Increasing specific conductance (SC) and chloride concentrations [Cl] negatively affect many stream ecosystems. We characterized spatial variability in SC, [Cl], and exceedances of Environmental Protection Agency [Cl] criteria using nearly 30 million high-frequency observations (2–15 min intervals) for SC and modeled [Cl] from 93 sites across three regions in the eastern United States: Southeast, Mid-Atlantic, and New England. SC and [Cl] increase substantially from south to north and within regions with impervious surface cover (ISC). In the Southeast, [Cl] weakly correlates with ISC, no [Cl] exceedances occur, and [Cl] concentrations are constant with time. In the Mid-Atlantic and New England, [Cl] and [Cl] exceedances strongly correlate with ISC. [Cl] criteria are frequently exceeded at sites with greater than 9–10% ISC and median [Cl] higher than 30–80 mg/L. Tens to hundreds of [Cl] exceedances observed annually at most of these sites help explain previous research where stream ecosystems showed changes at (primarily nonwinter) [Cl] as low as 30–40 mg/L. Mid-Atlantic chronic [Cl] exceedances occur primarily in December–March. In New England, exceedances are common in nonwinter months. [Cl] is increasing at nearly all Mid-Atlantic and New England sites with the largest increases at sites with higher [Cl].
Wildfire is a worldwide phenomenon that is expected to increase in extent and severity in the future, due to fuel accumulations, shifting land management practices, and climate change. It immediately affects the landscape by removing vegetation, depositing ash, influencing water-repellent soil formation, and physically weathering boulders and bedrock. These changes typically lead to increased erosion through sheetwash, rilling, dry ravel, and increased mass movement in the form of floods, debris flow, rockfall, and landslides. These process changes bring about landform changes as hillslopes are lowered and stream channels aggrade or incise at increased rates. Furthermore, development of alluvial fans, debris fans, and talus cones are enhanced. The window of disturbance to the landscape caused by wildfire is typically on the order of 3–4 years, with some effects persisting up to 30 years.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reference module in earth systems and environmental sciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","doi":"10.1016/B978-0-12-818234-5.00017-1","usgsCitation":"Santi, P., and Rengers, F.K., 2020, Wildfire and landscape change, chap. of Reference module in earth systems and environmental sciences, HTML Document, https://doi.org/10.1016/B978-0-12-818234-5.00017-1.","productDescription":"HTML Document","ipdsId":"IP-119751","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":382559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Santi, Paul M.","contributorId":247562,"corporation":false,"usgs":false,"family":"Santi","given":"Paul M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":807909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807910,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217341,"text":"70217341 - 2020 - Ratios of methylmercury to total mercury in predator and primary consumer insects from Adirondack streams in New York State","interactions":[],"lastModifiedDate":"2021-01-18T16:42:24.056408","indexId":"70217341","displayToPublicDate":"2020-11-01T10:35:15","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5792,"text":"Summary Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"20-32","title":"Ratios of methylmercury to total mercury in predator and primary consumer insects from Adirondack streams in New York State","docAbstract":"Mercury (Hg) is a global pollutant that affects aquatic biota in otherwise pristine settings such as the Adirondack region of New York State. Bioaccumulation of Hg is especially problematic in sensitive landscapes, where inorganic mercury from atmospheric deposition is readily converted, via natural processes, to methylmercury (MeHg), the toxic form that is taken up and biomagnified in aquatic food webs. There is great interest in monitoring MeHg in aquatic biota across these sensitive regions to evaluate responses to changes in Hg emissions. Aquatic insects, such as dragonfly larvae, have great potential as MeHg “biosentinels,” but currently are not widely used for this purpose. An important practical consideration in the use of aquatic insects for MeHg biomonitoring is whether total mercury (THg) is a suitable surrogate for MeHg, which is much more technically challenging and expensive to analyze than is THg. The objective of this project was to assess the suitability of THg as a surrogate for MeHg in stream-dwelling insects. Specifically, existing data on immature aquatic insects from nine Adirondack streams were used to characterize MeHg to THg ratios (i.e., MeHg%), and variation in these ratios (e.g., among sites, seasons, taxa) in predator and primary consumer insects, examine how well THg in different groups tracks measured stream water MeHg (i.e., filtered MeHg; FMeHg), and explore the influence of trophic position (indicated by nitrogen stable isotopes; δ15N) on the observed MeHg% patterns.
Three broad insect feeding groups were included in this analysis: predators, shredders, and scrapers. Predators had the highest MeHg% (median 94%), and MeHg% did not differ significantly among any of the taxa considered: stoneflies, damselflies, and three families of dragonflies (darners, common skimmers, and clubtails). Darners and common skimmers, the most numerous and abundant predators, were combined for further analyses. Site medians for these “selected dragonflies” were all at least 90% (summer-fall collections) and MeHg% did not differ significantly among sites. The correlation between FMeHg and THg in selected dragonflies was nearly as strong as that of FMeHg and dragonfly MeHg. In contrast, median MeHg% in shredders (northern caddisflies) and scrapers (flathead mayflies), which are both primary consumers, was lower overall (medians 52% and 35%, respectively), more variable, and less-well representative of FMeHg than predators. Stable isotope results indicate that variation in feeding position is an important influence on some of the MeHg% patterns observed in this study. This study’s findings suggest that THg is likely to be a suitable surrogate for MeHg in predatory aquatic insects from Adirondack streams, but do not support the use of THg in primary consumers for regional MeHg monitoring.
