The number of stranding response facilities for marine mammals in the United States has increased over the past two decades, resulting in thousands of rehabilitated marine mammals released back into the wild (Geraci and Lounsbury 2005; Moore et al. 2007; Johnson and Mayer 2015; Simeone et al. 2015). All rehabilitated marine mammals released in the United States must be tagged or marked (50 CFR 216.27) and post-release monitoring is recommended, if not required, for some taxonomic groups. This depends on their release category as determined by a veterinarian in concordance with guidelines established by the National Marine Fisheries Service (NMFS) and the US Fish and Wildlife Service (USFWS; Whaley and Borkowski 2009). Monitoring the fate of released, rehabilitated marine mammals is not only necessary for the validation and refinement of veterinary procedures and treatments, but allows for the recovery of individuals that are unable to adapt to the wild (Whaley and Borkowski 2009). For cases in which rehabilitation is used to enhance small or endangered populations, monitoring the ability of individuals to forage, survive, and ultimately reproduce following release is essential for assessing the conservation value of a given program’s efforts. Post-release monitoring has also been useful in some cases for elucidating poorly understood ranges and habitat use of wild populations (Moore et al. 2007).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"CRC handbook of marine mammal medicine, 3rd edition","language":"English","publisher":"CRC Press : Taylor & Francis Group","usgsCitation":"Lander, M.E., Westgate, A.J., Balmer, B.C., Reid, J.P., Murray, M.J., and Laidre, K.L., 2018, Tagging and tracking, chap. of CRC handbook of marine mammal medicine, 3rd edition, p. 767-798.","productDescription":"32 p.","startPage":"767","endPage":"798","ipdsId":"IP-080536","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":356956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":356309,"type":{"id":15,"text":"Index Page"},"url":"https://www.taylorfrancis.com/books/9781498796880"}],"edition":"3rd","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a2eae4b0702d0e84300a","contributors":{"authors":[{"text":"Lander, Michelle E.","contributorId":206850,"corporation":false,"usgs":false,"family":"Lander","given":"Michelle","email":"","middleInitial":"E.","affiliations":[{"id":37416,"text":"Marine Mammal Laboratory, Alaska Fisheries Science Center, NOAA, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":741940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Westgate, Andrew J.","contributorId":206851,"corporation":false,"usgs":false,"family":"Westgate","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":37417,"text":"Dept. of Biology and Marine Biology, University of North Carolina Wilmington, Wilmington, NC","active":true,"usgs":false}],"preferred":false,"id":741941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Balmer, Brian C.","contributorId":206853,"corporation":false,"usgs":false,"family":"Balmer","given":"Brian","email":"","middleInitial":"C.","affiliations":[{"id":27926,"text":"NOAA, National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":741943,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, James P. 0000-0002-8497-1132 jreid@usgs.gov","orcid":"https://orcid.org/0000-0002-8497-1132","contributorId":3460,"corporation":false,"usgs":true,"family":"Reid","given":"James","email":"jreid@usgs.gov","middleInitial":"P.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":741939,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Michael J.","contributorId":206852,"corporation":false,"usgs":false,"family":"Murray","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":37418,"text":"Monterey Bay Aquarium, Monterey, CA","active":true,"usgs":false}],"preferred":false,"id":741942,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Laidre, Kristen L.","contributorId":206854,"corporation":false,"usgs":false,"family":"Laidre","given":"Kristen","email":"","middleInitial":"L.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":741944,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196107,"text":"70196107 - 2018 - Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa","interactions":[],"lastModifiedDate":"2018-03-20T08:59:44","indexId":"70196107","displayToPublicDate":"2018-03-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2284,"text":"Journal of Field Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa","title":"Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa","docAbstract":"Endangered Hawai‘i ʻĀkepas (Loxops coccineus) are endemic to Hawai‘i island, where they occur in five spatially distinct populations. Data concerning the status and population trends of these unique Hawaiian honeycreepers are crucial for assessing the effectiveness of recovery and management actions. In 2016, we used point‐transect distance sampling to estimate the abundance of Hawai‘i ʻĀkepas in portions of Hawai‘i Volcanoes National Park (HAVO) and the Kaʻū Forest Reserve (KFR) on Mauna Loa volcano. We then compiled the survey data from four other populations to provide a global population estimate. In our HAVO and KFR study area, we mapped habitat classes to determine the population densities in each habitat. Densities were highest (1.03 birds/ha) in open‐canopy montane ʻōhiʻa (Metrosideros polymorpha) woodland. In contrast, densities of the largest ʻĀkepa population on Mauna Kea volcano were highest in closed‐canopy ʻōhiʻa and koa (Acacia koa) forest where the species is dependent on nest cavities in tall (> 15 m), large (> 50‐cm diameter at breast height) trees. We surveyed potential nesting habitat in HAVO and KFR and found only one cavity in the short‐stature montane ʻōhiʻa woodland and five cavities in the tall‐stature forest. Differences in densities between the Mauna Kea and Mauna Loa populations suggest that Hawai‘i ʻĀkepas may exhibit different foraging and nesting behaviors in the two habitats. The estimated overall population density in the HAVO and KFR study area was 0.52 birds/ha, which equates to 3663 (95% CI 1725–6961) birds in their 11,377‐ha population range. We calculated a global population of 16,428 (95% CI 10,065–25,198) birds, which is similar to an estimate of 13,892 (95% CI 10,315–17,469) birds made in 1986. Our results suggest that populations are stable to increasing in the two largest populations, but the three other populations are smaller (range = 77–1443 birds) and trends for those populations are unknown.
","language":"English","publisher":"Wiley","doi":"10.1111/jofo.12243","usgsCitation":"Judge, S.W., Camp, R.J., Hart, P.J., and Kichman, S.T., 2018, Population estimates of the Endangered Hawaiʻi ʻĀkepa (Loxops coccineus) in different habitats on windward Mauna Loa: Journal of Field Ornithology, v. 89, no. 1, p. 11-21, https://doi.org/10.1111/jofo.12243.","productDescription":"11 p.","startPage":"11","endPage":"21","ipdsId":"IP-094596","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":437983,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7S181SV","text":"USGS data release","linkHelpText":"HAVO Montane Ohia Diameter and Cavity Data 2017"},{"id":352647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Mauna Loa","volume":"89","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6fbe4b0da30c1bfc00e","contributors":{"authors":[{"text":"Judge, Seth W.","contributorId":8718,"corporation":false,"usgs":true,"family":"Judge","given":"Seth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":731375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":116175,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":false,"id":731376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hart, Patrick J.","contributorId":147728,"corporation":false,"usgs":false,"family":"Hart","given":"Patrick","email":"","middleInitial":"J.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":731377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kichman, Scott T.","contributorId":203396,"corporation":false,"usgs":false,"family":"Kichman","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":36609,"text":"NPS, Pacific Island Inventory and Monitoring Program","active":true,"usgs":false}],"preferred":false,"id":731378,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196104,"text":"70196104 - 2018 - Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using nitrogen isotopes","interactions":[],"lastModifiedDate":"2018-03-20T09:03:28","indexId":"70196104","displayToPublicDate":"2018-03-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using nitrogen isotopes","docAbstract":"Variation in source areas and source types of atmospheric nitrogen (N) deposition to high-elevation ecosystems in the Rocky Mountains were evaluated using spatially and temporally distributed N isotope data from atmospheric deposition networks for 1995-2016. This unique dataset links N in wet deposition and snowpack to mobile and stationary emissions sources, and enhances understanding of the impacts of anthropogenic activities and environmental policies that mitigate effects of accelerated N cycling across the Rocky Mountain region. δ15N−NO3− at 50 U.S. Geological Survey Rocky Mountain Snowpack (Snowpack) sites ranged from −3.3‰ to +6.5‰, with a mean value of +1.4‰. At 15 National Atmospheric Deposition Program (NADP)/National Trends Network wet deposition (NADP Wetfall) sites, summer δ15N−NO3− is significantly lower ranging from −7.6‰ to −1.3‰ while winter δ15N−NO3− ranges from −2.6‰ to +5.5‰, with a mean value of +0.7‰ during the cool season. The strong seasonal difference in NADP Wetfall δ15N−NO3− is due in part to variation in the proportion of N originating from source regions at different times of the year due to seasonal changes in weather patterns. Snowpack NO3− and δ15N−NO3− are significantly related to NADP Wetfall (fall and winter) suggesting that bulk snowpack samples provide a reliable estimate at high elevations. Spatial trends show higher NO3−concentrations and δ15N−NO3− in the Southern Rocky Mountains located near larger anthropogenic N emission sources compared to the Northern Rocky Mountains. NADP Wetfall δ15N−NH4+ ranged from −10‰ to 0‰, with no observed spatial pattern. However, the lowest δ15N−NH4+(−9‰), and the highest NH4+ concentration (35 μeq/L) were observed at a Utah site dominated by local agricultural activities, whereas the higher δ15N−NH4+observed in Colorado and Wyoming are likely due to mixed sources, including fossil fuel combustion and agricultural sources. These findings show spatial and seasonal variation in N isotope data that reflect differences in sources of anthropogenic N deposition to high-elevation ecosystems and have important implications for environmental policy across the Rocky Mountain region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2017.12.023","usgsCitation":"Nanus, L., Campbell, D.H., Lehmann, C.M., and Mast, M.A., 2018, Spatial and temporal variation in sources of atmospheric nitrogen deposition in the Rocky Mountains using nitrogen isotopes: Atmospheric Environment, v. 176, p. 110-119, https://doi.org/10.1016/j.atmosenv.2017.12.023.","productDescription":"10 p.","startPage":"110","endPage":"119","ipdsId":"IP-088572","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":468904,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2017.12.023","text":"Publisher Index Page"},{"id":352648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Rocky Mountains","volume":"176","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6fbe4b0da30c1bfc010","contributors":{"authors":[{"text":"Nanus, Leora","contributorId":27930,"corporation":false,"usgs":true,"family":"Nanus","given":"Leora","email":"","affiliations":[],"preferred":false,"id":731365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, Donald H. dhcampbe@usgs.gov","contributorId":1670,"corporation":false,"usgs":true,"family":"Campbell","given":"Donald","email":"dhcampbe@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":731366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehmann, Christopher M.B.","contributorId":84859,"corporation":false,"usgs":true,"family":"Lehmann","given":"Christopher","email":"","middleInitial":"M.B.","affiliations":[],"preferred":false,"id":731367,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731364,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196095,"text":"70196095 - 2018 - Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes","interactions":[],"lastModifiedDate":"2018-03-20T09:08:21","indexId":"70196095","displayToPublicDate":"2018-03-20T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3380,"text":"Sensors","active":true,"publicationSubtype":{"id":10}},"title":"Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes","docAbstract":"Assessing climate-related ecological changes across spatiotemporal scales meaningful to resource managers is challenging because no one method reliably produces essential data at both fine and broad scales. We recently confronted such challenges while integrating data from ground- and satellite-based sensors for an assessment of four wetland-rich study areas in the U.S. Midwest. We examined relations between temperature and precipitation and a set of variables measured on the ground at individual wetlands and another set measured via satellite sensors within surrounding 4 km2 landscape blocks. At the block scale, we used evapotranspiration and vegetation greenness as remotely sensed proxies for water availability and to estimate seasonal photosynthetic activity. We used sensors on the ground to coincidentally measure surface-water availability and amphibian calling activity at individual wetlands within blocks. Responses of landscape blocks generally paralleled changes in conditions measured on the ground, but the latter were more dynamic, and changes in ecological conditions on the ground that were critical for biota were not always apparent in measurements of related parameters in blocks. Here, we evaluate the effectiveness of decisions and assumptions we made in applying the remotely sensed data for the assessment and the value of integrating observations across scales, sensors, and disciplines.
