During September and October 2019, the U.S. Geological Survey mapped the shoreface and inner continental shelf offshore of the Rockaway Peninsula in New York using high-resolution chirp seismic reflection and single-beam bathymetry geophysical techniques. The results from this study are important for assessing the Quaternary evolution of the Rockaway Peninsula and determining coastal sediment availability, which is crucial for establishing sediment budgets, understanding sediment dispersal, and managing coastlines. This report presents preliminary interpretations of seismic profiles and maps of shoreface and Holocene sediment thickness from the shoreline to about 2 kilometers offshore. The results indicate that shoreface and Holocene sediment thickness demonstrates zonal variability because of underlying geology and sediment availability. Based on geomorphic features and underlying stratigraphy, the study area is separated into west, west-central, east-central, and east zones. Holocene sediment, which includes the shoreface and seafloor features with positive morphology (for example, nearshore bars, ebb-tide deltas, and sorted bedforms), thickens to the west and may be related to accommodation and westward dip of the regional unconformity. Shoreface units, which are thought to represent the active volume of littoral sediment, are thickest in the west-central peninsula where the geologic base of the shoreface is deeper. Shoreface units with moderate thickness are in the western and eastern peninsula where there are positive morphological features (for example, deposits accumulating updrift from the jetty, ebb-tide deltas, and so on). The thinnest shorefaces are in the east-central Rockaway Peninsula because of less accommodation caused by the shoaling regional unconformity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211100","collaboration":"Prepared in cooperation with the National Fish and Wildlife Foundation","usgsCitation":"Wei, E.A., Miselis, J.L., and Forde, A.S., 2021, Shoreface and Holocene sediment thickness offshore of Rockaway Peninsula, New York: U.S. Geological Survey Open-File Report 2021–1100, 14 p., https://doi.org/10.3133/ofr20211100.","productDescription":"Report: iv, 14 p.; 2 Data Releases","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125818","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":391426,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211100/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":391345,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1100/images/"},{"id":391343,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZO8QKJ","linkHelpText":"Archive of chirp subbottom profile data collected in 2019 from Rockaway Peninsula, New York"},{"id":391346,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.XML"},{"id":391344,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WNJSFN","linkHelpText":"Coastal bathymetry and backscatter data collected in September and October 2019 from Rockaway Peninsula, New York"},{"id":391342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1100/ofr20211100.pdf","text":"Report","size":"11.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1100"},{"id":391341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1100/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Rockaway Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.76152038574219,\n 40.57067539946112\n ],\n [\n -73.74229431152344,\n 40.593620934177494\n ],\n [\n -73.76083374023438,\n 40.59414233212419\n ],\n [\n -73.82469177246094,\n 40.58527801407785\n ],\n [\n -73.8885498046875,\n 40.563372896916164\n ],\n [\n -73.92974853515625,\n 40.549287249082035\n ],\n [\n -73.94622802734375,\n 40.53937335015618\n ],\n [\n -73.9441680908203,\n 40.529979881843865\n ],\n [\n -73.92974853515625,\n 40.526326510744006\n ],\n [\n -73.883056640625,\n 40.53311118427234\n ],\n [\n -73.83018493652344,\n 40.54772199417569\n ],\n [\n -73.77388000488281,\n 40.56389453066509\n ],\n [\n -73.76152038574219,\n 40.57067539946112\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Wild raptors are widely used to assess exposure to different environmental contaminants, including anticoagulant rodenticides (ARs). ARs are used on a global scale for rodent control, and act by disruption of the vitamin K cycle that results in haemorrhage usually accompanied by death within days. Some ARs are highly persistent and bioaccumulative, which can cause significant exposure of non-target species. We characterized AR exposure in a heterogeneous sample of dead raptors collected over 12 years (2008–2019) in south-eastern France. Residue analysis of 156 liver samples through LC-MS/MS revealed that 50% (78/156) were positive for ARs, with 13.5% (21/156) having summed second-generation AR (SGAR) concentrations >100 ng/g ww. While SGARs were commonly detected (97.4% of positive samples), first-generation ARs were rarely found (7.7% of positive samples). ARs were more frequently detected and at greater concentration in predators (prevalence: 82.5%) than in scavengers (38.8%). Exposure to multiple ARs was common (64.1% of positive samples). While chlorophacinone exposure decreased over time, an increasing exposure trend was observed for the SGAR brodifacoum, suggesting that public policies may not be efficient at mitigating risk of exposure for non-target species. Haemorrhage was observed in 88 birds, but AR toxicosis was suspected in only 2 of these individuals, and no difference in frequency of haemorrhage was apparent in birds displaying summed SGAR levels above or below 100 ng/g ww. As for other contaminants, 17.2% of liver samples (11/64) exhibited Pb levels compatible with sub-clinical poisoning (>6 μg/g dw), with 6.3% (4/64) above the threshold for severe/lethal poisoning (>30 μg/g dw). Nine individuals with Pb levels >6 μg/g dw also had AR residues, demonstrating exposure to multiple contaminants. Broad toxicological screening for other contaminants was positive for 18 of 126 individuals, with carbofuran and mevinphos exposure being the suspected cause of death of 17 birds. Our findings demonstrate lower but still substantial AR exposure of scavenging birds compared to predatory birds, and also illustrate the complexity of diagnosing AR toxicosis through forensic investigations.
Stony coral tissue loss disease (SCTLD) was first documented in 2014 near the Port of Miami, Florida, and has since spread north and south along Florida’s Coral Reef, killing large numbers of more than 20 species of coral and leading to the functional extinction of at least one species, Dendrogyra cylindrus. SCTLD is assumed to be caused by bacteria based on presence of different molecular assemblages of bacteria in lesioned compared to apparently healthy tissues, its apparent spread among colonies, and cessation of spread of lesions in individual colonies treated with antibiotics. However, light microscopic examination of tissues of corals affected with SCTLD has not shown bacteria associated with tissue death. Rather, microscopy shows dead and dying coral cells and symbiotic dinoflagellates (endosymbionts) indicating a breakdown of host cell and endosymbiont symbiosis. It is unclear whether host cells die first leading to death of endosymbionts or vice versa. Based on microscopy, hypotheses as to possible causes of SCTLD include infectious agents not visible at the light microscopy level or toxicosis, perhaps originating from endosymbionts. To clarify this, we examined corals affected with SCTLD and apparently healthy corals using transmission electron microscopy. Endosymbionts in SCTLD-affected and apparently healthy corals consistently had varying degrees of pathology associated with elongated particles compatible in morphology with filamentous positive single-stranded RNA viruses of plants termed anisometric viral-like particles (AVLP). There was apparent progression from early to late replication of AVLP in the cytoplasm of endosymbionts adjacent to or at times within chloroplasts, with morphologic changes in chloroplasts consistent with those seen in plant cells infected by viruses. Coral host cell pathology appeared limited to massive proliferation and lysis of mucus cells. Based on these findings, we hypothesize that SCTLD is a viral disease of endosymbionts leading to coral host death. Efforts to confirm the presence of a virus associated with SCTLD through other means would be appropriate. These include showing the presence of a virus through molecular assays such as deep sequencing, attempts to grow this virus in the laboratory through culture of endosymbionts, localization of virus in tissue sections using immunohistochemistry or in situ hybridization, and experimental infection of known-virus-negative corals to replicate disease at the gross and microscopic level.