","language":"English","publisher":"New York State Energy Research and Development Authority","usgsCitation":"Riva-Murray, K., 2020, Ratios of methylmercury to total mercury in predator and primary consumer insects from Adirondack streams in New York State: Summary Report 20-32, vi, 15 p.","productDescription":"vi, 15 p.","ipdsId":"IP-103615","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":382274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382272,"type":{"id":15,"text":"Index Page"},"url":"https://www.nyserda.ny.gov/About/Publications/Research-and-Development-Technical-Reports/Environmental-Research-and-Development-Technical-Reports#eco"}],"country":"United States","state":"New York","otherGeospatial":"Adirondack region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.805908203125,\n 44.02442151965934\n ],\n [\n -73.85009765625,\n 44.02442151965934\n ],\n [\n -73.85009765625,\n 44.5435052132082\n ],\n [\n -74.805908203125,\n 44.5435052132082\n ],\n [\n -74.805908203125,\n 44.02442151965934\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":2984,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":808421,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216557,"text":"70216557 - 2020 - Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek","interactions":[],"lastModifiedDate":"2020-11-25T16:12:04.955826","indexId":"70216557","displayToPublicDate":"2020-11-01T09:41:22","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek","title":"Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek","docAbstract":"Natural attenuation of heavy metals occurs via coupled microbial iron cycling and metal precipitation in creeks impacted by acid mine drainage (AMD). Here, we describe the isolation, characterization, and genomic sequencing of two iron-oxidizing bacteria (FeOB) species: Thiomonas ferrovorans FB-6 and Thiomonas metallidurans FB-Cd, isolated from slightly acidic (pH 6.3), Fe-rich, AMD-impacted creek sediments. These strains precipitated amorphous iron oxides, lepidocrocite, goethite, and magnetite or maghemite and grew at a pH optimum of 5.5. While Thiomonas spp. are known as mixotrophic sulfur oxidizers and As oxidizers, the FB strains oxidized Fe, which suggests they can efficiently remove Fe and other metals via coprecipitation. Previous evidence for Thiomonas sp. Fe oxidation is largely ambiguous, possibly because of difficulty demonstrating Fe oxidation in heterotrophic/mixotrophic organisms. Therefore, we also conducted a genomic analysis to identify genetic mechanisms of Fe oxidation, other metal transformations, and additional adaptations, comparing the two FB strain genomes with 12 other Thiomonas genomes. The FB strains fall within a relatively novel group of Thiomonas strains that includes another strain (b6) with solid evidence of Fe oxidation. Most Thiomonas isolates, including the FB strains, have the putative iron oxidation gene cyc2, but only the two FB strains possess the putative Fe oxidase genes mtoAB. The two FB strain genomes contain the highest numbers of strain-specific gene clusters, greatly increasing the known Thiomonas genetic potential. Our results revealed that the FB strains are two distinct novel species of Thiomonas with the genetic potential for bioremediation of AMD via iron oxidation.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/AEM.01424-20","usgsCitation":"Akob, D., Hallenbeck, M., Beulig, F., Fabisch, M., Kusel, K., Keffer, J.L., Woyke, T., Shapiro, N., Lapidus, A., Klenk, H., and Chan, C., 2020, Mixotrophic iron-oxidizing Thiomonas isolates from an acid mine drainage-affected creek: Applied and Environmental Microbiology, v. 86, no. 24, e01424-20, 18 p., https://doi.org/10.1128/AEM.01424-20.","productDescription":"e01424-20, 18 p.","ipdsId":"IP-118414","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":454911,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7688216","text":"External Repository"},{"id":380785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Germany","state":"Thuringia","otherGeospatial":"Ronneburg uranium mining district","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 11.854248046875,\n 50.65294336725709\n ],\n [\n 12.32666015625,\n 50.65294336725709\n ],\n [\n 12.32666015625,\n 50.972264889367494\n ],\n [\n 11.854248046875,\n 50.972264889367494\n ],\n [\n 11.854248046875,\n 50.65294336725709\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"86","issue":"24","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Liu, Shuang-Jiang","contributorId":245233,"corporation":false,"usgs":false,"family":"Liu","given":"Shuang-Jiang","email":"","affiliations":[],"preferred":false,"id":805654,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Akob, Denise M. 0000-0003-1534-3025","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":204701,"corporation":false,"usgs":true,"family":"Akob","given":"Denise 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":805596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hallenbeck, Michelle","contributorId":245191,"corporation":false,"usgs":false,"family":"Hallenbeck","given":"Michelle","email":"","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":805597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beulig, Felix","contributorId":245192,"corporation":false,"usgs":false,"family":"Beulig","given":"Felix","affiliations":[{"id":40121,"text":"Friedrich Schiller University Jena","active":true,"usgs":false}],"preferred":false,"id":805598,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fabisch, Maria","contributorId":191122,"corporation":false,"usgs":false,"family":"Fabisch","given":"Maria","email":"","affiliations":[],"preferred":false,"id":805599,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kusel, Kirsten","contributorId":171802,"corporation":false,"usgs":false,"family":"Kusel","given":"Kirsten","email":"","affiliations":[{"id":26947,"text":"Friedrich Schiller University, Germany","active":true,"usgs":false}],"preferred":false,"id":805600,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Keffer, Jessica L","contributorId":245193,"corporation":false,"usgs":false,"family":"Keffer","given":"Jessica","email":"","middleInitial":"L","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":805601,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Woyke, Tanja","contributorId":220021,"corporation":false,"usgs":false,"family":"Woyke","given":"Tanja","email":"","affiliations":[{"id":40122,"text":"DOE JGI","active":true,"usgs":false}],"preferred":false,"id":805602,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shapiro, Nicole","contributorId":220023,"corporation":false,"usgs":false,"family":"Shapiro","given":"Nicole","email":"","affiliations":[{"id":40122,"text":"DOE JGI","active":true,"usgs":false}],"preferred":false,"id":805603,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lapidus, Alla","contributorId":220024,"corporation":false,"usgs":false,"family":"Lapidus","given":"Alla","email":"","affiliations":[{"id":40122,"text":"DOE JGI","active":true,"usgs":false}],"preferred":false,"id":805604,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Klenk, Hans-Peter","contributorId":220025,"corporation":false,"usgs":false,"family":"Klenk","given":"Hans-Peter","email":"","affiliations":[{"id":33636,"text":"Newcastle University","active":true,"usgs":false}],"preferred":false,"id":805605,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chan, Clara","contributorId":245195,"corporation":false,"usgs":false,"family":"Chan","given":"Clara","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":805606,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70227617,"text":"70227617 - 2020 - Winter versus summer habitat selection in a threatened ground squirrel","interactions":[],"lastModifiedDate":"2022-01-21T15:53:54.569335","indexId":"70227617","displayToPublicDate":"2020-11-01T09:38:01","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Winter versus summer habitat selection in a threatened ground squirrel","docAbstract":"Hibernation is a strategy many species employ to survive periods of thermal stress or resource shortage (e.g., harsh thermal conditions, food limitations) and habitat requirements of hibernating species may differ between summer (the active season) and winter (during hibernation). Accounting for seasonal differences in habitat affinities will help ensure that management actions are more beneficial and land-use policies are more appropriate. The northern Idaho ground squirrel (Urocitellus brunneus) is a federally listed threatened species that is in decline and hibernates for approximately 8 months per year. We collared northern Idaho ground squirrels in Adams County, Idaho from 2013–2017. The majority of northern Idaho ground squirrels we collared selected hibernacula outside of the areas they used during the active season. Furthermore, habitat features of hibernacula locations differed from habitat features of active-season areas. Hibernacula locations had greater canopy closure compared to active-season locations (36.9% and 7.0% canopy closure, respectively) and hibernaculum habitat features (particularly distance to nearest log) influenced overwinter survival. Our results suggest that recovery efforts for northern Idaho ground squirrels should include protection and management for the full range of habitat conditions used throughout summer and winter. More broadly, we emphasize the need to identify and protect habitat during all seasons because habitat requirements can differ substantially during different portions of an animal's annual cycle and effective conservation will require management of year-round habitat needs.
