The northern California littoral cell of the Klamath River, which is a mixed rocky and sandy system with significant shoreline curvature, was investigated by examining ∼40 yr of satellite-derived shoreline positions and historical records. We find that an accretion wave of sediment was initiated near the Klamath River mouth in the late 1980s and translated downcoast over the subsequent decades. The wave passed rapidly (∼2,500 m/yr) through a rocky coastal reach with more oblique wave directions and slowly through a sandy reach (∼200 m/yr) where wave crests approach at more normal angles. Within the sandy reach, the accretion wave extended over 200 m offshore, was ∼10 km long, incorporated 20 ± 6 million m3 of sediment, and averaged 1.3 ± 0.4 million m3/yr of longshore sediment transport over a 20-yr interval. Diffusion of the accretion wave was observed, but the diffusivity coefficient (εobs ∼0.01 m2/s) was lower than values predicted by theory, which we attribute to net sediment transport convergence in the study area caused by the curvature of the shoreline. Examining historical records, we find that increased sediment discharge in the Klamath River occurred during the 20th century from industrial-scale logging and climatic extremes. Thus, we hypothesize that increased river sediment discharge introduced new sediment to the littoral cell that initiated the observed accretion wave. These hypotheses can be tested with stratigraphic and mineralogic investigations of the broad study area beach that has formed during the past 150 years.
We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) along Bull Creek, Haskell Creek, and the Los Angeles River (Sepulveda Dam project area) in Los Angeles County, California, in 2022. Four vireo surveys were completed from April 26 to July 14, and three flycatcher surveys were completed from May 19 to July 14. We detected 10 territorial male vireos, 5 of which were confirmed as paired, and 2 transient vireos. Of the 10 territorial vireos, 70 percent were detected along the Los Angeles River, 20 percent along Bull Creek, and 10 percent along Haskell Creek. Of the vireos detected, 80 percent were in habitats characterized as mixed willow, and most vireos were detected in habitats with greater than 50-percent native plant cover. One transient flycatcher was observed in the survey area in 2022.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1177","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Pottinger, R.E., and Kus, B.E., 2023, Least Bell’s Vireo (Vireo bellii pusillus) and Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys in the Sepulveda Dam Basin, Los Angeles County, California—2022 data summary: U.S. Geological Survey Data Report 1177, 8 p., https://doi.org/10.3133/dr1177.","productDescription":"vii, 8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-147329","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":418110,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/preview/dr1177/full"},{"id":418109,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1177/images"},{"id":418108,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1177/dr1177.xml"},{"id":418107,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1177/dr1177.pdf","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":418106,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1177/covrthb.jpg"}],"country":"United States","state":"California","county":"Los Angeles County","otherGeospatial":"Sepulveda Dam project area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.53187344095177,\n 34.199920176198304\n ],\n [\n -118.53187344095177,\n 34.137737606736394\n ],\n [\n -118.42583220728267,\n 34.137737606736394\n ],\n [\n -118.42583220728267,\n 34.199920176198304\n ],\n [\n -118.53187344095177,\n 34.199920176198304\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Understanding the factors limiting populations of animals is critical for effective conservation. Determining which factors limit populations of migratory species can be especially challenging because of their reliance on multiple, often geographically distant regions during their annual cycles.
We investigated whether distribution-wide variation in recent breeding population trends was more strongly associated with exposure to risk factors experienced during migration (i.e., natural and anthropogenic threats often associated with increased mortality or carry-over effects) or factors associated with breeding and nonbreeding areas in golden-winged warblers (Vermivora chrysoptera) and blue-winged warblers (V. cyanoptera), two Nearctic-Neotropical migrants experiencing regionally variable population trends.
We used geolocator data from 85 Vermivora warblers (n = 90 geolocator tracks) tracked from North American breeding locations and Central American nonbreeding locations from 2013 to 2017 to determine variation in space use among populations. We assessed whether differences in space use among populations of Vermivora warblers during migration were associated with exposure to migration risk-factors and whether increased relative exposure to migration risk factors was associated with population declines at regional and subregional scales.
Regional and subregional populations of Vermivora warblers exhibited variation in space use and exposure to anthropogenic and natural risk-factors. However, we found no evidence that recent variation in population trends of Vermivora warblers was associated with risk-factors experienced by different populations during migration. Instead, factors associated with land cover-types in breeding and nonbreeding areas were more strongly associated with recent population trends.
Understanding how populations of migratory birds are affected by factors experienced during migration is critical for their conservation. We did not find evidence that variation in exposure to migration risk-factors is associated with recent regional or subregional variation in Vermivora warbler population trends. Consequently, our results suggest that efforts to reverse ongoing population declines of Vermivora warblers may be more effective if directed toward conservation actions targeting limiting factors within the breeding and nonbreeding periods versus those directed at conditions encountered during migration. We caution that geographic variation in projected land-use change may differentially affect areas used by different populations of Vermivora warblers during migration, posing a potential threat to these species in the future.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10980-023-01701-2","usgsCitation":"Kramer, G., Andersen, D.E., Buehler, D., Wood, P.B., Peterson, S.M., Lehman, J., Aldinger, K.R., Bulluck, L.P., Harding, S., Jones, J.A., Loegering, J.P., Smalling, C., Vallender, R., and Streby, H.M., 2023, Exposure to risk factors experienced during migration is not associated with recent Vermivora warbler population trends: Landscape Ecology, v. 38, p. 2357-2380, https://doi.org/10.1007/s10980-023-01701-2.","productDescription":"24 p.","startPage":"2357","endPage":"2380","ipdsId":"IP-145286","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502557,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://open-science.canada.ca/handle/123456789/2861","text":"External Repository"},{"id":432039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Kramer, Gunnar R.","contributorId":276165,"corporation":false,"usgs":false,"family":"Kramer","given":"Gunnar R.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":907335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, David E. 0000-0001-9535-3404 dea@usgs.gov","orcid":"https://orcid.org/0000-0001-9535-3404","contributorId":199408,"corporation":false,"usgs":true,"family":"Andersen","given":"David","email":"dea@usgs.gov","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buehler, David A.","contributorId":274719,"corporation":false,"usgs":false,"family":"Buehler","given":"David A.","affiliations":[{"id":56640,"text":"University of Tennesse","active":true,"usgs":false}],"preferred":false,"id":907337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":907339,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peterson, Sean M.","contributorId":9354,"corporation":false,"usgs":false,"family":"Peterson","given":"Sean","email":"","middleInitial":"M.","affiliations":[{"id":13013,"text":"Department of Environmental Science, Policy and Management, University of California, Berkeley","active":true,"usgs":false},{"id":34539,"text":"Minnesota Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false}],"preferred":false,"id":907340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lehman, J.A.","contributorId":340532,"corporation":false,"usgs":false,"family":"Lehman","given":"J.A.","email":"","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":907338,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldinger, Kyle R.","contributorId":171892,"corporation":false,"usgs":false,"family":"Aldinger","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":34541,"text":"West Virginia Cooperative Fish and Wildlife Research Unit","active":true,"usgs":false},{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":907341,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bulluck, Lesley P.","contributorId":204987,"corporation":false,"usgs":false,"family":"Bulluck","given":"Lesley","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":907342,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harding, Sergio","contributorId":340539,"corporation":false,"usgs":false,"family":"Harding","given":"Sergio","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":907343,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, John A.","contributorId":200310,"corporation":false,"usgs":false,"family":"Jones","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":907344,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Loegering, John P.","contributorId":166933,"corporation":false,"usgs":false,"family":"Loegering","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":33353,"text":"University of Minnesota, Crookston","active":true,"usgs":false}],"preferred":false,"id":907345,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smalling, Curtis","contributorId":340542,"corporation":false,"usgs":false,"family":"Smalling","given":"Curtis","affiliations":[{"id":33352,"text":"Audubon North Carolina","active":true,"usgs":false}],"preferred":false,"id":907346,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vallender, Rachel","contributorId":194966,"corporation":false,"usgs":false,"family":"Vallender","given":"Rachel","email":"","affiliations":[{"id":27312,"text":"Canadian Wildlife Service, Environment and Climate Change Canada, 6 Bruce Street, Mount","active":true,"usgs":false},{"id":34540,"text":"Canadian Museum of Nature","active":true,"usgs":false}],"preferred":false,"id":907347,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Streby, Henry M.","contributorId":11024,"corporation":false,"usgs":false,"family":"Streby","given":"Henry","email":"","middleInitial":"M.","affiliations":[{"id":12455,"text":"University of Toledo","active":true,"usgs":false}],"preferred":false,"id":907348,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70245173,"text":"gip224 - 2023 - U.S. Geological Survey Colorado Water Science Center postcard","interactions":[],"lastModifiedDate":"2023-06-21T15:55:28.193317","indexId":"gip224","displayToPublicDate":"2023-06-21T10:50:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"224","displayTitle":"U.S. Geological Survey Colorado Water Science Center Postcard","title":"U.S. Geological Survey Colorado Water Science Center postcard","docAbstract":"The U.S. Geological Survey Colorado Water Science Center provides timely, high-quality science information on Colorado’s water resources to help planners, managers, and others to make the decisions necessary for the use of these limited and shared resources throughout the State.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/gip224","usgsCitation":"Oden, J.H., 2023, U.S. Geological Survey Colorado Water Science Center postcard: U.S. Geological Survey General Information Product 224, 2 p., https://doi.org/10.3133/gip224.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-152927","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":418255,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0224/gip224.pdf","text":"Report","size":"500 kB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 224"},{"id":418254,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0224/coverthb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.03842219005888,\n 40.98608357834959\n ],\n [\n -109.03842219005888,\n 36.990741871706874\n ],\n [\n -102.06179793705365,\n 36.990741871706874\n ],\n [\n -102.06179793705365,\n 40.98608357834959\n ],\n [\n -109.03842219005888,\n 40.98608357834959\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
Increasing density of pinyon (Pinus spp.) and juniper (Juniperus spp.) woodlands (hereinafter “pinyon-juniper”), as well as expansion of these woodlands into adjacent shrublands and grasslands, has altered ecosystem function and wildlife habitat across large areas of the interior western United States. Although there are many natural and human-caused drivers of woodland infilling and expansion, restoration of sagebrush (Artemisia spp.) habitat through removal of pinyon-juniper is considered an urgent management objective in many locations, particularly in support of sagebrush-dependent wildlife species of conservation concern. In December 2020, the Bureau of Land Management (BLM) established the Pinyon-Juniper Management Categorical Exclusion (PJCX) to expedite the regulatory process for pinyon-juniper removal projects on public lands, largely intended to benefit mule deer (Odocoileus hemionus) and greater sage-grouse (Centrocercus urophasianus) habitats. During final preparation of this report, the BLM discontinued use of the PJCX (as of November, 2022), but the pinyon-juniper tree removal techniques assessed in this report are commonly used and understanding their effects remains relevant to land use planning.