","language":"English","publisher":"MDPI","doi":"10.3390/s18030880","usgsCitation":"Gallant, A.L., Sadinski, W.J., Brown, J.F., Senay, G., and Roth, M.F., 2018, Challenges in complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate – lessons from temperate wetland-upland landscapes: Sensors, v. 18, no. 3, p. 1-38, https://doi.org/10.3390/s18030880.","productDescription":"Article 880; 38 p.","startPage":"1","endPage":"38","ipdsId":"IP-094477","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468903,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/s18030880","text":"Publisher Index Page"},{"id":437982,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QF8S3H","text":"USGS data release","linkHelpText":"Data files supporting the paper titled "Complementing data from ground-based sensors with satellite-derived products to measure ecological changes in relation to climate lessons from temperate wetland-upland landscapes""},{"id":352650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-16","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc012","contributors":{"authors":[{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":731314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadinski, Walter J. wsadinski@usgs.gov","contributorId":3287,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walter","email":"wsadinski@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":731316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":731317,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, Mark F. 0000-0001-5095-1865 mroth@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-1865","contributorId":3286,"corporation":false,"usgs":true,"family":"Roth","given":"Mark","email":"mroth@usgs.gov","middleInitial":"F.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":731318,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70191483,"text":"sir20175088 - 2018 - Hydrologic assessment of the Edwin B. Forsythe National Wildlife Refuge","interactions":[],"lastModifiedDate":"2018-03-19T16:50:38","indexId":"sir20175088","displayToPublicDate":"2018-03-19T12:15:00","publicationYear":"2018","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":"2017-5088","title":"Hydrologic assessment of the Edwin B. Forsythe National Wildlife Refuge","docAbstract":"The Edwin B. Forsythe National Wildlife Refuge (hereafter Forsythe refuge or the refuge) is situated along the central New Jersey coast and provides a mixture of freshwater and saltwater habitats for numerous bird, wildlife, and plant species. Little data and information were previously available regarding the freshwater dynamics that support the refuge’s ecosystems. In cooperation with the U.S. Fish and Wildlife Service, the U.S. Geological Survey conducted an assessment of the hydrologic resources and processes in the refuge and surrounding areas to provide baseline information for evaluating restoration projects and future changes in the hydrologic system associated with climate change and other anthropogenic stressors.
During spring 2015, water levels were measured at groundwater and surface-water sites in and near the Forsythe refuge. These water-level measurements, along with surface-water elevations obtained from digital elevation models, were used to construct water-table-elevation and depth-to-water maps of the refuge and surrounding areas. Water-table elevations in the refuge ranged from sea level to approximately 65 feet above sea level; in most of the refuge, the water-table elevation was within 3 feet of sea level. The water-table-elevation map indicates that the direction of shallow groundwater flow at the regional scale is generally from west to east (much of it from the northwest to the southeast), and groundwater moves downgradient from the uplands toward major groundwater discharge areas consisting of coastal streams and wetlands. The depth to water is estimated to be less than 2 feet for approximately 86 percent of the refuge, which coincides closely with the percentage of wetland area in the refuge. Depth to water in excess of 20 feet below land surface is limited to higher elevation areas of the refuge.
Streamflow data collected at continuous-record streamgages and partial-record stations within the Mullica-Toms Basin were summarized. Hydrograph separation of streamflow data for eight streamgages (2004–13) reveals that base flow accounts for 68–94 percent of streamflow in basins upstream from the refuge. The high base-flow inputs underscore the importance of groundwater as a source of freshwater that supports both the streams that flow into the refuge and the hydroecology of the contributing basins. Mean annual flow typically ranged from 1.7 to 2.1 cubic feet per second per square mile at the streamgages (2004–13) and between 1.2 and 2.3 cubic feet per second per square mile at the partial-record stations (1965–2015) but was notably greater or lower than these ranges at several stations.
Mean annual water budgets were estimated for multiple regions of the refuge for 2004–13 using data compiled from nearby meteorological stations and groundwater flows derived from previously calibrated groundwater-flow models. Precipitation, groundwater recharge, and evapotranspiration were estimated from available data; direct runoff was calculated as the residual component of the water balance. Groundwater recharge rates were greatest in the upland-dominated areas of the refuge with estimates of 14.4 to 18.9 inches per year, which are equivalent to 30 to 40 percent of precipitation. Groundwater recharge rates were nearly zero in the central coastal areas because these areas are major groundwater discharge zones, the water table is near land surface, the subsurface is close to saturation and cannot accept much recharge, and much of the area is underlain by thick marsh deposits likely with low permeability. Estimates of evapotranspiration varied from about 26 inches per year in the upland-dominated areas to more than 35 inches per year in the coastal wetlands, equivalent to 55–79 percent of mean annual precipitation, indicating that it is a major component of the hydrodynamics of the Forsythe refuge.
On the basis of output from previously calibrated groundwater-flow models, nearly all of the groundwater exiting the surficial aquifer system in the central coastal areas of the refuge is discharged to wetlands, which highlights the importance of groundwater discharge in supporting the ecosystems of the Forsythe refuge. In the central coastal areas, horizontal flow contributes more than 90 percent of the groundwater flow to the surficial system, indicating that the upbasin areas are a substantial source of water that ultimately discharges to streams and wetlands in the refuge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175088","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Wieben, C.M., and Chepiga, M.M., 2018, Hydrologic assessment of the Edwin B. Forsythe National Wildlife Refuge, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017–5088, 38 p., https://doi.org/10.3133/sir20175088.\n","productDescription":"Report: viii, 38 p.; 2 Plates: 24.0 x 36.0 inches; Data release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079840","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":352411,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088.pdf","text":"Report","size":"25.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5088"},{"id":352410,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5088/coverthb.jpg"},{"id":352412,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78G8JMN","text":"USGS data release","description":"USGS data release","linkHelpText":"Water-table elevation contours and depth-to-water grid for the Edwin B. Forsythe National Wildlife Refuge, New Jersey, and vicinity, spring 2015"},{"id":352535,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088_plate02.pdf","text":"Plate 2","size":"4.15 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Water-Table Elevation in and near the Southern Part of the Edwin B. Forsythe National Wildlife Refuge, New Jersey, Spring 2015"},{"id":352426,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175135","text":"Scientific Investigations Report 2017–5135","linkHelpText":"- Hydrogeology of, Simulation of Groundwater Flow in, and Potential Effects of Sea-Level Rise on the Kirkwood-Cohansey Aquifer System in the Vicinity of Edwin B. Forsythe National Wildlife Refuge, New Jersey"},{"id":352534,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5088/sir20175088_plate01.pdf","text":"Plate 1 ","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Water-Table Elevation in and near the Northern Part of the Edwin B. Forsythe National Wildlife Refuge, New Jersey, Spring 2015"}],"country":"United States","state":"New Jersey","otherGeospatial":"Edwin B. Forsythe National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74,\n 39.4167\n ],\n [\n -74,\n 40.07807142745009\n ],\n [\n -74.5,\n 40.07807142745009\n ],\n [\n -74.5,\n 39.4167\n ],\n [\n -74,\n 39.4167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The Edwin B. Forsythe National Wildlife Refuge encompasses more than 47,000 acres of New Jersey coastal habitats, including salt marshes, freshwater wetlands, tidal wetlands, barrier beaches, woodlands, and swamps. The refuge is along the Atlantic Flyway and provides breeding habitat for fish, migratory birds, and other wildlife species. The refuge area may be threatened by global climate change, including sea-level rise (SLR).
The Kirkwood-Cohansey aquifer system underlies the Edwin B. Forsythe National Wildlife Refuge. Groundwater is an important source of freshwater flow into the refuge, but information about the interaction of surface water and groundwater in the refuge area and the potential effects of SLR on the underlying aquifer system is limited. The U.S. Geological Survey (USGS), in cooperation with the U.S. Fish and Wildlife Service (USFWS), conducted a hydrologic assessment of the refuge in New Jersey and developed a groundwater flow model to improve understanding of the geohydrology of the refuge area and to serve as a tool to evaluate changes in groundwater-level altitudes that may result from a rise in sea level.