The Mojave Desert region is in a critical position for assessing models of Laramide orogenesis, which is hypothesized to have initiated as one or more seamounts subducted beneath the Cretaceous continental margin. Geochronological and geochemical characteristics of Late Cretaceous magmatic products provide the opportunity to test the validity of Laramide orogenic models. Laramide-aged plutons are exposed along a transect across the Cordilleran Mesozoic magmatic system from Joshua Tree National Park in the Eastern Transverse Ranges eastward into the central Mojave Desert. A transect at latitude ∼33.5°N to 34.5°N includes: (1) the large upper-crustal Late Cretaceous Cadiz Valley batholith, (2) a thick section of Proterozoic to Jurassic host rocks, (3) Late Cretaceous stock to pluton-sized bodies at mesozonal depths, and (4) a Jurassic to Late Cretaceous midcrustal sheeted complex emplaced at ∼20 km depth that transitions into a migmatite complex truncated along the San Andreas fault. This magmatic section is structurally correlative with the Big Bear Lake intrusive suite in the San Bernardino Mountains and similar sheeted rocks recovered in the Cajon Pass Deep Scientific Drillhole.
Zircon U-Pb geochronology of 12 samples via secondary ionization mass spectrometry (SIMS) (six from the Cadiz Valley batholith and six from the Cajon Pass Deep Scientific Drillhole) indicates that all Cretaceous igneous units investigated were intruded between 83 and 74 Ma, and Cajon Pass samples include a Jurassic age component. A compilation of new and published SIMS geochronological data demonstrates that voluminous magmatism in the Eastern Transverse Ranges and central Mojave Desert was continuous throughout the period suggested for the intersection and flat-slab subduction of the Shatsky Rise conjugate deep into the interior of western North America.
Whole-rock major-element, trace-element, and isotope geochemistry data from samples from a suite of 106 igneous rocks represent the breadth of Late Cretaceous units in the transect. Geochemistry indicates an origin in a subduction environment and intrusion into a crust thick enough to generate residual garnet. The lack of significant deflections of compositional characteristics and isotopic ratios in igneous products through space and time argues against a delamination event prior to 74 Ma.
We argue that Late Cretaceous plutonism from the Eastern Transverse Ranges to the central Mojave Desert represents subduction zone arc magmatism that persisted until ca. 74 Ma. This interpretation is inconsistent with the proposed timing of the docking of the Shatsky Rise conjugate with the margin of western North America, particularly models in which the leading edge of the Shatsky Rise was beneath Wyoming at 74 Ma. Alternatively, the timing of cessation of plutonism precedes the timing of the passage of the Hess Rise conjugate beneath western North America at ca. 70–65 Ma. The presence, geochemical composition, and age of arc products in the Eastern Transverse Ranges and central Mojave Desert region must be accounted for in any tectonic model of the transition from Sevier to Laramide orogenesis.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02225.1","usgsCitation":"Economos, R., Barth, A.P., Wooden, J., Paterson, S.R., Friesenhahn, B., Weigand, B., Anderson, J., Roell, J., Palmer, E., Ianno, A., and Howard, K.A., 2021, Testing models of Laramide orogenic initiation by investigation of Late Cretaceous magmatic-tectonic evolution of the central Mojave sector of the California arc: Geosphere, v. 17, no. 6, p. 2042-2061, https://doi.org/10.1130/GES02225.1.","productDescription":"20 p.","startPage":"2042","endPage":"2061","ipdsId":"IP-114848","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450270,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02225.1","text":"Publisher Index Page"},{"id":392846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.597412109375,\n 32.98102014898148\n ],\n [\n -114.5599365234375,\n 32.98102014898148\n ],\n [\n -114.5599365234375,\n 35.074964853989556\n ],\n [\n -118.597412109375,\n 35.074964853989556\n ],\n [\n -118.597412109375,\n 32.98102014898148\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Economos, R.C","contributorId":270083,"corporation":false,"usgs":false,"family":"Economos","given":"R.C","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":828384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Andrew P.","contributorId":214136,"corporation":false,"usgs":false,"family":"Barth","given":"Andrew","email":"","middleInitial":"P.","affiliations":[{"id":38983,"text":"Indiana University - Purdue University","active":true,"usgs":false}],"preferred":false,"id":828385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wooden, J.L.","contributorId":192664,"corporation":false,"usgs":false,"family":"Wooden","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":828386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paterson, S. R","contributorId":270084,"corporation":false,"usgs":false,"family":"Paterson","given":"S.","email":"","middleInitial":"R","affiliations":[{"id":13249,"text":"University of Southern California","active":true,"usgs":false}],"preferred":false,"id":828387,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Friesenhahn, Brody","contributorId":270085,"corporation":false,"usgs":false,"family":"Friesenhahn","given":"Brody","email":"","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":828388,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weigand, B.A","contributorId":270086,"corporation":false,"usgs":false,"family":"Weigand","given":"B.A","email":"","affiliations":[{"id":56075,"text":"University of Göttingen","active":true,"usgs":false}],"preferred":false,"id":828389,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, J.L.","contributorId":270087,"corporation":false,"usgs":false,"family":"Anderson","given":"J.L.","email":"","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":828390,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Roell, J.L.","contributorId":270088,"corporation":false,"usgs":false,"family":"Roell","given":"J.L.","email":"","affiliations":[{"id":56076,"text":"Indiana/Purdue University","active":true,"usgs":false}],"preferred":false,"id":828391,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Palmer, E.F.","contributorId":270089,"corporation":false,"usgs":false,"family":"Palmer","given":"E.F.","email":"","affiliations":[{"id":56076,"text":"Indiana/Purdue University","active":true,"usgs":false}],"preferred":false,"id":828392,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ianno, A.J.","contributorId":270090,"corporation":false,"usgs":false,"family":"Ianno","given":"A.J.","affiliations":[{"id":39566,"text":"Juniata College","active":true,"usgs":false}],"preferred":false,"id":828393,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":828394,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70231396,"text":"70231396 - 2021 - The Boreal-Arctic Wetland and Lake Dataset (BAWLD)","interactions":[],"lastModifiedDate":"2022-05-10T11:50:54.064361","indexId":"70231396","displayToPublicDate":"2021-11-05T06:47:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1426,"text":"Earth System Science Data","active":true,"publicationSubtype":{"id":10}},"title":"The Boreal-Arctic Wetland and Lake Dataset (BAWLD)","docAbstract":"Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (>10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (<0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/essd-13-5127-2021","usgsCitation":"Olefeldt, D., Hovemyr, M., Kuhn, M., Bastviken, D., Bohn, T., Connolly, J., Crill, P., Euskirchen, E., Finkelstein, S., Genet, H., Grosse, G., Harris, L., Heffernan, L., Helbig, M., Hugelium, G., Hutchins, R., Juutinen, S., Lara, M., Malhotra, A., Manies, K.L., McGuire, A., Natali, S., O’Donnell, J.A., Parmentier, F., Rasanen, A., Schaedel, C., Sonnentag, O., Strack, M., Tank, S., Treat, C., Varner, R., Virtanen, T., Watts, J., and Warren, R., 2021, The Boreal-Arctic Wetland and Lake Dataset (BAWLD): Earth System Science Data, v. 13, p. 5127-5149, https://doi.org/10.5194/essd-13-5127-2021.","productDescription":"23 p.","startPage":"5127","endPage":"5149","ipdsId":"IP-129170","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":450274,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5194/essd-13-5127-2021","text":"External Repository"},{"id":400379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2021-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Olefeldt, David","contributorId":169408,"corporation":false,"usgs":false,"family":"Olefeldt","given":"David","affiliations":[{"id":32365,"text":"Department of Renewable Resources, University of Alberta","active":true,"usgs":false}],"preferred":false,"id":842473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hovemyr, Mikael","contributorId":291509,"corporation":false,"usgs":false,"family":"Hovemyr","given":"Mikael","email":"","affiliations":[],"preferred":false,"id":842474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuhn, M.A.","contributorId":291510,"corporation":false,"usgs":false,"family":"Kuhn","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":842475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bastviken, D","contributorId":264953,"corporation":false,"usgs":false,"family":"Bastviken","given":"D","affiliations":[{"id":54595,"text":"Department of Thematic Studies - Environmental Change, Linköping University, Linköping, Sweden","active":true,"usgs":false}],"preferred":false,"id":842476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bohn, T.J.","contributorId":291513,"corporation":false,"usgs":false,"family":"Bohn","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":842477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connolly, J.","contributorId":291515,"corporation":false,"usgs":false,"family":"Connolly","given":"J.","email":"","affiliations":[],"preferred":false,"id":842478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Crill, P.M.","contributorId":248742,"corporation":false,"usgs":false,"family":"Crill","given":"P.M.","affiliations":[{"id":49996,"text":"Stockholm University, Department of Geological Sciences and Bolin Centre for Climate Research, Stockholm, Sweden","active":true,"usgs":false}],"preferred":false,"id":842479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Euskirchen, E.S.","contributorId":216778,"corporation":false,"usgs":false,"family":"Euskirchen","given":"E.S.","email":"","affiliations":[{"id":36971,"text":"University of Alaska","active":true,"usgs":false}],"preferred":false,"id":842480,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Finkelstein, S.A.","contributorId":257296,"corporation":false,"usgs":false,"family":"Finkelstein","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":842481,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Genet, H.","contributorId":291521,"corporation":false,"usgs":false,"family":"Genet","given":"H.","affiliations":[],"preferred":false,"id":842482,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Grosse, G.","contributorId":192805,"corporation":false,"usgs":false,"family":"Grosse","given":"G.","email":"","affiliations":[],"preferred":false,"id":842483,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Harris, L.I.","contributorId":291522,"corporation":false,"usgs":false,"family":"Harris","given":"L.I.","email":"","affiliations":[],"preferred":false,"id":842484,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Heffernan, L.","contributorId":291524,"corporation":false,"usgs":false,"family":"Heffernan","given":"L.","email":"","affiliations":[],"preferred":false,"id":842485,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Helbig, M.","contributorId":169378,"corporation":false,"usgs":false,"family":"Helbig","given":"M.","email":"","affiliations":[{"id":25485,"text":"Université de Montréal, Canada","active":true,"usgs":false}],"preferred":false,"id":842486,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hugelium, G.","contributorId":291527,"corporation":false,"usgs":false,"family":"Hugelium","given":"G.","email":"","affiliations":[],"preferred":false,"id":842487,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hutchins, R.","contributorId":291530,"corporation":false,"usgs":false,"family":"Hutchins","given":"R.","email":"","affiliations":[],"preferred":false,"id":842488,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Juutinen, S.","contributorId":257303,"corporation":false,"usgs":false,"family":"Juutinen","given":"S.","affiliations":[],"preferred":false,"id":842489,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Lara, M.J.","contributorId":291534,"corporation":false,"usgs":false,"family":"Lara","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":842490,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Malhotra, A.","contributorId":291536,"corporation":false,"usgs":false,"family":"Malhotra","given":"A.","affiliations":[],"preferred":false,"id":842491,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":842492,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"McGuire, A.D.","contributorId":199633,"corporation":false,"usgs":false,"family":"McGuire","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":842493,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Natali, S.M.","contributorId":291541,"corporation":false,"usgs":false,"family":"Natali","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":842494,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"O’Donnell, J. A.","contributorId":195376,"corporation":false,"usgs":false,"family":"O’Donnell","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":842495,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Parmentier, F-J.W.","contributorId":291544,"corporation":false,"usgs":false,"family":"Parmentier","given":"F-J.W.","affiliations":[],"preferred":false,"id":842496,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Rasanen, A.","contributorId":291546,"corporation":false,"usgs":false,"family":"Rasanen","given":"A.","email":"","affiliations":[],"preferred":false,"id":842497,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Schaedel, C.","contributorId":291547,"corporation":false,"usgs":false,"family":"Schaedel","given":"C.","email":"","affiliations":[],"preferred":false,"id":842498,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Sonnentag, O.","contributorId":257322,"corporation":false,"usgs":false,"family":"Sonnentag","given":"O.","affiliations":[],"preferred":false,"id":842499,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Strack, M.","contributorId":291552,"corporation":false,"usgs":false,"family":"Strack","given":"M.","email":"","affiliations":[],"preferred":false,"id":842500,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Tank, S.E.","contributorId":169370,"corporation":false,"usgs":false,"family":"Tank","given":"S.E.","email":"","affiliations":[{"id":12799,"text":"University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":842501,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Treat, C. C.","contributorId":257236,"corporation":false,"usgs":false,"family":"Treat","given":"C. C.","affiliations":[{"id":51984,"text":"University