This chapter comprises the following sections: names, taxonomy, subspecies and distribution, descriptive notes, habitat, movements and home range, activity patterns, feeding ecology, reproduction and growth, behavior, parasites and diseases, status in the wild, and status in captivity.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bears of the world: Ecology, conservation and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge University Press","doi":"10.1017/9781108692571.014","usgsCitation":"Haroldson, M.A., Clapham, M., Costello, C., Gunther, K.A., Kendall, K., Miller, S., Pigeon, K., Proctor, M.F., Rode, K.D., Servheen, C., Stenhouse, G., and van Manen, F.T., 2020, Brown Bear (Ursus arctos; North America), chap. 13 of Bears of the world: Ecology, conservation and management, p. 162-195, https://doi.org/10.1017/9781108692571.014.","productDescription":"34 p.","startPage":"162","endPage":"195","ipdsId":"IP-108729","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":382058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": 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mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":807863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clapham, Melanie","contributorId":247529,"corporation":false,"usgs":false,"family":"Clapham","given":"Melanie","email":"","affiliations":[{"id":49570,"text":"University of Victoria, Victoria, British Columbia","active":true,"usgs":false}],"preferred":false,"id":807864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":807865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunther, Kerry A.","contributorId":190246,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5130,"text":"Bear Management Office, Yellowstone National Park, WY 82190, USA","active":true,"usgs":false}],"preferred":false,"id":807866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, Kate 0000-0002-4831-2287","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":247530,"corporation":false,"usgs":false,"family":"Kendall","given":"Kate","affiliations":[{"id":49571,"text":"Ursine Ecological","active":true,"usgs":false}],"preferred":false,"id":807867,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Sterling","contributorId":247531,"corporation":false,"usgs":false,"family":"Miller","given":"Sterling","affiliations":[{"id":49572,"text":"Dunrovin Ranch and Research, LLC.","active":true,"usgs":false}],"preferred":false,"id":807868,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pigeon, Karine","contributorId":247532,"corporation":false,"usgs":false,"family":"Pigeon","given":"Karine","email":"","affiliations":[{"id":49573,"text":"fRi Research, Alberta","active":true,"usgs":false}],"preferred":false,"id":807869,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Proctor, Michael F.","contributorId":150939,"corporation":false,"usgs":false,"family":"Proctor","given":"Michael","email":"","middleInitial":"F.","affiliations":[{"id":18147,"text":"Birchdale Ecological","active":true,"usgs":false}],"preferred":false,"id":807870,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":807871,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Servheen, Christopher","contributorId":124584,"corporation":false,"usgs":false,"family":"Servheen","given":"Christopher","email":"","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":807872,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stenhouse, Gordon","contributorId":167054,"corporation":false,"usgs":false,"family":"Stenhouse","given":"Gordon","email":"","affiliations":[{"id":24604,"text":"Foothills Research Institute","active":true,"usgs":false}],"preferred":false,"id":807873,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":807874,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70217183,"text":"70217183 - 2020 - Ecological and social dimensions of sloth bear conservation in Sri Lanka","interactions":[],"lastModifiedDate":"2021-01-12T12:38:09.759517","indexId":"70217183","displayToPublicDate":"2020-11-01T09:22:08","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"28","title":"Ecological and social dimensions of sloth bear conservation in Sri Lanka","docAbstract":"Balancing the needs of humans and wildlife in Sri Lanka presents enormous socioeconomic and conservation challenges. Sloth bears are legally protected, but attacks on humans generate intense fear, which increases the potential for human-caused bear mortality and local extirpation of bears. In this chapter, what is known about the ecology and human dimensions of the sloth bear in a country with a teeming human population and a history of poverty and civil conflict is explored. We also address whether changes in land use in the aftermath of the civil war may have impacted sloth bear distribution and discuss the conservation outlook for bears.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bears of the world: Ecology, conservation and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Cambridge University Press","doi":"10.1017/9781108692571.029","usgsCitation":"Ratnayeke, S., and van Manen, F.T., 2020, Ecological and social dimensions of sloth bear conservation in Sri Lanka, chap. 28 of Bears of the world: Ecology, conservation and management, p. 379-386, https://doi.org/10.1017/9781108692571.029.","productDescription":"8 p.","startPage":"379","endPage":"386","ipdsId":"IP-107001","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":454915,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/9781108692571.029","text":"Publisher Index Page"},{"id":382057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Sri Lanka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 80.57373046875,\n 9.535748998133627\n ],\n [\n 80.04638671875,\n 9.817329187067783\n ],\n [\n 80.00244140625,\n 9.253936156814463\n ],\n [\n 79.7607421875,\n 8.667918002363121\n ],\n [\n 79.6728515625,\n 6.882800241767556\n ],\n [\n 80.31005859375,\n 5.637852598770866\n ],\n [\n 81.84814453125,\n 6.599130675207247\n ],\n [\n 81.97998046875,\n 7.514980942395872\n ],\n [\n 81.01318359375,\n 9.080400104155315\n ],\n [\n 80.57373046875,\n 9.535748998133627\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ratnayeke, Shyamala","contributorId":203978,"corporation":false,"usgs":false,"family":"Ratnayeke","given":"Shyamala","email":"","affiliations":[{"id":36779,"text":"Department of Biological Sciences, Sunway University, Malaysia","active":true,"usgs":false}],"preferred":false,"id":807875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":807876,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70222481,"text":"70222481 - 2020 - Wildfire and Earth surface processes","interactions":[],"lastModifiedDate":"2021-08-02T15:49:34.707051","indexId":"70222481","displayToPublicDate":"2020-11-01T08:31:55","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Wildfire and Earth surface processes","docAbstract":"Wildfire is a worldwide phenomenon that is expected to increase in extent and severity in the future, due to fuel accumulations, shifting land management practices, and climate change. It immediately affects the landscape by removing vegetation, depositing ash, influencing water-repellent soil formation, and physically weathering boulders and bedrock. These changes typically lead to increased erosion through sheetwash, rilling, dry ravel, and increased mass movement in the form of floods, debris flow, rockfall, and landslides. These process changes bring about landform changes as hillslopes are lowered and stream channels aggrade or incise at increased rates. Furthermore, development of alluvial fans, debris fans, and talus cones are enhanced. The window of disturbance to the landscape caused by wildfire is typically on the order of 3–4 years, with some effects persisting up to 30 years.
