,"usgs":false,"family":"Menounous","given":"Brian","email":"","affiliations":[{"id":65373,"text":"University of Northern British Columbia, Geography Program and Natural Resources and Environmental Studies Institute","active":true,"usgs":false}],"preferred":false,"id":863128,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70237048,"text":"70237048 - 2022 - Astrochronology of the Paleocene-Eocene Thermal Maximum on the Atlantic Coastal Plain","interactions":[],"lastModifiedDate":"2022-09-28T15:40:35.835405","indexId":"70237048","displayToPublicDate":"2022-09-24T10:35:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Astrochronology of the Paleocene-Eocene Thermal Maximum on the Atlantic Coastal Plain","docAbstract":"<p><span>The chronology of the Paleocene-Eocene Thermal Maximum (PETM, ~56 Ma) remains disputed, hampering complete understanding of the possible trigger mechanisms of this event. Here we present an astrochronology for the PETM carbon isotope excursion from Howards Tract, Maryland a paleoshelf environment, on the mid-Atlantic Coastal Plain. Statistical evaluation of variations in calcium content and magnetic susceptibility indicates astronomical forcing was involved and the PETM onset lasted about 6 kyr. The astrochronology and Earth system modeling suggest that the PETM onset occurred at an extreme in precession during a maximum in eccentricity, thus favoring high temperatures, indicating that astronomical forcing could have played a role in triggering the event. Ca content data on the paleo-shelf, along with other marine records, support the notion that a carbonate saturation overshoot followed global ocean acidification during the PETM.</span></p>","language":"English","publisher":"Nature Publications","doi":"10.1038/s41467-022-33390-x","usgsCitation":"Li, M., Bralower, T.J., Kump, L.R., Self-Trail, J., Zachos, J.C., Rush, W.D., and Robinson, M., 2022, Astrochronology of the Paleocene-Eocene Thermal Maximum on the Atlantic Coastal Plain: Nature Communications, v. 13, 5618, 13 p., https://doi.org/10.1038/s41467-022-33390-x.","productDescription":"5618, 13 p.","ipdsId":"IP-138026","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":446349,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-022-33390-x","text":"Publisher Index Page"},{"id":407515,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, Virginia","otherGeospatial":"mid-Atlantic Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -74.267578125,\n              40.463666324587685\n            ],\n            [\n              -74.90478515625,\n              40.069664523297774\n            ],\n            [\n              -75.4541015625,\n              39.83385008019448\n            ],\n            [\n              -75.882568359375,\n              39.70718665682654\n            ],\n            [\n              -77.0361328125,\n              39.12153746241925\n            ],\n            [\n              -77.376708984375,\n              38.976492485539396\n            ],\n            [\n              -77.71728515624999,\n              38.03078569382294\n            ],\n            [\n              -78.01391601562499,\n              36.86204269508728\n            ],\n            [\n              -78.0029296875,\n              36.589068371399115\n            ],\n            [\n              -75.7177734375,\n              36.54494944148322\n            ],\n            [\n              -74.59716796875,\n              38.84826438869913\n            ],\n            [\n              -73.970947265625,\n              40.027614437486655\n            ],\n            [\n              -73.970947265625,\n              40.40513069752789\n            ],\n            [\n              -74.267578125,\n              40.463666324587685\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2022-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Mingsong 0000-0002-5542-8106","orcid":"https://orcid.org/0000-0002-5542-8106","contributorId":297047,"corporation":false,"usgs":false,"family":"Li","given":"Mingsong","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":853169,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bralower, Timothy J.","contributorId":211826,"corporation":false,"usgs":false,"family":"Bralower","given":"Timothy","email":"","middleInitial":"J.","affiliations":[{"id":13035,"text":"Department of Geosciences, Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":853170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kump, Lee R.","contributorId":195147,"corporation":false,"usgs":false,"family":"Kump","given":"Lee","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":853171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":853172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zachos, James C.","contributorId":211829,"corporation":false,"usgs":false,"family":"Zachos","given":"James","email":"","middleInitial":"C.","affiliations":[{"id":38326,"text":"Earth & Planetary Sciences Department, University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":853173,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rush, William D. 0000-0002-8522-5684","orcid":"https://orcid.org/0000-0002-8522-5684","contributorId":297048,"corporation":false,"usgs":false,"family":"Rush","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":27155,"text":"University of California Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":853174,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robinson, Marci M. 0000-0002-9200-4097","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":261664,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":853175,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70238908,"text":"70238908 - 2022 - The effects of cheatgrass invasion on US Great Basin carbon storage depend on interactions between plant community composition, precipitation seasonality, and soil climate regime","interactions":[],"lastModifiedDate":"2022-12-16T15:50:22.385463","indexId":"70238908","displayToPublicDate":"2022-09-24T09:44:09","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The effects of cheatgrass invasion on US Great Basin carbon storage depend on interactions between plant community composition, precipitation seasonality, and soil climate regime","docAbstract":"<ol class=\"\"><li>Annual-grass invasions are transforming desert ecosystems in ways that affect ecosystem carbon (C) balance, but previous studies do not agree on the pattern, magnitude and direction of changes. A recent meta-analysis of 41 articles and 386 sites concludes that invasion by annual grasses such as cheatgrass (<i>Bromus tectorum</i><span>&nbsp;</span>L) reduces C in biomass across the Great Basin (Nagy et al., 2021). Reanalysis reveals that whether cheatgrass affects biomass C stocks is not generalizable, but rather depends on the considerable variation in climate across the subject sites. Our analysis suggests that accurate Great Basin-scale estimates of cheatgrass effects on C balance are not yet possible.</li><li>Addition of climate variables to the meta-analysis reveals that cheatgrass invasion (a) reduced C in above-ground biomass in relatively summer-wet sites but not in summer-dry sites, (b) increased surface soil C in sites with intermediate resistance and resilience classifications (R&amp;R) but not in low R&amp;R sites—that is, mesic/aridic soil climates and (c) did not affect deep soil C.</li><li>Considering that cheatgrass has expanded most in relatively summer-dry sites and mesic/aridic sites, omission of climate factors leads to model overestimates of cheatgrass effects on C when extrapolating to larger areas. Estimates of cheatgrass effects on C would also be improved if the analysis considered that (a) perennial grasslands are a common community state in the Great Basin that have intermediary C relative to annual grasslands and sagebrush stands, that is the omission of perennial grasslands from analysis inflates the baseline C storage of uninvaded Great Basin ecosystems, and( b) cheatgrass does not often exist in stable monocultures and soil carbon can reflect current or recent presence of other species.</li><li><i>Synthesis and applications</i>. Invasions often reveal heterogeneity in ecosystem structure and function that is not otherwise evident, and the heterogeneity can influence estimation of the net impacts of the invaders. For cheatgrass and other invaders, we propose that formally accounting for the spatial variability of invasion on ecosystem functions will improve the estimation of their net effect on ecosystem C, and thus improve prospects for adjusting management practices to optimize C sequestration.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.14289","usgsCitation":"Maxwell, T.M., and Germino, M., 2022, The effects of cheatgrass invasion on US Great Basin carbon storage depend on interactions between plant community composition, precipitation seasonality, and soil climate regime: Journal of Applied Ecology, v. 59, no. 11, p. 2863-2873, https://doi.org/10.1111/1365-2664.14289.","productDescription":"11 p.","startPage":"2863","endPage":"2873","ipdsId":"IP-133434","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":488757,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarworks.boisestate.edu/bio_facpubs/748","text":"External Repository"},{"id":410631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -101.84343812653191,\n              48.94865191756597\n            ],\n            [\n              -120.89716334634883,\n              48.94865191756597\n            ],\n            [\n              -120.89716334634883,\n              35.68015387897607\n            ],\n            [\n              -101.84343812653191,\n              35.68015387897607\n            ],\n            [\n              -101.84343812653191,\n              48.94865191756597\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"59","issue":"11","noUsgsAuthors":false,"publicationDate":"2022-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Maxwell, Toby M","contributorId":299955,"corporation":false,"usgs":false,"family":"Maxwell","given":"Toby","email":"","middleInitial":"M","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":859121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579 mgermino@usgs.gov","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":152582,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","email":"mgermino@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":859122,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70237580,"text":"70237580 - 2022 - Evaluating acid-aluminum stress in streams of the Northeastern U.S. at watershed, fish community and physiological scales","interactions":[],"lastModifiedDate":"2022-10-14T13:14:07.821412","indexId":"70237580","displayToPublicDate":"2022-09-23T14:39:56","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating acid-aluminum stress in streams of the Northeastern U.S. at watershed, fish community and physiological scales","docAbstract":"<p>In spite of overall improvements in air and water quality, biological stress from low pH and high concentrations of inorganic aluminum continue to impact fish and fish habitat in northeastern North America, with independent and interactive effects on individuals, populations and communities. Integrative indicators can therefore be useful in monitoring both impact and recovery across multiple scales. Using coupled water chemistry (pH, conductivity, and base cation and inorganic aluminum concentration), geographic (site elevation and watershed area) and biological (fish diversity, fish abundance, gill aluminum concentration and gill physiology) data, we developed an integrated indicator of acid aluminum stress across the White and Green mountains in central New England, USA. As has been established in a number of previous studies, preliminary analysis clearly indicated that across all sites, inorganic aluminum concentration was consistently greatest during the spring season. Structural Equation modelling (SEM) revealed that toxic conditions (concurrent low pH and high concentrations of inorganic aluminum) were well summarized with an integrated toxicity score, related to both base cation concentrations and elevation, with sites at higher elevations more likely to experience toxic conditions as well as low base cation concentrations. As hypothesized, fish diversity and abundance were negatively related to toxicity score. In spite of considerable variation among individuals, gill aluminum was positively related to toxicity score for both Atlantic salmon and brook trout. Observed elevated gill aluminum levels associated with reduced gill metabolic activity in Atlantic salmon smolts from impacted systems likely result in impaired osmoregulatory function and seawater tolerance. Overall, our results suggest that the integrated toxicity score metric is strongly associated with a syndrome of physiological stress, reduced abundance, and low species diversity for stream fishes in New England and can likely serve as a reliable indicator of continued impairment or recovery of acid-aluminum vulnerable systems in this ecoregion.