Over the first century of the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI), volcano geodesy grew from roots as an accidental and incidental system of measurements to an important method for monitoring volcanic activity and forecasting eruptions. The first practitioners in volcano geodesy were experts in other disciplines, and it was not until the latter half of the twentieth century that specialists in the field emerged—scientists who developed new methods, measured geodetic change at volcanoes, and quantitatively interpreted the results in terms of magmatic processes. Much of the early work in the field was restricted to a few volcanoes and involved techniques that had been adapted from other applications; relatively few methods were developed specifically for use on volcanoes. These volcanoes, however, provided the natural laboratories needed to advance the field. By the start of the twenty-first century, geodetic studies, especially using space-based techniques, contributed to the recognition of deformation and gravity change at hundreds of volcanoes on Earth. In coming years, IAVCEI researchers will focus on comprehensive exploitation of the growing volumes of geodetic data to better model, forecast, and track activity at volcanoes worldwide. Meanwhile, the field needs to become more diverse, better representing people who live in the shadows of volcanoes around the globe.
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Water balance covers, also known as ET covers, reduce percolation by storing precipitation then allowing vegetation to cycle it back to the atmosphere. For long-term (over 200 years) waste isolation, ET covers may provide significant benefits over conventional, resistive covers that rely on engineered components, such as compacted clay barriers and geomembranes, to divert precipitation. UMTRCA covers were designed to impede and attenuate radioactive radon-222 gas flux from the underlying tailings, while minimizing percolation of any contaminants to groundwater. Such covers have implicit regulatory compliance post-construction. Alternative cover systems, such as ET covers, must explicitly meet some anticipated performance, and demonstrate beneficial use. While all engineered structures will change over time, an ET cover evolves with nature rather than resisting it, which may perpetuate a more reliable waste isolation system. For example, UMTRCA sites must provide safe and environmentally sound disposal, long-term stabilization, and control of uranium mill tailings and remain effective for up to 1,000 years, to the extent reasonably achievable, and, in any case, for at least 200 years. UMTRCA covers rely on the engineered properties to meet regulatory requirements during and immediately after construction. Subsequent compliance is implicit in the design. The design of an ET cover is far more dependent on mesoscale meteorology, native vegetation, and edaphic soil properties which are site-specific. Therefore, the design and anticipated performance of an ET cover must be demonstrated through a combination of modeling, natural analogues and pilot studies, and then verified with monitoring data. There is no single ET cover design that can likely meet performance standards across different climates, available soils, and vegetation. The technical information presented in this report reviews guidelines and performance criteria commonly used for ET covers at municipal waste facilities and the consideration factors of such covers to meet the regulatory requirements at long-term disposal sites.","language":"English","publisher":"U.S. Nuclear Regulatory Commission","usgsCitation":"Caldwell, T., Huntington, J., Davies, G.E., Tabatabai, S., and Fuhrmann, M., 2022, Basis for technical guidance to evaluate evapotranspiration covers, 127 p.","productDescription":"127 p.","ipdsId":"IP-120445","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":410286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":403886,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrc.gov/reading-rm/doc-collections/nuregs/contract/cr7297/index.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Caldwell, Todd 0000-0003-4068-0648","orcid":"https://orcid.org/0000-0003-4068-0648","contributorId":217924,"corporation":false,"usgs":true,"family":"Caldwell","given":"Todd","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846716,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huntington, Jena 0000-0002-9291-1404","orcid":"https://orcid.org/0000-0002-9291-1404","contributorId":204033,"corporation":false,"usgs":true,"family":"Huntington","given":"Jena","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846717,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davies, Gwendolyn Elizabeth 0000-0003-1538-8610","orcid":"https://orcid.org/0000-0003-1538-8610","contributorId":293203,"corporation":false,"usgs":true,"family":"Davies","given":"Gwendolyn","email":"","middleInitial":"Elizabeth","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":846718,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tabatabai, S.","contributorId":293205,"corporation":false,"usgs":false,"family":"Tabatabai","given":"S.","affiliations":[{"id":12536,"text":"U.S. Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":846719,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuhrmann, M.","contributorId":138800,"corporation":false,"usgs":false,"family":"Fuhrmann","given":"M.","affiliations":[{"id":12528,"text":"US Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":846720,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70248325,"text":"70248325 - 2022 - Anaxyrus boreas (boreal toad). 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","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Lafrance, B., Moore, N., Pilliod, D., and Muths, E., 2022, Anaxyrus boreas (boreal toad). Egg predation: Herpetological Review, v. 53, no. 3.","productDescription":"1 p.","startPage":"462","ipdsId":"IP-132878","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":420623,"type":{"id":24,"text":"Thumbnail"},"url":"http://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":420607,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/publications/herpetological-review/","linkFileType":{"id":5,"text":"html"}}],"volume":"53","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lafrance, Benjamin","contributorId":303574,"corporation":false,"usgs":false,"family":"Lafrance","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":882531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Nina","contributorId":329529,"corporation":false,"usgs":false,"family":"Moore","given":"Nina","email":"","affiliations":[],"preferred":false,"id":882532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":882533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L.","contributorId":329530,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":882534,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70236641,"text":"70236641 - 2022 - A process-model perspective on recent changes in the carbon cycle of North America","interactions":[],"lastModifiedDate":"2022-09-14T14:51:20.282288","indexId":"70236641","displayToPublicDate":"2022-09-01T09:43:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7359,"text":"Journal of Geophysical Research Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"A process-model perspective on recent changes in the carbon cycle of North America","docAbstract":"Continental North America has been found to be a carbon (C) sink over recent decades by multiple studies employing a variety of estimation approaches. However, several key questions and uncertainties remain with these assessments. Here we used results from an ensemble of 19 state-of-the-art dynamic global vegetation models from the TRENDYv9 project to improve these estimates and study the drivers of its interannual variability. Our results show that North America has been a C sink with a magnitude of 0.37 ± 0.38 (mean and one standard deviation) PgC year−1 for the period 2000–2019 (0.31 and 0.44 PgC year−1 in each decade); split into 0.18 ± 0.12 PgC year−1 in Canada (0.15 and 0.20), 0.16 ± 0.17 in the United States (0.14 and 0.17), 0.02 ± 0.05 PgC year−1 in Mexico (0.02 and 0.02) and 0.01 ± 0.02 in Central America and the Caribbean (0.01 and 0.01). About 57% of the new C assimilated by terrestrial ecosystems is allocated into vegetation, 30% into soils, and 13% into litter. Losses of C due to fire account for 41% of the interannual variability of the mean net biome productivity for all North America in the model ensemble. Finally, we show that drought years (e.g., 2002) have the potential to shift the region to a small net C source in the simulations (−0.02 ± 0.46 PgC year−1). Our results highlight the importance of identifying the major drivers of the interannual variability of the continental-scale land C cycle along with the spatial distribution of local sink-source dynamics.