To address areas of uncertainty relative to potential ecological effects of the PJCX, we conducted a review of the peer-reviewed science literature to better understand the likely responses of vegetation, environmental (for example, soils), and wildlife variables to specific tree removal techniques permitted by the PJCX. In brief, the PJCX permitted removal of trees by either manual cutting, mechanical cutting, or mastication; allowed certain methods to redistribute or remove resulting tree biomass after treatment; and prohibited broadcast burning, roadbuilding, removal of old-growth, and seeding of non-native species. Specifically, we conducted our review to address the following questions:
To answer these questions, we considered studies related to pinyon-juniper ecosystems, focusing on research that occurred over a large portion of the interior western United States that is the primary focus of the PJCX. We also focused on papers published from 2014 onward, to avoid excessive overlap with other recent reviews on pinyon-juniper management effects. Using strict criteria, including only considering research that tested responses for statistical significance, we identified 48 papers that primarily examined treatment effects on vegetation and other environmental variables (1,709 responses), and 11 papers that addressed effects on wildlife (132 responses). Responses to the PJCX-permitted treatments were summarized as either positive (that is, a significant increase), negative (that is, a significant decrease), or non-significant (that is, no significant difference). Responses were assigned to categories (for example, Native Annual Grass/Forb Abundance) and hierarchical treatment levels.
We found that there were large proportions of non-significant responses among all categories combined, with roughly half or more of all responses non-significant (48 percent for wildlife, 60 percent for vegetation-environmental), comparable to other recent systematic reviews of pinyon-juniper treatment effects. However, we also found that when there were significant responses, some important trends potentially emerged. Important undesirable outcomes included far more positive than negative responses of exotic grass and forb abundance among nearly all treatment types. Cutting treatments were also more likely to decrease biocrust cover and microbial activity. Potentially beneficial outcomes included mostly positive responses among sagebrush obligate species, including more positive than negative responses for mule deer and sage-grouse. Some treatment types (for example, mastication) also resulted in more positive than negative responses for native grasses and forbs (although, non-significant responses were the majority). We also highlighted many limitations of this review, including how responses often come from few studies, and how some response-treatment category combinations lack adequate response data. Moreover, the existing research is often insufficient to address many key questions about treatment effects, largely owing to short time-scales and limited spatial extents of observations, which do not match the size of treatments being implemented by land managers, nor capture long-term, post-treatment ecological dynamics. We also identify a lack of research that addresses key interactions that could undermine restoration objectives, including potential effects of climate change and grazing on post-treatment environments. Thus, we emphasize the importance of integrating these factors into future pinyon-juniper treatment research, and we stress the need for use of monitoring programs and research studies that partake in data collection and analysis over long durations and broad spatial scales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231041","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Shinneman, D.J., McIlroy, S.K., Poessel, S.A., Downing, R.L., Johnson, T.N., Young, A.C., and Katzner, T.E., 2023, Ecological effects of pinyon-juniper removal in the Western United States—A synthesis of scientific research, January 2014–March 2021: U.S. Geological Survey Open-File Report 2023–1041, 56 p., https://doi.org/10.3133/ofr20231041.","productDescription":"viii, 56 p.","onlineOnly":"Y","ipdsId":"IP-147314","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":417951,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1041/images"},{"id":417950,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231041/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1041"},{"id":417949,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1041/ofr20231041.pdf","text":"Report","size":"96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1041"},{"id":417948,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1041/coverthb.jpg"},{"id":417952,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1041/ofr20231041.XML"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -127.07350481470358,\n 50.40448106244946\n ],\n [\n -127.07350481470358,\n 30.159124183877992\n ],\n [\n -101.68400762449346,\n 30.159124183877992\n ],\n [\n -101.68400762449346,\n 50.40448106244946\n ],\n [\n -127.07350481470358,\n 50.40448106244946\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
The Geysers geothermal field located in northern California, USA, is the world’s largest electricity-generating geothermal facility. To delineate the spatio-temporal distribution of reservoir steam and recharge water, we have collected microseismic and magnetotelluric (MT) data using a dense array of stations in 2021. The microseismic and MT data have been inverted together using a 3D cooperative joint inversion workflow. The joint inversion exploits a cross-gradient structural constraint because electrical conductivity structures observed in the geothermal field are strongly correlated with
","language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.1190/geo2022-0521.1","usgsCitation":"Um, E., Commer, M., Gritto, R., Peacock, J., Alumbaugh, D., Jarpe, S.P., and Hartline, C., 2023, Cooperative joint inversion of magnetotelluric and microseismic data for imaging the Geysers geothermal field, California, USA: Geophysics, v. 88, no. 5, p. WB45-WB54, https://doi.org/10.1190/geo2022-0521.1.","productDescription":"10 p.","startPage":"WB45","endPage":"WB54","ipdsId":"IP-147160","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":467106,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/64g3h0k7","text":"External Repository"},{"id":463039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Geysers geothermal field","volume":"88","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Um, Evan","contributorId":345396,"corporation":false,"usgs":false,"family":"Um","given":"Evan","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":916421,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Commer, Michael","contributorId":345398,"corporation":false,"usgs":false,"family":"Commer","given":"Michael","email":"","affiliations":[{"id":39617,"text":"Lawrence Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":916422,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gritto, Roland","contributorId":194798,"corporation":false,"usgs":false,"family":"Gritto","given":"Roland","email":"","affiliations":[],"preferred":false,"id":916423,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":916424,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alumbaugh, David 0000-0002-6975-7197","orcid":"https://orcid.org/0000-0002-6975-7197","contributorId":299109,"corporation":false,"usgs":false,"family":"Alumbaugh","given":"David","email":"","affiliations":[{"id":64775,"text":"Berkeley National Lab","active":true,"usgs":false}],"preferred":false,"id":916425,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jarpe, Steve P.","contributorId":345402,"corporation":false,"usgs":false,"family":"Jarpe","given":"Steve","email":"","middleInitial":"P.","affiliations":[{"id":38755,"text":"Calpine","active":true,"usgs":false}],"preferred":false,"id":916426,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hartline, Craig","contributorId":213429,"corporation":false,"usgs":false,"family":"Hartline","given":"Craig","email":"","affiliations":[{"id":38755,"text":"Calpine","active":true,"usgs":false}],"preferred":false,"id":916427,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244155,"text":"sir20235036 - 2023 - Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","interactions":[],"lastModifiedDate":"2026-03-06T21:18:08.428516","indexId":"sir20235036","displayToPublicDate":"2023-06-21T07:56:13","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5036","displayTitle":"Simulation of Future Streamflow and Irrigation Demand Based on Climate and Urban Growth Projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","title":"Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","docAbstract":"Water resources in the coastal region of North Carolina and South Carolina (Coastal Carolinas) are currently under stress from competing ecological and societal needs. Projected changes in climate and population are expected to place even more stress on water resources in the region. The Coastal Carolinas Focus Area Study was initiated by the U.S. Geological Survey Water Availability and Use Science Program’s National Water Census to investigate these stressors and their effects on water resources for the Coastal Carolinas. As part of that study, the Soil and Water Assessment Tool (SWAT) model was used to investigate future streamflow and irrigation demand under six scenarios for the Cape Fear and Pee Dee River Basins, which flow through the Coastal Carolinas and into the Atlantic Ocean.
For each river basin, historical (2000 through 2014) Soil and Water Assessment Tool models were minimally calibrated, and future (2055 through 2065) scenario models were developed based on three alternative global climate models, two alternative urban growth projections, and water-use projections that correspond to each global climate model and urban growth projection pair. The river basins were delineated into 2,928 and 5,678 subbasins for the Cape Fear and Pee Dee, respectively, each approximately 2.6 square miles (mi2) in size. The best available water-use and wastewater discharge data were used for historical model calibration. The models simulated monthly mean streamflow with median Nash-Sutcliffe efficiency values of 0.53 (n = 36) and 0.61 (n = 33) in the Cape Fear and Pee Dee River Basins, respectively. Average percent bias was −4.8 percent for the Cape Fear River Basin and −1.2 percent for the Pee Dee River Basin. Catchments for streamgages chosen for model calibration that were small (less than 100 mi2) to medium (100–1,000 mi2) in area tended to perform better than larger catchments (greater than 1,000 mi2).