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109480","usgsCitation":"Zdasiuk, B.J., Chen, C.Y., McCormick, S.D., Nislow, K., Singley, J.G., and Kelly, J.T., 2022, Evaluating acid-aluminum stress in streams of the Northeastern U.S. at watershed, fish community and physiological scales: Ecological Indicators, v. 144, 109480, 12 p., https://doi.org/10.1016/j.ecolind.2022.109480.","productDescription":"109480, 12 p.","ipdsId":"IP-138154","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446353,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109480","text":"Publisher Index Page"},{"id":408282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire, Vermont","otherGeospatial":"Ammonoosuc basin, Merrimack basin, Saco River basin, West River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -72.80502319335938,\n              42.837709559849614\n            ],\n            [\n              -72.54684448242188,\n              42.837709559849614\n            ],\n            [\n              -72.54684448242188,\n              43.03577208929465\n            ],\n            [\n              -72.80502319335938,\n              43.03577208929465\n            ],\n            [\n              -72.80502319335938,\n              42.837709559849614\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -71.9879150390625,\n              43.757208878849376\n            ],\n            [\n              -71.08978271484375,\n              43.757208878849376\n            ],\n            [\n              -71.08978271484375,\n              44.5063000997406\n            ],\n            [\n              -71.9879150390625,\n              44.5063000997406\n            ],\n            [\n              -71.9879150390625,\n              43.757208878849376\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"144","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Zdasiuk, Benjamin J","contributorId":297871,"corporation":false,"usgs":false,"family":"Zdasiuk","given":"Benjamin","email":"","middleInitial":"J","affiliations":[{"id":39657,"text":"Dartmouth College","active":true,"usgs":false}],"preferred":false,"id":854525,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Celia Y.","contributorId":145630,"corporation":false,"usgs":false,"family":"Chen","given":"Celia","email":"","middleInitial":"Y.","affiliations":[{"id":16179,"text":"Dartmouth College, Hanover NH","active":true,"usgs":false}],"preferred":false,"id":854526,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nislow, Keith H.","contributorId":276357,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith H.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":854528,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singley, Joel G","contributorId":297873,"corporation":false,"usgs":false,"family":"Singley","given":"Joel","email":"","middleInitial":"G","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":854529,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kelly, John T.","contributorId":212827,"corporation":false,"usgs":false,"family":"Kelly","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":38688,"text":"Department of Biology & Environmental Science, University of New Haven","active":true,"usgs":false}],"preferred":false,"id":854530,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70236125,"text":"ofr20201143 - 2022 - Eelgrass (Zostera marina) and seaweed abundance along the coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010","interactions":[],"lastModifiedDate":"2022-09-26T15:51:47.675735","indexId":"ofr20201143","displayToPublicDate":"2022-09-23T13:19:03","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1143","displayTitle":"Eelgrass (<em>Zostera marina</em>) and Seaweed Abundance Along the Coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010","title":"Eelgrass (Zostera marina) and seaweed abundance along the coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010","docAbstract":"<p>Eelgrass (&lt;em&gt;Zostera marina&lt;/em&gt;) is a highly productive seagrass that plays an essential role in the health of the estuarine and coastal ecosystems; however, information about its abundance and distribution is insufficient in the Bering Sea along the Yukon Delta National Wildlife Refuge. We inventoried the spatial extent and abundance of eelgrass and seaweed in Duchikthluk and Shoal bays on Nunivak Island in July 2010. Using Landsat Thematic Mapper imagery, we estimated the spatial extent of eelgrass to be 1,232 hectares in Duchikthluk Bay and 40 hectares in Shoal Bay. The overall accuracy of the assessments was high (86–87 percent) based on ground truthing using field reference points. We used point-sampling methodology to assess eelgrass abundance relative to the presence of associated seaweeds and selected macro-invertebrates within each of bays. Eelgrass was found at water depths ranging from 0.1 to 2.9 meters across both bays, but the greatest density (&gt;75 percent cover) occurred primarily in moderate to deep water (0.7–1.4 meters) in Duchikthluk Bay and deeper water (&gt;2 meters) in Shoal Bay. The mean aboveground biomass was 39.4±4.0 grams per meter squared in Duchikthluk Bay. The eelgrass biomass was greater (67.6±11.0 grams per meter squared) in Shoal Bay, but this estimate was based on a small sample size (n=3). Seaweeds, representing six species, occurred in low abundance across both bays and were primarily associated with eelgrass. Gastropods were the most common macro-invertebrate, occurring at 45 percent of field points in Duchikthluk Bay.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201143","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., Hogrefe, K.R., Donnelly, T.F., and Fairchild, L.L., 2022, Eelgrass (<em>Zostera marina</em>) and seaweed abundance along the coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010: U.S. Geological Survey Open-File Report 2020–1143, 13 p., https://doi.org/10.3133/ofr20201143.","productDescription":"Report: v, 13 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-119381","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":405857,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release","linkHelpText":"Mapping data of eelgrass (<em>Zostera marina</em>) distribution, Alaska and Baja California, Mexico"},{"id":405858,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K1ZOMY","text":"USGS data release","description":"USGS data release","linkHelpText":"Point sampling data from eelgrass (<em>Zostera marina</em>), seaweeds and selected invertebrates at six embayments and two islands at the end of the Alaska Peninsula"},{"id":435680,"rank":10,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QI7RCQ","text":"USGS data release","linkHelpText":"Point Sampling for Eelgrass (Zostera marina) and Seaweeds in Duchikthluk and Shoal Bays of Nunivak Island, Alaska, 2010"},{"id":405855,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1143/coverthb.jpg"},{"id":405863,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211034","text":"OFR 2021-1034 —","description":"OFR 2021-1034","linkHelpText":"Inventory of eelgrass (<em>Zostera marina</em>) and seaweeds at the end of the Alaska Peninsula, August–September 2012"},{"id":405861,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201144","text":"OFR 2020-1144 —","description":"OFR 2020-1144","linkHelpText":"Eelgrass (<em>Zostera marina</em>) and seaweed assessment Alaska Peninsula-Becharof National Wildlife Refuges, 2010"},{"id":405860,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201080","text":"OFR 2020-1080 —","description":"OFR 2020-01080","linkHelpText":"Distribution of eelgrass (<em>Zostera marina</em>) in coastal waters adjacent to Togiak National Wildlife Refuge, Alaska"},{"id":405862,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201114","text":"OFR 2020-1114 —","description":"OFR 2020-1114","linkHelpText":"Eelgrass (<em>Zostera marina</em>) and Seaweed Abundance along the Coast of Togiak National Wildlife Refuge, Alaska, 2008–10"},{"id":405856,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1143/ofr20201143.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1143"},{"id":405859,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201035","text":"OFR 2020-1035 —","description":"OFR 2020-1035","linkHelpText":"Abundance and distribution of eelgrass (<em>Zostera marina</em>) and seaweeds at Izembek National Wildlife Refuge, Alaska, 2007–10"}],"country":"United States","state":"Alaska","otherGeospatial":"Nunivak Island, Yukon Delta National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -167.67333984375,\n              59.517602921437295\n            ],\n            [\n              -164.06982421875,\n              59.517602921437295\n            ],\n            [\n              -164.06982421875,\n              60.60314950746827\n            ],\n            [\n              -167.67333984375,\n              60.60314950746827\n            ],\n            [\n              -167.67333984375,\n              59.517602921437295\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/asc/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/asc/\">Alaska Science Center</a><br>U.S. Geological Survey<br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>Future Research Needs</li><li>References Cited</li></ul>","publishedDate":"2022-09-23","noUsgsAuthors":false,"publicationDate":"2022-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":850165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogrefe, Kyle R. khogrefe@usgs.gov","contributorId":4264,"corporation":false,"usgs":true,"family":"Hogrefe","given":"Kyle","email":"khogrefe@usgs.gov","middleInitial":"R.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":850166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donnelly, Tyrone F. tfdonnelly@usgs.gov","contributorId":4369,"corporation":false,"usgs":true,"family":"Donnelly","given":"Tyrone","email":"tfdonnelly@usgs.gov","middleInitial":"F.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":850167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fairchild, Lucretia L.","contributorId":295916,"corporation":false,"usgs":false,"family":"Fairchild","given":"Lucretia","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":850168,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236829,"text":"ofr20221081 - 2022 - A sagebrush conservation design to proactively restore America’s sagebrush biome","interactions":[],"lastModifiedDate":"2022-09-22T16:12:53.285869","indexId":"ofr20221081","displayToPublicDate":"2022-09-22T10:55:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1081","displayTitle":"A Sagebrush Conservation Design to Proactively Restore America’s Sagebrush Biome","title":"A sagebrush conservation design to proactively restore America’s sagebrush biome","docAbstract":"<p>A working group of experts with diverse professional backgrounds and disciplinary expertise was assembled to conceptualize a spatially explicit conservation design to support and inform the Sagebrush Conservation Strategy Part 2. The goal was to leverage recent advancements in remotely sensed landcover products to develop spatially and temporally explicit maps of sagebrush rangeland condition and landscape threats. In addition, the group sought to provide a common basis for understanding the state of sagebrush rangelands through time.</p><p>First, the study team developed a spatially explicit model to assess geographic patterns in sagebrush ecological integrity and used this model to identify core sagebrush areas (CSAs), growth opportunity areas (GOAs), and other rangeland areas (ORAs) across the biome. Among the identified rangelands, 33.4 million acres were classified as CSAs; 84.3 million acres as GOAs; and 127.2 million acres as ORAs as of 2020. Second, the team sought to demonstrate the ecological relevance of the identified CSAs and GOAs by comparing these data with independent datasets for sagebrush obligate species of conservation concern. Geographical patterns in sagebrush ecological integrity were strongly associated with the occurrence of high-priority species and also displayed clear links to population performance for greater sage-grouse. Third, the team parsed out the type, location, and acres of primary threats within the different categories (CSAs, GOAs, and ORAs) to help focus active management by identifying places where multiagency and organization efforts can protect CSAs and GOAs that have higher levels of integrity with lower cumulative threats. The assessment of the condition of the sagebrush biome (that is, the location, amount, and conservation status) indicated that complex ecosystem function problems are driving ~73 percent of the demonstrated threats within the CSAs and GOAs (rather than point-source problems, such as human development). Fourth, the team developed trend estimates for the identified CSAs and GOAs and three selected primary threats (invasive annual grasses, conifer encroachment, and human modification) to the sagebrush biome from 2001 to 2020. Results showed that an average of 1.3 million acres per year have transitioned to ORAs at an annual rate of −1.34 percent. Fifth, the team developed an approach to integrate climate change effects into the threat-based landscape conservation design and conducted an initial assessment on the magnitude of near-term climate effects in the context of observed historical trends. The team’s analysis suggests that climate change alone is unlikely to be the dominant threat to sagebrush ecological integrity in the next few decades, although interactions of climate with wildfire and invasive annual grasses may be an important threat, especially in the longer term.