Groundwater flow simulations completed for this study include a calibrated baseline simulation that represents 2005–15 hydraulic conditions and three SLR scenarios―20, 40, and 60 centimeters (cm) (0.656, 1.312, and 1.968 feet, respectively). Results of the three SLR simulations indicate that the water table in the unconfined Kirkwood-Cohansey aquifer system in the refuge area will rise, resulting in increased discharge of fresh groundwater to freshwater wetlands and streams. As sea level rises, simulated groundwater discharge to the salt marsh, bay, and ocean is projected to decrease. Flow from the salt marsh, bay, and ocean to the overlying surface water is projected to increase as sea level rises.
The simulated movement of the freshwater-seawater interface as sea level rises depends on the hydraulic-head gradient. In the center of the Forsythe model area, topographic relief is 23 feet (ft) and the hydraulic-head gradient is 0.0033. In the center of the Forsythe model area, the simulated interface moved inland about 600 ft and downward about 15 ft from the baseline simulation to scenario 3 as a result of a SLR of 60 cm. In the southern part of the Forsythe model area, the topography is flatter (relief of 8 ft) and the hydraulic-head gradient is smaller (0.001). In the southern part of the Forsythe model study area, the simulated interface in this area is projected to move inland about 200 ft from the baseline simulation to scenario 3 and does not move downward.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175135","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Fiore, A.R., Voronin, L.M., and Wieben, C.M., 2018, Hydrogeology of, simulation of groundwater flow in, and potential effects of sea-level rise on the Kirkwood-Cohansey aquifer system in the vicinity of Edwin B. Forsythe National Wildlife Refuge, New Jersey: U.S. Geological Survey Scientific Investigations Report 2017-5135, 59 p., https://doi.org/10.3133/sir20175135.","productDescription":"Report: vii, 59 p.; Data releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074587","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":352424,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76W98JB","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 model used to evaluate the potential effects of sea-level rise on the Kirkwood-Cohansey aquifer system in the vicinity of Edwin B. Forsythe National Wildlife Refuge, New Jersey"},{"id":352423,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JH3KBD","text":"USGS data release","description":"USGS data release","linkHelpText":"Raw ground-penetrating radar data, Edwin B. Forsythe National Wildlife Refuge, New Jersey, 2014–15"},{"id":352422,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5135/sir20175135.pdf","text":"Report","size":"16.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5135"},{"id":352421,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5135/coverthb.jpg"},{"id":352425,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175088","text":"Scientific Investigations Report 2017–5088","linkHelpText":"- Hydrologic Assessment of the Edwin B. Forsythe National Wildlife Refuge, New Jersey"}],"country":"United States","state":"New Jersey","otherGeospatial":"Edwin B. Forsythe National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.67,\n 39.33\n ],\n [\n -73.67,\n 39.33\n ],\n [\n -73.67,\n 40.09067983779908\n ],\n [\n -74.67,\n 40.09067983779908\n ],\n [\n -74.67,\n 39.33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne synthetic aperture radar (SAR) imagery (Ku-, X-, C-, and L-band) have been used previously to determine whether lakes have a BI or FI regime in a given year, across a number of years, or across large regions. In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 SAR imagery for seven lake-rich regions in Arctic Alaska to analyze lake ice regime extents and dynamics over a 25-year period (1992–2016). Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes—lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability. Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2018.02.022","usgsCitation":"Engram, M., Arp, C.D., Jones, B.M., Ajadi, O.A., and Meyer, F.J., 2018, Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery: Remote Sensing of Environment, v. 209, p. 660-676, https://doi.org/10.1016/j.rse.2018.02.022.","productDescription":"17 p.","startPage":"660","endPage":"676","ipdsId":"IP-090354","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":468905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2018.02.022","text":"Publisher Index Page"},{"id":408647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -159.5263144061035,\n 71.43267111072981\n ],\n [\n -159.5263144061035,\n 68.42639425141334\n ],\n [\n -146.22562492863324,\n 68.42639425141334\n ],\n [\n -146.22562492863324,\n 71.43267111072981\n ],\n [\n -159.5263144061035,\n 71.43267111072981\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163.58954484767287,\n 66.64438234906729\n ],\n [\n -166.61500668033133,\n 66.64438234906729\n ],\n [\n -166.61500668033133,\n 65.88496852258822\n ],\n [\n -163.58954484767287,\n 65.88496852258822\n ],\n [\n -163.58954484767287,\n 66.64438234906729\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"209","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Engram, Melanie","contributorId":191062,"corporation":false,"usgs":false,"family":"Engram","given":"Melanie","email":"","affiliations":[],"preferred":false,"id":855648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":855649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":855650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajadi, Olaniyi A","contributorId":298461,"corporation":false,"usgs":false,"family":"Ajadi","given":"Olaniyi","email":"","middleInitial":"A","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":855651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Franz J","contributorId":298463,"corporation":false,"usgs":false,"family":"Meyer","given":"Franz","email":"","middleInitial":"J","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":855652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70219033,"text":"70219033 - 2018 - Development of Raman spectroscopy as a thermal maturity proxy in unconventional resource assessment","interactions":[],"lastModifiedDate":"2021-03-19T12:45:16.582845","indexId":"70219033","displayToPublicDate":"2018-03-19T07:43:56","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Development of Raman spectroscopy as a thermal maturity proxy in unconventional resource assessment","docAbstract":"The objective of this study was to correlate shale hydrous pyrolysis with thermal maturity measurements based on solid bitumen reflectance (BRo) at the U.S. Geological Survey (USGS) and Raman microscopy (RM) at WellDog. In semi-blind Phase I, BRo values of the initial set of 8 samples were withheld prior to RM analysis. As reported previously, a strong correlation was observed between BRo and Raman parameters. For Phase-II, BRo values for the second set of 8 samples were shared before RM. Observations from Phase-II are reported here as well as the ability of RM to correctly order the semi-blind Phase I samples.\n\nImmature shale samples from the Bakken (Phase-I) and Duvernay (Phase-II) formations were subjected to hydrous pyrolysis for 72 hours at temperatures from 280°C to 360°C. Rock residues from both series were mounted and polished (ASTM D2797) for analysis of BRo (ASTM D7708) and confocal laser-scanning Raman microscopy. For RM, multiple hyperspectral maps were collected from each sample, resulting in tens of thousands of spectra per sample. Map areas were ~5,000 μm2, with a spectrum collected from every square micrometer. The organic carbon G- (Graphitic-) and D- (Disordered) bands in each Raman spectrum were fit algorithmically to a multi-peak model, yielding a number of diagnostic parameters that correlate with changes occurring in samples as a result of thermal maturation and pyrolysis.\n\nParameters extracted from analysis of Raman spectra were plotted against the previously determined BRo values to determine which Raman parameters best correlate with thermal maturity. Plotting two of the sample-averaged anonymized spectral parameters versus BRo in the Bakken series indicated an exponential trend with strong correlations (R2>0.8) as reported at URTeC in 2017 (MS-2671253). Similar strong relationships occurred in the Duvernay samples with respect to increasing maturity when using Partial Least-Squares analysis.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Unconventional Resources Technology Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"URTeC","doi":"10.15530/urtec-2018-2903536","usgsCitation":"Myers, G.A., Kehoe, K., and Hackley, P.C., 2018, Development of Raman spectroscopy as a thermal maturity proxy in unconventional resource assessment, in Proceedings of the Unconventional Resources Technology Conference, 12 p., https://doi.org/10.15530/urtec-2018-2903536.","productDescription":"12 p.","ipdsId":"IP-098028","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":384503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Myers, Grant A.","contributorId":255533,"corporation":false,"usgs":false,"family":"Myers","given":"Grant","email":"","middleInitial":"A.","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":812507,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kehoe, Kelsey","contributorId":255534,"corporation":false,"usgs":false,"family":"Kehoe","given":"Kelsey","email":"","affiliations":[{"id":51579,"text":"WellDog Gas Sensing Technology Corp.","active":true,"usgs":false}],"preferred":false,"id":812508,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":812509,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196092,"text":"70196092 - 2018 - Spatial organization of the gastrointestinal microbiota in urban Canada geese","interactions":[],"lastModifiedDate":"2018-03-19T10:28:54","indexId":"70196092","displayToPublicDate":"2018-03-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Spatial organization of the gastrointestinal microbiota in urban Canada geese","docAbstract":"Recent reviews identified the reliance on fecal or cloacal samples as a significant limitation hindering our understanding of the avian gastrointestinal (gut) microbiota and its function. We investigated the microbiota of the esophagus, duodenum, cecum, and colon of a wild urban population of Canada goose (Branta canadensis). From a population sample of 30 individuals, we sequenced the V4 region of the 16S SSU rRNA on an Illumina MiSeq and obtained 8,628,751 sequences with a median of 76,529 per sample. These sequences were assigned to 420 bacterial OTUs and a single archaeon. Firmicutes, Proteobacteria, and Bacteroidetes accounted for 90% of all sequences. Microbiotas from the four gut regions differed significantly in their richness, composition, and variability among individuals. Microbial communities of the esophagus were the most distinctive whereas those of the colon were the least distinctive, reflecting the physical downstream mixing of regional microbiotas. The downstream mixing of regional microbiotas was also responsible for the majority of observed co-occurrence patterns among microbial families. Our results indicate that fecal and cloacal samples inadequately represent the complex patterns of richness, composition, and variability of the gut microbiota and obscure patterns of co-occurrence of microbial lineages.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-018-21892-y","usgsCitation":"Drovetski, S., O’Mahoney, M., Ransome, E.J., Matterson, K., Lim, H.C., Chesser, T., and Graves, G.R., 2018, Spatial organization of the gastrointestinal microbiota in urban Canada geese: Scientific Reports, v. 8, p. 1-10, https://doi.org/10.1038/s41598-018-21892-y.","productDescription":"Article number 3713; 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-093486","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468906,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-21892-y","text":"Publisher Index Page"},{"id":352628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-27","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc01a","contributors":{"authors":[{"text":"Drovetski, Sergei V.","contributorId":203364,"corporation":false,"usgs":false,"family":"Drovetski","given":"Sergei V.