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022JG006904","usgsCitation":"Murray-Tortarolo, G., Poulter, B., Vargas, R., Hayes, D., Michalak, A., Williams , C., Windham-Myers, L., Wang, J., Wickland, K., Butman, D., Tian, H., Sitch, S., Friedlingstein, P., O’Sullivan, M., Briggs, P., Arora, V., Lombardozzi, D., Jain, A., Yuan, W., Seferian, R., Nabel, J., Wiltshire, A., Arneth, A., Lienerte, S., Zaehle, S., Bastrikov, V., Goll, D., Vuichard, N., Walker, A.P., Kato, E., Xu, Y., Zhang, Z., Chaterjee, A., and Kurz, W., 2022, A process-model perspective on recent changes in the carbon cycle of North America: Journal of Geophysical Research Biogeosciences, v. 127, no. 9, e2022JG006904, 19 p., https://doi.org/10.1029/2022JG006904.","productDescription":"e2022JG006904, 19 p.","ipdsId":"IP-144503","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":446574,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jg006904","text":"Publisher Index Page"},{"id":406674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -42.1875,\n 60.413852350464914\n ],\n [\n -20.7421875,\n 70.61261423801925\n ],\n [\n -12.3046875,\n 82.02137801950887\n ],\n [\n -28.828124999999996,\n 83.63810565804015\n ],\n [\n -83.671875,\n 83.31873282163234\n ],\n [\n -130.78125,\n 75.58493740869223\n ],\n [\n -131.1328125,\n 70.72897946208789\n ],\n [\n -164.1796875,\n 71.74643171904148\n ],\n [\n -172.96875,\n 62.91523303947614\n ],\n [\n -159.9609375,\n 52.696361078274485\n ],\n [\n -142.03125,\n 58.07787626787517\n ],\n [\n -128.671875,\n 47.989921667414194\n ],\n [\n -120.9375,\n 24.84656534821976\n ],\n [\n -83.3203125,\n 4.915832801313164\n ],\n [\n -76.640625,\n 11.178401873711785\n ],\n [\n -67.8515625,\n 17.97873309555617\n ],\n [\n -42.1875,\n 60.413852350464914\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"127","issue":"9","noUsgsAuthors":false,"publicationDate":"2022-09-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Murray-Tortarolo, Guillermo","contributorId":296446,"corporation":false,"usgs":false,"family":"Murray-Tortarolo","given":"Guillermo","email":"","affiliations":[{"id":64038,"text":"Instituto de Investigaciones en Ecosistemas y Sustentabilidad. 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A.","contributorId":50644,"corporation":false,"usgs":true,"family":"Kurz","given":"Werner A.","affiliations":[],"preferred":false,"id":851707,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}} ,{"id":70236665,"text":"70236665 - 2022 - Integrating climate-informed planning into State Wildlife Action Plans in the north central United States","interactions":[],"lastModifiedDate":"2022-09-15T14:42:45.086223","indexId":"70236665","displayToPublicDate":"2022-09-01T09:34:34","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Integrating climate-informed planning into State Wildlife Action Plans in the north central United States","docAbstract":"State fish and wildlife agencies are required to submit a State Wildlife Action Plan (SWAP) every 10 years to be eligible for grants through the State Wildlife Grant Program. With the next round of revisions due in 2025, the U.S. Geological Survey North Central Climate Adaptation Science Center is evaluating how to best support states with further integrating climate-informed planning in their SWAPs. Here, we summarize how states in the North Central region, which includes Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, and Wyoming, addressed adaptation planning in their 2015 SWAPs. We review climate adaptation considerations in required SWAP elements one through five, including species, habitats, threats, conservation actions, and conservation monitoring, respectively. We also include a list of potential strategies that the North Central Climate Adaptation Science Center could use to support states in the North Central region with further advancing the integration of climate informed planning in ongoing and future SWAP revisions. These strategies were primarily identified during meetings in 2021 with six of seven state fish and wildlife agencies in the North Central region where we discussed their priority needs relating to climate-informed planning. Our hope is that these strategies will enhance existing efforts in the region to advance the integration of climate change in conservation planning.
","language":"English","publisher":"North Central Climate Adaptation Science Center","doi":"10.21429/a2et-te45","usgsCitation":"Szcodronski, K.E., Bannister, I., Hossack, B., and Wade, A., 2022, Integrating climate-informed planning into State Wildlife Action Plans in the north central United States, 41 p., https://doi.org/10.21429/a2et-te45.","productDescription":"41 p.","ipdsId":"IP-144078","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":406758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Kansas, Montana, Nebraska, North Dakota, South Dakota, 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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Szcodronski, Kimberly E 0000-0002-2387-5649","orcid":"https://orcid.org/0000-0002-2387-5649","contributorId":224232,"corporation":false,"usgs":true,"family":"Szcodronski","given":"Kimberly","email":"","middleInitial":"E","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":851806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bannister, Indigo 0000-0003-3384-6021","orcid":"https://orcid.org/0000-0003-3384-6021","contributorId":296556,"corporation":false,"usgs":true,"family":"Bannister","given":"Indigo","email":"","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":851807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":851808,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wade, Alisa 0000-0003-3976-2224","orcid":"https://orcid.org/0000-0003-3976-2224","contributorId":266157,"corporation":false,"usgs":true,"family":"Wade","given":"Alisa","email":"","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":851809,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237260,"text":"70237260 - 2022 - Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam","interactions":[],"lastModifiedDate":"2025-03-14T15:11:55.173887","indexId":"70237260","displayToPublicDate":"2022-09-01T09:22:40","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":8569,"text":"Boatman's Quarterly Review","active":true,"publicationSubtype":{"id":30}},"title":"Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam","docAbstract":"The undammed Colorado River in Grand Canyon was characterized by spring snow-melt floods that sometimes exceeded 100,000 cubic feet per second (cfs). These were followed by occasional flash floods during summer monsoons, then by low flows from fall through early spring (Figure 1; Topping and others, 2003). This seasonally variable flow regime carried huge loads of sediment and was an important driver of natural processes that sustained the Colorado River ecosystem. For instance, high turbidity associated with this flow regime likely restricted algal growth to the river’s edge or shallow cobble habitats, similar to other desert rivers. Aquatic invertebrate assemblages were probably diverse and adapted to these variable conditions (Vinson, 2001; Haden and others, 2003). Native fishes were likely opportunistic feeders, consuming ants, seeds, and other terrestrial resources during times of flooding and switching to aquatic-derived resources like algae and aquatic invertebrates at other times (Minckley, 1991; Behn and Baxter, 2019). Regulation of the Colorado River by Glen Canyon Dam in 1963 eliminated the annual snowmelt floods, it sharply increased base flows by more than 50 percent, and dramatically increased within-day fluctuations in discharge for hydropower production (the ‘daily tides’ of the river, Figure 1 and 2; Topping and others, 2003). Glen Canyon Dam also changed other aspects of the river’s physical template, particularly temperature, sediment, and nutrient regimes. These changes to the physical template of the river led to fundamental changes in the natural processes that the sustain Colorado River ecosystem. For example, algae are common throughout the river during periods of clear water and represent the foundation of aquatic food webs (Stevens and others, 1997; Cross and others 2013). Many types of aquatic insects have disappeared or become rare, particularly sensitive groups such as mayflies, stoneflies, and caddisflies (Kennedy and others, 2016). Because aquatic insect assemblages in the Colorado River in Grand Canyon are neither diverse nor productive, food webs are simplified and inherently unstable, limiting populations of hungry fish (Cross and others 2013; Korman and others 2021).