of Finland","active":true,"usgs":false}],"preferred":false,"id":842502,"contributorType":{"id":1,"text":"Authors"},"rank":30},{"text":"Varner, R.K.","contributorId":291557,"corporation":false,"usgs":false,"family":"Varner","given":"R.K.","affiliations":[],"preferred":false,"id":842503,"contributorType":{"id":1,"text":"Authors"},"rank":31},{"text":"Virtanen, T.","contributorId":291558,"corporation":false,"usgs":false,"family":"Virtanen","given":"T.","email":"","affiliations":[],"preferred":false,"id":842504,"contributorType":{"id":1,"text":"Authors"},"rank":32},{"text":"Watts, J.D.","contributorId":291559,"corporation":false,"usgs":false,"family":"Watts","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":842505,"contributorType":{"id":1,"text":"Authors"},"rank":33},{"text":"Warren, R.K.","contributorId":291562,"corporation":false,"usgs":false,"family":"Warren","given":"R.K.","email":"","affiliations":[],"preferred":false,"id":842506,"contributorType":{"id":1,"text":"Authors"},"rank":34}]}} ,{"id":70225637,"text":"sir20215099 - 2021 - Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","interactions":[],"lastModifiedDate":"2021-11-05T11:03:38.802132","indexId":"sir20215099","displayToPublicDate":"2021-11-04T16:15:00","publicationYear":"2021","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":"2021-5099","displayTitle":"Regression Models for Estimating Sediment, Nutrient Concentrations and Loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","title":"Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019","docAbstract":"Sediment and nutrient transport in the School Branch watershed (in central Indiana west of Indianapolis) is considered to be heavily affected by agricultural land use throughout the watershed. In 2015, the U.S. Geological Survey, in cooperation with the Indiana Department of Environmental Management, deployed continuous water-quality monitors and began collecting discrete water-quality samples at the streamflow-gaging station School Branch at CR750N at Brownsburg, Indiana (U.S. Geological Survey station 03353420). Regression models that estimate concentrations of suspended sediment, total nitrogen, and total phosphorus were developed by relating streamflow and continuously monitored water-quality data to concentrations measured in discrete water-quality samples collected from June 2015 through February 2019. Regression model diagnostics indicated that streamflow and sensor-measured turbidity concentrations explained about 95 percent of the variation in suspended-sediment concentration and 73 percent of the variation in total phosphorus concentration. Similarly, streamflow and sensor-measured nitrate plus nitrite concentrations explained about 97 percent of the variation in total nitrogen concentrations.
Daily loads of suspended sediment, total nitrogen, and total phosphorus were computed from regression model concentrations and instantaneous streamflow. The estimated mean daily suspended-sediment discharge (June 2015 through February 2019) was 1.184 tons per day; the estimated median suspended-sediment discharge was 0.053 tons per day. The estimated mean daily total nitrogen discharge (June 2015 through February 2019) was 127.50 pounds per day; the estimated median total nitrogen discharge was 28.49 pounds per day. The estimated mean daily total phosphorus discharge (June 2015 through February 2019) was 12.08 pounds per day; the estimated median total-phosphorus discharge was 1.208 pounds per day.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215099","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Downhour, M.S., Bunch, A.R., and Lathrop, T.R., 2021, Regression models for estimating sediment, nutrient concentrations and loads at School Branch at Brownsburg, Indiana, June 2015 through February 2019: U.S. Geological Survey Scientific Investigations Report 2021–5099, 15 p., https://doi.org/10.3133/sir20215099.","productDescription":"Report: v, 14 p.; Data Release; Dataset","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-119874","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":391136,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":391135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YWNBAQ","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Data and regression model for suspended sediment for School Branch at CR750N at Brownsburg, Indiana June 23, 2015, to February 6, 2019"},{"id":391133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5099/coverthb.jpg"},{"id":391134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5099/sir20215099.pdf","text":"Report","size":"1.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5099"}],"country":"United States","state":"Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.44866943359375,\n 39.81170080625297\n ],\n [\n -86.23306274414062,\n 39.81170080625297\n ],\n [\n -86.23306274414062,\n 40.01604611654875\n ],\n [\n -86.44866943359375,\n 40.01604611654875\n ],\n [\n -86.44866943359375,\n 39.81170080625297\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS–415
Denver, CO 80225–0046
The Partridge River Basin (PRB) covers 156 square miles in northeastern Minnesota with headwaters in the Mesabi Iron Range. The basin is characterized by extensive wetlands, lakes, and streams in poorly drained and often thin glacial material overlying Proterozoic bedrock. To better understand the interaction between these extensive surface water features and the groundwater system, a three-dimensional, steady-state, groundwater-flow model of the PRB was developed by the U.S. Geological Survey in cooperation with the Great Lakes Indian Fish & Wildlife Commission using the finite-difference computer code MODFLOW-NWT. The model simulates steady-state base flow in streams and groundwater interactions using the streamflow routing (SFR2) package. Existing mining features including tailings basins, stockpiles, pumped mine pits, and flooded mine pits were simulated using either high hydraulic conductivity zones or the drain (DRN) package. The unsaturated zone flow (UZF) package was used to better represent the groundwater system in areas with a high water table and for wetlands often associated with such areas. UZF typically is used to represent unsaturated zone processes but also can simulate the rejection of recharge and groundwater discharge to the land surface when the water table is near land surface. The steady-state model used data from the 2011 to 2013 period when 2011 high-resolution land surface (light detecting and ranging [lidar]) data were available that reflected land-surface and water elevations from mining activity in the basin. The parameter-estimation software suite PEST_HP was used to obtain a best fit of the modeled to measured groundwater levels, streamflow, pit inflow rates, and mapped peat deposits. The PEST calibration used the target residuals from two models with the same model parameters and targets from two separate periods: (1) a 1995–2015 calibration model, which provided a larger number of calibration targets, and (2) a 2011–2013 mining conditions model, which included calibration targets that reflected conditions consistent with the modeled mine-workings topography.