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Mahoney, Michael","contributorId":203365,"corporation":false,"usgs":false,"family":"O’Mahoney","given":"Michael","email":"","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ransome, Emma J.","contributorId":203366,"corporation":false,"usgs":false,"family":"Ransome","given":"Emma","email":"","middleInitial":"J.","affiliations":[{"id":24608,"text":"Imperial College London","active":true,"usgs":false}],"preferred":false,"id":731301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Matterson, Kenan O.","contributorId":203367,"corporation":false,"usgs":false,"family":"Matterson","given":"Kenan O.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lim, Haw Chuan","contributorId":203368,"corporation":false,"usgs":false,"family":"Lim","given":"Haw","email":"","middleInitial":"Chuan","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731303,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chesser, Terry 0000-0003-4389-7092 tchesser@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":177781,"corporation":false,"usgs":true,"family":"Chesser","given":"Terry","email":"tchesser@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":731298,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Graves, Gary R.","contributorId":203369,"corporation":false,"usgs":false,"family":"Graves","given":"Gary","email":"","middleInitial":"R.","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":731304,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196105,"text":"ofr20171164 - 2018 - Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model","interactions":[],"lastModifiedDate":"2018-03-21T10:52:15","indexId":"ofr20171164","displayToPublicDate":"2018-03-19T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1164","displayTitle":"Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model","title":"Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model","docAbstract":"The giant gartersnake (Thamnophis gigas) is a state and federally threatened species precinctive to California. The range of the giant gartersnake has contracted in the last century because its wetland habitat has been drained for agriculture and development. As a result of this habitat alteration, giant gartersnakes now largely persist in and near rice agriculture in the Sacramento Valley, because the system of canals that conveys water for rice growing approximates historical wetland habitat. Many aspects of the demography of giant gartersnakes are unknown, including how individuals grow throughout their life, how size influences reproduction, and how survival varies over time and among populations. We studied giant gartersnakes throughout the Sacramento Valley of California from 1995 to 2016 using capture-mark-recapture to study the growth, reproduction, and survival of this threatened species. We then use these data to construct an Integral Projection Model, and analyze this demographic model to understand which vital rates contribute most to the growth rate of giant gartersnake populations. We find that giant gartersnakes exhibit indeterminate growth; growth slows as individuals’ age. Fecundity, probability of reproduction, and survival all increase with size, although survival may decline for the largest female giant gartersnakes. The population growth rate of giant gartersnakes is most influenced by the survival and growth of large adult females, and the size at which 1 year old recruits enter the population. Our results indicate that management actions benefitting these influential demographic parameters will have the greatest positive effect on giant gartersnake population growth rates, and therefore population persistence. This study informs the conservation and management of giant gartersnakes and their habitat, and illustrates the effectiveness of hierarchical Bayesian models for the study of rare and elusive species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171164","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Rose, J.P., Ersan, J.S.M., Wylie, G.D., Casazza, M.L., and Halstead, B.J., 2018, Construction and analysis of a giant gartersnake (Thamnophis gigas) population projection model: U.S. Geological Survey Open-File Report 2017–1164, 98 p., https://doi.org/10.3133/ofr20171164.","productDescription":"viii, 98 p.","numberOfPages":"110","onlineOnly":"Y","ipdsId":"IP-090465","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":352644,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1164/ofr20171164.pdf","text":"Report","size":"8.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1164"},{"id":352643,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1164/coverthb.jpg"}],"contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This report provides an overview of the pilot study and description of the techniques developed for a future mitigation study of Pomacea maculata (giant applesnail) at the U.S. Fish and Wildlife Service Mandalay National Wildlife Refuge, Louisiana (MNWR). Egg mass suppression is a potential strategy for the mitigation of the invasive giant applesnail. In previous studies at Langan Municipal Park in Mobile, Alabama (LMP), and National Park Service Jean Lafitte National Park-Barataria Unit, Louisiana (JLNP), we determined that spraying food-grade oil (coconut oil or Pam™ spray) on egg masses significantly reduced egg hatching. At JLNP we also developed methods to estimate snail population size. The purpose of this pilot study was to adapt techniques developed for previous studies to the circumstances of MNWR in preparation for a larger experiment whereby we will test the effectiveness of egg mass suppression as an applesnail mitigation tool. We selected four canals that will be used as treatment and control sites for the experiment (two each). We established that an efficient way to destroy egg masses is to knock them down with a high-velocity stream of water pumped directly from the canal. The traps used at JLNP had to be modified to accommodate the greater range of water-level fluctuation at MNWR. One of the three marking methods used at JLNP was selected for use at MNWR.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181041","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Barataria-Terrebonne National Estuary Program","usgsCitation":"Carter, Jacoby, and Merino, Sergio, 2018, Pilot testing and protocol development of giant applesnail suppression at Mandalay National Wildlife Refuge, Louisiana—July–October 2017: U.S. Geological Survey Open-File Report 2018-1041, 17 p., https://doi.org/10.3133/ofr20181041.","productDescription":"vi, 17 p.","numberOfPages":"17","onlineOnly":"Y","ipdsId":"IP-093234","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":352641,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1041/ofr20181041.pdf","text":"Report","size":"903 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1041"},{"id":352640,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1041/coverthb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mandalay National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.84182739257812,\n 29.486378867043253\n ],\n [\n -90.76766967773438,\n 29.486378867043253\n ],\n [\n -90.76766967773438,\n 29.559422089438876\n ],\n [\n -90.84182739257812,\n 29.559422089438876\n ],\n [\n -90.84182739257812,\n 29.486378867043253\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
700 Cajundome Blvd.
Lafayette, LA 70506
The magmatic degassing history of newly erupted volcanic glass is recorded in its remaining volatile content. However, this history is subsequently overprinted by post-depositional (secondary) hydration, the rates and origins of which are not yet adequately constrained. Here, we present the results of a natural experiment using products of the 1980 eruptions of Mount St. Helens. We measured water concentration, δDglass, and δ18OBSG (δ18O of the bulk silicate glass) of samples collected during the dry summer months of 1980 and compared them with material resampled in 2015 from the same deposits. Samples collected from the subsurface near gas escape pipes show elevated water concentrations (near 2.0 wt%), and these are associated with lower δDglass (− 110 to − 130‰) and δ18OBSG (6.0 to 6.6‰) values than the 1980 glass (− 70 to − 100‰ and 6.8 to 6.9‰, respectively). Samples collected in 2015 from the surface to 10-cm subsurface of the 1980 summer deposits have a small increase in average water contents of 0.1–0.2 wt% but similar δ18OBSG (6.8–6.9‰) values compared to the 1980 glass values. These samples, however, show 15‰ higher δDglass values; exchange with meteoric water is expected to yield lower δDglass values. We attribute higher δDglass values in the upper portion of the 1980 deposits collected in 2015 to rehydration by higher δD waters that were degassed for several months to a year from the hot underlying deposits, which hydrated the overlying deposits with relatively high δD gases. Our data also contribute to magmatic degassing of crystal-rich volcanoes. Using the 1980 samples, our reconstructed δD-H2O trends for the dacitic Mount St. Helens deposits with rhyolitic groundmass yield a trend that overlaps with the degassing trend for crystal-poor rhyolitic eruptions studied previously elsewhere, suggesting similar behavior of volatiles upon exsolution from magma. Furthermore, our data support previous studies proposing that exsolved volatiles were trapped within a rapidly rising magma and started degassing only at shallow depths during the 1980 eruptions.
We investigated the fate of Sb and As downstream of the abandoned Su Suergiu mine (Sardinia, Italy) and surrounding areas. The mined area is a priority in the Sardinian remediation plan for contaminated sites due to the high concentrations of Sb and As in the mining-related wastes, which may impact the Flumendosa River that supplies water for agriculture and domestic uses. Hydrogeochemical surveys conducted from 2005 to 2015 produced time-series data and downstream profiles of water chemistry at 46 sites. Water was sampled at: springs and streams unaffected by mining; adits and streams in the mine area; drainage from the slag heaps; stream water downstream of the slag drainages; and the Flumendosa River downstream from the confluence of the contaminated waters. At specific sites, water sampling was repeated under different flow conditions, resulting in a total of 99 samples. The water samples were neutral to slightly alkaline. Elevated Sb (up to 30 mg L−1) and As (up to 16 mg L−1) concentrations were observed in water flowing from the slag materials from where the Sb ore was processed. These slag materials were the main Sb and As source at Su Suergiu. A strong base, Na-carbonate, from the foundry wastes, had a major influence on mobilizing Sb and As. Downstream contamination can be explained by considering that: (1) the predominant aqueous species, Sb(OH)6 − and HAsO4 −2, are not favored in sorption processes at the observed pH conditions; (2) precipitation of Sb- and As-bearing solid phases was not observed, which is consistent with modeling results indicating undersaturation; and (3) the main decrease in dissolved Sb and As concentrations was by dilution. Dissolved As concentrations in the Flumendosa River did not generally exceed the EU limit of 10 µg L−1, whereas dissolved Sb in the river downstream of the contamination source always exceeded the EU limit of 5 µg L−1. Recent actions aimed at retaining runoff from the slag heaps are apparently not sufficiently mitigating contamination in the Flumendosa River.