Of the world’s Brent Goose Branta bernicla populations, the migration routes and winter distribution of the East Asian population of Brent Geese B. b. nigricans are the least well known. We therefore marked Brent Geese at their primary pre-migratory staging area in Notsuke Bay, Hokkaido, Japan to describe their migration between breeding and wintering areas in East Asia. Additionally, count data were compiled from the literature to identify important wintering and staging sites for the species, following Ramsar Convention criteria, and to assess trends in numbers of Brent Geese recorded in Japan and South Korea. The tracking data provided the first direct evidence of migratory connectivity between staging sites in northern Japan and the Korean Peninsula. A total of 26 internationally important sites were identified in the Russian Far East (7), northern Japan (16), northeast China (2) and the Korean Peninsula (1). Autumn surveys made at staging sites in Japan indicate that the East Asian population is increasing, although more extensive surveys for Brent Geese in China and on the Korean Peninsula are needed to confirm overall population trends and to identify critical habitats and wintering sites. We encourage the continuation of tracking studies, to describe more precisely the main migration routes, staging areas and, importantly, the breeding grounds for this vulnerable Brent Geese population.
","language":"English","publisher":"Wildfowl & Wetlands Trust Limited","usgsCitation":"Sawa, Y., Tamura, C., Ikeuchi, T., Fujii, K., Ishioroshi, A., Shimada, T., Tatsuzawa, S., Deng, X., Cao, L., Kim, H., and Ward, D.H., 2020, Migration routes and population status of the Brent Goose Branta bernicla nigricans wintering in East Asia: Wildfowl, no. Special Issue 6, p. 244-266.","productDescription":"23 p.","startPage":"244","endPage":"266","ipdsId":"IP-119747","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":382291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382287,"type":{"id":15,"text":"Index Page"},"url":"https://wildfowl.wwt.org.uk/index.php/wildfowl/article/view/2744"}],"country":"China, Japan, North Korea, Russia, South Korea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 117.42187500000001,\n 36.31512514748051\n ],\n [\n 133.2421875,\n 31.353636941500987\n ],\n [\n 145.1953125,\n 37.16031654673677\n ],\n [\n 145.546875,\n 46.07323062540835\n ],\n [\n 160.3125,\n 52.26815737376817\n ],\n [\n 169.45312499999997,\n 64.62387720204688\n ],\n [\n 164.1796875,\n 71.52490903732816\n ],\n [\n 137.4609375,\n 73.82482034613932\n ],\n [\n 125.15625000000001,\n 72.18180355624855\n ],\n [\n 117.42187500000001,\n 36.31512514748051\n ]\n ]\n ]\n }\n }\n ]\n}","issue":"Special Issue 6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sawa, Yusuke","contributorId":221474,"corporation":false,"usgs":false,"family":"Sawa","given":"Yusuke","email":"","affiliations":[{"id":40387,"text":"BirdLife International Tokyo","active":true,"usgs":false}],"preferred":false,"id":808454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tamura, Chieko","contributorId":221475,"corporation":false,"usgs":false,"family":"Tamura","given":"Chieko","email":"","affiliations":[{"id":37275,"text":"none","active":true,"usgs":false}],"preferred":false,"id":808455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ikeuchi, Toshio","contributorId":221476,"corporation":false,"usgs":false,"family":"Ikeuchi","given":"Toshio","email":"","affiliations":[{"id":40388,"text":"Head Office of the \"Foster a Goose Program\"","active":true,"usgs":false}],"preferred":false,"id":808456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fujii, Kaoru","contributorId":221477,"corporation":false,"usgs":false,"family":"Fujii","given":"Kaoru","email":"","affiliations":[{"id":40389,"text":"Eastern Hokkaido Brent Goose Research Network","active":true,"usgs":false}],"preferred":false,"id":808457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ishioroshi, Aisa","contributorId":221478,"corporation":false,"usgs":false,"family":"Ishioroshi","given":"Aisa","email":"","affiliations":[{"id":40390,"text":"Notsuke Peninsula Nature Center","active":true,"usgs":false}],"preferred":false,"id":808458,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shimada, T.","contributorId":221479,"corporation":false,"usgs":false,"family":"Shimada","given":"T.","email":"","affiliations":[{"id":40391,"text":"The Miyagi Prefectural Izunuma-Uchinuma Environmental Foundation","active":true,"usgs":false}],"preferred":false,"id":808459,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tatsuzawa, Shiro","contributorId":247836,"corporation":false,"usgs":false,"family":"Tatsuzawa","given":"Shiro","email":"","affiliations":[{"id":16855,"text":"Hokkaido University","active":true,"usgs":false}],"preferred":false,"id":808460,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Deng, Xueqin","contributorId":247837,"corporation":false,"usgs":false,"family":"Deng","given":"Xueqin","email":"","affiliations":[{"id":27775,"text":"University of Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":808461,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cao, Lei","contributorId":181789,"corporation":false,"usgs":false,"family":"Cao","given":"Lei","email":"","affiliations":[],"preferred":false,"id":808462,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kim, Hwajung","contributorId":247840,"corporation":false,"usgs":false,"family":"Kim","given":"Hwajung","email":"","affiliations":[{"id":49671,"text":"National Institute of Biological Resources, Korea","active":true,"usgs":false}],"preferred":false,"id":808463,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":808464,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70220613,"text":"70220613 - 2020 - Council monitoring and assessment program (CMAP): A framework for using the monitoring program inventory to conduct gap assessments for the Gulf of Mexico Region","interactions":[],"lastModifiedDate":"2021-05-21T15:36:24.768626","indexId":"70220613","displayToPublicDate":"2020-10-31T10:23:22","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"284","title":"Council monitoring and assessment program (CMAP): A framework for using the monitoring program inventory to conduct gap assessments for the Gulf of Mexico Region","docAbstract":"Executive Summary Under the Resources and Ecosystem Sustainability, Tourist Opportunities, and Revived Economies of the Gulf Coast States Act of 2012 (RESTORE Act), the Gulf Coast Ecosystem Restoration Council (RESTORE Council or Council) is required to report on the progress of funded projects and programs. Systematic monitoring of restoration at the project-specific and programmatic-levels (watershed and Gulf of Mexico) enables consistent reporting and gives the public confidence that the restoration investments selected by the RESTORE Council will be evaluated and adaptively managed accordingly. Monitoring information that has been collected at different spatial and temporal scales can be used as the foundation to illustrate progress towards comprehensive ecosystem restoration goals and objectives that promote holistic Gulf of Mexico recovery (see ‘RESTORE Council Background’ at the beginning of this report for additional Council information).