Calibration of the PRB model resulted in ranges of glacial horizontal hydraulic conductivity parameters that generally agreed with literature values and other models of the region. Horizontal hydraulic conductivity of the bedrock was higher in the upper bedrock layers where numerous and continuous fractures have been observed and lower in the deeper bedrock layers. Average basin-wide calibrated infiltration was 5.3 inches per year. An average of 4.6 inches per year of infiltration crosses the water table and becomes recharge and 0.7 inch per year is rejected by UZF due to saturated conditions at the land surface. Simulated groundwater runoff (the sum of rejected recharge and groundwater seepage to the land surface) can either be routed to streams or removed from the model as evapotranspiration. The calibrated model indicates relatively shallow groundwater-flow paths dominating and approximately 50 percent of the stream base flow coming from groundwater runoff.
The 2011–2013 mining conditions model was then used to develop five model scenarios simulating the response of the groundwater and surface-water system to potential hydrologic stress. The purpose of these mine pit scenarios is to present a possible workflow to quantify a model’s uncertainty for a given model forecast and serve as a possible guide for initial data collection that may improve a future model’s ability to make such a forecast. The scenarios included one scenario with the currently existing Peter Mitchell pit at final buildout and flooded to an elevation of 1,500 feet, and four scenarios with a hypothetical, new mine pit plus the flooded Peter Mitchell at final buildout. The five model scenarios were used to forecast streamflow at six locations in the PRB, pit inflow rates for the new mine pits and the flooded Peter Mitchell pit, and the average depth to water in 12 wetlands. A linear uncertainty analysis was performed using information from the PEST calibration and tools in the PyEMU python package to assess model uncertainty propagation to the model forecasts. Streamflows generally were reduced with future mining and the greatest streamflow reductions occurred from the flooded Peter Mitchell Pit, probably due to its large size. Average depth to groundwater in wetlands was most affected the closer the wetland was to a new mine pit.
Linear uncertainty methods were also used to evaluate data worth, which is the ability for potential new groundwater elevation observations to reduce the uncertainty in scenario forecasts. Data worth was performed for a grid of new hydraulic head observations. Overall, areas with nonnegligible data worth generally corresponded to wetland areas with no groundwater seepage to land surface from UZF. These model behaviors indicated that the land-surface boundary condition simulated by the UZF package was pinning the groundwater elevations to the land surface in areas with groundwater seepage (33 percent of the 2011–2013 base conditions model) such that the sensitivity to new observations in these areas was minimal. Therefore, representing wetlands as boundary conditions minimized the usefulness of data worth calculations because wetland areas were present over a large part of the model domain.
Probabilistic capture zones were estimated for each of the mines in the model scenarios. A capture zone represents the area contributing recharge to a model feature, like a well or a mine pit, and can be calculated by forward tracking particles from the water table. By using Monte Carlo techniques, it is possible to generate estimated capture zones that include the probability of recharge capture given the uncertainty present in the model. Monte Carlo techniques use randomly generated model parameter sets sampled from a plausible parameter range to create many possible realizations. The resulting capture zone arrays were calculated by tallying the total number of realizations in which a particle from a model cell was captured by the feature. Probabilities from the Monte Carlo runs ranged from 1 (captured in 100 percent of the runs) near the pits to 0 (captured in 0 percent of the runs) at the edges of the capture zone. Capture zones were not always spatially continuous; for example, the capture zone for the proposed mine pits south of the flooded Peter Mitchell pit was discontinuous with capture surrounding the proposed mine pit and north of the flooded Peter Mitchell pit. This northern section represents deeper groundwater flow paths that originate in the topographic high, move under the flooded pit, and discharge into the proposed pit. This pattern of capture indicates the possibility of some deeper flow through the upper fractured bedrock when the shallow groundwater flow system is modified. These results underscore that future site-specific applications of the base condition model require the input of site-specific data and recalibration to focus on the site of interest.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215038","collaboration":"Prepared in cooperation with the Great Lakes Indian Fish & Wildlife Commission","usgsCitation":"Haserodt, M.J., Hunt, R.J., Fienen, M.N., and Feinstein, D.T., 2021, Groundwater/surface-water interactions in the Partridge River Basin and evaluation of hypothetical future mine pits, Minnesota: U.S. Geological Survey Scientific Investigations Report 2021–5038, 94 p., https://doi.org/10.3133/sir20215038.","productDescription":"Report: ix, 87 p.; Data Release; Dataset","numberOfPages":"102","onlineOnly":"Y","ipdsId":"IP-123210","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391131,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5038/sir20215038.xml","text":"Report xml","size":"277 kB","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2021–5038 xml"},{"id":391130,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"— USGS water data for the Nation"},{"id":391132,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5038/images"},{"id":391129,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VODOU8","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"MODFLOW-NWT and MODPATH models, capture zones and uncertainty data analysis for the Partridge River Basin, Minnesota"},{"id":391127,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5038/coverthb.jpg"},{"id":391128,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5038/sir20215038.pdf","text":"Report","size":"69.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5038"}],"country":"United States","state":"Minnesota","otherGeospatial":"Partridge River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.25,\n 47.4\n ],\n [\n -91.75,\n 47.4\n ],\n [\n -91.75,\n 47.8\n ],\n [\n -92.25,\n 47.8\n ],\n [\n -92.25,\n 47.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
1 Gifford Pinchot Drive,
Madison, WI 53726
Context: Lethal control of predators is often undertaken to protect species of conservation concern. Traps are frequently baited to increase capture efficacy, but baited traps can potentially increase predation risk by attracting predators to protected areas. This is especially important if targeted predators can escape capture due to low trap success. Snake traps using live mouse lures may be beneficial if traps effectively remove snakes in the presence of birds and do not attract additional snakes to the area.