</p><p>A spatial overlap analysis was performed and highlighted 45.8 million acres of shared priorities among existing conservation frameworks to help anchor and guide collaborative landscape-scale conservation of areas that still have no to low threats. This information is critical to provide context for decisions about the volume and nature of conservation actions and funding requirements.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221081","collaboration":"Prepared in cooperation with the Western Association of Fish and Wildlife Agencies and the U.S. Fish and Wildlife Service","usgsCitation":"Doherty, K., Theobald, D.M., Bradford, J.B., Wiechman, L.A., Bedrosian, G., Boyd, C.S., Cahill, M., Coates, P.S., Creutzburg, M.K., Crist, M.R., Finn, S.P., Kumar, A.V., Littlefield, C.E., Maestas, J.D., Prentice, K.L., Prochazka, B.G., Remington, T.E., Sparklin, W.D., Tull, J.C., Wurtzebach, Z., and Zeller, K.A., 2022, A sagebrush conservation design to proactively restore America’s sagebrush biome: U.S. Geological Survey Open-File Report 2022–1081, 38 p., https://doi.org/10.3133/ofr20221081.","productDescription":"Report: viii, 38 p.; Data Release; 3 Figures: 7.99 × 6.10 inches or smaller","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-138940","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":407103,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081_fig10.pdf","text":"Figure 10, full size","size":"5.46 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Conifer 2020"},{"id":407104,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081_fig11.pdf","text":"Figure 11, full size","size":"9.45 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Human Modification 2020"},{"id":407025,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081_fig09.pdf","text":"Figure 9, full size","size":"5.57 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Invasive Annual Grass 2020"},{"id":407023,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1081/ofr20221081.pdf","text":"Report","size":"32.4 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":407022,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1081/coverthb.jpg"},{"id":407024,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94Y5CDV","text":"USGS data release","linkHelpText":"Biome-wide sagebrush core habitat and growth areas estimated from a threat-based conservation design"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.6845703125,\n              33\n            ],\n            [\n              -101.25,\n              33\n            ],\n            [\n              -101.25,\n              49\n            ],\n            [\n              -121.6845703125,\n              49\n            ],\n            [\n              -121.6845703125,\n              33\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Sagebrush Ecosystem Specialist<br><a href=\"https://www.usgs.gov/mission-areas/ecosystems/land-management-research-program\" data-mce-href=\"https://www.usgs.gov/mission-areas/ecosystems/land-management-research-program\">Land Management Research Program</a><br>Ecosystems Mission Area <br>U.S. Geological Survey<br>2150 Centre Ave., Bldg. C<br>Fort Collins, CO 80526</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>Introduction</li><li>Study Area</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Supporting Information</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-09-22","noUsgsAuthors":false,"publicationDate":"2022-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Doherty, Kevin 0000-0003-3635-7346","orcid":"https://orcid.org/0000-0003-3635-7346","contributorId":176149,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin","email":"","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":true,"id":852637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Theobald, David M. 0000-0002-1271-9368","orcid":"https://orcid.org/0000-0002-1271-9368","contributorId":10271,"corporation":false,"usgs":false,"family":"Theobald","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13470,"text":"Conservation Science 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Geoffrey","contributorId":198920,"corporation":false,"usgs":false,"family":"Bedrosian","given":"Geoffrey","email":"","affiliations":[],"preferred":false,"id":852641,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyd, Chad S.","contributorId":255106,"corporation":false,"usgs":false,"family":"Boyd","given":"Chad","email":"","middleInitial":"S.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":852642,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cahill, Matthew","contributorId":245219,"corporation":false,"usgs":false,"family":"Cahill","given":"Matthew","email":"","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":852643,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":852644,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Creutzburg, Megan K.","contributorId":296727,"corporation":false,"usgs":false,"family":"Creutzburg","given":"Megan","email":"","middleInitial":"K.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":852645,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Crist, Michele R. 0000-0002-3506-3402","orcid":"https://orcid.org/0000-0002-3506-3402","contributorId":202575,"corporation":false,"usgs":true,"family":"Crist","given":"Michele","email":"","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":852646,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Finn, Sean P.","contributorId":106623,"corporation":false,"usgs":true,"family":"Finn","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":852647,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kumar, Alexander V. 0000-0003-3831-5924","orcid":"https://orcid.org/0000-0003-3831-5924","contributorId":224038,"corporation":false,"usgs":false,"family":"Kumar","given":"Alexander","email":"","middleInitial":"V.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":852648,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Littlefield, Caitlin E. 0000-0003-3771-7956","orcid":"https://orcid.org/0000-0003-3771-7956","contributorId":220623,"corporation":false,"usgs":false,"family":"Littlefield","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":852649,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Maestas, Jeremy D.","contributorId":117298,"corporation":false,"usgs":true,"family":"Maestas","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":852650,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Prentice, Karen L.","contributorId":184046,"corporation":false,"usgs":false,"family":"Prentice","given":"Karen","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":852651,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":852652,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Remington, Thomas E.","contributorId":296730,"corporation":false,"usgs":false,"family":"Remington","given":"Thomas E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":852653,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Sparklin, William D. 0000-0002-7243-9894","orcid":"https://orcid.org/0000-0002-7243-9894","contributorId":296729,"corporation":false,"usgs":false,"family":"Sparklin","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":852654,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Tull, John C. 0000-0002-0680-008X","orcid":"https://orcid.org/0000-0002-0680-008X","contributorId":201650,"corporation":false,"usgs":false,"family":"Tull","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":852655,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wurtzebach, Zachary 0000-0002-1795-1852","orcid":"https://orcid.org/0000-0002-1795-1852","contributorId":296731,"corporation":false,"usgs":false,"family":"Wurtzebach","given":"Zachary","email":"","affiliations":[{"id":35059,"text":"Center for Large Landscape Conservation","active":true,"usgs":false}],"preferred":false,"id":852656,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Zeller, Katherine A.","contributorId":204574,"corporation":false,"usgs":false,"family":"Zeller","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":852657,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}}
,{"id":70237004,"text":"70237004 - 2022 - Estimating Pacific walrus abundance and survival with multievent mark-recapture models","interactions":[],"lastModifiedDate":"2024-02-13T20:51:18.474673","indexId":"70237004","displayToPublicDate":"2022-09-22T10:34:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Estimating Pacific walrus abundance and survival with multievent mark-recapture models","docAbstract":"<p><span>Arctic marine ecosystems are undergoing rapid physical and biological change associated with climate warming and loss of sea ice. Sea ice loss will impact many species through altered spatial and temporal availability of resources. In the Bering and Chukchi Seas, the Pacific walrus&nbsp;</span><i>Odobenus rosmarus divergens</i><span>&nbsp;is one species that could be impacted by rapid environmental change, and thus, population assessments are needed to monitor changes in the status of this ecologically and culturally important marine mammal. We conducted a 5 yr genetic mark-recapture study to estimate demographic parameters for the Pacific walrus. We developed a Bayesian multievent mark-recapture model to estimate walrus survival and abundance while accounting for age misclassification. We estimated the probability of juvenile annual survival as 0.63 (95% credible interval [CrI]: 0.39-0.87) and adult female annual survival as 0.90 (95% CrI: 0.74-1.00). We estimated total abundance as 257 193 (95% CrI: 171 138-366 366). We provide the first estimate of total Pacific walrus abundance since an aerial survey in 2006, which generated a substantially less precise total population size estimate (129 000; 95% CI: 55 000-507 000). The emerging ecosystem state in the northern Bering and Chukchi Seas will likely result in a decline in Pacific walrus abundance, but there is substantial uncertainty regarding the magnitude of the anticipated decline. Our demographic estimates provide critical information to evaluate future population trends of this subsistence resource vital to communities that border the Bering and Chukchi Seas in the USA and Russia.</span></p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps14131","usgsCitation":"Beatty, W., Lemons, P., Everett, J.P., Lewis, C.J., Taylor, R.L., Lynn, R.J., Sethi, S.A., Quakenbush, L.T., Citta, J.J., Kissling, M., Kryukova, N., and Wennburg, J.K., 2022, Estimating Pacific walrus abundance and survival with multievent mark-recapture models: Marine Ecology Progress Series, v. 697, p. 167-182, https://doi.org/10.3354/meps14131.","productDescription":"16 p.","startPage":"167","endPage":"182","ipdsId":"IP-137159","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":473,"text":"New York Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":446361,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps14131","text":"Publisher Index Page"},{"id":407409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Bering Sea, Chukchi Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              60.413852350464914\n            ],\n            [\n              -159.2578125,\n              60.413852350464914\n            ],\n            [\n              -159.2578125,\n              74\n            ],\n            [\n              -179.9,\n              74\n            ],\n            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P.","contributorId":296986,"corporation":false,"usgs":false,"family":"Everett","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":64270,"text":"U.S. Fish and Wildlife Service, Conservation Genetics Laboratory, Anchorage, Alaska 99503","active":true,"usgs":false}],"preferred":false,"id":853041,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewis, Cara J.","contributorId":288794,"corporation":false,"usgs":false,"family":"Lewis","given":"Cara","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":853042,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Rebecca L. 0000-0001-8459-7614 rebeccataylor@usgs.gov","orcid":"https://orcid.org/0000-0001-8459-7614","contributorId":5112,"corporation":false,"usgs":true,"family":"Taylor","given":"Rebecca","email":"rebeccataylor@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":853043,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynn, Robert J.","contributorId":288795,"corporation":false,"usgs":false,"family":"Lynn","given":"Robert","email":"","middleInitial":"J.