Historical models were used to develop future model scenarios by replacing historical weather, land-use, and water-use input datasets with projected datasets. One small, gaged catchment was selected to illustrate how the models can be used to evaluate the relative differences in simulated streamflow resulting from alternative global climate models and urban growth projections. For the selected catchment, future climate projections had a much greater influence on simulated streamflow than urban growth projections. Simulated cumulative monthly mean streamflow results for this catchment differed by 26 percent under alternative global climate models and differed by 2.4 percent under alternative urban growth projections.
Irrigation demand was modeled for subbasins with cropland. Simulated differences in irrigation demand were more pronounced and widespread across the model domain under the alternative future climate scenarios compared to alternative urban growth scenarios.
The calibrated and future scenario models have the capability to run on a daily time step and simulate streamflow and irrigation demand for thousands of small subbasins in the Cape Fear and Pee Dee River Basins. The models and underlying datasets enable future analyses for large and small areas within the basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235036","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Gurley, L.N., García, A.M., Pfeifle, C.A., and Sanchez, G.M., 2023, Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65: U.S. Geological Survey Scientific Investigations Report 2023–5036, 23 p., https://doi.org/10.3133/sir20235036.","productDescription":"Report: viii, 23 p.; 2 Data Releases","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-118241","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":417754,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P951VE5P","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Pee Dee River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417749,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.pdf","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5036"},{"id":500906,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114934.htm","linkFileType":{"id":5,"text":"html"}},{"id":417753,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PVDBW","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Cape Fear River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417752,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5036/images/"},{"id":417751,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235036/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5036 HTML"},{"id":417750,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5036 XML"},{"id":417748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5036/coverthb.jpg"}],"country":"United States","state":"North Carolina, South Carolina","otherGeospatial":"Cape Fear and Pee Dee River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.57121892850378,\n 32.91032390352079\n ],\n [\n -79.1296411830063,\n 33.177656538712625\n ],\n [\n -78.78619182539771,\n 33.72348311575605\n ],\n [\n -77.91939106571822,\n 33.920494939888584\n ],\n [\n -77.52687751416516,\n 34.40766001221573\n ],\n [\n -76.77455987368852,\n 35.02604160967191\n ],\n [\n -78.54904822133423,\n 36.169665661169745\n ],\n [\n -79.23594693655193,\n 36.51875607367013\n ],\n [\n -80.06186086794473,\n 36.51218395574713\n ],\n [\n -81.09220894077154,\n 36.66976065554749\n ],\n [\n -81.87723604387764,\n 35.792485806453826\n ],\n [\n -80.6996953892185,\n 34.985853498019594\n ],\n [\n -80.79782377710687,\n 34.42115219807647\n ],\n [\n -80.72422748619073,\n 33.5123831107352\n ],\n [\n -79.57121892850378,\n 32.91032390352079\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"For more information about this publication, contact
Program Coordinator
U.S. Geological Survey
Water Availability and Use Science Program
National Water Quality Program
Email: wausp-info@usgs.gov
For additional information, visit
https://www.usgs.gov/programs/national-water-quality-program
Sablefish (Anoplopoma fimbria) is a commercially valuable groundfish species in Alaska, with the population assessed annually by the National Oceanic and Atmospheric Administration Alaska Fisheries Science Center. Sablefish recruit into the commercially fished population at 2 years old and are poorly sampled by most surveys before that age. However, information on the abundance, distribution, and size of pre-recruitment age fish is valuable as an ecosystem indicator for older fish. Size and an index of growth rate of age-0 sablefish were quantified using samples from seabird diets at Middleton Island, Alaska, an island in the northern Gulf of Alaska. Age-0 sablefish information may serve as an indicator for potential recruitment into older age populations. This report (1) provides information on the data collection for age-0 sablefish from seabird diets at Middleton Island, Alaska from 1978 to 2022, (2) describes a method for quantifying age-0 sablefish size and growth rate, and (3) describes the size and growth rate of sablefish sampled over time. An annual release of age-0 sablefish size and growth data by U.S. Geological Survey based on continued collections on Middleton Island, Alaska, may be used to assess ecosystem status and as a recruitment indicator for sablefish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231049","collaboration":"Prepared in cooperation with National Oceanic and Atmospheric Administration Alaska Fisheries Science Center","usgsCitation":"Arimitsu, M.L., and Hatch, S.A., 2023, Age-0 sablefish size and growth indices from seabird diets at Middleton Island, Gulf of Alaska: U.S. Geological Survey Open-File Report 2023–1049, 4 p., https://doi.org/10.3133/ofr20231049.","productDescription":"Report: v, 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-151412","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":418265,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94KVH9X","text":"USGS data release","description":"USGS data release","linkHelpText":"Age-0 Sablefish size and growth indices from seabird diets at Middleton Island, Alaska"},{"id":418263,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1049/ofr20231049.pdf","text":"Report","size":"2.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1049"},{"id":418262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1049/coverthb.jpg"},{"id":418267,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1049/ofr20231049.XML"},{"id":418266,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1049/images"},{"id":418264,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231049/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1049"}],"country":"United States","state":"Alaska","otherGeospatial":"Middleton Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -147.10005001165774,\n 59.77785521975687\n ],\n [\n -147.10005001165774,\n 58.9779941146154\n ],\n [\n -145.39789946473627,\n 58.9779941146154\n ],\n [\n -145.39789946473627,\n 59.77785521975687\n ],\n [\n -147.10005001165774,\n 59.77785521975687\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
How to identify the drivers of population connectivity remains a fundamental question in ecology and evolution. Answering this question can be challenging in aquatic environments where dynamic lake and ocean currents coupled with high levels of dispersal and gene flow can decrease the utility of modern population genetic tools. To address this challenge, we used RAD-Seq to genotype 959 yellow perch (Perca flavescens), a species with an ~40-day pelagic larval duration (PLD), collected from 20 sites circumscribing Lake Michigan. We also developed a novel, integrative approach that couples detailed biophysical models with eco-genetic agent-based models to generate “predictive” values of genetic differentiation. By comparing predictive and empirical values of genetic differentiation, we estimated the relative contributions for known drivers of population connectivity (e.g., currents, behavior, PLD). For the main basin populations (i.e., the largest contiguous portion of the lake), we found that high gene flow led to low overall levels of genetic differentiation among populations (FST = 0.003). By far the best predictors of genetic differentiation were connectivity matrices that were derived from periods of time when there were strong and highly dispersive currents. Thus, these highly dispersive currents are driving the patterns of population connectivity in the main basin. We also found that populations from the northern and southern main basin are slightly divergent from one another, while those from Green Bay and the main basin are highly divergent (FST = 0.11). By integrating biophysical and eco-genetic models with genome-wide data, we illustrate that the drivers of population connectivity can be identified in high gene flow systems.
Introduction: Animal movements are influenced by landscape features; disturbances to the landscape can alter movements, dispersal, and ultimately connectivity among populations. Faster or longer movements adjacent to a localized disturbance or within disturbed areas could indicate reduced habitat quality whereas slower or shorter movements and reduced movements may indicate greater availability of resources. The Mojave desert tortoise (Gopherus agassizii) is a threatened species that is challenged by anthropogenic disturbances.
Methods: We studied tortoise movements using Global Positioning System (GPS) loggers at multiple sites in the Mojave Desert of Nevada and California. Tortoises at our sites encountered localized, linear human infrastructure, including paved roads, dirt roads, and fences, as well as landscape-scale disturbances [wildfire, off highway vehicle use (OHV), livestock grazing area]. We fit two-state (moving and encamped) Hidden Markov models to GPS logger data to infer how tortoise movement behavior relates to anthropogenic and natural features.
Results: We found that temporal covariates, individual-level random effects (intercepts), and sex best explained state transition probability in all sites. We compared relationships between tortoise movement and linear disturbances, which varied depending on site and context. Tortoises made longer movements within the OHV recreation area, near most dirt roads, and near a low-traffic paved road, indicating that tortoises avoid these habitat disturbances. Conversely, tortoises made shorter movements in areas of higher slope and near highways, suggesting that these features may restrict movement or provide resources that result in prolonged use (e.g., forage or drinking locations). Tortoises that encountered fences around utility-scale solar installations were more active and made longer movements near fences, indicative of pacing behavior.
Discussion: These results provide insight into how different disturbances alter tortoise movement behavior and modify tortoise habitat use, providing information that can be used to manage tortoise habitat.