Aims: The present study evaluated whether mouse-lure traps in areas occupied by birds (simulated by deploying bird-lure traps) could influence predation risk from an invasive snake on Guam.
Methods: Snake traps were used, with Japanese quail (Coturnix japonica) as a proxy for predation risk, to assess if an adjacent trap with a mouse (Mus musculus) would attract brown treesnakes (Boiga irregularis) to a focal area and increase contact between an invasive snake and avian prey. Catch per unit effort (CPUE) at stations containing either a bird-lure trap, mouse-lure trap or pair of traps (i.e. one bird-lure and one mouse-lure trap) was evaluated.
Key results: Bird-lure traps paired with mouse-lure traps did not differ in CPUE from isolated bird-lure traps. At paired stations, CPUE of snakes in mouse-lure traps was 2.3× higher than bird-lure traps, suggesting mouse lures were capable of drawing snakes away from avian prey. Bird-lure traps at paired stations experienced a decay in captures over time, whereas CPUE for isolated bird-lure traps increased after 9 weeks and exceeded mouse-lure traps after 7 weeks.
Conclusions: Mouse lures did not increase the risk of snakes being captured in bird-lure traps. Instead, mouse-lure traps may have locally suppressed snakes, whereas stations without mouse-lure traps still had snakes in the focal area, putting avian prey at greater risk. However, snakes caught with bird lures tended to be larger and in better body condition, suggesting preference for avian prey over mammalian prey in larger snakes.
Implications: Strategic placement of olfactory traps within areas of conservation concern may be beneficial for protecting birds of conservation concern from an invasive snake predator.
","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WR21022","usgsCitation":"Klug, P.E., Yackel Adams, A.A., and Reed, R., 2021, Olfactory lures in predator control do not increase predation risk to birds in areas of conservation concern: Wildlife Research, v. 49, no. 2, p. 183-192, https://doi.org/10.1071/WR21022.","productDescription":"10 p.","startPage":"183","endPage":"192","ipdsId":"IP-124833","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":450278,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wr21022","text":"Publisher Index Page"},{"id":398376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"2","noUsgsAuthors":false,"publicationDate":"2021-11-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Klug, Page E.","contributorId":210065,"corporation":false,"usgs":false,"family":"Klug","given":"Page","email":"","middleInitial":"E.","affiliations":[{"id":38064,"text":"USDA WS NWRC","active":true,"usgs":false}],"preferred":false,"id":840081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":840082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Robert 0000-0001-8349-6168","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":267796,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":840083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70225703,"text":"sir20215117 - 2021 - Groundwater hydrology and chemistry of Jamestown Island, Virginia—Potential effects of tides, storm surges, and sea-level rise on archaeological, cultural, and ecological resources","interactions":[],"lastModifiedDate":"2022-03-18T16:34:09.868008","indexId":"sir20215117","displayToPublicDate":"2021-11-03T16:25:00","publicationYear":"2021","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":"2021-5117","displayTitle":"Groundwater Hydrology and Chemistry of Jamestown Island, Virginia—Potential Effects of Tides, Storm Surges, and Sea-Level Rise on Archaeological, Cultural, and Ecological Resources","title":"Groundwater hydrology and chemistry of Jamestown Island, Virginia—Potential effects of tides, storm surges, and sea-level rise on archaeological, cultural, and ecological resources","docAbstract":"As the site of the first permanent English settlement in North America in 1607, Jamestown Island, Colonial National Historical Park (COLO), Virginia, contains a rich archaeological record that extends from the Paleoindian period (15,000 to 8,000 years ago) through the 20th century. The island is located on the lower James River near the mouth of Chesapeake Bay. Jamestown Island vegetation is dominated by upland forests surrounded by tidal, freshwater-to-oligohaline marshes. Along the Virginia coast, relative sea-level rise was more than 2.5 times the global average during the 20th century. Consequently, the National Park Service (NPS) has identified COLO as one of the 25 national parks most threatened by climate change.
Surface waters across the island are hydraulically connected to the laterally continuous Surficial aquifer. The land-surface altitude of the island is low, with two-thirds of the island less than 5 feet (ft) above the North American Vertical Datum of 1988 (NAVD 88). Consequently, sea-level rise, combined with tides and storm surges, threatens the island and its resources as surface-water and groundwater levels rise, saltwater enters the Surficial aquifer, and groundwater chemistry changes. The impact of sea-level rise on the island’s surface-water resources has been well studied, but groundwater effects have been largely ignored. Quantifying the effects of tides, storm surges, and sea-level rise on groundwater levels and chemistry is essential to developing an effective strategy for managing climate-induced changes. The first step in developing a response strategy includes a parkwide general risk assessment for archaeological sites on the island, so that sites can be prioritized for management actions. The U.S. Geological Survey and the NPS began a study in 2015 to develop a long-term groundwater-monitoring program to evaluate this risk and to develop an updated management strategy.
The groundwater-monitoring program consists of 45 wells and piezometers in two individual clusters and three transects across the island in different hydrologic and chemical settings. Samples for water quality were collected from the wells and piezometers from October 2015 through September 2018 at variable time intervals. Results of the monitoring identified disparate hydrologic and chemical responses to saltwater intrusion across the island. Specific conductance (an indicator of salinity) of groundwater beneath several marshes responded differently to changes in James River salinity. Groundwater response to changes in James River specific conductance appeared to be controlled by land-surface altitude and slope, differences in lateral and vertical sediment characteristics, distance from surface waters, and the degree of surface water/groundwater connectivity between channels and the aquifer.
Groundwater chemistry data from monitoring wells at Black Point, a low-altitude, upland setting, are in contrast with conditions observed in Island House observation wells, a high-altitude, upland setting. Specific conductance (less than 200 microsiemens per centimeter [μS/cm]) and pH (greater than 5.0) of groundwater beneath much of the uplands that characterize the Island House observation wells are typical of groundwater in noncarbonate sedimentary aquifers recharged by precipitation. At Black Point, specific conductance ranged from 2,490 to 15,200 μS/cm, and pH ranged from 3.1 to 6.6 standard units. At the Black Point observation wells, the most saline and dense water was at the water table rather than deeper in the aquifer, causing a density inversion that persisted throughout the study. The density inversion likely resulted from differences in permeability between the shallow clay and fine-grained sands and the deeper coarse-grained sand and gravel. Groundwater with the lowest pH was at the water table. As saline groundwater flows through organic sediment beneath the marshes, bacterial biodegradation of organic matter creates anoxic conditions. Continued biodegradation concomitantly reduces iron-oxide minerals in the sediment and sulfate in saline water. When oxygen is reintroduced into groundwater, iron and sulfur can reoxidize to form sulfuric acid, locally lowering the pH of the water.