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":853044,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sethi, Suresh A. 0000-0002-0053-1827","orcid":"https://orcid.org/0000-0002-0053-1827","contributorId":296987,"corporation":false,"usgs":false,"family":"Sethi","given":"Suresh","email":"","middleInitial":"A.","affiliations":[{"id":64271,"text":"U.S. Geological Survey, New York Cooperative Fish and Wildlife Research Unit, Ithaca, New York 14853","active":true,"usgs":false}],"preferred":false,"id":853045,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Quakenbush, Lori T.","contributorId":192737,"corporation":false,"usgs":false,"family":"Quakenbush","given":"Lori","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":853046,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Citta, John J.","contributorId":175350,"corporation":false,"usgs":false,"family":"Citta","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":853047,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kissling, Michelle","contributorId":222160,"corporation":false,"usgs":false,"family":"Kissling","given":"Michelle","affiliations":[{"id":40501,"text":"U.S. Fish and Wildlife Service, Marine Mammals Management, 3000 Vintage Blvd., Suite 201, Juneau, AK 99801","active":true,"usgs":false}],"preferred":false,"id":853048,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kryukova, Natalia","contributorId":296988,"corporation":false,"usgs":false,"family":"Kryukova","given":"Natalia","email":"","affiliations":[{"id":64272,"text":"Kamchatka Branch of the Pacific Geographical Institute of Far Eastern Branch of Russian Academy of Sciences, Petropavlovsk-Kamchatsky, Russia, 683000","active":true,"usgs":false}],"preferred":false,"id":853049,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wennburg, John K.","contributorId":296989,"corporation":false,"usgs":false,"family":"Wennburg","given":"John","email":"","middleInitial":"K.","affiliations":[{"id":64270,"text":"U.S. Fish and Wildlife Service, Conservation Genetics Laboratory, Anchorage, Alaska 99503","active":true,"usgs":false}],"preferred":false,"id":853050,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70248069,"text":"70248069 - 2022 - Multi-objective modeling as a decision-support tool for free-roaming horse management","interactions":[],"lastModifiedDate":"2023-09-05T15:08:53.279712","indexId":"70248069","displayToPublicDate":"2022-09-22T10:04:21","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Multi-objective modeling as a decision-support tool for free-roaming horse management","docAbstract":"<p><span>Decisions related to controversial problems in natural resource management receive the greatest support when they account for multiple objectives of stakeholders in a structured and transparent fashion. In the United States, management of free-roaming horses (</span><i>Equus caballus</i><span>; horses) is a controversial multiple-objective problem because disparate stakeholder groups have varying objectives and opinions about how to manage fast-growing horse populations in ways that sustain both natural ecosystems and healthy horses. Despite much decision-support research on management alternatives that prevent excessive population size or cost, horse management decisions still receive resistance from a variety of stakeholder groups, potentially because decisions fail to explicitly or transparently account for multiple objectives of diverse stakeholders. Here, we used a predictive model for horse populations to evaluate the degree to which alternative management strategies involving removals and fertility control treatment with the immunocontraceptive vaccine PZP-22 maximize 4 objectives in horse management: maximize ecosystem health, maximize horse health, minimize effects on horse behavior, and minimize management cost. We simulated scenarios varying in management action, frequency, magnitude, and starting population size over a 10-year interval and evaluated scenario performance with a weighted multiple-objective utility reward function. Management involving high-magnitude removals along with PZP-22 treatment generally outperformed other alternatives by achieving higher reward relative to alternatives in 2 scenario analyses. Simulation of 1,372 scenarios at 5 starting population sizes generally found that management with biannual removals and 2 doses of PZP-22 treatment for half of eligible females during years 1 and 5 generated the most rewarding outcomes. However, a removal scenario with more frequent PZP-22 application generated the greatest reward when starting population size was already within target population size range. Our paper demonstrates how values and objectives of diverse stakeholders can be used to support management decisions in ways that might lead to greater acceptance of decisions by a broad array of stakeholder groups.</span></p>","language":"English","publisher":"Utah State University","doi":"10.26077/a6e8-0759","usgsCitation":"Folt, B.P., Schoenecker, K., and Ekernas, L.S., 2022, Multi-objective modeling as a decision-support tool for free-roaming horse management: Human-Wildlife Interactions, v. 16, no. 2, p. 233-250, https://doi.org/10.26077/a6e8-0759.","productDescription":"18 p.","startPage":"233","endPage":"250","ipdsId":"IP-134038","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":435684,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HRF1H9","text":"USGS data release","linkHelpText":"Multi-objective Modeling as a Decision-support Tool for Feral Horse Management"},{"id":420482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Folt, Brian Patrick 0000-0003-2278-2018","orcid":"https://orcid.org/0000-0003-2278-2018","contributorId":328937,"corporation":false,"usgs":true,"family":"Folt","given":"Brian","email":"","middleInitial":"Patrick","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ekernas, L. Stefan 0000-0002-9205-1985","orcid":"https://orcid.org/0000-0002-9205-1985","contributorId":223034,"corporation":false,"usgs":true,"family":"Ekernas","given":"L.","email":"","middleInitial":"Stefan","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":881745,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70238505,"text":"70238505 - 2022 - Laysan albatross exhibit complex behavioral plasticity in the subtropical and subarctic North Pacific Ocean","interactions":[],"lastModifiedDate":"2022-11-28T13:39:00.114514","indexId":"70238505","displayToPublicDate":"2022-09-22T07:34:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Laysan albatross exhibit complex behavioral plasticity in the subtropical and subarctic North Pacific Ocean","docAbstract":"<p><span>Animals that regularly traverse habitat extremes between the subtropics and subarctic are expected to exhibit foraging behaviors that respond to changes in dynamic ocean habitats, and these behaviors may facilitate adaptations to novel and changing climates. During the chick-provisioning stage, Laysan albatross&nbsp;</span><i>Phoebastria immutabilis</i><span>&nbsp;parents regularly undertake short- and long-distance foraging trips throughout the vast central North Pacific Ocean. We examined GPS tracking data among chick-provisioning albatrosses in Hawai‘i to characterize habitats during short- and long-distance trips. The study period encompassed a marine heatwave (2014) and the cooling period after an extreme El Niño event (2016), enabling us to examine foraging habitats under novel and changing climates. First passage time and generalized additive mixed models indicated that during 183 short and 110 long trips (n = 32 birds), wind-assisted flight efficiency, proximity to productive areas, and moonlit-searching were important in both subtropical and subarctic habitats. Laysan albatross took foraging trips that had similar lengths and durations in 2014 and 2016 and visited similar areas, indicating that their foraging range did not expand in response to climatic variability. A strategy that uses similar foraging areas across years combined with reliance on environmental processes that enhance flight efficiency (wind) and that enable searching behaviors (moonlight) indicate that Laysan albatross exhibit complex behavioral plasticity that allows them to utilize subtropical and subarctic habitats affected by dynamic climate variability. This strategy may benefit their ability to respond to oceanographic and climatic change, including expanding warm water regions and changing atmospheric conditions influenced by global warming.</span></p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/meps14148","usgsCitation":"Gilmour, M.E., Felis, J.J., Hester, M.M., Young, L.C., and Adams, J., 2022, Laysan albatross exhibit complex behavioral plasticity in the subtropical and subarctic North Pacific Ocean: Marine Ecology Progress Series, v. 697, p. 125-147, https://doi.org/10.3354/meps14148.","productDescription":"23 p.","startPage":"125","endPage":"147","ipdsId":"IP-137932","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":446368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps14148","text":"Publisher Index Page"},{"id":409685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska, Hawaii","otherGeospatial":"Pacific Ocean","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              35.095301697524135\n            ],\n            [\n              -177.86550682042343,\n              28.860574564487507\n            ],\n            [\n              -155.53062317940885,\n              20.809565675106214\n            ],\n            [\n              -147.22958348721264,\n              19.95935891124141\n            ],\n            [\n              -134.00475959018274,\n              35.360858467785576\n            ],\n            [\n              -136.90695297728425,\n              50.99805127330757\n            ],\n            [\n              -142.66136789996617,\n              59.0913410074362\n            ],\n            [\n              -147.22441346291703,\n              60.36962329343831\n            ],\n            [\n              -154.7675208704121,\n              56.641133852727194\n            ],\n            [\n              -176.45903611138576,\n              54.11395665374428\n            ],\n            [\n              -178,\n              52.825004330008824\n            ],\n            [\n              -179.9,\n              35.095301697524135\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"697","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gilmour, Morgan Elizabeth 0000-0002-2618-1095","orcid":"https://orcid.org/0000-0002-2618-1095","contributorId":289509,"corporation":false,"usgs":true,"family":"Gilmour","given":"Morgan","email":"","middleInitial":"Elizabeth","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felis, Jonathan J. 0000-0002-0608-8950 jfelis@usgs.gov","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":4825,"corporation":false,"usgs":true,"family":"Felis","given":"Jonathan","email":"jfelis@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hester, Michelle M. 0000-0002-0769-5904","orcid":"https://orcid.org/0000-0002-0769-5904","contributorId":197785,"corporation":false,"usgs":false,"family":"Hester","given":"Michelle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":857664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Lindsay C.","contributorId":149044,"corporation":false,"usgs":false,"family":"Young","given":"Lindsay","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":857665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857666,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70259620,"text":"70259620 - 2022 - The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil","interactions":[],"lastModifiedDate":"2024-10-17T12:03:37.308351","indexId":"70259620","displayToPublicDate":"2022-09-22T06:55:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil","docAbstract":"Fungi and bacteria are the two dominant groups of soil microbial communities worldwide. By controlling the turnover of soil organic matter, these organisms directly regulate the exchange of carbon between the soil and the atmosphere. Fundamental differences in the physiology and life history of bacteria and fungi suggest that variation in the biogeography of soil fungal and bacterial relative abundance could drive striking differences in carbon decomposition and soil organic matter formation across different biomes. However, a lack of global and predictive information on the distribution of these organisms in terrestrial 45 ecosystems has prevented the inclusion of soil fungal and bacterial relative abundance and the associated processes into global biogeochemical models. Here, we used a global scale dataset in the top soil surface (>3000 distinct observations of soil fungal and bacterial abundance) to generate the first quantitative and spatially high resolution (1km) explicit map of soil fungal proportion, defined as fungi/fungi + bacteria, across terrestrial ecosystems. We reveal striking latitudinal trends where fungal dominance increases in cold and high latitude environments with large soil carbon stocks. There was strong non-linear response of fungal 50 dominance to environmental gradient, i.e., mean annual