","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.971337","usgsCitation":"Hromada, S.J., Esque, T., Vandergast, A.G., Drake, K.K., Chen, F., Gottsacker, B.O., Swart, J.A., and Nussear, K., 2023, Linear and landscape disturbances alter Mojave desert tortoise movement behavior: Frontiers in Ecology and Evolution, v. 11, 971337, 14 p., https://doi.org/10.3389/fevo.2023.971337.","productDescription":"971337, 14 p.","ipdsId":"IP-144743","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.971337","text":"Publisher Index Page"},{"id":418620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.85708110970195,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 36.70940504207991\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Felicia 0000-0002-7408-5946","orcid":"https://orcid.org/0000-0002-7408-5946","contributorId":210469,"corporation":false,"usgs":true,"family":"Chen","given":"Felicia","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876508,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gottsacker, Benjamin O 0000-0002-9481-6267","orcid":"https://orcid.org/0000-0002-9481-6267","contributorId":315424,"corporation":false,"usgs":true,"family":"Gottsacker","given":"Benjamin","email":"","middleInitial":"O","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876509,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swart, Jordan Andrew 0000-0002-3348-4721","orcid":"https://orcid.org/0000-0002-3348-4721","contributorId":315425,"corporation":false,"usgs":true,"family":"Swart","given":"Jordan","email":"","middleInitial":"Andrew","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876510,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nussear, Ken E","contributorId":221816,"corporation":false,"usgs":false,"family":"Nussear","given":"Ken E","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876511,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246266,"text":"70246266 - 2023 - Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","interactions":[],"lastModifiedDate":"2023-11-07T15:07:54.763698","indexId":"70246266","displayToPublicDate":"2023-06-21T07:04:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","docAbstract":"Riparian vegetation is widely recognized as a critical component of functioning fluvial systems. Human pressures on woody vegetation including riparian areas have had lasting effects, especially at high latitude. In Iceland, prior to human settlement, native downy birch woodlands covered approximately 15%–40% of the land area compared to 1%–2% today. Afforestation efforts include planting seedlings, protecting native forest remnants, and acquiring land areas as national forests. The planted and protected nature of vegetation along rivers within forests provides a unique opportunity to evaluate the various taxa within riparian zones and the channel stabilizing characteristics of the vegetation used in afforestation. We investigated bank properties, sediment textures, and root characteristics within riparian zones along four rivers in forests in Iceland. Bank sediment textures are dominantly sandy loam overlying coarser textures. Undercut banks are common because of erosion of the less cohesive subsurface layer. Quantitative root data indicate that the woody taxa have greater root densities, rooting depths, and more complex root structures than forbs or graminoids. The native downy birch has the highest root densities, with <1 mm roots most abundant. Modeling of added bank cohesion indicates that willow provides up to six times and birch up to four times more added cohesion to the coarse sediment textures comprising stream banks compared to no vegetation. We conclude that planting and protecting the native birch and willow helps to reduce bank erosion, especially where long-term grazing exclusion can be maintained.
A central focus of modern fisheries management is eradicating invaders that threaten imperiled native fishes. However, vast landscapes and limited funding and personnel resources demand a prioritized approach to management. Brook Stickleback Culaea inconstans (Kirtland, 1840) is an aquatic invasive species in Wyoming, USA, that may pose a risk to native biodiversity. Our aim was to evaluate Brook Stickleback’s invasive potential in the North Platte River drainage. We updated the current distribution of Brook Stickleback, evaluated for possible range expansion, and determined landscape-level habitat drivers and occurrence potential for streams across the North Platte River drainage. Additionally, we examined Brook Stickleback’s spatial overlap with native nongame fishes. At the landscape scale, Brook Stickleback preferred low-gradient streams with moderate disturbance risk. Though we did not find evidence of current Brook Stickleback range expansion 61% of streams in the drainage have landscape-level environmental characteristics that are likely suitable for Brook Stickleback, creating potential for future expansion. Brook Stickleback overlapped spatially with 13 native nongame species, though spatial overlap was less common than expected for species with similar habitat preferences. Our work serves as a case study of the factors to consider when assessing a species’ invasive potential in a previously unstudied region.
Management regimes on publicly owned freshwater wetlands in the Mississippi Flyway of North America (i.e., Flyway) have historically emphasized waterfowl, but there is limited information on how waterfowl-focused wetland management affects other wetland-dependent wildlife. Secretive marsh birds (SMBs) depend on wetlands with emergent vegetation throughout their migratory life cycle and often encounter vegetation and water conditions resulting from waterfowl-focused management regimes. Thus, there is a need for better understanding of how SMBs are affected by wetland management and the extent to which waterfowl-focused management regimes provide habitat for SMBs. In this review, we identify the vegetation and water conditions resulting from typical management objectives on freshwater emergent wetlands in the Flyway, review and qualitatively synthesize results from studies that directly evaluate how wetland management practices affect SMBs or their habitat, and assess how the vegetation and water conditions being produced for target species (mainly waterfowl) align with SMB habitat requirements. We searched online databases and used Google Scholar to locate peer-reviewed literature, technical reports, and graduate theses that pertained to responses of SMBs or their habitat to water-level manipulation, herbicide application, prescribed fire, disking, mowing, and planting crops. There are several management strategies that complement SMBs and waterfowl, such as reducing cover of woody species and providing flooded emergent vegetation. We also highlight management strategies that may not currently align with SMB life-cycle needs and suggest adjustments that might promote habitat for SMBs while still achieving waterfowl population objectives. For example, adjusting the dates and duration of spring water-level drawdowns on a portion of wetlands within a larger complex can provide for spring migrating waterfowl and ensure habitat for migrating and nesting SMBs. Ideally, future studies would address how modifications to management practices affect SMBs and monitor potential effects on waterfowl, resulting in a more holistic approach to wetland management.
Ecosystems—whether agricultural, urban, or natural—depend on pollinators, great and small. Pollinators in the form of bees, birds, butterflies, bats, and even moths provide vital, but often invisible services, from contributing to biodiverse terrestrial wildlife and plant communities to supporting healthy watersheds. Pollinator declines worldwide have been noted as land-use and climate changes occur on the landscape. This is alarming because up to 75 percent of crop species that are important for human food production depend on pollinators for production.
Biodiversity of pollinators in the United States includes more than 4,000 species of insects, birds, and mammals. Pollinator species in the United States are in crisis based on broad-scale changes in land-use and climate. The Committee on the Status of Pollinators in North America summarized active and passive management alternatives to benefit pollinators and reduce their decline. Because assessment of pollinators in the United States has historically lagged behind other regions of the world, the Committee challenged the U.S. Geological Survey (USGS) and U.S. Fish and Wildlife Service (USFWS) to develop conservation plans, for pollinators, including quantification of the effects of climate change. As an example of the immediate need to focus efforts on pollinator conservation, Inouye and others cited the USFWS’s 2017 listing of the rusty-patched bumble bee (Bombus affinis) as Endangered under the U.S. Endangered Species Act (ESA) of 1973. Strategies are developed to accomplish pollinator conservation goals and the USGS is contributing scientific expertise toward those goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233026","programNote":"Cooperative Research Units Program","usgsCitation":"Irwin, E., and Mawdsley, J., 2023, Pollinator conservation and climate science at the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2023–3026, 4 p., \nhttps://doi.org/10.3133/fs20233026.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153934","costCenters":[{"id":203,"text":"Cooperative Research Unit Atlanta","active":false,"usgs":true}],"links":[{"id":418094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3026/coverthb.jpg"},{"id":418287,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/fs20233026/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2023-3026"},{"id":418288,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3026/images/"},{"id":418289,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3026/fs20233026.XML"},{"id":499689,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114933.htm","linkFileType":{"id":5,"text":"html"}},{"id":418095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3026/fs20233026.pdf","text":"Report","size":"16.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3026"}],"contact":"Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