","language":"English","publisher":"Grand Canyon River Guides Association","usgsCitation":"Kennedy, T., Metcalfe, A., Deemer, B., Ford, M., Szydlo, C.M., Yackulic, C., and Muehlbauer, J., 2022, Little bugs, big data, and Colorado River adaptive management: Preliminary findings from the ongoing bug flow experiment at Glen Canyon Dam: Boatman's Quarterly Review, v. 35, no. 3, p. 26-31.","productDescription":"6 p.","startPage":"26","endPage":"31","ipdsId":"IP-143763","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":483348,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcrg.org/bqr"},{"id":407960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.48968696594237,\n 36.93095788125762\n ],\n [\n -111.47878646850586,\n 36.93095788125762\n ],\n [\n -111.47878646850586,\n 36.94021961852396\n ],\n [\n -111.48968696594237,\n 36.94021961852396\n ],\n [\n -111.48968696594237,\n 36.93095788125762\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kennedy, Theodore 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":221741,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Metcalfe, Anya 0000-0002-6286-4889","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":221738,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853870,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, Morgan 0000-0001-5104-9566","orcid":"https://orcid.org/0000-0001-5104-9566","contributorId":221740,"corporation":false,"usgs":true,"family":"Ford","given":"Morgan","email":"","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szydlo, Cheyenne Maxime 0000-0003-4818-2395","orcid":"https://orcid.org/0000-0003-4818-2395","contributorId":297340,"corporation":false,"usgs":true,"family":"Szydlo","given":"Cheyenne","email":"","middleInitial":"Maxime","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muehlbauer, Jeffrey 0000-0003-1808-580X","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":221739,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":853874,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70236341,"text":"70236341 - 2022 - Comparing root cohesion estimates from three models at a shallow landslide in the Oregon Coast Range","interactions":[],"lastModifiedDate":"2022-09-02T14:17:32.925032","indexId":"70236341","displayToPublicDate":"2022-09-01T09:13:29","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12565,"text":"GeoHazards","active":true,"publicationSubtype":{"id":10}},"title":"Comparing root cohesion estimates from three models at a shallow landslide in the Oregon Coast Range","docAbstract":"Although accurate root cohesion model estimates are essential to quantify the effect of vegetation roots on shallow slope stability, few means exist to independently validate such model outputs. One validation approach for cohesion estimates is back-calculation of apparent root cohesion at a landslide site with well-documented failure conditions. The catchment named CB1, near Coos Bay, Oregon, USA, which experienced a shallow landslide in 1996, is a prime locality for cohesion model validation, as an abundance of data and observations from the site generated broad insights related to hillslope hydrology and slope stability. However, previously published root cohesion values at CB1 used the Wu and Waldron model (WWM), which assumes simultaneous root failure and therefore likely overestimates root cohesion. Reassessing published cohesion estimates from this site is warranted, as more recently developed models include the fiber bundle model (FBM), which simulates progressive failure with load redistribution, and the root bundle model-Weibull (RBMw), which accounts for differential strain loading. We applied the WWM, FBM, and RBMw at CB1 using post-failure root data from five vegetation species. At CB1, the FBM and RBMw predict values that are less than 30% of the WWM-estimated values. All three models show that root cohesion has substantial spatial heterogeneity. Most parts of the landslide scarp have little root cohesion, with areas of high cohesion concentrated near plant roots. These findings underscore the importance of using physically realistic models and considering lateral and vertical spatial heterogeneity of root cohesion in shallow landslide initiation and provide a necessary step towards independently assessing root cohesion model validity.
","language":"English","publisher":"MDPI","doi":"10.3390/geohazards3030022","usgsCitation":"Cronkite-Ratcliff, C., Schmidt, K.M., and Wirion, C., 2022, Comparing root cohesion estimates from three models at a shallow landslide in the Oregon Coast Range: GeoHazards, v. 3, no. 3, p. 428-451, https://doi.org/10.3390/geohazards3030022.","productDescription":"24 p.","startPage":"428","endPage":"451","ipdsId":"IP-133079","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":446579,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geohazards3030022","text":"Publisher Index Page"},{"id":406136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","city":"Coos Bay","otherGeospatial":"Coast Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.56298828125001,\n 43.14909399920127\n ],\n [\n -123.50830078125,\n 43.14909399920127\n ],\n [\n -123.50830078125,\n 43.75522505306928\n ],\n [\n -124.56298828125001,\n 43.75522505306928\n ],\n [\n -124.56298828125001,\n 43.14909399920127\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Cronkite-Ratcliff, Collin 0000-0001-5485-3832 ccronkite-ratcliff@usgs.gov","orcid":"https://orcid.org/0000-0001-5485-3832","contributorId":203951,"corporation":false,"usgs":true,"family":"Cronkite-Ratcliff","given":"Collin","email":"ccronkite-ratcliff@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wirion, Charlotte 0000-0003-0721-3036","orcid":"https://orcid.org/0000-0003-0721-3036","contributorId":296101,"corporation":false,"usgs":false,"family":"Wirion","given":"Charlotte","email":"","affiliations":[{"id":63984,"text":"ETH Zurich, Switzerland (now at WEO, Luxembourg)","active":true,"usgs":false}],"preferred":false,"id":850666,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256644,"text":"70256644 - 2022 - Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico","interactions":[],"lastModifiedDate":"2024-08-29T14:09:34.922004","indexId":"70256644","displayToPublicDate":"2022-09-01T09:02:56","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":"Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico","docAbstract":"The northern Gulf of Mexico (nGoM) is a globally important region for oil extraction and supports a diverse assemblage of marine birds. Due to their frequent contact with surface waters, diverse foraging strategies, and the ease with which oil adheres to feathers, seabirds are particularly susceptible to hydrocarbon contamination. Given the chronic and acute exposure of seabirds to oiling and a lack of studies that focus on the exposure of seabirds to oiling in sub-tropical and tropical regions, a greater understanding of the vulnerability of seabirds to oil in the nGoM appears warranted. We present an oil vulnerability index for seabirds in the nGoM tailored to the current state of knowledge using new, spatiotemporally expensive vessel-based seabird observations. We use information on the exposure and sensitivity of seabirds to oil to rank seabird vulnerability. Exposure variables characterized the potential to encounter oil and gas (O&G). Sensitivity variables characterized the potential impact of seabirds interacting with O&G and are related to life history and productivity. We also incorporated uncertainty in each variable, identifying data gaps. We found that the percent of seabirds’ habitat defined as highly suitable within 10 km of an O&G platform ranged from 0%-65% among 24 species. Though O&G platforms only overlap with 15% of highly suitable seabird habitat, overlap occurs in areas of moderate to high vulnerability of seabirds, particularly along the shelf-slope. Productivity-associated sensitivity variables were primarily responsible for creating the gradient in vulnerability scores and had greater uncertainty than exposure variables. Highly vulnerable species (e.g., Northern gannet (Morus bassanus)) tended to have high exposure to the water surface via foraging behaviors (e.g., plunge-diving), older age at first breeding, and an extended incubating and fledging period compared to less vulnerable species (e.g., Pomarine jaeger (Stercorarius pomarinus)). Uncertainty related to productivity could be reduced through at-colony monitoring. Strategic seabird satellite tagging could help target monitoring efforts to colonies known to use the nGoM, and continued vessel-based observations could improve habitat characterization. As offshore energy development in the nGoM continues, managers and researchers could use these vulnerability ranks to identify information gaps to prioritize research and focal species.