temperature (MAT) and net primary productivity (NPP). Fungi and bacteria dominated in regions with low and high MAT and NPP, respectively, thus representing slow vs. fast soil energy channels, a concept with a long history in soil ecology. These high-resolution models provide the first steps towards representing the major soil microbial groups and their functional differences in global biogeochemical models to improve predictions of soil organic matter turnover under current and future climate scenarios","language":"English","publisher":"Earth System Science Data","doi":"10.5194/essd-14-4339-2022","usgsCitation":"Yu, K., Hoogen, J.V., Wang, Z., Averill, C., Routh, D., Smith, G.R., Drenovsky, R.E., Scow, K., Mo, F., Waldrop, M., Yang, Y., Tang, W., De Vries, F., Bardgett, R., Manning, P., Bastida, F., Baer, S.G., Bach, E., Garcia, C.J., Wang, Q., Ma, L., Chen, B., He, X., Teurlinex, S., Heijboer, A., Bradley, J.A., and Crowther, T.W., 2022, The biogeography of relative abundance of soil fungi versus bacteria in surface topsoil: Earth System Science Data, v. 14, p. 4339-4350, https://doi.org/10.5194/essd-14-4339-2022.","productDescription":"12 p,","startPage":"4339","endPage":"4350","ipdsId":"IP-116714","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467161,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/essd-14-4339-2022","text":"Publisher Index Page"},{"id":462936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2022-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Yu, Kailiang","contributorId":221398,"corporation":false,"usgs":false,"family":"Yu","given":"Kailiang","email":"","affiliations":[{"id":40362,"text":"Department of Environmental Sciences, University of Virginia, Charlottesville, VA 22904, USA","active":true,"usgs":false}],"preferred":false,"id":915995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoogen, Johan van den","contributorId":345210,"corporation":false,"usgs":false,"family":"Hoogen","given":"Johan","email":"","middleInitial":"van den","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":915996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Zhiqiang","contributorId":345211,"corporation":false,"usgs":false,"family":"Wang","given":"Zhiqiang","email":"","affiliations":[{"id":82525,"text":"Chengdu University","active":true,"usgs":false}],"preferred":false,"id":915997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Averill, Colin","contributorId":245299,"corporation":false,"usgs":false,"family":"Averill","given":"Colin","email":"","affiliations":[],"preferred":false,"id":915998,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Routh, Devin","contributorId":345212,"corporation":false,"usgs":false,"family":"Routh","given":"Devin","email":"","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":915999,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Gabriel Reuben","contributorId":345213,"corporation":false,"usgs":false,"family":"Smith","given":"Gabriel","email":"","middleInitial":"Reuben","affiliations":[{"id":12483,"text":"ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":916000,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Drenovsky, Rebecca E.","contributorId":345214,"corporation":false,"usgs":false,"family":"Drenovsky","given":"Rebecca","email":"","middleInitial":"E.","affiliations":[{"id":27555,"text":"John Carroll University","active":true,"usgs":false}],"preferred":false,"id":916001,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Scow, Kate M.","contributorId":345215,"corporation":false,"usgs":false,"family":"Scow","given":"Kate M.","affiliations":[{"id":82527,"text":"U. California Davis","active":true,"usgs":false}],"preferred":false,"id":916002,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mo, Fei","contributorId":344978,"corporation":false,"usgs":false,"family":"Mo","given":"Fei","email":"","affiliations":[{"id":82451,"text":"College of Agronomy, Northwest A&F University, Yangling, Xianyang, Shaanxi, 712100, China;","active":true,"usgs":false}],"preferred":false,"id":916003,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waldrop, Mark 0000-0003-1829-7140","orcid":"https://orcid.org/0000-0003-1829-7140","contributorId":216769,"corporation":false,"usgs":true,"family":"Waldrop","given":"Mark","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":916004,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yang, Yuanhe","contributorId":247646,"corporation":false,"usgs":false,"family":"Yang","given":"Yuanhe","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":916005,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Tang, Weize","contributorId":345216,"corporation":false,"usgs":false,"family":"Tang","given":"Weize","email":"","affiliations":[],"preferred":false,"id":916006,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"De Vries, Franciska","contributorId":345217,"corporation":false,"usgs":false,"family":"De Vries","given":"Franciska","affiliations":[{"id":37958,"text":"University of Amsterdam","active":true,"usgs":false}],"preferred":false,"id":916007,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bardgett, Richard D.","contributorId":266148,"corporation":false,"usgs":false,"family":"Bardgett","given":"Richard D.","affiliations":[{"id":54928,"text":"School of Earth and Environmental Sciences, Michael Smith Building, The University of Manchester, Oxford Road, Manchester M13 9PT, UK","active":true,"usgs":false}],"preferred":false,"id":916008,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Manning, Peter","contributorId":345218,"corporation":false,"usgs":false,"family":"Manning","given":"Peter","email":"","affiliations":[],"preferred":false,"id":916009,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Bastida, Felipe","contributorId":240755,"corporation":false,"usgs":false,"family":"Bastida","given":"Felipe","email":"","affiliations":[],"preferred":false,"id":916010,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Baer, Sara G.","contributorId":189135,"corporation":false,"usgs":false,"family":"Baer","given":"Sara","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":916011,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Bach, Elizabeth","contributorId":345219,"corporation":false,"usgs":false,"family":"Bach","given":"Elizabeth","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":916012,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Garcia, Carlos J.","contributorId":342669,"corporation":false,"usgs":false,"family":"Garcia","given":"Carlos","email":"","middleInitial":"J.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":916013,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Wang, Qingkui","contributorId":345220,"corporation":false,"usgs":false,"family":"Wang","given":"Qingkui","email":"","affiliations":[{"id":82528,"text":"CAS Key Laboratory of Forest Ecology and Management, China","active":true,"usgs":false}],"preferred":false,"id":916014,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Ma, Linna","contributorId":345221,"corporation":false,"usgs":false,"family":"Ma","given":"Linna","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":916015,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Chen, Baodong","contributorId":345222,"corporation":false,"usgs":false,"family":"Chen","given":"Baodong","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":916016,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"He, Xianjing","contributorId":345223,"corporation":false,"usgs":false,"family":"He","given":"Xianjing","email":"","affiliations":[{"id":34946,"text":"Lanzhou University, China","active":true,"usgs":false}],"preferred":false,"id":916017,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Teurlinex, Sven","contributorId":345224,"corporation":false,"usgs":false,"family":"Teurlinex","given":"Sven","email":"","affiliations":[{"id":35358,"text":"Netherlands Institute of Ecology","active":true,"usgs":false}],"preferred":false,"id":916018,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Heijboer, Amber","contributorId":345225,"corporation":false,"usgs":false,"family":"Heijboer","given":"Amber","email":"","affiliations":[{"id":36528,"text":"Wageningen University & Research","active":true,"usgs":false}],"preferred":false,"id":916019,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Bradley, James A.","contributorId":345226,"corporation":false,"usgs":false,"family":"Bradley","given":"James","email":"","middleInitial":"A.","affiliations":[{"id":35299,"text":"Queen Mary University of London","active":true,"usgs":false}],"preferred":false,"id":916020,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Crowther, Thomas W.","contributorId":177398,"corporation":false,"usgs":false,"family":"Crowther","given":"Thomas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":916021,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}}
,{"id":70236867,"text":"fs20223074 - 2022 - Loss of street tree canopy increases stormwater runoff","interactions":[],"lastModifiedDate":"2026-03-25T16:41:23.615596","indexId":"fs20223074","displayToPublicDate":"2022-09-21T14:01:11","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3074","displayTitle":"Loss of Street Tree Canopy Increases Stormwater Runoff","title":"Loss of street tree canopy increases stormwater runoff","docAbstract":"<p>Urban forests have largely been overlooked for the role they play in reducing stormwater runoff volume by using hydrologic processes such as interception (rainfall intercepted by tree canopy), evapotranspiration (the transfer of water from vegetation into the atmosphere) and infiltration (percolation of rainwater into the Earth’s soil). Early research into the effects of trees on urban stormwater runoff used simple estimates based on assumptions of canopy coverage and design storm criteria. In a review of available literature on how capable urban trees are at reducing runoff, the Center for Watershed Protection (2017) found only six studies; three of them used measured data from a single plot, and the other three used models. When identifying gaps in research on the role of trees in stormwater management, Kuehler and others (2017) highlighted the need for studies that scale the local effects of urban trees to the larger sewershed catchment area, allowing a more holistic understanding of the urban tree canopy effects on hydrology.</p><p>For these reasons, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, U.S. Forest Service, and the University of Wisconsin, quantified the effect of removing urban street trees and their canopy on stormwater generation in a medium-density residential area. Using a paired-catchment experimental design, rainfall-runoff relations were characterized in two medium-density residential catchments in Fond du Lac, Wisconsin, during May through September in 2018–20. Results of the study are detailed in Selbig and others (2022).</p><p>During the calibration phase, hydrograph metrics from paired runoff events were used to develop the relation between the control and test catchments with street trees in place. The ability to measure changes to the rainfall-runoff response after removal of tree canopy was made possible by an aggressive tree removal program by the city as a response to rapid infestation from the <i>Agrilus planipennis</i> (emerald ash borer). In March 2020, a total of 31 street trees were removed at the onset of the treatment period, resulting in a loss of 2,990 square meters of canopy over streets, driveways, sidewalks, and grassed areas.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223074","usgsCitation":"Selbig, W.R., Loheide, S.P., II, Shuster, W., Scharenbroch, B.C., Coville, R.C., Kruegler, J., Avery, W., Haefner, R., and Nowak, D., 2022, Loss of street tree canopy increases stormwater runoff: U.S. Geological Survey Fact Sheet 2022–3074, 4 p., https://doi.org/10.3133/fs20223074.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-141242","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":407081,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3074/fs20223074.XML"},{"id":407082,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3074/images"},{"id":407157,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20223074/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":407079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3074/coverthb.jpg"},{"id":407080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3074/fs20223074.pdf","text":"Report","size":"1.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022–3074"},{"id":501510,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113526.