The demography of, and factors that influence these metrics, are largely unknown for most vultures in the Americas. Survivorship of Turkey Vultures (Cathartes aura) may be influenced by landscape heterogeneity and human disturbance. We quantified the effects of landscape composition (Shannon’s diversity index) and configuration (contagion, edge density, and largest patch index), and human disturbance (road density) on the annual and seasonal survival probabilities of the three North American breeding populations (western, central, and eastern) of Turkey Vultures that spend the nonbreeding season in the southeastern portion of the Nearctic and the northern Neotropics during a 17-year period. We used Cox’s proportional hazards models with time-varying covariates to estimate spatial and temporal changes in survival rates of adult Turkey Vultures. Road density, but not landscape composition or configuration, influenced survival rates in space and time. Overall annual survival averaged 0.87 (95% confidence interval [CI]: 0.74–0.98). Mortality risk was low in western and central populations (hazard ratio < 1) but was 3.7 times greater for vultures in the eastern population. Survival during the breeding (0.97, 95% CI: 0.96–0.98) and outbound migration (1.0, 95% CI: 1–1) seasons was significantly higher than the other seasons. Average survival tended to be higher for nonbreeding (0.81, 95% CI: 0.71–0.88) compared to return migration (0.69, 95% CI: 0.56–0.81) seasons. The risk of mortality for all vulture populations increased with road density, and this was greater during the nonbreeding and return migration seasons. The spatial variation in road density across the Americas may generate a network of ecological traps for Turkey Vultures induced to stop in areas of greater road-kill abundance. Road-killed animals acting as an attractant for vultures can increase the occurrence of vulture–vehicle collisions and potentially aggravate human–wildlife conflicts. Further analyses are needed to address survivorship and mortality factors for young birds. Our results may help the implementation of specific mitigation efforts to reduce human–vulture conflicts and vulture mortality. For instance, concentrating efforts to remove road-killed animals in areas where road density is highest can likely reduce vulture–vehicle collisions and associated mortalities of these birds.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duad024","usgsCitation":"Naveda-Rodriguez, A., Bildstein, K.L., Barber, D.R., Therrien, J., Avery, M., Kluever, B., Rush, S.A., and Vilella, F., 2023, Turkey Vulture survival is reduced in areas of greater road density, v. 125, no. 4, duad024, 9 p., https://doi.org/10.1093/ornithapp/duad024.","productDescription":"duad024, 9 p.","ipdsId":"IP-149701","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":498061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duad024","text":"Publisher Index Page"},{"id":432157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Naveda-Rodriguez, Adrian","contributorId":340683,"corporation":false,"usgs":false,"family":"Naveda-Rodriguez","given":"Adrian","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":907452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bildstein, Keith L.","contributorId":150854,"corporation":false,"usgs":false,"family":"Bildstein","given":"Keith","email":"","middleInitial":"L.","affiliations":[{"id":18119,"text":"Hawk Mountain Sanctuary, Acopian Center for Conservation Learning","active":true,"usgs":false}],"preferred":false,"id":907453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber, David R.","contributorId":340686,"corporation":false,"usgs":false,"family":"Barber","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":81649,"text":"Acopian Center for Conservation Science","active":true,"usgs":false}],"preferred":false,"id":907454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Therrien, Jean-Francois","contributorId":336846,"corporation":false,"usgs":false,"family":"Therrien","given":"Jean-Francois","email":"","affiliations":[{"id":80885,"text":"Université de Moncton, Moncton, NB, Canada","active":true,"usgs":false}],"preferred":false,"id":907455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Avery, Michael L.","contributorId":48890,"corporation":false,"usgs":true,"family":"Avery","given":"Michael L.","affiliations":[],"preferred":false,"id":907456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kluever, Bryan M.","contributorId":340689,"corporation":false,"usgs":false,"family":"Kluever","given":"Bryan M.","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":907457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rush, Scott A.","contributorId":92139,"corporation":false,"usgs":true,"family":"Rush","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":907458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907459,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70238775,"text":"70238775 - 2023 - China, the Democratic Republic of the Congo, and artisanal cobalt mining from 2000 through 2020","interactions":[],"lastModifiedDate":"2023-06-21T15:47:29.366973","indexId":"70238775","displayToPublicDate":"2023-06-20T10:44:02","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"China, the Democratic Republic of the Congo, and artisanal cobalt mining from 2000 through 2020","docAbstract":"From 2000 through 2020, demand for cobalt to manufacture batteries grew 26-fold. Eighty-two percent of this growth occurred in China and China’s cobalt refinery production increased 78-fold. Diminished industrial cobalt mine production in the early-to-mid 2000s led many Chinese companies to purchase ores from artisanal cobalt miners in the Democratic Republic of the Congo (DRC), many of whom have been found to be children. Despite extensive research on artisanal cobalt mining, fundamental questions about its production remain unanswered. This gap is addressed here by estimating artisanal cobalt production, processing, and trade. The results show that, while total DRC cobalt mine production grew from 11,000 metric tons (t) in 2000 to 98,000 t in 2020, artisanal production only grew from 1,000 to 2,000 t in 2000 to 9,000 to 11,000 t in 2020 (with a peak of 17,000 to 21,000 t in 2018). Artisanal production’s share of world and DRC cobalt mine production peaked around 2008 at 18 to 23% and 40 to 53%, respectively, before trending down to 6 to 8% and 9 to 11% in 2020, respectively. Artisanal production was chiefly exported to China or processed within the DRC by Chinese firms. An average of 72 to 79% of artisanal production was processed at facilities within the DRC from 2016 through 2020. As such, these facilities may be potential monitoring points for artisanal production and its downstream consumers. This finding may help to support responsible sourcing initiatives and better address abuses related to artisanal cobalt mining by focusing local efforts at the artisanal processing facilities through which most artisanal cobalt production flows.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2212037120","usgsCitation":"Gulley, A.L., 2023, China, the Democratic Republic of the Congo, and artisanal cobalt mining from 2000 through 2020: PNAS, v. 120, no. 26, e2212037120, 11 p., https://doi.org/10.1073/pnas.2212037120.","productDescription":"e2212037120, 11 p.","ipdsId":"IP-140831","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":443005,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2212037120","text":"Publisher Index Page"},{"id":418300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Democratic Republic of the Congo","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[110.33919,18.6784],[109.47521,18.1977],[108.65521,18.50768],[108.62622,19.36789],[109.11906,19.82104],[110.2116,20.10125],[110.78655,20.07753],[111.01005,19.69593],[110.57065,19.25588],[110.33919,18.6784]]],[[[127.65741,49.76027],[129.39782,49.4406],[130.58229,48.72969],[130.98728,47.79013],[132.50667,47.78897],[133.3736,48.18344],[135.02631,48.47823],[134.50081,47.57844],[134.11236,47.21247],[133.76964,46.11693],[133.09713,45.14407],[131.88345,45.32116],[131.02521,44.96795],[131.28856,44.11152],[131.14469,42.92999],[130.63387,42.90301],[130.64002,42.39501],[129.99427,42.98539],[129.59667,42.42498],[128.05222,41.99428],[128.20843,41.46677],[127.34378,41.50315],[126.86908,41.81657],[126.18205,41.10734],[125.07994,40.56982],[124.26562,39.92849],[122.86757,39.63779],[122.13139,39.17045],[121.05455,38.89747],[121.58599,39.36085],[121.37676,39.75026],[122.1686,40.42244],[121.64036,40.94639],[120.76863,40.59339],[119.6396,39.89806],[119.02346,39.25233],[118.04275,39.20427],[117.5327,38.73764],[118.0597,38.06148],[118.87815,37.89733],[118.91164,37.44846],[119.7028,37.15639],[120.82346,37.87043],[121.71126,37.48112],[122.35794,37.45448],[122.51999,36.93061],[121.10416,36.65133],[120.63701,36.11144],[119.66456,35.60979],[119.15121,34.90986],[120.22752,34.36033],[120.62037,33.37672],[121.22901,32.46032],[121.90815,31.69217],[121.89192,30.94935],[121.26426,30.67627],[121.50352,30.14291],[122.09211,29.83252],[121.93843,29.01802],[121.68444,28.22551],[121.12566,28.13567],[120.39547,27.05321],[119.5855,25.74078],[118.65687,24.54739],[117.28161,23.6245],[115.89074,22.78287],[114.76383,22.66807],[114.15255,22.22376],[113.80678,22.54834],[113.24108,22.05137],[111.84359,21.55049],[110.78547,21.39714],[110.44404,20.34103],[109.88986,20.28246],[109.62766,21.00823],[109.86449,21.39505],[108.52281,21.71521],[108.05018,21.55238],[107.04342,21.8119],[106.56727,22.2182],[106.7254,22.79427],[105.81125,22.97689],[105.32921,23.35206],[104.47686,22.81915],[103.50451,22.70376],[102.70699,22.7088],[102.17044,22.46475],[101.65202,22.3182],[101.80312,21.17437],[101.27003,21.20165],[101.18001,21.43657],[101.15003,21.84998],[100.41654,21.55884],[99.98349,21.74294],[99.2409,22.11831],[99.53199,22.94904],[98.89875,23.14272],[98.66026,24.06329],[97.60472,23.8974],[97.72461,25.08364],[98.67184,25.9187],[98.71209,26.74354],[98.68269,27.50881],[98.24623,27.74722],[97.91199,28.33595],[97.32711,28.26158],[96.24883,28.41103],[96.58659,28.83098],[96.11768,29.4528],[95.4048,29.03172],[94.56599,29.27744],[93.41335,28.64063],[92.50312,27.89688],[91.69666