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2022.880750","usgsCitation":"Michael, P.E., Hixson, K.M., Haney, J., Satge, Y., Gleason, J., and Jodice, P.G., 2022, Seabird vulnerability to oil: Exposure potential, sensitivity, and uncertainty in the northern Gulf of Mexico: Frontiers in Marine Science, v. 9, 880750, 20 p., https://doi.org/10.3389/fmars.2022.880750.","productDescription":"880750, 20 p.","ipdsId":"IP-136731","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2022.880750","text":"Publisher Index Page"},{"id":433301,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"northern Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.65064732144825,\n 24.16865530700734\n ],\n [\n -80.74028091647656,\n 24.49674089923498\n ],\n [\n -80.6110475132637,\n 25.375716312633244\n ],\n [\n -82.48124501487644,\n 27.87595132514076\n ],\n [\n -82.50401354053463,\n 28.975470074471573\n ],\n [\n -84.01377542803263,\n 30.278116834370664\n ],\n [\n -85.21105352771927,\n 29.813919882762193\n ],\n [\n -86.41030861654544,\n 30.53771106924384\n ],\n [\n -88.05949534476994,\n 30.614388650912403\n ],\n [\n -89.250977846713,\n 30.128789114669402\n ],\n [\n -88.84045762268858,\n 28.94436305824601\n ],\n [\n -90.45644421555457,\n 29.213975074748845\n ],\n [\n -91.6391457751865,\n 29.567867845383958\n ],\n [\n -92.61153919455367,\n 29.52398569897167\n ],\n [\n -94.15861129214014,\n 29.615060750195013\n ],\n [\n -95.85111266718562,\n 28.497269906948034\n ],\n [\n -97.05244440317941,\n 27.930797727982196\n ],\n [\n -97.4997935110664,\n 26.841188159759383\n ],\n [\n -97.23172322974906,\n 26.093166420472286\n ],\n [\n -86.07549373074224,\n 26.17610757333493\n ],\n [\n -85.31650372657558,\n 24.614391708025977\n ],\n [\n -83.65064732144825,\n 24.16865530700734\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","noUsgsAuthors":false,"publicationDate":"2022-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Michael, Pamela E.","contributorId":341457,"corporation":false,"usgs":false,"family":"Michael","given":"Pamela","email":"","middleInitial":"E.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hixson, K. M.","contributorId":341458,"corporation":false,"usgs":false,"family":"Hixson","given":"K.","email":"","middleInitial":"M.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haney, J.C.","contributorId":288019,"corporation":false,"usgs":false,"family":"Haney","given":"J.C.","email":"","affiliations":[{"id":61685,"text":"Terra Mar Applied Sciences","active":true,"usgs":false}],"preferred":false,"id":908455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Satge, Y.G.","contributorId":279816,"corporation":false,"usgs":false,"family":"Satge","given":"Y.G.","email":"","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":908456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gleason, J.S.","contributorId":288017,"corporation":false,"usgs":false,"family":"Gleason","given":"J.S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jodice, Patrick G.R. 0000-0001-8716-120X","orcid":"https://orcid.org/0000-0001-8716-120X","contributorId":219852,"corporation":false,"usgs":true,"family":"Jodice","given":"Patrick","middleInitial":"G.R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908458,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70248063,"text":"70248063 - 2022 - Microbiome assembly in thawing permafrost and its feedbacks to climate","interactions":[],"lastModifiedDate":"2023-09-05T14:04:35.097815","indexId":"70248063","displayToPublicDate":"2022-09-01T08:47:10","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Microbiome assembly in thawing permafrost and its feedbacks to climate","docAbstract":"The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost–climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post-thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose that Assembly Theory provides a framework to better understand thaw-mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well-suited to thrive in changing environmental conditions. We predict that on a short timescale and following high-disturbance thaw (e.g., thermokarst), stochasticity dominates post-thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower-intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post-thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.16231","usgsCitation":"Ernakovich, J.G., Barbato, R.A., Rich, V., Schädel, C., Hewitt, R.E., Doherty, S., Whalen, E., Abbott, B., Barta, J., Biasi, C., Chabot, C., Hultman, J., Knoblauch, C., Lau Vetter, M.C., Leewis, M., Liebner, S., Mackelprang, R., Onstott, T., Richter, A., Schutte, U.M., Siljanen, H., Tas, N., Timling, I., Vishnivetskaya, T., Waldrop, M., and Winkel, M., 2022, Microbiome assembly in thawing permafrost and its feedbacks to climate: Global Change Biology, v. 28, no. 17, p. 5007-5026, https://doi.org/10.1111/gcb.16231.","productDescription":"20 p.","startPage":"5007","endPage":"5026","ipdsId":"IP-122106","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":446583,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/gcb.16231","text":"External Repository"},{"id":420474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"17","noUsgsAuthors":false,"publicationDate":"2022-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Ernakovich, Jessica G. 0000-0002-4493-2489","orcid":"https://orcid.org/0000-0002-4493-2489","contributorId":257626,"corporation":false,"usgs":false,"family":"Ernakovich","given":"Jessica","email":"","middleInitial":"G.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":881701,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbato, Robyn A.","contributorId":328915,"corporation":false,"usgs":false,"family":"Barbato","given":"Robyn","email":"","middleInitial":"A.","affiliations":[{"id":78528,"text":"US Army Cold Regions Research and Engineering Laboratory","active":true,"usgs":false}],"preferred":false,"id":881702,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rich, Virginia 0000-0003-0558-102X","orcid":"https://orcid.org/0000-0003-0558-102X","contributorId":328916,"corporation":false,"usgs":false,"family":"Rich","given":"Virginia","email":"","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":881703,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schädel, Christina","contributorId":298813,"corporation":false,"usgs":false,"family":"Schädel","given":"Christina","affiliations":[],"preferred":false,"id":881704,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hewitt, Rebecca E.","contributorId":267276,"corporation":false,"usgs":false,"family":"Hewitt","given":"Rebecca","email":"","middleInitial":"E.","affiliations":[{"id":12698,"text":"Northern Arizona 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Chemofacies from hierarchical cluster analysis","interactions":[],"lastModifiedDate":"2022-09-09T13:45:13.121553","indexId":"70236517","displayToPublicDate":"2022-09-01T08:41:21","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: II. Chemofacies from hierarchical cluster analysis","docAbstract":"Hierarchical cluster analysis (HCA) was applied to a geochemical dataset representing the Eocene Green River Formation in the Piceance Basin of Colorado to identify chemofacies in core and outcrop samples from the basin margin and the basin center. The input dataset consisted of inductively coupled plasma optical emission spectroscopy and mass spectrometry and total organic carbon (TOC) content analyses of 186 basin margin outcrop samples and 190 basin center core samples discussed in Part 1 of this study (this volume). TOC values and twenty-five major and trace elements were used as variables to define statistical clusters of samples for the overall dataset, for the two basin center cores, and for each separate core or outcrop dataset by HCA applying Euclidean distance and Ward’s method algorithms. For each dataset, five cluster-defined chemofacies were identified. The chemofacies for each dataset show chemical affinities with five informally defined rock types– mudstone, marlstone, carbonate-rich mudstone, siliciclastic-rich mudstone/siltstone/sandstone, and Na-rich (saline) mudstone, with each showing variations in TOC content and abundance of redox sensitive minor and trace elements. A close relationship between enrichment of redox sensitive elements, particularly As and Mo, and TOC is identified in the basin center. Whereas enrichment factors (relative to average shale) are relatively low for many Period IV (PIV) transition metals, as discussed in Part 1 of this study, their consistent coherence in enrichment or depletion in HCA-defined chemofacies demonstrates the expected relationship between redox state and organic richness. Enrichment in PIV transition metals also shows a correlation to enrichment in elements with affinity for siliciclastic sediment. Enrichment/depletion among several groups of redox indicators is not everywhere consistent, with some chemofacies showing, for example, enrichment of PIV transition metals and depletion of sulfur and arsenic. Early timing of saline conditions in the basin margin is clearly displayed in the chemofacies log display, consistent with observations based on geochemical interpretations of concentrations and elemental ratios discussed in Part 1. Overall, the chemofacies are consistent with major mineralogical units and lake history stages defined in previous work, but provide more detail on the fluctuations in lake chemistry that occurred during deposition of Green River oil shale in the Piceance Basin.