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wisconsin","city":"Fond du Lac","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.494873046875,\n              43.72148995228582\n            ],\n            [\n              -88.37127685546875,\n              43.72148995228582\n            ],\n            [\n              -88.37127685546875,\n              43.82065657651688\n            ],\n            [\n              -88.494873046875,\n              43.82065657651688\n            ],\n            [\n              -88.494873046875,\n              43.72148995228582\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/upper-midwest-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/upper-midwest-water-science-center\">Upper Midwest Water Science Center</a><br>U.S. Geological Survey<br>1 Gifford Pinchot Drive<br>Madison, WI 53726</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Changes in Stormwater Runoff After Tree Removal</li><li>Implications for Stormwater Management</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2022-09-21","noUsgsAuthors":false,"publicationDate":"2022-09-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loheide, Steven P. II","contributorId":62377,"corporation":false,"usgs":false,"family":"Loheide","given":"Steven","suffix":"II","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":852408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shuster, William","contributorId":147261,"corporation":false,"usgs":false,"family":"Shuster","given":"William","affiliations":[{"id":16813,"text":"Sustainable Environments Branch, National Risk Management Research Laboratory, Office of Research and Development, EPA","active":true,"usgs":false}],"preferred":false,"id":852409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scharenbroch, Bryant C. 0000-0002-9342-7550","orcid":"https://orcid.org/0000-0002-9342-7550","contributorId":269849,"corporation":false,"usgs":false,"family":"Scharenbroch","given":"Bryant","email":"","middleInitial":"C.","affiliations":[{"id":17613,"text":"University of Wisconsin - Stevens Point","active":true,"usgs":false}],"preferred":false,"id":852410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coville, Robert C. 0000-0002-6895-2564","orcid":"https://orcid.org/0000-0002-6895-2564","contributorId":269851,"corporation":false,"usgs":false,"family":"Coville","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":40823,"text":"Davey Institute","active":true,"usgs":false}],"preferred":false,"id":852411,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kruegler, James 0000-0002-2671-0807","orcid":"https://orcid.org/0000-0002-2671-0807","contributorId":269853,"corporation":false,"usgs":false,"family":"Kruegler","given":"James","email":"","affiliations":[{"id":40823,"text":"Davey Institute","active":true,"usgs":false}],"preferred":false,"id":852412,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Avery, William 0000-0002-2651-9906","orcid":"https://orcid.org/0000-0002-2651-9906","contributorId":269858,"corporation":false,"usgs":false,"family":"Avery","given":"William","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":852413,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haefner, Ralph J. 0000-0002-4363-9010 rhaefner@usgs.gov","orcid":"https://orcid.org/0000-0002-4363-9010","contributorId":1793,"corporation":false,"usgs":true,"family":"Haefner","given":"Ralph","email":"rhaefner@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":852414,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nowak, David 0000-0002-2043-0062","orcid":"https://orcid.org/0000-0002-2043-0062","contributorId":269856,"corporation":false,"usgs":false,"family":"Nowak","given":"David","email":"","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":852415,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70237157,"text":"70237157 - 2022 - Undeveloped and developed phases in the centennial evolution of a barrier-marsh-lagoon system: The case of Long Beach Island, New Jersey","interactions":[],"lastModifiedDate":"2022-11-08T16:52:42.128656","indexId":"70237157","displayToPublicDate":"2022-09-21T11:58:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Undeveloped and developed phases in the centennial evolution of a barrier-marsh-lagoon system: The case of Long Beach Island, New Jersey","docAbstract":"<p><span>Barrier islands and their associated backbarrier environments protect mainland population centers and infrastructure from storm impacts, support biodiversity, and provide long-term carbon storage, among other ecosystem services. Despite their socio-economic and ecological importance, the response of coupled barrier-marsh-lagoon environments to sea-level rise is poorly understood. Undeveloped barrier-marsh-lagoon systems typically respond to sea-level rise through the process of landward migration, driven by storm overwash and landward mainland marsh expansion. Such response, however, can be affected by human development and engineering activities such as lagoon dredging and shoreline stabilization. To better understand the difference in the response between developed and undeveloped barrier-marsh-lagoon environments to sea-level rise, we perform a local morphologic analysis that describes the evolution of Long Beach Island (LBI), New Jersey, over the last 182 years. We find that between 1840 and 1934 the LBI system experienced landward migration of all five boundaries, including 171 meters of shoreline retreat. Between the 1920s and 1950s, however, there was a significant shift in system behavior that coincided with the onset of groin construction, which was enhanced by beach nourishment and lagoon dredging practices. From 1934 to 2022 the LBI system experienced ~22 meters of shoreline progradation and a rapid decline in marsh platform extent. Additionally, we extend a morphodynamic model to describe the evolution of the system in terms of five geomorphic boundaries: the ocean shoreline and backbarrier-marsh interface, the seaward and landward lagoon-marsh boundaries, and the landward limit of the inland marsh. We couple this numerical modeling effort with the map analysis during the undeveloped phase of LBI evolution, between 1840 and 1934. Despite its simplicity, the modeling framework can describe the average cross-shore evolution of the barrier-marsh-lagoon system during this period without accounting for human landscape modifications, supporting the premise that natural processes were the key drivers of morphological change. Overall, these results suggest that anthropogenic effects have played a major role in the evolution of LBI over the past century by altering overwash fluxes and marsh-lagoon geometry; this is likely the case for other barrier-marsh-lagoon environments around the world.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2022.958573","usgsCitation":"Tenebruso, C., Nichols-O’Neill, S., Lorenzo-Trueba, J., Ciarletta, D.J., and Miselis, J.L., 2022, Undeveloped and developed phases in the centennial evolution of a barrier-marsh-lagoon system: The case of Long Beach Island, New Jersey: Frontiers in Marine Science, v. 9, 958573, 15 p., https://doi.org/10.3389/fmars.2022.958573.","productDescription":"958573, 15 p.","ipdsId":"IP-141531","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":446374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2022.958573","text":"Publisher Index Page"},{"id":409230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Long Beach island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.07802920592502,\n              39.74949430937235\n            ],\n            [\n              -74.11619642132992,\n              39.76972910720298\n            ],\n            [\n              -74.32809027237006,\n              39.48488546642025\n            ],\n            [\n              -74.27149750470127,\n              39.46863133845025\n            ],\n            [\n              -74.07802920592502,\n              39.74949430937235\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Tenebruso, Christopher","contributorId":297141,"corporation":false,"usgs":false,"family":"Tenebruso","given":"Christopher","email":"","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":853509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nichols-O’Neill, Shane","contributorId":297142,"corporation":false,"usgs":false,"family":"Nichols-O’Neill","given":"Shane","email":"","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":853510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenzo-Trueba, Jorge","contributorId":297143,"corporation":false,"usgs":false,"family":"Lorenzo-Trueba","given":"Jorge","affiliations":[{"id":36592,"text":"Montclair State University","active":true,"usgs":false}],"preferred":false,"id":853511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ciarletta, Daniel J. 0000-0002-8555-2239","orcid":"https://orcid.org/0000-0002-8555-2239","contributorId":256700,"corporation":false,"usgs":true,"family":"Ciarletta","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":853513,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70237705,"text":"70237705 - 2022 - Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development","interactions":[],"lastModifiedDate":"2022-10-31T14:56:21.921244","indexId":"70237705","displayToPublicDate":"2022-09-21T08:23:19","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Context</h3><p>Wildlife avoid human disturbances, including roads and development. Avoidance and displacement of wildlife into less suitable habitat due to human development can affect their energy expenditures and fitness. The heart rate and oxygen uptake of large mammals varies with both natural aspects of their habitat (terrain, climate, predators, etc.) and anthropogenic influence (noise, light, fragmentation, etc.). Although incorporating physiological analyses of energetics can inform the impacts of both development and conservation, management decisions rarely incorporate individuals’ energetic requirements when deciding on locations for potential development.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Objectives</h3><p>We aimed to estimate the change in expected energy expenditure, numerically and spatially, for mule deer to traverse a landscape with varying levels of oil and gas development through time.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>Using calculations of energy expenditure of mule deer (<i>Odocoileus hemionus</i>) by weight, in relation to physical terrain components, plus avoidance factors for anthropogenic disturbance, we developed a spatiotemporal model of the minimum energy required for mule deer to traverse a landscape. We compared expected energy expenditure across 12 study sites with increasing levels of oil and gas development and over time in our study area, on the northern Colorado Plateau of Utah.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>We found that energy expenditure can be increased by development, regardless of terrain, through increased travel distance associated with avoidance behavior. Maximum median energy expenditure to traverse a 1400&nbsp;ha sample area rose from 1135 to 1935&nbsp;kilocalories, a 70% increase in energy required of a mule deer. There was a significant relationship between energy expenditure and the size of oil and gas development (p &lt; 0.001), its compactness (p &lt; 0.05), and its ‘thinness’ (p &lt; 0.001), but not terrain ruggedness (p = 0.25).</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusion</h3><p>As the energy costs of movement correlate across multiple species of large mammals, our analysis of the energetic cost, for mule deer, associated with development can serve as a quantitative representative of the impacts of oil and gas development for multiple mammals—including threatened or endangered species. Our bioenergetic cost-distance model provides a means of delineating impediments to efficient movement and can be used to quantify the expected energetic costs of proposed future developments. As wildlife are exposed to increasing anthropogenic stressors which reduce fitness, it is important to make strategic siting decisions to reduce energetic costs imposed by human activities.