This report describes the groundwater monitoring network design, rationale for site selection, monitoring approach, and results of monitoring from October 2015 through September 2018. Maps of inundation at selected water-level altitudes are included to identify the risk to archaeological, cultural, and ecological resources. The monitoring results of the hydrology and chemistry data are interpreted, and the different hydrologic and chemical settings are described. The implications of the study results for management decisions are presented, and suggestions for improving the monitoring network are included.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215117","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"McCoy, K.J., Rice, K.C., Rickles, E., Frederick, D., Cramer, J., and Geyer, D., 2021, Groundwater hydrology and chemistry of Jamestown Island, Virginia—Potential effects of tides, storm surges, and sea-level rise on archaeological, cultural, and ecological resources: U.S. Geological Survey Scientific Investigations Report 2021–5117, 50 p., https://doi.org/10.3133/sir20215117.","productDescription":"Report: x, 50 p.; Data Release","numberOfPages":"50","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-115948","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":391337,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K7X61F","text":"USGS data release","linkHelpText":"Field parameters and water levels from monitoring sites at Jamestown Island, Virginia, 2016 - 2018"},{"id":391336,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5117/sir20215117.pdf","text":"Report","size":"14.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5117"},{"id":391335,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5117/coverthb2.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Jamestown Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.86309814453125,\n 37.16797725379289\n ],\n [\n -76.48544311523436,\n 37.16797725379289\n ],\n [\n -76.48544311523436,\n 37.36033397019125\n ],\n [\n -76.86309814453125,\n 37.36033397019125\n ],\n [\n -76.86309814453125,\n 37.16797725379289\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
This report provides a step-by-step method for compiling hydraulic fracturing data in the United States from the IHS Markit, 2019, U.S. Well History and Production Relational Database. Data on hydraulically fractured wells include their location (geologic province, State, county), well type (oil or gas), orientation (directional, horizontal, or vertical), spud date, completion date and the hydraulic fracturing treatments, treatment fluids types, treatment fluid volumes, additive types, agent types (“proppants”), and proppant amounts injected. This method also describes how to associate each unique well with the hydraulic fracturing treatments to provide an indication of the total amount of all treatment fluids injected into a well for hydraulic fracturing and the volume of each individual treatment fluid type injected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211090","usgsCitation":"Varela, B.A., and Gallegos, T.J., 2021, Method for compiling temporally and spatially aggregated data on hydraulic fracturing—Treatments and wells: U.S. Geological Survey Open-File Report 2021–1090, 30 p., https://doi.org/10.3133/ofr20211090.","productDescription":"vi, 30 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118145","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":436123,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P933SF16","text":"USGS data release","linkHelpText":"Spatial and Temporal Data on Hydraulic Fracturing Fluid Types and Amounts Injected into Oil and Gas Wells Across the U.S., 2015-2019"},{"id":391203,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1090/coverthb.jpg"},{"id":391204,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1090/ofr20211090.pdf","text":"Report","size":"730 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1090"}],"contact":"Geology, Energy and Minerals Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
A concern about statistics in wildlife studies, particularly of endangered and threatened species, is whether the data collected meet the assumptions necessary for the use of parametric statistics. This study identified published papers on the nine endangered and six threatened species found only on Puerto Rico using five different databases. The results from the Zoological Record database identified the most articles, including all identified by the other databases. Of the 222 identified articles, 108 included some form of statistics, 26 used only descriptive statistics, 34 included only parametric statistics, 26 used only nonparametric statistics, and 22 reported both parametric and nonparametric statistical analyses. This meta-study showed that the percentage of articles with no statistical treatment decreased in the most recent 20 years, and that although parametric statistics continue to be the most commonly used in published wildlife studies of Puerto Rican wildlife, there has been a distinct increase in the use of nonparametric statistics over time.
","language":"English","publisher":"College of Arts and Sciences of the University of Puerto Rico, Mayagüez","doi":"10.18475/cjos.v51i2.a10","usgsCitation":"Rivera, S., Alpi, K., Collazo, J.A., and Stoskopf, M., 2021, Statistical methods used in research concerning endangered and threatened animal species of Puerto Rico: A meta-study: Caribbean Journal of Science, v. 51, no. 2, p. 225-241, https://doi.org/10.18475/cjos.v51i2.a10.","productDescription":"17 p.","startPage":"225","endPage":"241","ipdsId":"IP-130807","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.27875878556765,\n 18.57988531442932\n ],\n [\n -67.27875878556765,\n 17.89880355641135\n ],\n [\n -65.58075886661939,\n 17.89880355641135\n ],\n [\n -65.58075886661939,\n 18.57988531442932\n ],\n [\n -67.27875878556765,\n 18.57988531442932\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rivera, S.J.","contributorId":341725,"corporation":false,"usgs":false,"family":"Rivera","given":"S.J.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":908833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpi, K.M.","contributorId":341726,"corporation":false,"usgs":false,"family":"Alpi","given":"K.M.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":908834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collazo, Jaime A. 0000-0002-1816-7744","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":217287,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime","email":"","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stoskopf, M.K.","contributorId":341728,"corporation":false,"usgs":false,"family":"Stoskopf","given":"M.K.","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":908836,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70230154,"text":"70230154 - 2021 - Distribution of tiger salamanders in northern Sonora, Mexico: Comparison of sampling methods and possible implications for an endangered subspecies","interactions":[],"lastModifiedDate":"2022-04-01T22:09:52.066304","indexId":"70230154","displayToPublicDate":"2021-11-03T09:17:49","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":751,"text":"Amphibia-Reptilia","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of tiger salamanders in northern Sonora, Mexico: Comparison of sampling methods and possible implications for an endangered subspecies","docAbstract":"Many aquatic species in the arid USA-Mexico borderlands region are imperiled, but limited information on distributions and threats often hinders management. To provide information on the distribution of the Western Tiger Salamander (Ambystoma mavortium), including the USA-federally endangered Sonoran Tiger Salamander (Ambystoma mavortium stebbinsi), we used traditional (seines, dip-nets) and modern (environmental DNA [eDNA]) methods to sample 91 waterbodies in northern Sonora, Mexico, during 2015-2018. The endemic Sonoran Tiger Salamander is threatened by introgressive hybridization and potential replacement by another sub-species of the Western Tiger Salamander, the non-native Barred Tiger Salamander (A. m. mavortium). Based on occupancy models that accounted for imperfect detection, eDNA sampling provided a similar detection probability (0.82 [95% CI: 0.56-0.94]) as seining (0.83 [0.46-0.96]) and much higher detection than dip-netting (0.09 [0.02-0.23]). Volume of water filtered had little effect on detection, possibly because turbid sites had greater densities of salamanders. Salamanders were estimated to occur at 51 sites in 3 river drainages in Sonora. These results indicate tiger salamanders are much more widespread in northern Sonora than previously documented, perhaps aided by changes in land and water management practices. However, because the two subspecies of salamanders cannot be reliably distinguished based on morphology or eDNA methods that are based on mitochondrial DNA, we are uncertain if we detected only native genotypes or if we documented recent invasion of the area by the non-native sub-species. Thus, there is an urgent need for methods to reliably distinguish the subspecies so managers can identify appropriate interventions.