Currently, federal, state and local agencies, universities, private industry, and non-governmental organizations (NGOs) are conducting monitoring activities at various scales around the Gulf of Mexico. In addition, each RESTORE Council-funded project will, at a minimum, perform project-specific monitoring. This collection of monitoring activities was inventoried and coordinated into a network of existing programs by the Council-funded RESTORE Council Monitoring and Assessment Program (CMAP), which will suggest opportunities for efficiencies and collaborative cross-program review of performance with other Gulf ecosystem recovery efforts. CMAP was designed and funded to inventory and integrate existing monitoring efforts, improve discovery and accessibility of existing monitoring data, and ensure the collected information supports management decisions.
The fundamental approach to building the CMAP Gulf of Mexico water quality monitoring, habitat monitoring, and mapping network was to: 1. Adopt, or construct as needed, a comprehensive inventory of existing habitat and water quality observation, monitoring, and mapping programs in the Gulf of Mexico (hereafter referred to as the “Inventory”; NOAA and USGS, 2019a); 2. Evaluate the suitability/applicability of each program and its existing and prospective data for use in restoration activities; 3. Develop a process to use the Inventory to conduct gap assessments; 4. Develop a catalog of baseline assessments conducted in the Gulf of Mexico (NOAA and USGS, 2019b); and 5. Develop a searchable monitoring information portal/database to enable access to collected information and products.
","language":"English","publisher":"National Oceanic and Atmospheric Administration (NOAA)","doi":"10.25923/mrdd-h727","usgsCitation":"Bosch, J., Burkart, H.B., Chivoiu, B., Clark, R., Clement, C., Enwright, N., Giordano, S., Jeffrey, C., Johnson, E., Hart, R., Hile, S.D., Howell, J.S., Laurenzano, C., Lee, M., McCloskey, T., McTigue, T., Meyers, M.B., Miller, K.E., Mize, S., Monaco, M.E., Owen, K., Rebich, R., Rendon, S.H., Robertson, A., Sample, T., Sanks, K.M., Steyer, G., Suir, K., Swarzenski, C.M., and Thurman, H.R., 2020, Council monitoring and assessment program (CMAP): A framework for using the monitoring program inventory to conduct gap assessments for the Gulf of Mexico Region: NOAA Technical Memorandum 284, ii, 55 p., https://doi.org/10.25923/mrdd-h727.","productDescription":"ii, 55 p.","startPage":"55 p.","ipdsId":"IP-119233","costCenters":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research 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,{"id":70216170,"text":"70216170 - 2020 - Wetlands in agricultural landscapes—Significant findings and recent advances from CEAP-Wetlands","interactions":[],"lastModifiedDate":"2020-11-07T15:59:50.088468","indexId":"70216170","displayToPublicDate":"2020-10-31T09:53:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Wetlands in agricultural landscapes—Significant findings and recent advances from CEAP-Wetlands","docAbstract":"The Wetlands Component of the USDA's Conservation Effects Assessment Project (CEAP-Wetlands) is a multi-agency effort advancing science related to quantifying and interpreting effects and effectiveness of conservation practices and programs on ecosystem services provided by wetlands in agricultural landscapes. This special section originated from a symposium held at the 73rd Soil and Water Conservation Society's International Annual Conference in Albuquerque New Mexico, July 29 to August 1, 2018. The symposium was jointly organized by the USDA Natural Resources Conservation Service and the US Geological Survey. To facilitate CEAP-Wetlands efforts, several regional assessments were conducted across the United States. These regional assessments were designed to address science gaps hindering wetland conservation and to develop tools facilitating conservation assessments. Conservation decisions affect not just agricultural wetlands, but also the services that these complex ecosystems provide to society. Papers in this special section of the Journal of Soil and Water Conservation present key findings and recent advances from several CEAP-Wetlands regional assessments and discuss the significant contributions of each assessment to an ever-increasing understanding of wetland ecosystems and their provisioning of ecosystem services. Modeling efforts using the Agricultural Policy and Environmental eXtender (APEX) and other process-based models are an integral component of CEAP-Wetlands. Results of these modeling efforts are also presented, and conservation implications are discussed.
Wind fetch is defined as the unobstructed distance that wind can travel over water in a constant direction. Fetches are limited by landforms surrounding the body of water. Fetch is an important characteristic of open water because longer fetches can result in larger wind-generated waves. The larger waves, in turn, can increase shoreline erosion and sediment resuspension (Rohweder and others 2012). Increases in sediment resuspension lead to increases in water turbidity, which in turn decreases light penetration and, therefore, create conditions less conducive to aquatic plant growth (Giblin and others 2010).