","language":"English","publisher":"Springer","doi":"10.1007/s10230-017-0479-8","usgsCitation":"Cidu, R., Dore, E., Biddau, R., and Nordstrom, D.K., 2018, Fate of antimony and arsenic in contaminated waters at the abandoned Su Suergiu mine (Sardinia, Italy): Mine Water and the Environment, v. 37, no. 1, p. 151-165, https://doi.org/10.1007/s10230-017-0479-8.","productDescription":"15 p.","startPage":"151","endPage":"165","ipdsId":"IP-071489","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":352624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","state":"Sardinia","otherGeospatial":"Su Suergiu mine","volume":"37","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-31","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc020","contributors":{"authors":[{"text":"Cidu, Rosa","contributorId":194017,"corporation":false,"usgs":false,"family":"Cidu","given":"Rosa","affiliations":[{"id":36605,"text":"University of Cagliari, Cagliari, Sardinia","active":true,"usgs":false}],"preferred":false,"id":731269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dore, Elisabetta","contributorId":203363,"corporation":false,"usgs":false,"family":"Dore","given":"Elisabetta","email":"","affiliations":[{"id":36605,"text":"University of Cagliari, Cagliari, Sardinia","active":true,"usgs":false}],"preferred":false,"id":731271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biddau, Riccardo","contributorId":203362,"corporation":false,"usgs":false,"family":"Biddau","given":"Riccardo","email":"","affiliations":[{"id":36605,"text":"University of Cagliari, Cagliari, Sardinia","active":true,"usgs":false}],"preferred":false,"id":731270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":731268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196088,"text":"70196088 - 2018 - Bioremediation in fractured rock: 1. Modeling to inform design, monitoring, and expectations","interactions":[],"lastModifiedDate":"2018-03-17T17:45:14","indexId":"70196088","displayToPublicDate":"2018-03-17T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Bioremediation in fractured rock: 1. Modeling to inform design, monitoring, and expectations","docAbstract":"Field characterization of a trichloroethene (TCE) source area in fractured mudstones produced a detailed understanding of the geology, contaminant distribution in fractures and the rock matrix, and hydraulic and transport properties. Groundwater flow and chemical transport modeling that synthesized the field characterization information proved critical for designing bioremediation of the source area. The planned bioremediation involved injecting emulsified vegetable oil and bacteria to enhance the naturally occurring biodegradation of TCE. The flow and transport modeling showed that injection will spread amendments widely over a zone of lower‐permeability fractures, with long residence times expected because of small velocities after injection and sorption of emulsified vegetable oil onto solids. Amendments transported out of this zone will be diluted by groundwater flux from other areas, limiting bioremediation effectiveness downgradient. At nearby pumping wells, further dilution is expected to make bioremediation effects undetectable in the pumped water. The results emphasize that in fracture‐dominated flow regimes, the extent of injected amendments cannot be conceptualized using simple homogeneous models of groundwater flow commonly adopted to design injections in unconsolidated porous media (e.g., radial diverging or dipole flow regimes). Instead, it is important to synthesize site characterization information using a groundwater flow model that includes discrete features representing high‐ and low‐permeability fractures. This type of model accounts for the highly heterogeneous hydraulic conductivity and groundwater fluxes in fractured‐rock aquifers, and facilitates designing injection strategies that target specific volumes of the aquifer and maximize the distribution of amendments over these volumes.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12585","usgsCitation":"Tiedeman, C.R., Shapiro, A.M., Hsieh, P.A., Imbrigiotta, T.E., Goode, D.J., Lacombe, P., DeFlaun, M.F., Drew, S.R., Johnson, C.D., Williams, J., and Curtis, G.P., 2018, Bioremediation in fractured rock: 1. Modeling to inform design, monitoring, and expectations: Groundwater, v. 56, no. 2, p. 300-316, https://doi.org/10.1111/gwat.12585.","productDescription":"17 p.","startPage":"300","endPage":"316","ipdsId":"IP-088879","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-05","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc01e","contributors":{"authors":[{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":731272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shapiro, Allen M. 0000-0002-6425-9607 ashapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-6425-9607","contributorId":2164,"corporation":false,"usgs":true,"family":"Shapiro","given":"Allen","email":"ashapiro@usgs.gov","middleInitial":"M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":731273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hsieh, Paul A. 0000-0003-4873-4874 pahsieh@usgs.gov","orcid":"https://orcid.org/0000-0003-4873-4874","contributorId":1634,"corporation":false,"usgs":true,"family":"Hsieh","given":"Paul","email":"pahsieh@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":39113,"text":"WMA - Office of Quality Assurance","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":731274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Imbrigiotta, Thomas E. 0000-0003-1716-4768 timbrig@usgs.gov","orcid":"https://orcid.org/0000-0003-1716-4768","contributorId":152114,"corporation":false,"usgs":true,"family":"Imbrigiotta","given":"Thomas","email":"timbrig@usgs.gov","middleInitial":"E.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":193394,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel","email":"djgoode@usgs.gov","middleInitial":"J.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":731276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lacombe, Pierre 0000-0002-9596-7622 placombe@usgs.gov","orcid":"https://orcid.org/0000-0002-9596-7622","contributorId":152113,"corporation":false,"usgs":true,"family":"Lacombe","given":"Pierre","email":"placombe@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731277,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeFlaun, Mary F.","contributorId":203177,"corporation":false,"usgs":false,"family":"DeFlaun","given":"Mary","email":"","middleInitial":"F.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":731278,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Drew, Scott R.","contributorId":203178,"corporation":false,"usgs":false,"family":"Drew","given":"Scott","email":"","middleInitial":"R.","affiliations":[{"id":36571,"text":"Geosyntec Consultants","active":true,"usgs":false}],"preferred":false,"id":731279,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":731280,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Williams, John 0000-0002-6054-6908 jhwillia@usgs.gov","orcid":"https://orcid.org/0000-0002-6054-6908","contributorId":1553,"corporation":false,"usgs":true,"family":"Williams","given":"John","email":"jhwillia@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731281,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Curtis, Gary P. 0000-0003-3975-8882 gpcurtis@usgs.gov","orcid":"https://orcid.org/0000-0003-3975-8882","contributorId":2346,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","middleInitial":"P.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":731282,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70196083,"text":"70196083 - 2018 - Calibration of a field-scale Soil and Water Assessment Tool (SWAT) model with field placement of best management practices in Alger Creek, Michigan","interactions":[],"lastModifiedDate":"2018-03-26T13:40:10","indexId":"70196083","displayToPublicDate":"2018-03-16T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Calibration of a field-scale Soil and Water Assessment Tool (SWAT) model with field placement of best management practices in Alger Creek, Michigan","docAbstract":"Subwatersheds within the Great Lakes “Priority Watersheds” were targeted by the Great Lakes Restoration Initiative (GLRI) to determine the effectiveness of the various best management practices (BMPs) from the U.S. Department of Agriculture-Natural Resources Conservation Service National Conservation Planning (NCP) Database. A Soil and Water Assessment Tool (SWAT) model is created for Alger Creek, a 50 km2 tributary watershed to the Saginaw River in Michigan. Monthly calibration yielded very good Nash–Sutcliffe efficiency (NSE) ratings for flow, sediment, total phosphorus (TP), dissolved reactive phosphorus (DRP), and total nitrogen (TN) (0.90, 0.79, 0.87, 0.88, and 0.77, respectively), and satisfactory NSE rating for nitrate (0.51). Two-year validation results in at least satisfactory NSE ratings for flow, sediment, TP, DRP, and TN (0.83, 0.54, 0.73, 0.53, and 0.60, respectively), and unsatisfactory NSE rating for nitrate (0.28). The model estimates the effect of BMPs at the field and watershed scales. At the field-scale, the most effective single practice at reducing sediment, TP, and DRP is no-tillage followed by cover crops (CC); CC are the most effective single practice at reducing nitrate. The most effective BMP combinations include filter strips, which can have a sizable effect on reducing sediment and phosphorus loads. At the watershed scale, model results indicate current NCP BMPs result in minimal sediment and nutrient reductions (<10%).