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Utah Geological Association","doi":"10.31711/ugap.v50i.115","usgsCitation":"Wu, T., Boak, J., and Birdwell, J.E., 2022, Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: II. Chemofacies from hierarchical cluster analysis, chap. of The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record, v. 50, p. 298-323, https://doi.org/10.31711/ugap.v50i.115.","productDescription":"26 p.","startPage":"298","endPage":"323","ipdsId":"IP-127905","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":446585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31711/ugap.v50i.115","text":"Publisher Index Page"},{"id":406450,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Green River Formation, Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.1439208984375,\n 39.48284540453334\n ],\n [\n -107.8692626953125,\n 39.64799732373418\n ],\n [\n -107.91320800781249,\n 40.027614437486655\n ],\n [\n -108.2647705078125,\n 40.17467622056341\n ],\n [\n -108.6492919921875,\n 40.069664523297774\n ],\n [\n -108.7811279296875,\n 39.88023492849342\n ],\n [\n -108.5394287109375,\n 39.6437675734185\n ],\n [\n -108.1439208984375,\n 39.48284540453334\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationDate":"2022-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Tengfei 0000-0003-2804-5537","orcid":"https://orcid.org/0000-0003-2804-5537","contributorId":296330,"corporation":false,"usgs":false,"family":"Wu","given":"Tengfei","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":851291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boak, Jeremy 0000-0003-0251-434X","orcid":"https://orcid.org/0000-0003-0251-434X","contributorId":296328,"corporation":false,"usgs":false,"family":"Boak","given":"Jeremy","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":851292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":851293,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236510,"text":"70236510 - 2022 - Geologic characterization and depositional history of the Uteland Butte member, Green River Formation, southwestern Uinta Basin, Utah","interactions":[],"lastModifiedDate":"2022-09-09T13:39:43.82889","indexId":"70236510","displayToPublicDate":"2022-09-01T08:33:14","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geologic characterization and depositional history of the Uteland Butte member, Green River Formation, southwestern Uinta Basin, Utah","docAbstract":"The 15- to 65-m-thick informal Uteland Butte member of the Eocene Green River Formation represents the first widespread transgression of Lake Uinta in the Uinta Basin, Utah. This study assesses the spatial and temporal variation of Uteland Butte member deposits along a 40-km transect in the southwestern margin of the Uinta Basin using detailed measured sections, organic and inorganic geochemical data, and outcrop gamma ray logs. Fourteen lithofacies are identified, which comprise seven facies associations linked to with lacustrine, palustrine, and deltaic depositional settings. Facies associations are traceable laterally across the study area, where five 4- to 12-m-thick depositional cycles are identified. Each shallowing upwards cycle is defined by a >1.5-m-thick basal package of organic-rich, argillaceous laminated mudstone, and is capped by thick packages of bedded carbonate. In the far western study area (Kyune Creek Canyon), thick deposits of organic-rich mudstone are present and represent the most distal outcrop section; time-equivalent strata in the eastern study area (Minnie Maud Creek Canyon) are relatively organic lean with higher silt and clay content, interpreted to represent proximal lake margin deposits influenced by a nearby delta. The outcrop belt is correlated to more distal cores and well logs across the western Uinta Basin. Similar lithological and petrophysical patterns across the western Uinta Basin are used to subdivide stratigraphy into nine laterally contiguous sub-units based on nomenclature from the oil-producing area of the central basin (from base to top: lower Uteland Butte, D Bench, D Shale, C Bench, C Shale, B Bench, B Shale, A Bench, and A Shale). Siliciclastic clay-rich and carbonaterich intervals are correlated across the region and indicate distinct siliciclastic- and carbonate-dominated lake phases during Uteland Butte member deposition. Climate is interpreted to be the dominant driver of these claycarbonate cycles, in which relatively humid periods resulted in increased fluvially derived siliciclastic sediment into the basin (clay-rich periods), and arid periods resulted in evaporative conditions with decreased fluvial sediment input that favor carbonate accumulation. Climatically driven depositional cycles within the Uteland Butte member reflect, to a smaller degree, the larger scale climatically driven depositional cycles observed at the member- and formation levels of Paleocene and Eocene Uinta Basin stratigraphy. Importantly, the Uteland Butte member clay-carbonate cycles showcase how relatively small-scale climate shifts can impact basin-scale lacustrine deposition.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Utah Geological Association","doi":"10.31711/ugap.v50i.106","usgsCitation":"Gall, R.D., Birdwell, J.E., Brinkerhoff, R., and Vanden Berg, M.D., 2022, Geologic characterization and depositional history of the Uteland Butte member, Green River Formation, southwestern Uinta Basin, Utah, chap. of The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record, v. 50, p. 37-62, https://doi.org/10.31711/ugap.v50i.106.","productDescription":"26 p.","startPage":"37","endPage":"62","ipdsId":"IP-127906","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":446587,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31711/ugap.v50i.106","text":"Publisher Index Page"},{"id":435703,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9X66RQ4","text":"USGS data release","linkHelpText":"Geochemical and spectroscopic data on outcrop samples from the informal Uteland Butte member of the Eocene Green River Formation in Uinta Basin, Utah"},{"id":406449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Uinta Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.786376953125,\n 39.757879992021756\n ],\n [\n -109.281005859375,\n 40.283716270542584\n ],\n [\n -109.49523925781249,\n 40.56389453066509\n ],\n [\n -110.2972412109375,\n 40.543026009955014\n ],\n [\n -110.8740234375,\n 40.35073056591789\n ],\n [\n -110.687255859375,\n 40.057052221322\n ],\n [\n -110.28076171875,\n 39.85915479295669\n ],\n [\n -109.8797607421875,\n 39.73253798438173\n ],\n [\n -109.786376953125,\n 39.757879992021756\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationDate":"2022-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gall, Ryan D.","contributorId":296324,"corporation":false,"usgs":false,"family":"Gall","given":"Ryan","email":"","middleInitial":"D.","affiliations":[{"id":17626,"text":"Utah Geological Survey","active":true,"usgs":false}],"preferred":false,"id":851281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":851282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinkerhoff, Riley","contributorId":296326,"corporation":false,"usgs":false,"family":"Brinkerhoff","given":"Riley","email":"","affiliations":[{"id":64017,"text":"Wasatch Energy Management","active":true,"usgs":false}],"preferred":false,"id":851283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanden Berg, Michael D.","contributorId":177609,"corporation":false,"usgs":false,"family":"Vanden Berg","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":851284,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70249920,"text":"70249920 - 2022 - Puerto Rico’s state of the climate 2014-2021","interactions":[],"lastModifiedDate":"2023-11-07T14:32:49.34824","indexId":"70249920","displayToPublicDate":"2022-09-01T08:28:32","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"Puerto Rico’s State of the Climate 2014-2021","title":"Puerto Rico’s state of the climate 2014-2021","docAbstract":"The climate of Puerto Rico is influenced by the changing global climate. The following chapters present the current knowledge of the geophysical and chemical drivers and signals of global climate change as they affect the climate of Puerto Rico and influence the climate-dependent services, risks, and vulnerabilities that govern human well-being. These include sustainable economic development, delivery of ecosystem services, the conservation of natural and cultural resources, resiliency in built and natural systems, and food security. The chapters draw on global expertise of land, atmosphere, and ocean geophysical interactions associated with increasing greenhouse gases that drive global warming and on local scientific expertise, data, observations, and modeled projections. They present the global warming scenario (section 1), the contribution of Puerto Rico to global climate change as GHG emissions and aerosols (section 2), the context of natural climate variability (section 3), observed and projected trends in temperature (section 4), rainfall (section 5), sea level rise (section 6), ocean acidification and sea surface warming (section 7), and the expected implications of warming climate on tropical cyclones affecting Puerto Rico (section 8).","language":"English","publisher":"Puerto Rico Climate Change Council","usgsCitation":"Gould, W.A., Dias, E., Terando, A., Jury, M., Bowden, J., Chardon, P., Melendez Oyola, M., and Morell, J., 2022, Puerto Rico’s state of the climate 2014-2021, 260 p.","productDescription":"260 p.","ipdsId":"IP-133876","costCenters":[{"id":40926,"text":"Southeast Climate Adaptation Science 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Patricia","contributorId":331444,"corporation":false,"usgs":false,"family":"Chardon","given":"Patricia","email":"","affiliations":[{"id":79213,"text":"University of Puerto Rico - Mayagüez","active":true,"usgs":false}],"preferred":false,"id":887715,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Melendez Oyola, Melissa","contributorId":212213,"corporation":false,"usgs":false,"family":"Melendez Oyola","given":"Melissa","email":"","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":887717,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morell, Julio","contributorId":331446,"corporation":false,"usgs":false,"family":"Morell","given":"Julio","email":"","affiliations":[{"id":79213,"text":"University