A wind fetch model was developed by David Finlayson, U. S. Geological Survey, Pacific Science Center, while he was a Ph.D. student at the University of Washington (Finlayson 2005). This method calculates effective fetch using the recommended procedure of the Shore Protection Manual (USACE 1984). Scientists at the United States Geological Survey, Upper Midwest Environmental Sciences Center (UMESC) and the United States Army Corps of Engineers (USACE) further refined this model (Rohweder and others 2012) and structured it to operate using the most recent version of the ArcMap Geographic Information System platform (Esri, 2019). At the time the analysis was performed, the version of ArcMap used was 10.7.1. The model refined in 2012 was used for the analyses described in this report.
Using this model, UMESC performed an analysis to model weighted wind fetch for the Upper Mississippi River System (UMRS) corresponding to three separate time periods of land cover spatial data acquisition (1989, 2000, and 2010/2011). The purpose of the analysis was to examine how fetch varies over time and space within the UMRS for potential management applications. For more detailed information on the wind fetch model, examine the USGS Open-File Report by Rohweder and others (2012).
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\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Persons, Trevor","contributorId":247703,"corporation":false,"usgs":false,"family":"Persons","given":"Trevor","affiliations":[{"id":49619,"text":"Field Herpetologist, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":808137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":808138,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70217097,"text":"70217097 - 2020 - Using hair cortisol to assess physiological stress in Alaska polar bears","interactions":[],"lastModifiedDate":"2025-03-07T15:42:57.149246","indexId":"70217097","displayToPublicDate":"2020-10-31T08:27:38","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":251,"text":"Final Report","active":false,"publicationSubtype":{"id":4}},"title":"Using hair cortisol to assess physiological stress in Alaska polar bears","docAbstract":"The concentration of cortisol in hair (HCC) of polar bears (Ursus maritimus) may provide a retrospective view of physiological stress they experience and a link to their response to environmental change. To understand this relationship, we assayed HCC from polar bears captured in the Alaska Beaufort, Bering and Chukchi seas during 1983–1989 and 2004–2016. Cortisol accumulated in hair through summer and autumn and into the subsequent winter. HCC was similar between adult males and adult females. No difference in HCC across regions suggested all bears responded similarly to the environment. HCC in spring was elevated following years with a high winter Arctic Oscillation index and highly variable wind speed. HCC increased non-linearly with increasing duration of the continental shelf summer open water period up to 50 days and then decreased. HCC of spring samples declined with increasing body size, indicating that the stress response was more active in smaller bears or those in poor body condition. HCC of spring samples was greater and more variable in 2004–2006 than during either 1983–1989 or 2008–2016, and significantly so for females with 1st year cubs and subadult females. Elevated HCC in 2004–2006 coincided with years of reduced survival of southern Beaufort Sea polar bears and suggests that unidentified environmental perturbations impacted Alaska polar bears. Because HCC may be obtained by relatively non-invasive means, it has potential use for assessing polar bear populations that are difficult to study by capturing. Hence, information gained from HCC can inform polar bear conservation, especially on the vulnerability of subadult females and adult females with new cubs, and possible future environmental perturbations impacts on bear physiology.","language":"English","publisher":"Northern Pacific Research Board","usgsCitation":"Durner, G.M., 2020, Using hair cortisol to assess physiological stress in Alaska polar bears: Final Report, 79 p.","productDescription":"79 p.","ipdsId":"IP-123453","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":381912,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://nprb.org/project-search/#metadata/9be4eee1-a9a4-4026-a477-02da9460d0d3/project/files"},{"id":381946,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Bering Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.1083984375,\n 69.61120561869633\n ],\n [\n -135.17578125,\n 70.40734767606811\n ],\n [\n -140.18554687499997,\n 72.3157853052617\n ],\n [\n -154.3798828125,\n 72.93253803407026\n ],\n [\n -160.576171875,\n 73.18861179538935\n ],\n [\n -162.509765625,\n 73.20131708476698\n ],\n [\n -164.2236328125,\n 72.79008827319015\n ],\n [\n -160.7080078125,\n 71.00265967789278\n ],\n [\n -159.2578125,\n 70.8446726342528\n ],\n [\n -156.8408203125,\n 70.91664110709776\n ],\n [\n -152.0068359375,\n 70.34831755984779\n ],\n [\n -141.1083984375,\n 69.54987728327795\n ],\n [\n -141.1083984375,\n 69.61120561869633\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.1787109375,\n 65.6582745198266\n ],\n [\n -164.00390625,\n 66.60067571342496\n ],\n [\n -163.6083984375,\n 67.13582938531948\n ],\n [\n -166.6845703125,\n 68.39918004344189\n ],\n [\n -166.201171875,\n 69.06856318696033\n ],\n [\n -165.05859375,\n 68.95839084822076\n ],\n [\n -163.4765625,\n 69.4421276134176\n ],\n [\n -162.9052734375,\n 70.24460360904779\n ],\n [\n -167.5634765625,\n 70.88788500718185\n ],\n [\n -170.244140625,\n 70.17020068549206\n ],\n [\n -168.1787109375,\n 65.6582745198266\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -171.650390625,\n 63.68524808030715\n ],\n [\n -168.046875,\n 63.11463763252091\n ],\n [\n -167.51953124999997,\n 63.87939001720202\n ],\n [\n -169.541015625,\n 64.4348920430406\n ],\n [\n -171.38671874999997,\n 64.41592147626879\n ],\n [\n -172.3095703125,\n 64.03374392176401\n ],\n [\n -171.650390625,\n 63.68524808030715\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Durner, George M. 0000-0002-3370-1191 gdurner@usgs.gov","orcid":"https://orcid.org/0000-0002-3370-1191","contributorId":3576,"corporation":false,"usgs":true,"family":"Durner","given":"George","email":"gdurner@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":807603,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70268708,"text":"70268708 - 2020 - On the robustness of annual daily precipitation maxima estimates over Monsoon Asia","interactions":[],"lastModifiedDate":"2025-07-07T16:11:01.608215","indexId":"70268708","displayToPublicDate":"2020-10-30T11:09:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21978,"text":"Frontiers in Climate Services","active":true,"publicationSubtype":{"id":10}},"title":"On the robustness of annual daily precipitation maxima estimates over Monsoon Asia","docAbstract":"Understanding precipitation extremes over Monsoon Asia is vital for water resource management and hazard mitigation, but there are many gaps and uncertainties in observations in this region. To better understand observational uncertainties, this study uses a high-resolution validation dataset to assess the consistency of the representation of annual daily precipitation maxima (Rx1day) over land in 13 observational datasets from the Frequent Rainfall Observations on Grids (FROGS) database. The FROGS datasets are grouped into three categories: in situ-based and satellite-based with and without corrections to rain gauges. We also look at three sub-regions: Japan, India, and the Maritime Continent based on their different station density, orography, and coastal complexity. We find broad similarities in spatial and temporal distributions among in situ-based products over Monsoon Asia. Satellite products with correction to rain gauges show better general agreement and less inter-product spread than