","language":"English","publisher":"MDPI","doi":"10.3390/su10030851","usgsCitation":"Merriman, K.R., Russell, A.M., Rachol, C.M., Daggupati, P., Srinivasan, R., Hayhurst, B.A., and Stuntebeck, T.D., 2018, Calibration of a field-scale Soil and Water Assessment Tool (SWAT) model with field placement of best management practices in Alger Creek, Michigan: Sustainability, v. 10, no. 3, p. 1-23, https://doi.org/10.3390/su10030851.","productDescription":"Article 851; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-092133","costCenters":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":468908,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su10030851","text":"Publisher Index Page"},{"id":352617,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Alger Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.9167,\n 42.8333\n ],\n [\n -83.75,\n 42.8333\n ],\n [\n -83.75,\n 42.95\n ],\n [\n -83.9167,\n 42.95\n ],\n [\n -83.9167,\n 42.8333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-16","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc022","contributors":{"authors":[{"text":"Merriman, Katherine R. 0000-0002-1303-2410","orcid":"https://orcid.org/0000-0002-1303-2410","contributorId":203352,"corporation":false,"usgs":true,"family":"Merriman","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Amy M. 0000-0003-0582-0094 arussell@usgs.gov","orcid":"https://orcid.org/0000-0003-0582-0094","contributorId":200011,"corporation":false,"usgs":true,"family":"Russell","given":"Amy","email":"arussell@usgs.gov","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731244,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rachol, Cynthia M. 0000-0001-9984-3435","orcid":"https://orcid.org/0000-0001-9984-3435","contributorId":203353,"corporation":false,"usgs":true,"family":"Rachol","given":"Cynthia","email":"","middleInitial":"M.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daggupati, Prasad 0000-0002-7044-3435","orcid":"https://orcid.org/0000-0002-7044-3435","contributorId":189193,"corporation":false,"usgs":false,"family":"Daggupati","given":"Prasad","email":"","affiliations":[],"preferred":false,"id":731247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Srinivasan, Raghavan","contributorId":189191,"corporation":false,"usgs":false,"family":"Srinivasan","given":"Raghavan","affiliations":[],"preferred":false,"id":731248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hayhurst, Brett A. 0000-0002-1717-2015 bhayhurs@usgs.gov","orcid":"https://orcid.org/0000-0002-1717-2015","contributorId":3398,"corporation":false,"usgs":true,"family":"Hayhurst","given":"Brett","email":"bhayhurs@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731245,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731249,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196077,"text":"70196077 - 2018 - Prey fish returned to Forster’s tern colonies suggest spatial and temporal differences in fish composition and availability","interactions":[],"lastModifiedDate":"2018-03-16T15:20:12","indexId":"70196077","displayToPublicDate":"2018-03-16T00:00:00","publicationYear":"2018","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":"Prey fish returned to Forster’s tern colonies suggest spatial and temporal differences in fish composition and availability","docAbstract":"Predators sample the available prey community when foraging; thus, changes in the environment may be reflected by changes in predator diet and foraging preferences. We examined Forster’s tern (Sterna forsteri) prey species over an 11-year period by sampling approximately 10,000 prey fish returned to 17 breeding colonies in south San Francisco Bay, California. We compared the species composition among repeatedly-sampled colonies (≥ 4 years), using both relative species abundance and the composition of total dry mass by species. Overall, the relative abundances of prey species at seven repeatedly-sampled tern colonies were more different than would be expected by chance, with the most notable differences in relative abundance observed between geographically distant colonies. In general, Mississippi silverside (Menidia audens) and topsmelt silverside (Atherinops affinis) comprised 42% of individuals and 40% of dry fish mass over the study period. Three-spined stickleback (Gasterosteus aculeatus) comprised the next largest proportion of prey species by individuals (19%) but not by dry mass (6%). Five additional species each contributed ≥ 4% of total individuals collected over the study period: yellowfin goby (Acanthogobius flavimanus; 10%), longjaw mudsucker (Gillichthys mirabilis; 8%), Pacific herring (Clupea pallasii; 6%), northern anchovy (Engraulis mordax; 4%), and staghorn sculpin (Leptocottus armatus; 4%). At some colonies, the relative abundance and biomass of specific prey species changed over time. In general, the abundance and dry mass of silversides increased, whereas the abundance and dry mass of three-spined stickleback and longjaw mudsucker decreased. As central place foragers, Forster’s terns are limited in the distance they forage; thus, changes in the prey species returned to Forster’s tern colonies suggest that the relative availability of some fish species in the environment has changed, possibly in response to alteration of the available habitat.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0193430","usgsCitation":"Peterson, S.H., Ackerman, J., Eagles-Smith, C.A., Herzog, M.P., and Hartman, C.A., 2018, Prey fish returned to Forster’s tern colonies suggest spatial and temporal differences in fish composition and availability: PLoS ONE, v. 13, no. 3, p. 1-23, https://doi.org/10.1371/journal.pone.0193430.","productDescription":"e0193430; 23 p.","startPage":"1","endPage":"23","ipdsId":"IP-090278","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":468907,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0193430","text":"Publisher Index Page"},{"id":437985,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PG1QXT","text":"USGS data release","linkHelpText":"Prey fish returned to Forsters tern colonies in South San Francisco Bay during 2005-2015"},{"id":352619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.2,\n 37.4\n ],\n [\n -121.9,\n 37.4\n ],\n [\n -121.9,\n 37.6\n ],\n [\n -122.2,\n 37.6\n ],\n [\n -122.2,\n 37.4\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6fce4b0da30c1bfc024","contributors":{"authors":[{"text":"Peterson, Sarah H. 0000-0003-2773-3901 sepeterson@usgs.gov","orcid":"https://orcid.org/0000-0003-2773-3901","contributorId":167181,"corporation":false,"usgs":true,"family":"Peterson","given":"Sarah","email":"sepeterson@usgs.gov","middleInitial":"H.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":731222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":731224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":731225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, C. Alex 0000-0002-7222-1633 chartman@usgs.gov","orcid":"https://orcid.org/0000-0002-7222-1633","contributorId":131109,"corporation":false,"usgs":true,"family":"Hartman","given":"C.","email":"chartman@usgs.gov","middleInitial":"Alex","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":731226,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70249425,"text":"70249425 - 2018 - Attribution analysis of the Ethiopian drought of 2015","interactions":[],"lastModifiedDate":"2023-10-06T14:09:55.757687","indexId":"70249425","displayToPublicDate":"2018-03-15T09:01:08","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"Attribution analysis of the Ethiopian drought of 2015","docAbstract":"In northern and central Ethiopia, 2015 was a very dry year. Rainfall was only from one-half to three-quarters of the usual amount, with both the “belg” (February–May) and “kiremt” rains (June–September) affected. The timing of the rains that did fall was also erratic. Many crops failed, causing food shortages for many millions of people. The role of climate change in the probability of a drought like this is investigated, focusing on the large-scale precipitation deficit in February–September 2015 in northern and central Ethiopia. Using a gridded analysis that combines station data with satellite observations, it is estimated that the return period of this drought was more than 60 years (lower bound 95% confidence interval), with a most likely value of several hundred years. No trend is detected in the observations, but the large natural variability and short time series means large trends could go undetected in the observations. Two out of three large climate model ensembles that simulated rainfall reasonably well show no trend while the third shows an increased probability of drought. Taking the model spread into account the drought still cannot be clearly attributed to anthropogenic climate change, with the 95% confidence interval ranging from a probability decrease between preindustrial and today of a factor of 0.3 and an increase of a factor of 5 for a drought like this one or worse. A soil moisture dataset also shows a nonsignificant drying trend. According to ENSO correlations in the observations, the strong 2015 El Niño did increase the severity of the drought.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JCLI-D-17-0274.1","usgsCitation":"Philip, S., Kew, S.F., van Oldenborgh, G.J., Otto, F., O’Keefe, S., Haustein, K., King, A.L., Zegeye, A., Eshetu, Z., Hailemariam, K., Singh, R., Jjemba, E., Funk, C., and Cullen, H., 2018, Attribution analysis of the Ethiopian drought of 2015: Journal of Climate, v. 31, no. 6, p. 2465-2486, https://doi.org/10.1175/JCLI-D-17-0274.1.","productDescription":"22 p.","startPage":"2465","endPage":"2486","ipdsId":"IP-091117","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":468909,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://ora.ox.ac.uk/objects/uuid:f057b9f9-2a54-4a67-9c5f-492b38cdb84d","text":"External 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F.","contributorId":330669,"corporation":false,"usgs":false,"family":"Kew","given":"Sarah","email":"","middleInitial":"F.","affiliations":[{"id":16158,"text":"Royal Netherlands Meteorological Institute","active":true,"usgs":false}],"preferred":false,"id":885562,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Oldenborgh, Geert Jan","contributorId":330670,"corporation":false,"usgs":false,"family":"van Oldenborgh","given":"Geert","email":"","middleInitial":"Jan","affiliations":[{"id":16158,"text":"Royal Netherlands Meteorological Institute","active":true,"usgs":false}],"preferred":false,"id":885563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Otto, Friederike","contributorId":330671,"corporation":false,"usgs":false,"family":"Otto","given":"Friederike","email":"","affiliations":[{"id":78958,"text":"Environmental Change 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Research","active":true,"usgs":false}],"preferred":false,"id":885567,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zegeye, Abiy","contributorId":330674,"corporation":false,"usgs":false,"family":"Zegeye","given":"Abiy","email":"","affiliations":[{"id":78960,"text":"Addis Ababa University, Addis Ababa, Ethiopia","active":true,"usgs":false}],"preferred":false,"id":885568,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Eshetu, Zewdu","contributorId":330675,"corporation":false,"usgs":false,"family":"Eshetu","given":"Zewdu","affiliations":[{"id":78960,"text":"Addis Ababa University, Addis Ababa, Ethiopia","active":true,"usgs":false}],"preferred":false,"id":885569,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hailemariam, Kinfe","contributorId":330676,"corporation":false,"usgs":false,"family":"Hailemariam","given":"Kinfe","email":"","affiliations":[{"id":78961,"text":"National Meteorology Agency, Addis Ababa, Ethiopia","active":true,"usgs":false}],"preferred":false,"id":885570,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Singh, Roop","contributorId":330677,"corporation":false,"usgs":false,"family":"Singh","given":"Roop","email":"","affiliations":[{"id":78962,"text":"Red Cross Red Crescent Climate Centre","active":true,"usgs":false}],"preferred":false,"id":885571,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jjemba, Eddie","contributorId":330678,"corporation":false,"usgs":false,"family":"Jjemba","given":"Eddie","email":"","affiliations":[{"id":78962,"text":"Red Cross Red Crescent Climate Centre","active":true,"usgs":false}],"preferred":false,"id":885572,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Funk, Chris 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":167070,"corporation":false,"usgs":true,"family":"Funk","given":"Chris","email":"cfunk@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":885573,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cullen, Heidi","contributorId":330679,"corporation":false,"usgs":false,"family":"Cullen","given":"Heidi","email":"","affiliations":[{"id":78963,"text":"Climate Central, Princeton, US","active":true,"usgs":false}],"preferred":false,"id":885574,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70216327,"text":"70216327 - 2018 - Capture versus capture zones: Clarifying terminology related to sources of water to wells","interactions":[],"lastModifiedDate":"2020-11-12T13:24:30.056454","indexId":"70216327","displayToPublicDate":"2018-03-15T07:19:15","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Capture versus capture zones: Clarifying terminology related to sources of water to wells","docAbstract":"The term capture, related to the source of water derived from wells, has been used in two distinct yet related contexts by the hydrologic community. The first is a water‐budget context, in which capture refers to decreases in the rates of groundwater outflow and (or) increases in the rates of recharge along head‐dependent boundaries of an aquifer in response to pumping. The second is a transport context, in which capture zone refers to the specific flowpaths that define the three‐dimensional, volumetric portion of a groundwater flow field that discharges to a well. A closely related issue that has become associated with the source of water to wells is streamflow depletion, which refers to the reduction in streamflow caused by pumping, and is a type of capture. Rates of capture and streamflow depletion are calculated by use of water‐budget analyses, most often with groundwater‐flow models. Transport models, particularly particle‐tracking methods, are used to determine capture zones to wells. In general, however, transport methods are not useful for quantifying actual or potential streamflow depletion or other types of capture along aquifer boundaries. To clarify the sometimes subtle differences among these terms, we describe the processes and relations among capture, capture zones, and streamflow depletion, and provide proposed terminology to distinguish among them.
Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine surface water dynamics. We used Landsat imagery to characterize variability in surface water extent across 11 Landsat path/rows representing the PPR and NP (images spanned 1985–2015). The PPR not only experienced a 2.6-fold greater surface water extent under median conditions relative to the NP, but also showed a 3.4-fold greater change in surface water extent between drought and deluge conditions. The relationship between surface water extent and accumulated water availability (precipitation minus potential evapotranspiration) was quantified per watershed and statistically related to variables representing hydrology-related landscape characteristics (e.g., infiltration capacity, surface storage capacity, stream density). To investigate the influence stream connectivity has on the rate at which surface water leaves a given location, we modeled stream-connected and stream-disconnected surface water separately. Stream-connected surface water showed a greater expansion with wetter climatic conditions in landscapes with greater total wetland area, but lower total wetland density. Disconnected surface water showed a greater expansion with wetter climatic conditions in landscapes with higher wetland density, lower infiltration and less anthropogenic drainage. From these findings, we can expect that shifts in precipitation and evaporative demand will have uneven effects on surface water quantity. Accurate predictions regarding the effect of climate change on surface water quantity will require consideration of hydrology-related landscape characteristics including wetland storage and arrangement.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-1851-2018","usgsCitation":"Vanderhoof, M.K., Lane, C., McManus, M.L., Alexander, L.C., and Christensen, J.R., 2018, Wetlands inform how climate extremes influence surface water expansion and contraction: Hydrology and Earth System Sciences, v. 22, p. 1851-1873, https://doi.org/10.5194/hess-22-1851-2018.","productDescription":"23 p.","startPage":"1851","endPage":"1873","ipdsId":"IP-090618","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468912,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-1851-2018","text":"Publisher Index Page"},{"id":352699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Prairie Pothole Regino","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109,\n 39.198205348894795\n ],\n [\n -91.0986328125,\n 39.198205348894795\n ],\n [\n -91.0986328125,\n 48.980216985374994\n ],\n [\n -109,\n 48.980216985374994\n ],\n [\n -109,\n 39.198205348894795\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-15","publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc026","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":731498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":731499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McManus, Michael L.","contributorId":189612,"corporation":false,"usgs":false,"family":"McManus","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":731500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander, Laurie C.","contributorId":196285,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":731501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Jay R.","contributorId":179361,"corporation":false,"usgs":false,"family":"Christensen","given":"Jay","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":731502,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70195496,"text":"sir20185027 - 2018 - Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development","interactions":[],"lastModifiedDate":"2018-09-25T06:18:31","indexId":"sir20185027","displayToPublicDate":"2018-03-15T00:00:00","publicationYear":"2018","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":"2018-5027","title":"Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development","docAbstract":"As the demand for energy increases in the United States, so does the demand for water used to produce many forms of that energy. Technological advances, limited access to conventional oil and gas accumulations, and the rise of oil and gas prices resulted in increased development of unconventional oil and gas (UOG) accumulations. Unconventional oil and gas is developed using a method that combines directional drilling and hydraulic fracturing techniques, allowing for greater oil and gas production from previously unrecoverable reservoirs. Quantification of the water resources required for UOG development and production is difficult because of disparate data sources, variable reporting requirements across boundaries (local, State, and national), and incomplete or proprietary datasets.
A topical study was started in 2015 under the U.S. Geological Survey’s Water Availability and Use Science Program, as part of the directive in the Secure Water Act for the U.S. Geological Survey to conduct a National Water Census, to better understand the relation between production of UOG resources for energy and the amount of water needed to produce and sustain this type of energy development in the United States. The Water Availability and Use Science Program goal for this topical study is to develop and apply a statistical model to better estimate the water use associated with UOG development, regardless of the location and target geologic formation. As a first step, a conceptual model has been developed to characterize the life cycle of water use in areas of UOG development.
Categories of water use and the way water-use data are collected might change over time; therefore, a generic approach was used in developing the conceptual model to allow for greater flexibility in adapting to future changes or newly available data. UOG development can be summarized into four stages: predrilling construction, drilling, hydraulic fracturing, and ongoing production. The water used in UOG production can be categorized further as direct, indirect, or ancillary water use. Direct water use is defined as the water used for drilling and hydraulic fracturing a well and for maintaining the well during ongoing production. Indirect water use is defined as the water used at or near a well pad. The water used for dust abatement also is considered an indirect use but may be applied away from the well pad. Ancillary water use is defined as the additional local or regional water use resulting from a change (for example, population) directly related to UOG development throughout the life cycle that is not used directly in the well or indirectly for any other purpose at the well pad.
The conceptual model presented in this report consists of five elements: (1) input data, (2) processes, (3) decisions, (4) output data, and (5) outcomes. The input data requirements for estimating water use associated with UOG development are somewhat onerous, and obtaining suitable datasets can be challenging because local, State, and Federal agencies do not collect data similarly. The quality of a water-use assessment that uses the conceptual model presented in this report is dependent on the quality and quantity of data that are available for a UOG play. The conceptual model can be used for an assessment with sparse data; however, having sparse data likely will result in greater uncertainty in the water-use estimates.
The conceptual model presented in this report is designed to be robust to characterize and simulate the data processing to estimate water use associated with UOG development. Although the results of an analysis that includes missing data have greater uncertainty, the analysis still can be insightful because it can establish a baseline estimate of UOG water use that may be refined further as more data become available. Analysis of models that include missing data also could aid in identifying the data most needed for future water-use estimates. Characterizing individual model limitations is important because the conceptual model can be used in future water-use studies to facilitate data compiling, data processing, estimating, and assessing UOG activities regardless of location.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185027","collaboration":"U.S. Geological Survey Water Availability and Use Science Program","usgsCitation":"Valder, J.F., McShane, R.R., Barnhart, T.B., Sando, R., Carter, J.M., and Lundgren, R.F., 2018, Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development: U.S. Geological Survey Scientific Investigations Report 2018–5027, 22 p., https://doi.org/10.3133/sir20185027.","productDescription":"v, 22 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-092881","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":352571,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5027/coverthb2.jpg"},{"id":352572,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5027/sir20185027.pdf","text":"Report","size":"3.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5027"},{"id":352573,"rank":3,"type":{"id":18,"text":"Project Site"},"url":"https://water.usgs.gov/wausp/","text":"Water Availability and Use Science Program"}],"contact":"Director, Dakota Water Science Center, South Dakota Office
U.S. Geological Survey
1608 Mountain View Road
Rapid City, SD 57702
Aim
Conservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.
Location
Conterminous U.S.A.
Time period
1977–2014.
Major taxa studied
Passerine birds.
Methods
We estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.
Results
Species distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.
Main conclusions
Models failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and frameworks continue to be refined, performance assessments and validation efforts should focus on the measures of risk and vulnerability useful for decision-making.
","language":"English","publisher":"Wiley","doi":"10.1111/geb.12726","usgsCitation":"Sofaer, H., Jarnevich, C.S., and Flather, C.H., 2018, Misleading prioritizations from modelling range shifts under climate change: Global Ecology and Biogeography, v. 27, no. 6, p. 658-666, https://doi.org/10.1111/geb.12726.","productDescription":"9 p.","startPage":"658","endPage":"666","ipdsId":"IP-085159","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":468913,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/geb.12726","text":"Publisher Index Page"},{"id":437986,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0S4R","text":"USGS data release","linkHelpText":"Breeding Bird Survey songbird occurrences during 1977-1979 and 2012-2014 in conterminous 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\"}}]}\n\n\n","volume":"27","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-09","publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc02a","contributors":{"authors":[{"text":"Sofaer, Helen 0000-0002-9450-5223 hsofaer@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-5223","contributorId":169118,"corporation":false,"usgs":true,"family":"Sofaer","given":"Helen","email":"hsofaer@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":false,"id":731163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":731164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flather, Curtis H.","contributorId":177590,"corporation":false,"usgs":false,"family":"Flather","given":"Curtis","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":731165,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196066,"text":"70196066 - 2018 - Stress concentrations at structural discontinuities in active fault zones in the western United States: Implications for permeability and fluid flow in geothermal fields","interactions":[],"lastModifiedDate":"2018-07-03T11:32:17","indexId":"70196066","displayToPublicDate":"2018-03-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Stress concentrations at structural discontinuities in active fault zones in the western United States: Implications for permeability and fluid flow in geothermal fields","docAbstract":"Slip can induce concentration of stresses at discontinuities along fault systems. These structural discontinuities, i.e., fault terminations, fault step-overs, intersections, bends, and other fault interaction areas, are known to host fluid flow in ore deposition systems, oil and gas reservoirs, and geothermal systems. We modeled stress transfer associated with slip on faults with Holocene-to-historic slip histories at the Salt Wells and Bradys geothermal systems in western Nevada, United States. Results show discrete locations of stress perturbation within discontinuities along these fault systems. Well field data, surface geothermal manifestations, and subsurface temperature data, each a proxy for modern fluid circulation in the fields, indicate that geothermal fluid flow is focused in these same areas where stresses are most highly perturbed. These results suggest that submeter- to meter-scale slip on these fault systems generates stress perturbations that are sufficiently large to promote slip on an array of secondary structures spanning the footprint of the modern geothermal activity. Slip on these secondary faults and fractures generates permeability through kinematic deformation and allows for transmission of fluids. Still, mineralization is expected to seal permeability along faults and fractures over time scales that are generally shorter than either earthquake recurrence intervals or the estimated life span of geothermal fields. This suggests that though stress perturbations resulting from fault slip are broadly important for defining the location and spatial extent of enhanced permeability at structural discontinuities, continual generation and maintenance of flow conduits throughout these areas are probably dependent on the deformation mechanism(s) affecting individual structures.