of Puerto Rico - Mayagüez","active":true,"usgs":false}],"preferred":false,"id":887718,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236514,"text":"70236514 - 2022 - Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: I. Major, minor, and trace elements","interactions":[],"lastModifiedDate":"2022-09-09T13:32:07.905743","indexId":"70236514","displayToPublicDate":"2022-09-01T08:22:11","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: I. Major, minor, and trace elements","docAbstract":"The Eocene Green River Formation contains the largest oil shale deposits in the world and is a welldocumented example of a lacustrine depositional system. In addition, mineral resources associated with oil shale in the Piceance Basin nahcolite [NaHCO3] and dawsonite [NaAl(CO3)(OH)2)] are of current and potential economic value, respectively. Detailed geochemical analysis across the basin can aid in the understanding of the depositional environment, sedimentary processes, and water-chemistry evolution in this system. Quantitative geochemical data for Green River oil shale from the Piceance Basin of Colorado were collected by inductively coupled plasma optical emission spectroscopy and mass spectrometry as part of this study. The basin margin is represented by samples from exposures at Douglas Pass (Garfield County) and the basin center area is characterized by core samples from two drilled wells: the Shell 23X-2 and John Savage 24-1 (Rio Blanco County). Major elements and groups of elements are used as proxies for clastic influx (Si, Al, K, Ti), carbonate deposition (Ca, Mg), salinity (Na), paleo-productivity (P), and redox state (Fe, S), respectively. Minor and trace elements reinforce observations based on major elements, including Rb, Zr, Nb for clastic influx and Mn, Sr for carbonate. Trace elements are used to characterize redox conditions (As, Mo, U, V, Co, Ni, Cu, Zn) and salinity (Rb/K, B/Ga). Chemical distinctions between the basin margin and the basin center, in terms of these components and total organic carbon concentrations, support the model of a permanently stratified lake through most of the depositional interval. A primary purpose of the study was to conduct more extensive sampling to confirm conclusions of a previous reconnaissance study. Geochemical data from this study indicates elevated Na around the basin margin occurring earlier than in the deeper basin. Early in the history of Lake Uinta, the salinity may have been elevated first in the shallower marginal waters, due to increased evaporation, which then led to elevated salinity in the basin center through transport of saline density currents. Other indicators of salinity (Rb/K, B/Ga) do not track Na content in intervals where clay minerals are absent due to diagenetic alteration under hypersaline conditions but may be used to indicate the salinities at which authigenic Na-bearing minerals begin to form. Most Na-rich samples show high proportions of clastic constituents (Si, Al, K, Ti) compared to conventional carbonate constituents (Ca, Mg). Redox-sensitive period IV transition metal elements (V, Co, Ni, Cu, Zn) show only local occurrence of significant enrichment relative to average shale abundances. Analysis of Fe/Al ratios for this dataset suggests that the depletion of these elements may be related to source rocks depleted in mafic constituents, with apparent redox-related enrichments subdued by this effect. The basin margin samples reflect generally oxic bottom waters, with some intervals deposited under more reducing, possibly dysoxic to anoxic conditions. The basin center results indicate more reducing conditions, with Mo and U enrichment factors suggesting operation of a particulate shuttle mechanism that scavenged Mo on Fe/Mn-oxyhydroxides that redissolved at depth, with Mo precipitating along with sulfides and/or organic matter at or near the sediment/water interface.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Utah Geological Association","doi":"10.31711/ugap.v50i.114","usgsCitation":"Boak, J., Wu, T., and Birdwell, J.E., 2022, Geochemical studies of the Green River Formation in the Piceance Basin, Colorado: I. Major, minor, and trace elements, chap. of The lacustrine Green River Formation: Hydrocarbon potential and Eocene climate record, v. 50, p. 266-297, https://doi.org/10.31711/ugap.v50i.114.","productDescription":"32 p.","startPage":"266","endPage":"297","ipdsId":"IP-127516","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":446590,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31711/ugap.v50i.114","text":"Publisher Index Page"},{"id":435705,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q5VOQB","text":"USGS data release","linkHelpText":"Geochemical data for the Green River Formation in the Piceance Basin, Colorado: Major and trace element concentrations and total organic carbon content"},{"id":406448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Green River Formation, Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.1439208984375,\n 39.48284540453334\n ],\n [\n -107.8692626953125,\n 39.64799732373418\n ],\n [\n -107.91320800781249,\n 40.027614437486655\n ],\n [\n -108.2647705078125,\n 40.17467622056341\n ],\n [\n -108.6492919921875,\n 40.069664523297774\n ],\n [\n -108.7811279296875,\n 39.88023492849342\n ],\n [\n -108.5394287109375,\n 39.6437675734185\n ],\n [\n -108.1439208984375,\n 39.48284540453334\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","noUsgsAuthors":false,"publicationDate":"2022-09-01","publicationStatus":"PW","contributors":{"editors":[{"text":"Hurst, C. J.","contributorId":206942,"corporation":false,"usgs":false,"family":"Hurst","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":851360,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Boak, Jeremy 0000-0003-0251-434X","orcid":"https://orcid.org/0000-0003-0251-434X","contributorId":296328,"corporation":false,"usgs":false,"family":"Boak","given":"Jeremy","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":851288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Tengfei 0000-0003-2804-5537","orcid":"https://orcid.org/0000-0003-2804-5537","contributorId":296330,"corporation":false,"usgs":false,"family":"Wu","given":"Tengfei","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":851289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":851290,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251892,"text":"70251892 - 2022 - Changes in aquatic vegetation cover following lock closure on the Illinois Waterway from 2019 – 2021","interactions":[],"lastModifiedDate":"2024-03-05T15:06:25.784988","indexId":"70251892","displayToPublicDate":"2022-09-01T08:18:54","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":17168,"text":"Completion Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"LTRMP-2019AER7","title":"Changes in aquatic vegetation cover following lock closure on the Illinois Waterway from 2019 – 2021","docAbstract":"Over the summer of 2020, the Illinois Waterway was closed to complete maintenance on lock chambers along the Illinois River. This closure restricted inter-pool vessel traffic along the river and potentially changed habitat characteristics for aquatic vegetation establishment and growth. To assess if patterns of vegetation establishment and growth changed during the closure, peak biomass imagery from 2019 (pre closure) and 2021 (post closure) were compared for a vegetation response. This assessment found locations where aquatic vegetation increased and locations where aquatic vegetation decreased. However, due to unforeseen limitations in vegetation and water sampling, a causal reason for observed changed in vegetation could not be established.","language":"English","publisher":"U.S. Army Corps of Engineers’ Upper Mississippi River Restoration Program","usgsCitation":"Strassman, A.C., 2022, Changes in aquatic vegetation cover following lock closure on the Illinois Waterway from 2019 – 2021: Completion Report LTRMP-2019AER7, 44 p.","productDescription":"44 p.","ipdsId":"IP-145368","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":426307,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/data_library/ltrmp_other/IWW_Closure_Veg_Change_Co-op_Report_Final_20221201.pdf"},{"id":426318,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.28788998955925,\n 42.108326944582615\n ],\n [\n -90.7915689421851,\n 42.108326944582615\n ],\n [\n -90.7915689421851,\n 38.76757015391274\n ],\n [\n -87.28788998955925,\n 38.76757015391274\n ],\n [\n -87.28788998955925,\n 42.108326944582615\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":895948,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70238985,"text":"70238985 - 2022 - Potential cheatgrass abundance within lightly invaded areas of the Great Basin","interactions":[],"lastModifiedDate":"2022-12-20T14:13:06.35989","indexId":"70238985","displayToPublicDate":"2022-09-01T08:06:38","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":"Potential cheatgrass abundance within lightly invaded areas of the Great Basin","docAbstract":"Context
Anticipating where an invasive species could become abundant can help guide prevention and control efforts aimed at reducing invasion impacts. Information on potential abundance can be combined with information on the current status of an invasion to guide management towards currently uninvaded locations where the threat of invasion is high.