,27.77174],[91.25885,28.04061],[90.73051,28.06495],[90.01583,28.29644],[89.47581,28.04276],[88.81425,27.29932],[88.73033,28.08686],[88.12044,27.87654],[86.95452,27.97426],[85.82332,28.20358],[85.01164,28.64277],[84.23458,28.83989],[83.89899,29.32023],[83.33712,29.46373],[82.32751,30.11527],[81.5258,30.42272],[81.11126,30.18348],[79.72137,30.88271],[78.73889,31.51591],[78.45845,32.61816],[79.17613,32.48378],[79.20889,32.99439],[78.81109,33.5062],[78.91227,34.32194],[77.83745,35.49401],[76.19285,35.8984],[75.8969,36.66681],[75.15803,37.13303],[74.98,37.41999],[74.82999,37.99001],[74.86482,38.37885],[74.25751,38.60651],[73.92885,38.50582],[73.67538,39.43124],[73.96001,39.66001],[73.82224,39.89397],[74.77686,40.36643],[75.46783,40.56207],[76.52637,40.42795],[76.90448,41.06649],[78.1872,41.18532],[78.54366,41.58224],[80.11943,42.12394],[80.25999,42.35],[80.18015,42.92007],[80.86621,43.18036],[79.96611,44.91752],[81.94707,45.31703],[82.45893,45.53965],[83.18048,47.33003],[85.16429,47.00096],[85.72048,47.45297],[85.76823,48.45575],[86.59878,48.54918],[87.35997,49.21498],[87.75126,49.2972],[88.01383,48.59946],[88.8543,48.06908],[90.28083,47.69355],[90.97081,46.88815],[90.58577,45.71972],[90.94554,45.28607],[92.13389,45.11508],[93.48073,44.97547],[94.68893,44.35233],[95.30688,44.24133],[95.76245,43.31945],[96.3494,42.72564],[97.45176,42.74889],[99.51582,42.52469],[100.84587,42.6638],[101.83304,42.51487],[103.31228,41.90747],[104.52228,41.90835],[104.96499,41.59741],[106.12932,42.13433],[107.74477,42.48152],[109.2436,42.51945],[110.4121,42.87123],[111.12968,43.40683],[111.82959,43.74312],[111.66774,44.07318],[111.34838,44.45744],[111.87331,45.10208],[112.43606,45.01165],[113.46391,44.80889],[114.46033,45.33982],[115.9851,45.72724],[116.71787,46.3882],[117.4217,46.67273],[118.87433,46.80541],[119.66327,46.69268],[119.77282,47.04806],[118.86657,47.74706],[118.06414,48.06673],[117.29551,47.69771],[116.30895,47.85341],[115.74284,47.72654],[115.48528,48.13538],[116.1918,49.1346],[116.6788,49.88853],[117.87924,49.51098],[119.28846,50.14288],[119.27937,50.58291],[120.18205,51.64357],[120.73819,51.96412],[120.72579,52.51623],[120.17709,52.75389],[121.00308,53.2514],[122.24575,53.43173],[123.57151,53.4588],[125.06821,53.16104],[125.94635,52.7928],[126.5644,51.78426],[126.93916,51.35389],[127.28746,50.7398],[127.65741,49.76027]]],[[[30.83386,3.50917],[30.77335,2.33988],[31.17415,2.20447],[30.85267,1.8494],[30.46851,1.58381],[30.08615,1.06231],[29.87578,0.59738],[29.8195,-0.20531],[29.58784,-0.58741],[29.57947,-1.34131],[29.29189,-1.62006],[29.25483,-2.21511],[29.11748,-2.29221],[29.02493,-2.83926],[29.27638,-3.29391],[29.34,-4.49998],[29.51999,-5.41998],[29.41999,-5.94],[29.62003,-6.52002],[30.2,-7.07998],[30.74002,-8.34001],[30.34609,-8.23826],[29.00291,-8.40703],[28.73487,-8.52656],[28.44987,-9.16492],[28.67368,-9.60592],[28.49607,-10.78988],[28.37225,-11.79365],[28.64242,-11.97157],[29.34155,-12.36074],[29.616,-12.17889],[29.69961,-13.25723],[28.93429,-13.24896],[28.52356,-12.6986],[28.15511,-12.27248],[27.3888,-12.13275],[27.16442,-11.60875],[26.55309,-11.92444],[25.75231,-11.78497],[25.41812,-11.33094],[24.78317,-11.23869],[24.31452,-11.26283],[24.25716,-10.95199],[23.91222,-10.92683],[23.45679,-10.86786],[22.83735,-11.01762],[22.4028,-10.99308],[22.15527,-11.0848],[22.20875,-9.8948],[21.87518,-9.52371],[21.8018,-8.90871],[21.94913,-8.3059],[21.74646,-7.92008],[21.72811,-7.29087],[20.51475,-7.29961],[20.60182,-6.93932],[20.09162,-6.94309],[20.03772,-7.11636],[19.4175,-7.15543],[19.16661,-7.73818],[19.01675,-7.98825],[18.46418,-7.84701],[18.13422,-7.98768],[17.47297,-8.06855],[17.09,-7.54569],[16.86019,-7.2223],[16.57318,-6.62264],[16.32653,-5.87747],[13.3756,-5.86424],[13.02487,-5.98439],[12.73517,-5.96568],[12.32243,-6.10009],[12.18234,-5.78993],[12.43669,-5.6843],[12.468,-5.24836],[12.63161,-4.99127],[12.99552,-4.7811],[13.25824,-4.88296],[13.60023,-4.50014],[14.14496,-4.51001],[14.20903,-4.79309],[14.5826,-4.97024],[15.17099,-4.34351],[15.75354,-3.85516],[16.00629,-3.53513],[15.9728,-2.71239],[16.40709,-1.74093],[16.86531,-1.22582],[17.52372,-0.74383],[17.63864,-0.42483],[17.66355,-0.05808],[17.82654,0.28892],[17.77419,0.85566],[17.89884,1.74183],[18.09428,2.36572],[18.39379,2.90044],[18.45307,3.50439],[18.54298,4.20179],[18.93231,4.70951],[19.46778,5.03153],[20.29068,4.69168],[20.92759,4.32279],[21.65912,4.22434],[22.40512,4.02916],[22.70412,4.63305],[22.84148,4.71013],[23.29721,4.60969],[24.41053,5.10878],[24.80503,4.89725],[25.12883,4.92724],[25.2788,5.17041],[25.65046,5.25609],[26.40276,5.15087],[27.04407,5.12785],[27.37423,5.23394],[27.97998,4.40841],[28.42899,4.28715],[28.69668,4.45508],[29.15908,4.38927],[29.716,4.6008],[29.9535,4.1737],[30.83386,3.50917]]]]},\"properties\":{\"name\":\"China\"}}]}","volume":"120","issue":"26","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Gulley, Andrew L. 0000-0003-4717-2080","orcid":"https://orcid.org/0000-0003-4717-2080","contributorId":203953,"corporation":false,"usgs":true,"family":"Gulley","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":858559,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70245601,"text":"70245601 - 2023 - A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","interactions":[],"lastModifiedDate":"2023-06-26T13:27:30.871321","indexId":"70245601","displayToPublicDate":"2023-06-20T08:23:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"displayTitle":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","title":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","docAbstract":"Climate warming is rapidly altering Arctic ecosystems. Polar bears (Ursus maritimus) need sea ice as a platform from which to hunt seals, but increased sea-ice loss is lengthening periods when bears are without access to primary hunting habitat. During periods of food scarcity, survival depends on the energy that a bear has stored in body reserves, termed storage energy, making this a key metric in predictive models assessing climate change impacts on polar bears. Here, we developed a body composition model for polar bears that estimates storage energy while accounting for changes in storage tissue composition. We used data of dissected polar bears (n = 31) to link routinely collected field measures of total body mass and straight-line body length to the body composition of individual bears, described in terms of structural mass and two storage compartments, adipose and muscle. We then estimated the masses of metabolizable proteins and lipids within these storage compartments, giving total storage energy. We tested this multi-storage model by using it to predict changes in the lipid stores from an independent dataset of wild polar bears (n = 36) that were recaptured 8–200 days later. Using length and mass measurements, our model successfully predicted direct measurements of lipid changes via isotopic dilutions (root mean squared error of 14.5 kg). Separating storage into two compartments, and allowing the molecular composition of storage to vary, provides new avenues for quantifying energy stores of individuals across their life cycle. The multi-storage body composition model thus provides a basis for further exploring energetic costs of physiological processes that contribute to individual survival and reproductive success. Given bioenergetic models are increasingly used as a tool to predict individual fitness and population dynamics, our approach for estimating individual energy stores could be applicable to a wide range of species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coad043","usgsCitation":"Penk, S.R., Sadana, P., Archer, L.C., Pagano, A.M., Cattet, M.R., Lunn, N.J., Thiemann, G.W., and Molnar, P.K., 2023, A body composition model with multiple storage compartments for polar bears (Ursus maritimus), v. 11, no. 1, coad043, 20 p., https://doi.org/10.1093/conphys/coad043.","productDescription":"coad043, 20 p.","ipdsId":"IP-142122","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":443007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coad043","text":"Publisher Index Page"},{"id":418459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Penk, Stephanie R. 0000-0002-8027-4372","orcid":"https://orcid.org/0000-0002-8027-4372","contributorId":312472,"corporation":false,"usgs":false,"family":"Penk","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadana, Pranav","contributorId":312473,"corporation":false,"usgs":false,"family":"Sadana","given":"Pranav","email":"","affiliations":[{"id":16930,"text":"University of Winnipeg","active":true,"usgs":false}],"preferred":false,"id":876208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archer, Louise C. 0000-0002-1983-3825","orcid":"https://orcid.org/0000-0002-1983-3825","contributorId":312474,"corporation":false,"usgs":false,"family":"Archer","given":"Louise","email":"","middleInitial":"C.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":876210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cattet, Marc R. L. 0000-0002-2318-1452","orcid":"https://orcid.org/0000-0002-2318-1452","contributorId":312475,"corporation":false,"usgs":false,"family":"Cattet","given":"Marc","email":"","middleInitial":"R. L.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":876211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lunn, Nicholas J. 0000-0003-0189-5494","orcid":"https://orcid.org/0000-0003-0189-5494","contributorId":312476,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":876212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":876213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Molnar, Peter K. 0000-0001-7260-2674","orcid":"https://orcid.org/0000-0001-7260-2674","contributorId":312477,"corporation":false,"usgs":false,"family":"Molnar","given":"Peter","email":"","middleInitial":"K.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245787,"text":"70245787 - 2023 - Ensemble estimation of historical evapotranspiration for the conterminous U.S.","interactions":[],"lastModifiedDate":"2023-06-27T11:48:52.454255","indexId":"70245787","displayToPublicDate":"2023-06-20T06:45:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Ensemble estimation of historical evapotranspiration for the conterminous U.S.","docAbstract":"Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.