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-022-01521-w","usgsCitation":"Chambers, S.N., Villarreal, M.L., Duane, O.J., Munson, S.M., Stuber, E.F., Tyree, G., Waller, E.K., and Duniway, M.C., 2022, Conflict of energies: Spatially modeling mule deer caloric expenditure in response to oil and gas development: Landscape Ecology, v. 37, p. 2947-2961, https://doi.org/10.1007/s10980-022-01521-w.","productDescription":"15 p.","startPage":"2947","endPage":"2961","ipdsId":"IP-138879","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":435685,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99JGAYG","text":"USGS data release","linkHelpText":"Maps of mule deer avoidance areas based on density of oil and gas developments, Book Cliffs, Utah"},{"id":408538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"northern Colorado Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -110.753173828125,\n              38.77978137804918\n            ],\n            [\n              -109.072265625,\n              38.77978137804918\n            ],\n            [\n              -109.072265625,\n              40.49709237269567\n            ],\n            [\n              -110.753173828125,\n              40.49709237269567\n            ],\n            [\n              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Center","active":true,"usgs":true}],"preferred":true,"id":855076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duane, Olivia Jane Marie","contributorId":298083,"corporation":false,"usgs":true,"family":"Duane","given":"Olivia","email":"","middleInitial":"Jane Marie","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":855077,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":855078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stuber, Erica Francis 0000-0002-2687-6874","orcid":"https://orcid.org/0000-0002-2687-6874","contributorId":298084,"corporation":false,"usgs":true,"family":"Stuber","given":"Erica","email":"","middleInitial":"Francis","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":855079,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tyree, Gayle L","contributorId":298085,"corporation":false,"usgs":false,"family":"Tyree","given":"Gayle L","affiliations":[{"id":64492,"text":"Plant and Environmental Sciences Department, New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":855080,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waller, Eric K","contributorId":298087,"corporation":false,"usgs":false,"family":"Waller","given":"Eric","email":"","middleInitial":"K","affiliations":[{"id":64493,"text":"Independent USGS contractor","active":true,"usgs":false}],"preferred":false,"id":855081,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":855082,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70232986,"text":"70232986 - 2022 - Evolution of design ground motions in California: NEHRP 2009 to 2020","interactions":[],"lastModifiedDate":"2023-01-13T17:53:46.459843","indexId":"70232986","displayToPublicDate":"2022-09-20T11:51:31","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Evolution of design ground motions in California: NEHRP 2009 to 2020","docAbstract":"The U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) is used in construction codes, such as the National Earthquake Hazard Reduction Program (NEHRP) Provisions, to develop ground motions for structural and geotechnical design. When the NSHM is updated (e.g. changes to its earthquake rupture forecast or ground motion models), or the manner in which it is implemented in construction codes changes, design ground motion values can increase or decrease at a given location. This study presents an analysis of 21 sites in California to characterize how design ground motion values (SS, S1, SMS, SM1) have changed from the 2009 to 2015 to 2020 NEHRP Provisions. Four sites are presented in greater detail: two in Southern California and two in Northern California. The results show that significant changes in design ground motion values between NEHRP releases are explained by major changes in the NSHM science (e.g., inclusion of basin effects) and its use (e.g., for a broader range of site classes), but in ways that are difficult to ascertain beforehand. It is therefore likely that design ground motion values may continue to evolve between NSHM and construction code updates as the earthquake science and engineering field's understanding continues to advance.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Waldvogel, S.E., Makdisi, A.J., Peralta, K.S., Mason, H., Luco, N., and Rezaeian, S., 2022, Evolution of design ground motions in California: NEHRP 2009 to 2020, <i>in</i> Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 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,{"id":70233183,"text":"70233183 - 2022 - A theoretical framework for integrating ground failure models into regional seismic performance assessments of buried pipelines","interactions":[],"lastModifiedDate":"2023-01-13T17:49:18.224903","indexId":"70233183","displayToPublicDate":"2022-09-20T11:47:34","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A theoretical framework for integrating ground failure models into regional seismic performance assessments of buried pipelines","docAbstract":"A variety of models exist for characterizing earthquake-induced ground failures, but application of these models towards regional seismic performance assessments of buried pipelines remains challenging. One challenge is that ground failures often occur at localized geospatial scales while buried pipelines are spatially distributed over long distances. In this study, we propose a theoretical framework to integrate ground failure models into such assessments. We demonstrate a proof of concept via a numerical example with an illustrative gas transmission network in southern California subjected to ground shaking from the 1994 M6.7 Northridge earthquake.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Kwong, N.S., and Jaiswal, K.S., 2022, A theoretical framework for integrating ground failure models into regional seismic performance assessments of buried pipelines, <i>in</i> Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134606","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403884,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kwong, N. Simon 0000-0003-3017-9585","orcid":"https://orcid.org/0000-0003-3017-9585","contributorId":241863,"corporation":false,"usgs":true,"family":"Kwong","given":"N.","email":"","middleInitial":"Simon","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":846709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":846710,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70234406,"text":"70234406 - 2022 - Spatially continuous models of aleatory variability in seismic site response for southern California","interactions":[],"lastModifiedDate":"2023-01-13T17:58:19.319891","indexId":"70234406","displayToPublicDate":"2022-09-20T11:38:18","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Spatially continuous models of aleatory variability in seismic site response for southern California","docAbstract":"<p>We develop an empirical, spatially continuous model for the single-station within-event (<i>ϕ</i><sub>SS</sub>) component of earthquake ground motion variability in the Los Angeles area. <i>ϕ</i><sub>SS</sub> represents event-to-event variability in site response or remaining variability due to path effects not captured by ground motion models. Site-specific values of <i>ϕ</i><sub>SS</sub> at permanent seismic network stations were estimated during our previous work [1]. Here we first fit a model to <i>ϕ</i><sub>SS</sub> conditioned on the time-averaged shear wave velocity in the upper 30 m (V<sub>S30</sub>). We observe that stations on soft soil have larger average variability in site response than those on rock, especially at short periods. We use regression kriging to spatially interpolate <i>ϕ</i><sub>SS</sub> to an even grid spacing, using the V<sub>S30</sub>-scaling as the background model [2]. This improves on previous work that used ordinary kriging for interpolation [1]. We find that <i>ϕ</i><sub>SS</sub> ranges from about 0.1 to 0.4 natural log units in our study area, representing variations in site response at single locations of a factor of 1.1 up to a factor of 1.5. There is both greater variability and more coherency in the variability for short-period site response than for long periods. We recommend using these <i>ϕ</i><sub>SS</sub> models with the site response models of [1] for applications where quantification of variability is needed, such as probabilistic seismic hazard analyses.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Parker, G.A., Baltay Sundstrom, A.S., and Thompson, E.M., 2022, Spatially continuous models of aleatory variability in seismic site response for southern California, <i>in</i> Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134370","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411890,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411887,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117,\n              35\n            ],\n            [\n              -119,\n              35\n            ],\n            [\n              -119,\n              33\n            ],\n            [\n              -117,\n              33\n            ],\n            [\n              -117,\n              35\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":848815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baltay Sundstrom, 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 Sundstrom","given":"Annemarie","email":"abaltay@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":848816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":848817,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70234408,"text":"70234408 - 2022 - Performance of NGA-East GMMs and site amplification models relative to CENA ground motions","interactions":[],"lastModifiedDate":"2023-01-13T17:37:46.927262","indexId":"70234408","displayToPublicDate":"2022-09-20T11:33:49","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Performance of NGA-East GMMs and site amplification models relative to CENA ground motions","docAbstract":"<p>We investigate bias in ground motions predicted for Central and Eastern North America (CENA) using ground motion models (GMMs) combined with site amplification models developed in the NGA-East project. Bias is anticipated because of de-coupled procedures used in the development of the GMMs and site amplification models. The NGA-East GMMs were mainly calibrated by adjusting CENA data to a reference site condition using a site amplification model appropriate for active tectonic regions. Hence, these GMMs are likely biased relative to the CENA reference site condition (3000 m/sec shear wave velocity). Moreover, the NGA-East site amplification model recommended for hazard applications contains a simulation-based term for amplification between the reference condition and time-averaged shear wave velocity V<sub>S30</sub>=760 m/sec, which is uncertain and has not been calibrated against data from sites with that reference condition. Using the NGA-East dataset, we apply mixed-effects residual analysis and identify that period-dependent bias in 5% damped response spectral acceleration is present across a wide frequency range, but is strongest (i.e., overestimating by a factor of 2) at short oscillator periods &lt;0.2 sec. Ongoing work to remedy this bias consists of expanding the NGA-East dataset with more recent recordings and enhanced metadata, particularly regarding site conditions.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Ramos-Sepulveda, M.E., Parker, G.A., Li, M., Ilhan, O., Hashash, Y.M., Rathje, E., and Stewart, J.P., 2022, Performance of NGA-East GMMs and site amplification models relative to CENA ground motions, <i>in</i> Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 4 p.","productDescription":"4 p.","ipdsId":"IP-134994","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":411886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411885,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ramos-Sepulveda, Maria E.","contributorId":294748,"corporation":false,"usgs":false,"family":"Ramos-Sepulveda","given":"Maria","email":"","middleInitial":"E.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":848818,"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":848819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Meibai","contributorId":294749,"corporation":false,"usgs":false,"family":"Li","given":"Meibai","email":"","affiliations":[{"id":34217,"text":"UT Austin","active":true,"usgs":false}],"preferred":false,"id":848820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ilhan, Okan","contributorId":294751,"corporation":false,"usgs":false,"family":"Ilhan","given":"Okan","email":"","affiliations":[{"id":63637,"text":"Ankara Bildirim Beyazıt University, Turkey","active":true,"usgs":false}],"preferred":false,"id":848821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hashash, Youssef M. 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,{"id":70235827,"text":"70235827 - 2022 - Applicability of the NGA-West2 damping scaling factors to ground motions recorded in France","interactions":[],"lastModifiedDate":"2023-01-13T17:59:24.302106","indexId":"70235827","displayToPublicDate":"2022-09-20T11:26:46","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Applicability of the NGA-West2 damping scaling factors to ground motions recorded in France","docAbstract":"This paper presents a summary of the applicability of the NGA-West2 damping scaling factors to ground motions recorded in France. In developing ground motion models for response spectra, generally, the damping of the oscillator is set to a reference value of five percent of the critical damping. Damping scaling factors (DSF) are used to translate the predictions of 5%-damped ground motion models to any damping ratio of interest. Rezaeian et al. (2014) developed a DSF model based on the NGA-West2 database, capturing the effect of oscillator period, event magnitude, and source-to-site distance. This paper investigates the applicability of that model for the horizontal component of ground motions recorded in France, using Traversa et al. 