Objectives
We aimed to support management by developing predictive maps of potential cover for cheatgrass (Bromus tectorum), a problematic invader that can transform plant communities. We integrated our predictions of potential abundance with mapped estimates of current cover to quantify invasion potential within lightly invaded areas.
Methods
We used quantile regression to model cheatgrass abundance as a function of climate, weather, and disturbance, treating outputs as low to high invasion scenarios. We developed a species-specific set of covariates and validated model performance using spatially and temporally independent data.
Results
Potential cheatgrass abundance was higher in areas that had burned, at low elevations, and when fall germination conditions were more favorable. Our results highlight the extensive areas across the Great Basin where cheatgrass abundance could increase to levels that can alter fire behavior and cause other ecological impacts.
Conclusions
We predict potential cheatgrass abundance to quantify relative invasion risk. Our model results provide high and low scenarios of cheatgrass abundance to guide resource allocation and planning efforts across shrubland ecosystems of the Great Basin that remain relatively uninvaded. Combining information on an invasive species’ current and potential abundance can yield spatial predictions to guide resource allocation and management action.
Anthropogenic alterations have resulted in widespread degradation of stream conditions. To aid in stream restoration and management, baseline estimates of conditions and improved explanation of factors driving their degradation are needed. We used random forests to model biological conditions using a benthic macroinvertebrate index of biotic integrity for small, non-tidal streams (upstream area ≤200 km2) in the Chesapeake Bay watershed (CBW) of the mid-Atlantic coast of North America. We utilized several global and local model interpretation tools to improve average and site-specific model inferences, respectively. The model was used to predict condition for 95,867 individual catchments for eight periods (2001, 2004, 2006, 2008, 2011, 2013, 2016, 2019). Predicted conditions were classified as Poor, FairGood, or Uncertain to align with management needs and individual reach lengths and catchment areas were summed by condition class for the CBW for each period. Global permutation and local Shapley importance values indicated percent of forest, development, and agriculture in upstream catchments had strong impacts on predictions. Development and agriculture negatively influenced stream condition for model average (partial dependence [PD] and accumulated local effect [ALE] plots) and local (individual condition expectation and Shapley value plots) levels. Friedman's H-statistic indicated large overall interactions for these three land covers, and bivariate global plots (PD and ALE) supported interactions among agriculture and development. Total stream length and catchment area predicted in FairGood conditions decreased then increased over the 19-years (length/area: 66.6/65.4% in 2001, 66.3/65.2% in 2011, and 66.6/65.4% in 2019). Examination of individual catchment predictions between 2001 and 2019 showed those predicted to have the largest decreases in condition had large increases in development; whereas catchments predicted to exhibit the largest increases in condition showed moderate increases in forest cover. Use of global and local interpretative methods together with watershed-wide and individual catchment predictions support conservation practitioners that need to identify widespread and localized patterns, especially acknowledging that management actions typically take place at individual-reach scales.
ABSTRACT: Nuclear inclusion X (NIX), the etiological agent of bacterial gill disease in Pacific razor clams Siliqua patula, was associated with host mortality events in coastal Washington State, USA, during the mid-1980s. Ongoing observations of truncated razor clam size distributions in Kalaloch Beach, Washington, raised concerns that NIX continues to impact populations. We conducted a series of spatial and longitudinal NIX surveillances, examined archived razor clam gill tissue, and used population estimates from stock assessments to test whether (1) the prevalence and intensity of NIX infections is higher at Kalaloch Beach relative to nearby beaches, (2) infected gill tissue has features consistent with historical descriptions of NIX-associated histopathology, and (3) annual clam survival is inversely related to NIX infection prevalence and intensity. NIX prevalence exceeded 85% at all sampled locations, and infection intensity was the highest at Kalaloch Beach by 0.9-2.6 orders of magnitude. Kalaloch Beach clams revealed histopathology consistent with previous NIX epidemics, including enlarged and/or rupturing branchial epithelial cells, branchial necrosis, and high hemocyte densities. Estimated annual survival was 22% at Kalaloch Beach, and ranged between 57 and 99% at other study sites. NIX infection intensity (via quantitative PCR) was not significantly correlated with annual survival; however, annual survival was lowest at Kalaloch Beach, where infection intensities were highest, suggesting that clams can tolerate infections up to a lethal threshold. Collectively these data support the hypothesis that high NIX intensities are associated with host mortality. NIX-associated mortality appears to be more pronounced at Kalaloch Beach relative to other Washington beaches.