Assessing the influence of marshes on mitigating flooding along estuarine shorelines under the pressures of sea level rise requires understanding wave transformation across the marsh. A numerical model was applied to investigate how vegetated marshes influence wave transformation. XBeach non-hydrostatic (XB-NH) was calibrated and validated with high frequency pressure data from the marsh at China Camp State Park in San Pablo Bay, California (USA). The model was used to examine how marsh and hydrodynamic characteristics change the potential for marshes to mitigate wave driven flooding. Model results demonstrate that hydrodynamics, vegetation, and marsh width influence wave transformation most, while marsh morphology parameters such as elevation and slope had least effect. Results suggest that in the range of settings explored here (incident wave heights ranging from 0.5 to 3 m and water levels ranging from current mean higher high water to 3 m above current mean higher high water), in comparison to wave propagation over an unvegetated mudflat, marsh vegetation reduces runup by a median of 40 cm and wave height by a median of 35 cm. Results illustrate how marshes can be strategically utilized to provide flood reduction benefits.
On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water-rich plume at least 58 km high. Using a combination of satellite- and ground-based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min−1) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co-located with an internal gravity wave traveling >80 m s−1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high-current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 109 kg s−1), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma-water interaction at the submarine vent.
Sea level rise is affecting reaches of coastal rivers by increasing water levels and propagating tides inland. The transition of river systems into tidal estuaries has been neglected in hydrogeomorphic studies. A better understanding of transitioning reaches is critical to understanding ecosystem dynamics, services, and developing predictive capabilities of change as sea levels rise. We hypothesized that river-floodplain morphology changes from fluvial to tidally dominated regimes, changing suspended sediment concentrations (SSC), sediment deposition, vegetation, and landforms. We tested this using lidar, satellite imagery, and SSC and conductivity measurements along two Coastal Plain rivers of Virginia, USA. Geomorphic channel and floodplain parameters indicated breakpoints into three regimes: fluvial, mixed, and tidal. Maximum channel width occurred with minimum floodplain widths in the mixed regime. Tidal freshwater forests had considerable elevational overlap with marshes but typically were 9.5 cm higher. SSC increased with shoal width through the mixed reaches, with maxima in the tidal reaches where estuarine influences increased. Channel erosion rates indicated that modern sediment loads and hydrology produce slow changes to channel planform and geomorphology that may not be apparent from visual comparisons. Our findings indicated that tidal floodplain forests and marshes in the mixed and tidal reaches are expected to convert to marshes or open water as sea levels rise as limited gradual sloping area exists between the active floodplain and terraces. Tidal floodplain surfaces along mixed hydrology reaches, inland of the estuarine turbidity maximum may be expected to convert to open water while inland sloping floodplains could support tidal wetland migration.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-023-01226-6","usgsCitation":"Kroes, D., Noe, G.E., Hupp, C.R., Doody, T.R., and Bukaveckas, P., 2023, Hydrogeomorphic changes along mid-Atlantic coastal plain rivers transitioning from non-tidal to tidal: Implications for a rising sea level: Estuaries and Coasts, v. 46, p. 1438-1458, https://doi.org/10.1007/s12237-023-01226-6.","productDescription":"21 p.","startPage":"1438","endPage":"1458","ipdsId":"IP-135089","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435281,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B1UCFT","text":"USGS data release","linkHelpText":"Hydrogeomorphic data along transitioning Coastal Plain rivers (Mattaponi and Pamunkey Rivers): implications for a rising sea level"},{"id":418223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Chesapeake Bay Watershed, Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.65344171287853,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.86125997466432\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","noUsgsAuthors":false,"publicationDate":"2023-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":875659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doody, Thomas Rossiter 0000-0002-2102-738X tdoody@contractor.usgs.gov","orcid":"https://orcid.org/0000-0002-2102-738X","contributorId":223569,"corporation":false,"usgs":true,"family":"Doody","given":"Thomas","email":"tdoody@contractor.usgs.gov","middleInitial":"Rossiter","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bukaveckas, P.A. 0000-0002-2636-7818","orcid":"https://orcid.org/0000-0002-2636-7818","contributorId":310428,"corporation":false,"usgs":false,"family":"Bukaveckas","given":"P.A.","affiliations":[{"id":38728,"text":"Virginia Commonwealth University","active":true,"usgs":false}],"preferred":false,"id":875661,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245159,"text":"70245159 - 2023 - The nitty-gritty forces that shape planetary surfaces","interactions":[],"lastModifiedDate":"2023-06-19T17:19:28.308949","indexId":"70245159","displayToPublicDate":"2023-06-19T12:13:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7458,"text":"Eos Science News","active":true,"publicationSubtype":{"id":10}},"title":"The nitty-gritty forces that shape planetary surfaces","docAbstract":"No abstract available.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023EO230227","usgsCitation":"Jackson, B., Diniega, S., Titus, T.N., Soto, A., and Rivera-Valentin, E., 2023, The nitty-gritty forces that shape planetary surfaces: Eos Science News, v. 104, 16 p., https://doi.org/10.1029/2023EO230227.","productDescription":"16 p.","ipdsId":"IP-150345","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":443015,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1029/2023eo230227","text":"Publisher Index Page"},{"id":418220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars, Titan","volume":"104","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jackson, Brian","contributorId":184119,"corporation":false,"usgs":false,"family":"Jackson","given":"Brian","affiliations":[],"preferred":false,"id":875704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diniega, Serina","contributorId":212017,"corporation":false,"usgs":false,"family":"Diniega","given":"Serina","email":"","affiliations":[{"id":36276,"text":"JPL","active":true,"usgs":false}],"preferred":false,"id":875705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":875706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soto, Alejandro","contributorId":237034,"corporation":false,"usgs":false,"family":"Soto","given":"Alejandro","email":"","affiliations":[{"id":41659,"text":"SWRI","active":true,"usgs":false}],"preferred":false,"id":875707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rivera-Valentin, Edgard","contributorId":310447,"corporation":false,"usgs":false,"family":"Rivera-Valentin","given":"Edgard","email":"","affiliations":[{"id":67194,"text":"JHU/APL","active":true,"usgs":false}],"preferred":false,"id":875708,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245161,"text":"70245161 - 2023 - High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia","interactions":[],"lastModifiedDate":"2023-06-19T17:12:31.329271","indexId":"70245161","displayToPublicDate":"2023-06-19T11:51:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia","docAbstract":"During a volcanic crisis, high-rate, localized deformation can indicate magma close to the surface, with important implications for eruption forecasting. However, only a few such examples have been reported, because frequent, dense monitoring is needed. High-resolution Synthetic Aperture Radar (SAR) is capable of achieving <1 m spatial resolution and sub-weekly revisit times, but is under-used. Here we use high-resolution satellite SAR imagery from COSMO-SkyMed, TerraSAR-X, and Sentinel-1 to detect intra-crater uplift preceding the November 2017 onset of eruptive activity at Agung, Indonesia. Processing the SAR imagery with an up-to-date, accurate, high-resolution digital elevation model was crucial for preventing aliasing of the deformation signal and for accurate georeferencing. We show that >15 cm of line-of-sight shortening occurred over a 400-by-400 m area on the crater floor in September-October 2017, accompanying a deep seismic swarm and flank dyke intrusion. We attribute the deformation to the pressurization of a shallow (<200 m deep) hydrothermal system by the injection of magmatic gases and fluids. We also observe a second pulse of intra-crater deformation of 3–5 cm within 4 days to 11 hr prior to the first phreatomagmatic eruption, which is consistent with interaction between the hydrothermal system and the ascending magma. This phreatomagmatic eruption created the central pathway used during the final stages of magma ascent. Our observations have important implications for understanding unrest and eruption forecasting, and demonstrate the potential of monitoring with high-resolution SAR.