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,{"id":70243540,"text":"70243540 - 2022 - Earthquake scenario development in the 2023 USGS NSHM update","interactions":[],"lastModifiedDate":"2024-02-28T17:14:07.040659","indexId":"70243540","displayToPublicDate":"2022-09-20T11:11:11","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Earthquake scenario development in the 2023 USGS NSHM update","docAbstract":"Earthquake scenarios are generally selected to serve a wide variety of local and regional needs ranging from testing a community’s ability to respond to earthquakes to developing proactive targeted mitigation strategies for minimizing impending risk. These deterministic scenarios can also be used to communicate seismic hazard and risk to audiences who are not well versed in more complex methods like probabilistic seismic hazard assessment (PSHA). Accordingly, the U.S. Geological Survey plans to produce a suite of scenarios to accompany the release of the 2023 update to the National Seismic Hazard Model (NSHM). The manuscript describes a preliminary framework for scenario development from hazard and risk/consequence perspectives. Historical seismicity-, hazard-, and consequence-based scenario selection techniques as well as other factors in scenario selection are discussed. The 2023 NSHM scenario development efforts aim to incorporate both hazard and risk considerations while working in close collaboration with local experts and stakeholders.","conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Chase, R.E., Jaiswal, K.S., and Petersen, M.D., 2022, Earthquake scenario development in the 2023 USGS NSHM update, 12th National Conference on Earthquake Engineering, Salt Lake City, UT, June 27-July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134741","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":426077,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416947,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eeri.org/what-we-offer/digital-library/?lid=12862"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Chase, Robert Edward 0000-0002-8155-6830","orcid":"https://orcid.org/0000-0002-8155-6830","contributorId":271198,"corporation":false,"usgs":true,"family":"Chase","given":"Robert","email":"","middleInitial":"Edward","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":872281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":872282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":872283,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70247437,"text":"70247437 - 2022 - Earthquake scenario selection for portfolio holders in CEUS: A case study with Oklahoma DOT","interactions":[],"lastModifiedDate":"2024-02-28T17:04:27.503045","indexId":"70247437","displayToPublicDate":"2022-09-20T10:55:56","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Earthquake scenario selection for portfolio holders in CEUS: A case study with Oklahoma DOT","docAbstract":"<p>Portfolio managers of spatially distributed assets in the central and eastern United States (CEUS) and other low- to moderate seismic hazard regions require scenario-based seismic risk assessment for the purpose of emergency management and planning. Uncertainties regarding the long-term seismicity of the region, unknown faults, and limited historical records complicate the selection of an earthquake scenario. Through a case study with the Oklahoma Department of Transportation (ODOT) and their&nbsp; portfolio of bridges, we look at one such exercise, which consists of two scenario earthquakes: one scenario earthquake selected from the U.S. Geological Survey Building Seismic Safety Commission (BSSC) scenario catalog, a magnitude (M) 7.2 event on the Meers fault, and a second aftershock selected by the consequence-driven earthquake scenario selection (Co-DESS) method. The latter is driven by ODOT’s desired service actions to be included during the earthquake drill; in this case, we identify an earthquake that is likely to trigger inspections for bridges across multiple districts, thereby testing not only inspection protocols but also coordination efforts between district groups. We find that the Co-DESS selected event is smaller in magnitude and offers different geographical options than selection through conventional selection methods, while still meeting necessary consequences for an effective earthquake exercise.</p>","conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"June 27-July 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Lin, Y.C., Rotche, L.L., Lin, K., Thompson, E.M., Lallemant, D., Peters, W., and Wald, D.J., 2022, Earthquake scenario selection for portfolio holders in CEUS: A case study with Oklahoma DOT, 12th National Conference on Earthquake Engineering, Salt Lake City, UT, June 27-July 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-134897","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":426076,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":419563,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eeri.org/what-we-offer/digital-library/?lid=12848","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lin, Yolanda C 0000-0002-0423-4248","orcid":"https://orcid.org/0000-0002-0423-4248","contributorId":317878,"corporation":false,"usgs":false,"family":"Lin","given":"Yolanda","email":"","middleInitial":"C","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":879626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotche, L. L.","contributorId":317880,"corporation":false,"usgs":false,"family":"Rotche","given":"L.","email":"","middleInitial":"L.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":879627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lin, Kuo-wan 0000-0002-7520-8151 klin@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-8151","contributorId":1539,"corporation":false,"usgs":true,"family":"Lin","given":"Kuo-wan","email":"klin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879629,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lallemant, David 0000-0001-5759-9972","orcid":"https://orcid.org/0000-0001-5759-9972","contributorId":290680,"corporation":false,"usgs":false,"family":"Lallemant","given":"David","email":"","affiliations":[{"id":16631,"text":"Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":879630,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peters, W.","contributorId":334405,"corporation":false,"usgs":false,"family":"Peters","given":"W.","affiliations":[],"preferred":false,"id":879631,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879632,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70236045,"text":"70236045 - 2022 - Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada","interactions":[],"lastModifiedDate":"2023-01-13T16:57:17.889035","indexId":"70236045","displayToPublicDate":"2022-09-20T10:51:36","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada","docAbstract":"<p>We present a framework to evaluate the inclusion of candidate basin depth models in the U.S. Geological Survey National Seismic Hazard Model. We compute intensity measures (peak and spectral amplitudes) from uniformly processed earthquake ground motions in and around the basin of interest and compare these to ground-motion model (GMM) estimates over a range of oscillator periods. The GMMs use depth to specific shear-wave velocity isosurfaces (Z<sub>x</sub>) as a proxy for basin depth. We quantify whether the GMM estimates using Z<sub>x</sub> from the candidate basin depth model outperform the default estimates based on V<sub>S30</sub> (the time-averaged shear wave velocity in the upper 30 m). We partition GMM residuals into event and site terms and compare site terms for stations within the basin to non-basin sites. We apply this framework to the greater Reno, Nevada, region, which has shallow basin depths (less than 450 m) and empirical amplifications of up to a factor of 2.2 at 1.0 s. There are no strong trends in site terms with basin depth, and the use of Z<sub>x</sub> values from the new candidate basin model shows marginal improvement of GMM total residuals compared to the default V<sub>S30</sub>-based model (the condition of no relative basin amplification).</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings from the 12th national conference on earthquake engineering","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th National Conference on Earthquake Engineering","conferenceDate":"Jun 27 - Jul 1, 2022","conferenceLocation":"Salt Lake City, UT","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Ahdi, S.K., Moschetti, M.P., Aagaard, B.T., Abernathy, K., Boyd, O.S., and Stephenson, W.J., 2022, Implementation of basin models and sediment depth terms in the 2023 update of the U.S. National Seismic Hazard Model: Example from Reno, Nevada, <i>in</i> Proceedings from the 12th national conference on earthquake engineering, Salt Lake City, UT, Jun 27 - Jul 1, 2022, 5 p.","productDescription":"5 p.","ipdsId":"IP-140743","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":411876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":411875,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://12ncee.org/program/proceedings","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","city":"Reno","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.93834598508883,\n              39.62289066656979\n            ],\n            [\n              -119.93834598508883,\n              39.395646949350606\n            ],\n            [\n              -119.63341035528262,\n              39.395646949350606\n            ],\n            [\n              -119.63341035528262,\n              39.62289066656979\n            ],\n            [\n              -119.93834598508883,\n              39.62289066656979\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ahdi, Sean Kamran 0000-0003-0274-5180","orcid":"https://orcid.org/0000-0003-0274-5180","contributorId":265143,"corporation":false,"usgs":true,"family":"Ahdi","given":"Sean","email":"","middleInitial":"Kamran","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aagaard, Brad T. 0000-0002-8795-9833 baagaard@usgs.gov","orcid":"https://orcid.org/0000-0002-8795-9833","contributorId":192869,"corporation":false,"usgs":true,"family":"Aagaard","given":"Brad","email":"baagaard@usgs.gov","middleInitial":"T.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":849797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Abernathy, Kaitlyn 0000-0002-0360-8519","orcid":"https://orcid.org/0000-0002-0360-8519","contributorId":295721,"corporation":false,"usgs":true,"family":"Abernathy","given":"Kaitlyn","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849798,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":849799,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":849800,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70237207,"text":"70237207 - 2022 - Wildlife population dynamics","interactions":[],"lastModifiedDate":"2022-10-05T15:43:52.58506","indexId":"70237207","displayToPublicDate":"2022-09-20T10:42:46","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","title":"Wildlife population dynamics","docAbstract":"In this chapter we provide an overview of some core concepts, describe exponential growth as the basic foundation for understanding population dynamics, and discuss some of the factors that can affect wildlife population dynamics. We then show how management insights that can be gained from analyzing the dynamics of individual age or stage classes, examine dynamics of multiple populations across a landscape, consider key aspects of monitoring wildlife population dynamics, and close with a case study applying many of the topics in the chapter. Throughout we stress a few key themes: (1) variation is as important as the mean in understanding population dynamics (embrace uncertainty!); (2) some of the most powerful insights into outcomes of wildlife management actions are nonintuitive, revealed by applying data to models; and (3) because different management actions influence population dynamics in different ways, we must understand population processes to identify the most effective actions to meet population objectives.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wildlife management and conservation: Contemporary principles and practices","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Johns Hopkins University Press","usgsCitation":"Mills, L.S., and Johnson, H.E., 2022, Wildlife population dynamics, chap. 7 <i>of</i> Wildlife management and conservation: Contemporary principles and practices, p. 107-135.","productDescription":"19 p.","startPage":"107","endPage":"135","ipdsId":"IP-125277","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":407965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Second Edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mills, L. Scott","contributorId":236757,"corporation":false,"usgs":false,"family":"Mills","given":"L.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":853630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Heather E. 0000-0001-5392-7676 hejohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-5392-7676","contributorId":205919,"corporation":false,"usgs":true,"family":"Johnson","given":"Heather","email":"hejohnson@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":853631,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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