their uncorrected counterparts. However, this comparison also reveals strong sub-regional differences that can be explained by the quantity and quality of rain gauges. High consistency in spatial and temporal patterns are observed over Japan, which has a dense station network, while large inter-product spread is found over the Maritime Continent and India, which have sparser station density. We also highlight that while corrected satellite products show improvement compared to uncorrected products in regions of high station density (e.g., Japan) they have mixed success over other regions (e.g., India and the Maritime Continent). In addition, the length of record available at each station can also affect the satellite correction over these poorly sampled regions. Results of the additional comparison between all considered datasets and the sub-regional high resolution dataset remain the same, indicating that the overall quality of the station network has implications for the reliability of the in situ-based products derived and also the satellite products that use a correction to in situ data. Given these uncertainties in observations, there is no single best dataset for assessment of Rx1day in Monsoon Asia. In all cases we recommend users understand how each dataset is produced in order to select the most appropriate product to estimate precipitation extremes to fit their purpose.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fclim.2020.578785","usgsCitation":"Nguyen, P., Bador, M., Alexander, L., Lane, T., and Funk, C., 2020, On the robustness of annual daily precipitation maxima estimates over Monsoon Asia: Frontiers in Climate Services, v. 2, 578785, 19 p., https://doi.org/10.3389/fclim.2020.578785.","productDescription":"578785, 19 p.","ipdsId":"IP-121958","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":492046,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fclim.2020.578785","text":"Publisher Index Page"},{"id":491743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Monsoon Asia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 67.82681208821384,\n 28.08149631086141\n ],\n [\n 67.82681208821384,\n 4.541379126404635\n ],\n [\n 88.69639230102973,\n 4.541379126404635\n ],\n [\n 88.69639230102973,\n 28.08149631086141\n ],\n [\n 67.82681208821384,\n 28.08149631086141\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 148.23729356007158,\n 45.2939171288528\n ],\n [\n 129.57288839651233,\n 45.2939171288528\n ],\n [\n 129.57288839651233,\n 29.638462684082825\n ],\n [\n 148.23729356007158,\n 29.638462684082825\n ],\n [\n 148.23729356007158,\n 45.2939171288528\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 90.4186427916805,\n 10.095537024904786\n ],\n [\n 90.4186427916805,\n -11.16935497577198\n ],\n [\n 155.06835956423896,\n -11.16935497577198\n ],\n [\n 155.06835956423896,\n 10.095537024904786\n ],\n [\n 90.4186427916805,\n 10.095537024904786\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationDate":"2020-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Nguyen, Phuong-Loan","contributorId":357544,"corporation":false,"usgs":false,"family":"Nguyen","given":"Phuong-Loan","affiliations":[{"id":85452,"text":"ARC Centre of Excellence for Climate Extremes, UNSW Sydney, Sydney, New South Wales, Australia","active":true,"usgs":false}],"preferred":false,"id":941695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bador, Margot","contributorId":223056,"corporation":false,"usgs":false,"family":"Bador","given":"Margot","email":"","affiliations":[{"id":40656,"text":"Climate Change Research Centre, UNSW Sydney","active":true,"usgs":false}],"preferred":false,"id":941696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alexander, Lisa","contributorId":223054,"corporation":false,"usgs":false,"family":"Alexander","given":"Lisa","email":"","affiliations":[{"id":40656,"text":"Climate Change Research Centre, UNSW Sydney","active":true,"usgs":false}],"preferred":false,"id":941697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, Todd P.","contributorId":357545,"corporation":false,"usgs":false,"family":"Lane","given":"Todd P.","affiliations":[{"id":85454,"text":"2School of Earth Science and ARC Centre of Excellence for Climate Extremes, The University of Melbourne, Melbourne, Victoria, Australia","active":true,"usgs":false}],"preferred":false,"id":941698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":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":941699,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227642,"text":"70227642 - 2020 - Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data","interactions":[],"lastModifiedDate":"2022-01-24T14:57:06.932262","indexId":"70227642","displayToPublicDate":"2020-10-30T08:48:53","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data","docAbstract":"Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R2, RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year (p < 0.01), and harvesting dates were delayed by 0.78 days/year (p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.
No abstract available.
","language":"English","publisher":"Bonneville Power Administration","collaboration":"Bonneville Power Administration","usgsCitation":"Jezorek, I., 2020, Wind River Subbasin Restoration annual report of U.S. Geological Survey activities January 2019 through December 2019, 74 p.","productDescription":"74 p.","ipdsId":"IP-121318","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":382093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382077,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P179251/83769-2.pdf"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.2119140625,\n 45.644768217751924\n ],\n [\n -121.09130859375,\n 45.644768217751924\n ],\n [\n -121.09130859375,\n 46.195042108660154\n ],\n [\n -122.2119140625,\n 46.195042108660154\n ],\n [\n -122.2119140625,\n 45.644768217751924\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jezorek, Ian 0000-0002-3842-3485","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":217811,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":808006,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70217144,"text":"70217144 - 2020 - Riparian plant communities remain stable in response to a second cycle of Tamarix biocontrol defoliation","interactions":[],"lastModifiedDate":"2021-01-07T13:24:15.179148","indexId":"70217144","displayToPublicDate":"2020-10-30T07:20:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Riparian plant communities remain stable in response to a second cycle of Tamarix biocontrol defoliation","docAbstract":"Reduced abundance of non-native Tamarix shrubs in western U.S. riparian systems following biological control by a defoliating beetle has led to concerns that replacement plant communities could be dominated by other invasive species and/or not provide some of the ecosystem services that Tamarix was providing. In previous studies, Tamarix decline following biocontrol was accompanied by small increases in native and non-native herbaceous species, with variable responses of woody vegetation. However, none of these studies spanned periods longer than a decade since beetle release. This is an important caveat, given the cyclical nature of plant-herbivore interactions and potential lags in vegetation recovery. We report plant community response to an eight-year-long second cycle of Tamarix defoliation-refoliation in two reaches of the upper Colorado River in eastern Utah, 11–13 years after beetle arrival. Tamarix cover across sites initially declined an average of ca. 50% in response to the beetle, but then recovered. Changes in the associated plant community were small but supported common management goals, including a 47% average increase in cover of a native shrub (Salix exigua), and no secondary invasions by other non-native plants. We suggest that the effectiveness of biocontrol programs must be assessed case-by-case, and on a long-term basis.