","language":"English","publisher":"Wiley","doi":"10.1029/2022JB025669","usgsCitation":"Bemelmans, M., Biggs, J., Poland, M.P., Wookey, J., Ebmeier, S., Diefenbach, A., and Syahbana, D.D., 2023, High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia: Journal of Geophysical Research B: Solid Earth, v. 128, no. 5, e2022JB025669, 27 p., https://doi.org/10.1029/2022JB025669.","productDescription":"e2022JB025669, 27 p.","ipdsId":"IP-145594","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":443019,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jb025669","text":"Publisher Index Page"},{"id":418219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Agung Volcano, Bali","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115.49507682936888,\n -8.406300591448016\n ],\n [\n 115.51391236474785,\n -8.425323602450476\n ],\n [\n 115.52198473705289,\n -8.44129377777513\n ],\n [\n 115.53026409326424,\n -8.430851814741729\n ],\n [\n 115.55944882390781,\n -8.390309758644221\n ],\n [\n 115.58221705348922,\n -8.367402141157967\n ],\n [\n 115.58263102130024,\n -8.335659853363467\n ],\n [\n 115.5604837434351,\n -8.30350536078592\n ],\n [\n 115.524675527824,\n -8.28425236518369\n ],\n [\n 115.48783239268414,\n -8.28793125803746\n ],\n [\n 115.44064006228348,\n -8.31005143321569\n ],\n [\n 115.42863499577669,\n -8.344867699330223\n ],\n [\n 115.44871243458851,\n -8.381933371662427\n ],\n [\n 115.49507682936888,\n -8.406300591448016\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bemelmans, Mark","contributorId":310454,"corporation":false,"usgs":false,"family":"Bemelmans","given":"Mark","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggs, Juliet","contributorId":206389,"corporation":false,"usgs":false,"family":"Biggs","given":"Juliet","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wookey, James","contributorId":310455,"corporation":false,"usgs":false,"family":"Wookey","given":"James","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebmeier, Susanna","contributorId":174225,"corporation":false,"usgs":false,"family":"Ebmeier","given":"Susanna","affiliations":[{"id":7172,"text":"University of Bristol, U.K. and University of Oregon, Eugene","active":true,"usgs":false}],"preferred":false,"id":875722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875723,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Syahbana, Devy Damil","contributorId":243233,"corporation":false,"usgs":false,"family":"Syahbana","given":"Devy","email":"","middleInitial":"Damil","affiliations":[],"preferred":false,"id":875724,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70245142,"text":"70245142 - 2023 - Land development and road salt usage drive long-term changes in major-ion chemistry of streamwater in six exurban and suburban watersheds, southeastern Pennsylvania, 1999-2019","interactions":[],"lastModifiedDate":"2023-06-19T16:50:45.814465","indexId":"70245142","displayToPublicDate":"2023-06-19T11:39:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Land development and road salt usage drive long-term changes in major-ion chemistry of streamwater in six exurban and suburban watersheds, southeastern Pennsylvania, 1999-2019","docAbstract":"In urbanized areas, the “freshwater salinization syndrome” (FSS), which pertains to long-term increases in concentrations of major ions and metals in fresh surface waters, has been attributed to road salt application. In addition to FSS, the water composition changes as an influx of sodium (Na+) in recharge may displace calcium (Ca2+), magnesium (Mg2+), potassium (K+), and trace metals by reverse cation exchange. These changing ion fluxes can result in adverse impacts on groundwater and surface waters used for municipal supplies. Few datasets exist to quantify the FSS on a watershed scale or link its manifestation to potential controlling factors such as changes in urban development, land use/land cover (LULC), or wastewater treatment plant (WWTP) discharges in upstream areas. Here, we use two decades (1999–2019) of monthly streamwater quality data combined with daily streamflow for six exurban and suburban watersheds in southeastern Pennsylvania to examine the relations among Ca2+, Mg2+, K+, Na+, chloride (Cl−), sulfate (SO42-), and alkalinity (HCO3−) concentrations and upstream controlling factors. Flow-normalized annual and baseflow (August ̶ November) concentrations for Ca2+, Mg2+, Na+, and Cl− increased in all six watersheds over the 20-year study, providing evidence of FSS’s impacts on groundwater that sustains streamflow. Additionally, a redundancy analysis using 2019 flow-normalized values identified the following positive associations between solute concentrations and controlling variables: 1) Cl−, Mg2+, and Ca2+ with impervious surface cover (ISC), 2) Na+ and SO42- with ISC and total WWTP discharge volume, and 3) HCO3− with agriculture and total WWTP discharge volume. From a human health perspective, 2019 flow-normalized Na+ concentrations exceeded the U.S. Environmental Protection Agency’s 20 mg L-1 threshold for individuals restricted to a low sodium diet. Furthermore, indices used to evaluate the corrosivity of source waters to drinking water infrastructure and inform municipal water treatment practices, such as the Chloride to Sulfate Mass Ratio and Larson Ratio, increased between two- and seven-fold over the 20-year time. Collectively, the results elucidate the causal factors of the FSS in suburban and exurban watersheds and its potential impacts on human health and drinking water infrastructure.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2023.1153133","usgsCitation":"Rossi, M.L., Kremer, P., Cravotta, C., Seng, K.E., and Goldsmith, S.T., 2023, Land development and road salt usage drive long-term changes in major-ion chemistry of streamwater in six exurban and suburban watersheds, southeastern Pennsylvania, 1999-2019: Frontiers in Environmental Science, v. 11, 1153133, 21 p ., https://doi.org/10.3389/fenvs.2023.1153133.","productDescription":"1153133, 21 p .","ipdsId":"IP-147665","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":443021,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1153133","text":"Publisher Index Page"},{"id":418218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Chester Creek, Crum Creek, East Branch Brandywine Creek, Neshaminy Creek, Perkiomen Creek, Ridley Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.5237058720174,\n 39.713850779802925\n ],\n [\n -74.67929211102248,\n 39.713850779802925\n ],\n [\n -74.67929211102248,\n 40.9985953543042\n ],\n [\n -76.5237058720174,\n 40.9985953543042\n ],\n [\n -76.5237058720174,\n 39.713850779802925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-05-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Rossi, Marissa Lee 0000-0003-2341-0312","orcid":"https://orcid.org/0000-0003-2341-0312","contributorId":310430,"corporation":false,"usgs":true,"family":"Rossi","given":"Marissa","email":"","middleInitial":"Lee","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875662,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kremer, Peleg","contributorId":296521,"corporation":false,"usgs":false,"family":"Kremer","given":"Peleg","email":"","affiliations":[{"id":12766,"text":"Villanova University","active":true,"usgs":false}],"preferred":false,"id":875663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":875664,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seng, Krista E.","contributorId":310432,"corporation":false,"usgs":false,"family":"Seng","given":"Krista","email":"","middleInitial":"E.","affiliations":[{"id":67185,"text":"Aqua Pennsylvania, Inc.","active":true,"usgs":false}],"preferred":false,"id":875665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goldsmith, Steven T.","contributorId":193458,"corporation":false,"usgs":false,"family":"Goldsmith","given":"Steven","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":875666,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245153,"text":"70245153 - 2023 - A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong","interactions":[],"lastModifiedDate":"2023-06-19T16:38:44.155755","indexId":"70245153","displayToPublicDate":"2023-06-19T11:22:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong","docAbstract":"Non-invasively collected faecal samples are an alternative source of DNA to tissue samples, that may be used in genetic studies of wildlife when direct sampling of animals is difficult. Although several faecal DNA extraction methods exist, their efficacy varies between species. Previous attempts to amplify mitochondrial DNA (mtDNA) markers from faeces of wild dugongs (Dugong dugon) have met with limited success and nuclear markers (microsatellites) have been unsuccessful. This study aimed to establish a tool for sampling both mtDNA and nuclear DNA (nDNA) from dugong faeces by modifying approaches used in studies of other large herbivores. First, a streamlined, cost-effective DNA extraction method that enabled the amplification of both mitochondrial and nuclear markers from large quantities of dugong faeces was developed. Faecal DNA extracted using a new ‘High Volume- Cetyltrimethyl Ammonium Bromide- Phenol-Chloroform-Isoamyl Alcohol’ (HV-CTAB-PCI) method was found to achieve comparable amplification results to extraction of DNA from dugong skin. As most prevailing practices advocate sampling from the outer surface of a stool to maximise capture of sloughed intestinal cells, this study compared amplification success of mtDNA between the outer and inner layers of faeces, but no difference in amplification was found. Assessment of the impacts of faecal age or degradation on extraction, however, demonstrated that fresher faeces with shorter duration of environmental (seawater) exposure amplified both markers better than eroded scats. Using the HV-CTAB-PCI method, nuclear markers were successfully amplified for the first time from dugong faeces. The successful amplification of single nucleotide polymorphism (SNP) markers represents a proof-of-concept showing that DNA from dugong faeces can potentially be utilised in population genetic studies. This novel DNA extraction protocol offers a new tool that will facilitate genetic studies of dugongs and other large and cryptic marine herbivores in remote locations.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0278792","usgsCitation":"Ooi, V., McMichael, L., Hunter, M., Takoukam Kamla, A., and Lanyon, J.M., 2023, A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong: PLoS ONE, v. 18, no. 6, e0278792, 29 p., https://doi.org/10.1371/journal.pone.0278792.","productDescription":"e0278792, 29 p.","ipdsId":"IP-147065","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":443024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0278792","text":"Publisher Index Page"},{"id":418217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Queensland","otherGeospatial":"Moreton Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 153.37192416070502,\n -27.859614592565208\n ],\n [\n 153.42962470601918,\n -27.687005800163497\n ],\n [\n 153.43511999604937,\n -27.504375776224627\n ],\n [\n 153.46534409121273,\n -27.406848872159316\n ],\n [\n 153.3939053208257,\n -27.204205934764204\n ],\n [\n 153.38566238578045,\n -27.050146132142267\n ],\n [\n 153.17134607461963,\n -27.050146132142267\n ],\n [\n 153.0422067589185,\n -27.106414779566876\n ],\n [\n 152.99824443867976,\n -27.194430673154535\n ],\n [\n 153.08891672417235,\n -27.23108348366104\n ],\n [\n 153.0202255988005,\n -27.297028138020522\n ],\n [\n 153.08616907915723,\n -27.362933646179656\n ],\n [\n 153.14661726948384,\n -27.38489343868985\n ],\n [\n 153.18233665467994,\n -27.492189631662583\n ],\n [\n 153.2345419099613,\n -27.51168681530772\n ],\n [\n 153.2867471652453,\n -27.601816322987915\n ],\n [\n 153.29224245527553,\n -27.711333458802045\n ],\n [\n 153.34994300058702,\n -27.786714713843168\n ],\n [\n 153.37192416070502,\n -27.859614592565208\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ooi, Vicky","contributorId":310440,"corporation":false,"usgs":false,"family":"Ooi","given":"Vicky","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMichael, Lee","contributorId":310441,"corporation":false,"usgs":false,"family":"McMichael","given":"Lee","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":214742,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takoukam Kamla, Aristide","contributorId":204221,"corporation":false,"usgs":false,"family":"Takoukam Kamla","given":"Aristide","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":875696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lanyon, Janet M.","contributorId":204224,"corporation":false,"usgs":false,"family":"Lanyon","given":"Janet","email":"","middleInitial":"M.","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875697,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}