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31729.1","usgsCitation":"Siler, D.L., Hinz, N., and Faulds, J., 2018, Stress concentrations at structural discontinuities in active fault zones in the western United States: Implications for permeability and fluid flow in geothermal fields: GSA Bulletin, v. 130, no. 7-8, p. 1273-1288, https://doi.org/10.1130/B31729.1.","productDescription":"16 p.","startPage":"1273","endPage":"1288","ipdsId":"IP-080783","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":352584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"7-8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-05","publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc028","contributors":{"authors":[{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":731188,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hinz, Nicholas H.","contributorId":184260,"corporation":false,"usgs":false,"family":"Hinz","given":"Nicholas H.","affiliations":[],"preferred":false,"id":731189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulds, James E.","contributorId":184258,"corporation":false,"usgs":false,"family":"Faulds","given":"James E.","affiliations":[],"preferred":false,"id":731190,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196049,"text":"70196049 - 2018 - Downstream fish passage guide walls: A hydraulic scale model analysis","interactions":[],"lastModifiedDate":"2018-03-15T10:02:19","indexId":"70196049","displayToPublicDate":"2018-03-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Downstream fish passage guide walls: A hydraulic scale model analysis","docAbstract":"Partial-depth guide walls are used to improve passage efficiency and reduce the delay of out-migrating anadromous fish species by guiding fish to a bypass route (i.e. weir, pipe, sluice gate) that circumvents the turbine intakes, where survival is usually lower. Evaluation and monitoring studies, however, indicate a high propensity for some fish to pass underneath, rather than along, the guide walls, compromising their effectiveness. In the present study we evaluated a range of guide wall structures to identify where/if the flow field shifts from sweeping (i.e. flow direction primarily along the wall and towards the bypass) to downward-dominant. Many migratory fish species, particularly juveniles, are known to drift with the flow and/or exhibit rheotactic behaviour during their migration. When these behaviours are present, fish follow the path of the flow field. Hence, maintaining a strong sweeping velocity in relation to the downward velocity along a guide wall is essential to successful fish guidance. Nine experiments were conducted to measure the three-dimensional velocity components upstream of a scale model guide wall set at a wide range of depths and angles to flow. Results demonstrated how each guide wall configuration affected the three-dimensional velocity components, and hence the downward and sweeping velocity, along the full length of the guide wall. In general, the velocities produced in the scale model were sweeping dominant near the water surface and either downward dominant or close to the transitional depth near the bottom of the guide wall. The primary exception to this shift from sweeping do downward flow was for the minimum guide wall angle tested in this study (15°). At 15° the flow pattern was fully sweeping dominant for every cross-section, indicating that a guide wall with a relatively small angle may be more likely to produce conditions favorable to efficient guidance. A critical next step is to evaluate the behaviour of migratory fish as they approach and swim along a guide wall in a controlled laboratory environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2018.02.006","usgsCitation":"Mulligan, K., Towler, B., Haro, A.J., and Ahlfeld, D.P., 2018, Downstream fish passage guide walls: A hydraulic scale model analysis: Ecological Engineering, v. 115, p. 122-138, https://doi.org/10.1016/j.ecoleng.2018.02.006.","productDescription":"17 p.","startPage":"122","endPage":"138","ipdsId":"IP-080365","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":468911,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2018.02.006","text":"Publisher Index Page"},{"id":352541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6fde4b0da30c1bfc02c","contributors":{"authors":[{"text":"Mulligan, Kevin 0000-0002-3534-4239 kmulligan@usgs.gov","orcid":"https://orcid.org/0000-0002-3534-4239","contributorId":177024,"corporation":false,"usgs":true,"family":"Mulligan","given":"Kevin","email":"kmulligan@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":731136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Towler, Brett","contributorId":141164,"corporation":false,"usgs":false,"family":"Towler","given":"Brett","email":"","affiliations":[{"id":6927,"text":"USFWS, National Wildlife Refuge System","active":true,"usgs":false}],"preferred":false,"id":731137,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haro, Alexander J. 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":2917,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":731138,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ahlfeld, David P.","contributorId":196530,"corporation":false,"usgs":false,"family":"Ahlfeld","given":"David","email":"","middleInitial":"P.","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":731139,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196043,"text":"ofr20181034 - 2018 - A conservation paradox in the Great Basin—Altering sagebrush landscapes with fuel breaks to reduce habitat loss from wildfire","interactions":[],"lastModifiedDate":"2018-03-15T16:33:34","indexId":"ofr20181034","displayToPublicDate":"2018-03-15T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1034","title":"A conservation paradox in the Great Basin—Altering sagebrush landscapes with fuel breaks to reduce habitat loss from wildfire","docAbstract":"Interactions between fire and nonnative, annual plant species (that is, “the grass/fire cycle”) represent one of the greatest threats to sagebrush (Artemisia spp.) ecosystems and associated wildlife, including the greater sage-grouse (Centrocercus urophasianus). In 2015, U.S. Department of the Interior called for a “science-based strategy to reduce the threat of large-scale rangeland fire to habitat for the greater sage-grouse and the sagebrush-steppe ecosystem.” An associated guidance document, the “Integrated Rangeland Fire Management Strategy Actionable Science Plan,” identified fuel breaks as high priority areas for scientific research. Fuel breaks are intended to reduce fire size and frequency, and potentially they can compartmentalize wildfire spatial distribution in a landscape. Fuel breaks are designed to reduce flame length, fireline intensity, and rates of fire spread in order to enhance firefighter access, improve response times, and provide safe and strategic anchor points for wildland fire-fighting activities. To accomplish these objectives, fuel breaks disrupt fuel continuity, reduce fuel accumulation, and (or) increase plants with high moisture content through the removal or modification of vegetation in strategically placed strips or blocks of land.
Fuel breaks are being newly constructed, enhanced, or proposed across large areas of the Great Basin to reduce wildfire risk and to protect remaining sagebrush ecosystems (including greater sage-grouse habitat). These projects are likely to result in thousands of linear miles of fuel breaks that will have direct ecological effects across hundreds of thousands of acres through habitat loss and conversion. These projects may also affect millions of acres indirectly because of edge effects and habitat fragmentation created by networks of fuel breaks. Hence, land managers are often faced with a potentially paradoxical situation: the need to substantially alter sagebrush habitats with fuel breaks to ultimately reduce a greater threat of their destruction from wildfire. However, there is relatively little published science that directly addresses the ability of fuel breaks to influence fire behavior in dryland landscapes or that addresses the potential ecological effects of the construction and maintenance of fuel breaks on sagebrush ecosystems and associated wildlife species.
This report is intended to provide an initial assessment of both the potential effectiveness of fuel breaks and their ecological costs and benefits. To provide this assessment, we examined prior studies on fuel breaks and other scientific evidence to address three crucial questions: (1) How effective are fuel breaks in reducing or slowing the spread of wildfire in arid and semi-arid shrubland ecosystems? (2) How do fuel breaks affect sagebrush plant communities? (3) What are the effects of fuel breaks on the greater sage-grouse, other sagebrush obligates, and sagebrush-associated wildlife species? We also provide an overview of recent federal policies and management directives aimed at protecting remaining sagebrush and greater sage-grouse habitat; describe the fuel conditions, fire behavior, and fire trends in the Great Basin; and suggest how scientific inquiry and management actions can improve our understanding of fuel breaks and their effects in sagebrush landscapes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181034","collaboration":"Prepared in cooperation with the U.S. Forest Service","usgsCitation":"Shinneman, D.J., Aldridge, C.L., Coates, P.S., Germino, M.J., Pilliod, D.S., and Vaillant, N.M., 2018, A conservation paradox in the Great Basin—Altering sagebrush landscapes with fuel breaks to reduce habitat loss from wildfire: U.S. Geological Survey Open-File Report 2018–1034, 70 p., https://doi.org/10.3133/ofr20181034.","productDescription":"vi, 70 p.","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-092468","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":352531,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1034/coverthb.jpg"},{"id":352532,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1034/ofr20181034.pdf","text":"Report","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1034"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Thermal evolution modeling has yielded a variety of interior structures for Ceres, ranging from a modestly differentiated interior to more advanced evolution with a dry silicate core, a hydrated silicate mantle, and a volatile‐rich crust. Here we compute the mass and hydrostatic flattening from more than one hundred billion three‐layer density models for Ceres and describe the characteristics of the population of density structures that are consistent with the Dawn observations. We show that the mass and hydrostatic flattening constraints from Ceres indicate the presence of a high‐density core with greater than a 1σ probability, but provide little constraint on the density, allowing for core compositions that range from hydrous and/or anhydrous silicates to a mixture of metal and silicates. The crustal densities are consistent with surface observations of salts, water ice, carbonates, and ammoniated clays, which indicate hydrothermal alteration, partial fractionation, and the possible settling of heavy sulfide and metallic particles, which provide a potential process for increasing mass with depth.
","language":"English","publisher":"Wiley","doi":"10.1111/maps.13063","usgsCitation":"King, S., Castillo-Rogez, J.C., Toplis, M.J., Bland, M.T., Raymond, C.A., and Russell, C.T., 2018, Ceres internal structure from geophysical constraints: Meteoritics and Planetary Science, v. 53, no. 9, p. 1999-2007, https://doi.org/10.1111/maps.13063.","productDescription":"9 p.","startPage":"1999","endPage":"2007","ipdsId":"IP-092685","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468914,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/maps.13063","text":"External Repository"},{"id":377531,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Ceres","volume":"53","issue":"9","noUsgsAuthors":false,"publicationDate":"2018-03-14","publicationStatus":"PW","contributors":{"authors":[{"text":"King, S.J.","contributorId":197182,"corporation":false,"usgs":false,"family":"King","given":"S.J.","email":"","affiliations":[],"preferred":false,"id":796241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castillo-Rogez, J. C.","contributorId":177375,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":796242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toplis, M. J.","contributorId":238461,"corporation":false,"usgs":false,"family":"Toplis","given":"M.","email":"","middleInitial":"J.","affiliations":[{"id":47711,"text":"University of Toulouse","active":true,"usgs":false}],"preferred":false,"id":796243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":796244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raymond, C. A.","contributorId":238463,"corporation":false,"usgs":false,"family":"Raymond","given":"C.","email":"","middleInitial":"A.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":796245,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Russell, C. T.","contributorId":238465,"corporation":false,"usgs":false,"family":"Russell","given":"C.","email":"","middleInitial":"T.","affiliations":[{"id":13399,"text":"UCLA","active":true,"usgs":false}],"preferred":false,"id":796246,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}