A geochemical characterization of groundwater in the Big Chino subbasin of Arizona was conducted by the U.S. Geological Survey, in cooperation with the City of Prescott, the Town of Prescott Valley, and the Salt River Project, to understand groundwater evolution through the study area and the source of water to springs along the gaining reach of the Verde River just downstream from its confluence with Granite Creek. Samples were collected between 2011 and 2018 in groundwater wells completed in basin-fill and carbonate aquifers and at selected springs, including two discrete springs discharging along the aforementioned stretch of the Verde River. Five newly installed monitoring wells completed in the carbonate aquifer were sampled in 2018. Water-quality results obtained from these samples include the first known geochemical data for carbonate groundwater beneath the basin-fill in the Big Chino subbasin downgradient from Walnut Creek near Paulden, Arizona, as well as other parts of the study area without previous data. Groundwater samples were collected and analyzed for major ions, arsenic, nutrients, stable isotopes of oxygen and hydrogen (δ18O and δ2H), strontium isotopes (87Sr/86Sr), carbon-14, isotopes of carbon (δ13C), and noble gases.
Significant differences in groundwater geochemistry between the basin-fill and carbonate aquifers were driven primarily by higher pH, tritium, and δ18O and δ2H in the basin-fill aquifer samples and higher specific conductance and higher concentrations of calcium, sodium, bicarbonate, fluoride, and arsenic in the carbonate aquifer samples. All but one sample from the carbonate aquifer and two samples from the basin-fill aquifer exceeded the U.S. Environmental Protection Agency (EPA) drinking water standard for arsenic of 10 micrograms per liter. One basin-fill aquifer sample exceeded the EPA drinking water standard for fluoride of 4 milligrams per liter, and one carbonate aquifer sample exceeded the EPA secondary drinking water standard for fluoride of 2 milligrams per liter. A component of modern groundwater recharged following aboveground nuclear testing beginning in the mid-1950s is present in some basin-fill and spring groundwater from this study. Groundwater that can be dated using radiocarbon decay is also present in the study area, with four groundwater samples indicating possible recharge during the Pleistocene with groundwater ages ranging from approximately 34,600 to 13,300 years before present. Other groundwater sampled during this study that can dated using radiocarbon decay ranged in age from about 7,500 to 1,100 years before present, indicating possible recharge during the Holocene.
The gaining reach of the Verde River downstream from the confluence with Granite Creek shows areal changes in temperature, pH, and specific conductance, indicating multiple zones of groundwater input. Surface-water samples for analyses of δ18O and δ2H have been collected at the Verde River near Paulden, Ariz. streamgage (09503700) during discharge measurements since 2009, and a trend analysis of the δ18O and δ2H data indicated no significant trend exists for the 10-year period of record. Additional groundwater samples from the carbonate aquifer beneath the basin-fill upgradient and downgradient from Walnut Creek would provide valuable information to understand groundwater evolution along the Big Chino subbasin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205094","collaboration":"Prepared in cooperation with the City of Prescott, the Town of Prescott Valley, and the Salt River Project","usgsCitation":"Beisner, K.R., and Jones, C.J.R., 2020, Geochemical assessment of groundwater in the Big Chino subbasin, Arizona, 2011–18: U.S. Geological Survey Scientific Investigations Report 2020–5094, 49 p., https://doi.org/10.3133/sir20205094.","productDescription":"Report: viii, 49 p.; 2 Appendixes; 2 Data Releases","numberOfPages":"61","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-113409","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":379927,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HMZNIK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Carbon and strontium isotopic data for rock, soil, and soil gas from the Big Chino Sub-Basin, Arizona, 2017 and 2018"},{"id":379924,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5094/sir20205094_appendix_1.csv","text":"Appendix 1","size":"14.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2020–5094 Appendix 1","linkHelpText":"— Groundwater Geochemistry Data for Samples Collected by the U.S. Geological Survey from the Big Chino Subbasin Between 2011 and 2018"},{"id":379923,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5094/sir20205094.pdf","text":"Report","size":"37.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5094"},{"id":379926,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P909LD47","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Water quality parameters in the Verde River below Granite Creek, Arizona, June 2018"},{"id":379922,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5094/coverthb.jpg"},{"id":379925,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2020/5094/sir20205094_appendix_1.xlsx","text":"Appendix 1","size":"33.8 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2020–5094 Appendix 1","linkHelpText":"— Groundwater Geochemistry Data for Samples Collected by the U.S. Geological Survey from the Big Chino Subbasin Between 2011 and 2018"}],"country":"United States","state":"Arizona","otherGeospatial":"Big Chino subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.18389892578125,\n 34.3366324743773\n ],\n [\n -111.8463134765625,\n 34.3366324743773\n ],\n [\n -111.8463134765625,\n 35.1154153142536\n ],\n [\n -113.18389892578125,\n 35.1154153142536\n ],\n [\n -113.18389892578125,\n 34.3366324743773\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
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Albuquerque, NM 87111
We present measurements of the density, hydraulic conductivity, and specific discharge of a widespread firn aquifer in Antarctica, within the Wilkins Ice Shelf. At the field site, the aquifer is 16.2 m thick, starting at 13.4 m from the snow surface and transitioning from water‐saturated firn to ice at 29.6 m. Hydraulic conductivity derived from slug tests show a geometric mean value of 1.4 ± 1.2 × 10−4 m s−1, equivalent to permeability of 2.6 ± 2.2 × 10−11 m2. A borehole dilution test indicates an average specific discharge value of 1.9 ± 2.8 × 10−6 m s−1. Ground‐penetrating radar profiles and a groundwater flow model show the aquifer is draining laterally into a large nearby rift. Our findings indicate that the firn aquifer in the vicinity of the field site is likely not in a steady state and its presence likely contributed to past ice shelf instability.
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