","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03685","usgsCitation":"Groner, M., Hershberger, P., Fradkin, S.C., Conway, C.M., Hawthorn, A.C., and Purcell, M.K., 2022, Evaluating the effect of nuclear inclusion X (NIX) infections on Pacific razor clam populations: Diseases of Aquatic Organisms, v. 151, p. 1-9, https://doi.org/10.3354/dao03685.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-138482","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":435707,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IV2C3L","text":"USGS data release","linkHelpText":"Histological and molecular testing of nuclear inclusion X in Pacific Razor clams from select locations in Washington, USA"},{"id":407125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"151","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Groner, Maya L. 0000-0002-3381-6415","orcid":"https://orcid.org/0000-0002-3381-6415","contributorId":292708,"corporation":false,"usgs":false,"family":"Groner","given":"Maya","middleInitial":"L.","affiliations":[{"id":62985,"text":"Senior Research Scientist, Bigelow Laboratory for Ocean Sciences, 60 Bigelow Drive, East Boothbay, ME 04544","active":true,"usgs":false}],"preferred":false,"id":852437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hershberger, Paul 0000-0002-2261-7760","orcid":"https://orcid.org/0000-0002-2261-7760","contributorId":203322,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fradkin, Steven C.","contributorId":168638,"corporation":false,"usgs":false,"family":"Fradkin","given":"Steven","email":"","middleInitial":"C.","affiliations":[{"id":5106,"text":"National Park Service, Yellowstone National Park, Mammoth, Wyoming 82190","active":true,"usgs":false}],"preferred":false,"id":852439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conway, Carla M. 0000-0002-3851-3616 cmconway@usgs.gov","orcid":"https://orcid.org/0000-0002-3851-3616","contributorId":2946,"corporation":false,"usgs":true,"family":"Conway","given":"Carla","email":"cmconway@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852440,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hawthorn, Aine C. 0000-0002-8029-1383","orcid":"https://orcid.org/0000-0002-8029-1383","contributorId":292709,"corporation":false,"usgs":true,"family":"Hawthorn","given":"Aine","email":"","middleInitial":"C.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":852441,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Purcell, Maureen K. 0000-0003-0154-8433 mpurcell@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8433","contributorId":168475,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen","email":"mpurcell@usgs.gov","middleInitial":"K.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":852442,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70262281,"text":"70262281 - 2022 - Lake Sturgeon movement after trap and transfer around two dams on the Menominee River, Wisconsin-Michigan","interactions":[],"lastModifiedDate":"2025-01-21T15:17:43.018461","indexId":"70262281","displayToPublicDate":"2022-09-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Lake Sturgeon movement after trap and transfer around two dams on the Menominee River, Wisconsin-Michigan","docAbstract":"Fish behavior after passage or transfer around dams is a critical component in determining whether the goals of these efforts are achieved, but these behaviors are often poorly understood. An elevator was constructed in the lowermost hydroelectric dam on the Menominee River, Wisconsin–Michigan; it is the first elevator specifically designed to capture Lake Sturgeon Acipenser fulvescens for upstream transfer above two dams, providing access to high-quality spawning and early life habitat. Our objectives were to determine whether (1) Lake Sturgeon transferred upstream remained upstream for at least one spawning opportunity; (2) spawning opportunity, time to reach the next dam upstream, and residency in different segments of the river were related to sex, capture method (elevator versus electrofishing), and season of transfer; and (3) the probability of fish transitioning back downstream of the two dams varied among months. We evaluated posttransfer behaviors of 139 Lake Sturgeon that were captured in the elevator or by electrofishing, implanted with acoustic transmitters, transferred upstream (in spring or fall) from fall 2014 to spring 2017, and monitored until fall 2018 using 20–23 stationary acoustic receivers deployed throughout the river. Most Lake Sturgeon (91%) remained upstream for at least one spawning opportunity. The probability of remaining for one spawning opportunity was not related to sex, fish capture method, or season of transfer. Residency times within the two impoundments and time to reach the next dam upstream varied among individual fish. A multistate model indicated that monthly survival after upstream transfer was high and that Lake Sturgeon typically remained above both dams in late fall to early spring, with most downstream movements occurring in April and May. Our results indicate that Lake Sturgeon transferred upstream have the potential to contribute offspring that may help to bolster the Lake Sturgeon population in Lake Michigan, but additional research may help in determining whether these contributions occur.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10379","usgsCitation":"Isermann, D.A., Raabe, J., Easterly, E., Schulze, J., Porter, N., Dembkowski, D., Donofrio, M., Kramer, D., and Elliott, R., 2022, Lake Sturgeon movement after trap and transfer around two dams on the Menominee River, Wisconsin-Michigan: Transactions of the American Fisheries Society, v. 151, no. 5, p. 611-629, https://doi.org/10.1002/tafs.10379.","productDescription":"19 p.","startPage":"611","endPage":"629","ipdsId":"IP-137127","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480742,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan, Wisconsin","otherGeospatial":"Menominee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.52923848272457,\n 45.083121335445355\n ],\n [\n -87.52923848272457,\n 45.431368318822194\n ],\n [\n -87.97927795298747,\n 45.431368318822194\n ],\n [\n -87.97927795298747,\n 45.083121335445355\n ],\n [\n -87.52923848272457,\n 45.083121335445355\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"151","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Isermann, Daniel A. 0000-0003-1151-9097 disermann@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-9097","contributorId":5167,"corporation":false,"usgs":true,"family":"Isermann","given":"Daniel","email":"disermann@usgs.gov","middleInitial":"A.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Raabe, Joshua K.","contributorId":348735,"corporation":false,"usgs":false,"family":"Raabe","given":"Joshua K.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Easterly, Emma G.","contributorId":348736,"corporation":false,"usgs":false,"family":"Easterly","given":"Emma G.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schulze, Joshua C.","contributorId":348738,"corporation":false,"usgs":false,"family":"Schulze","given":"Joshua C.","affiliations":[{"id":83404,"text":"USDA Forest Service Region 1","active":true,"usgs":false}],"preferred":false,"id":923729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Porter, Nicholas J.","contributorId":348741,"corporation":false,"usgs":false,"family":"Porter","given":"Nicholas J.","affiliations":[{"id":17717,"text":"University of Wisconsin-Stevens Point","active":true,"usgs":false}],"preferred":false,"id":923730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dembkowski, Daniel J.","contributorId":348743,"corporation":false,"usgs":false,"family":"Dembkowski","given":"Daniel J.","affiliations":[{"id":65894,"text":"Wisconsin Cooperative Fishery Research Unit","active":true,"usgs":false}],"preferred":false,"id":923731,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Donofrio, Michael C.","contributorId":348744,"corporation":false,"usgs":false,"family":"Donofrio","given":"Michael C.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923732,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kramer, Darren R.","contributorId":348745,"corporation":false,"usgs":false,"family":"Kramer","given":"Darren R.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":923733,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Elliott, Robert F.","contributorId":348746,"corporation":false,"usgs":false,"family":"Elliott","given":"Robert F.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":923734,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262305,"text":"70262305 - 2022 - Stream macroinvertebrate reintroductions: A cautionary approach for restored urban streams","interactions":[],"lastModifiedDate":"2025-01-17T15:49:41.674407","indexId":"70262305","displayToPublicDate":"2022-09-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Stream macroinvertebrate reintroductions: A cautionary approach for restored urban streams","docAbstract":"Macroinvertebrate assemblages often remain depauperate in physically restored urban streams despite efforts to improve habitat conditions and increase species abundance and diversity. The lack of biological recovery may be due to a lack of a natural, nearby source of colonists, and this has inspired researchers and practitioners to reintroduce macroinvertebrates in otherwise restored urban streams to jump start the recovery process. However, without standardized guidelines that describe reintroduction best practices, some reintroduction programs may create additional problems (e.g., disease spread, genetic homogenization, population loss). To reduce these risks and limit a potential waste of resources, a cautionary approach is warranted. In this paper we summarize current stream reintroduction knowledge and detail best practices for aquatic macroinvertebrate reintroduction in restored urban streams. We provide criteria that managers can use to determine whether reintroduction is appropriate and demonstrate how researchers can use reintroduction as a tool to test hypotheses regarding factors limiting recolonization. We provide guidance for how to set clear reintroduction goals, select donor sites, determine the number of organisms required, establish reintroduction frequency and timing, and overcome challenges associated with monitoring. This framework can help managers create more successful reintroduction programs that can benefit urban stream restoration.
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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
This synthesis focuses on the history of research on coral reefs within two U.S. National Park Service units in St. Croix, U.S. Virgin Islands: Buck Island Reef National Monument (from 1961 to 2022) and Salt River Bay National Historical Park and Ecological Preserve (from 1980 to 2022). Buck Island Reef National Monument (BUIS) is off the north shore of the island of St. Croix, in the U.S. Virgin Islands. Established in 1961 and expanded in 2001, it is under the jurisdiction of the National Park Service (NPS). Long-term monitoring programs maintained by the NPS and jointly by the University of the Virgin Islands (UVI) and the Virgin Islands Department of Planning and Natural Resources (VIDPN).
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