","language":"English","publisher":"Brill","doi":"10.1163/15685381-bja10072","usgsCitation":"Hossack, B., Lemos-Espinal, J.A., Sigafus, B., Muths, E., Carreon Arroyo, G., Toyos Martinez, D., Hurtado Felix, D., Molina Padilla, G., Goldberg, C., Jones, T.R., Sredl, M.J., Chambert, T., and Rorabaugh, J.C., 2021, Distribution of tiger salamanders in northern Sonora, Mexico: Comparison of sampling methods and possible implications for an endangered subspecies: Amphibia-Reptilia, v. 43, p. 13-23, https://doi.org/10.1163/15685381-bja10072.","productDescription":"11 p.","startPage":"13","endPage":"23","ipdsId":"IP-108340","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":450280,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":397935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","state":"Sonora","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.8515625,\n 30.524413269923986\n ],\n [\n -108.6328125,\n 30.221101852485987\n ],\n [\n -108.80859375,\n 31.50362930577303\n ],\n [\n -111.181640625,\n 31.39115752282472\n ],\n [\n -114.78515624999999,\n 32.54681317351514\n ],\n [\n -114.9169921875,\n 31.952162238024975\n ],\n [\n -114.3017578125,\n 31.57853542647338\n ],\n [\n -113.8623046875,\n 31.541089879585808\n ],\n [\n -113.15917968749999,\n 31.240985378021307\n ],\n [\n -112.8515625,\n 30.524413269923986\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":229347,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":839312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lemos-Espinal, Julio A.","contributorId":237891,"corporation":false,"usgs":false,"family":"Lemos-Espinal","given":"Julio","email":"","middleInitial":"A.","affiliations":[{"id":47636,"text":"FES Iztacala UNAM","active":true,"usgs":false}],"preferred":false,"id":839313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sigafus, Brent H. 0000-0002-7422-8927","orcid":"https://orcid.org/0000-0002-7422-8927","contributorId":264740,"corporation":false,"usgs":true,"family":"Sigafus","given":"Brent H.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":839314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":839315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carreon Arroyo, Gerardo","contributorId":289549,"corporation":false,"usgs":false,"family":"Carreon Arroyo","given":"Gerardo","affiliations":[{"id":62189,"text":"Naturalia","active":true,"usgs":false}],"preferred":false,"id":839316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Toyos Martinez, Daniel","contributorId":167619,"corporation":false,"usgs":false,"family":"Toyos Martinez","given":"Daniel","email":"","affiliations":[{"id":24783,"text":"Naturalia, A.C., El Cajon # 9 Col., Santa Fe, C.P. 83249, Hermosillo, Sonora 83299, Mexico","active":true,"usgs":false}],"preferred":false,"id":839317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hurtado Felix, David","contributorId":289550,"corporation":false,"usgs":false,"family":"Hurtado Felix","given":"David","affiliations":[],"preferred":false,"id":839318,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Molina Padilla, Guillermo","contributorId":289551,"corporation":false,"usgs":false,"family":"Molina Padilla","given":"Guillermo","email":"","affiliations":[{"id":37275,"text":"none","active":true,"usgs":false}],"preferred":false,"id":839319,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goldberg, Caren S.","contributorId":289552,"corporation":false,"usgs":false,"family":"Goldberg","given":"Caren S.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":839320,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jones, T. R.","contributorId":289553,"corporation":false,"usgs":false,"family":"Jones","given":"T.","email":"","middleInitial":"R.","affiliations":[{"id":54870,"text":"Arizona Game and Fish Dept","active":true,"usgs":false}],"preferred":false,"id":839321,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sredl, M. J.","contributorId":289554,"corporation":false,"usgs":false,"family":"Sredl","given":"M.","email":"","middleInitial":"J.","affiliations":[{"id":54870,"text":"Arizona Game and Fish Dept","active":true,"usgs":false}],"preferred":false,"id":839322,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chambert, Thierry 0000-0002-9450-9080 tchambert@usgs.gov","orcid":"https://orcid.org/0000-0002-9450-9080","contributorId":191979,"corporation":false,"usgs":false,"family":"Chambert","given":"Thierry","email":"tchambert@usgs.gov","affiliations":[],"preferred":false,"id":839323,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rorabaugh, J. C.","contributorId":289555,"corporation":false,"usgs":false,"family":"Rorabaugh","given":"J.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":839324,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70225712,"text":"70225712 - 2021 - Seven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs","interactions":[],"lastModifiedDate":"2021-11-04T14:03:24.155896","indexId":"70225712","displayToPublicDate":"2021-11-03T08:55:37","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Seven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs","docAbstract":"Observational data of coastal change over much of the Arctic are limited largely due to its immensity, remoteness, harsh environment, and restricted periods of sunlight and ice-free conditions. Barter Island, Alaska, is one of the few locations where an extensive, observational dataset exists, which enables a detailed assessment of the trends and patterns of coastal change over decadal to annual time scales. Coastal bluff and shoreline positions were delineated from maps, aerial photographs, and satellite imagery acquired between 1947 and 2020, and at a nearly annual rate since 2004. Rates and patterns of shoreline and bluff change varied widely over the observational period. Shorelines showed a consistent trend of southerly erosion and westerly extension of the western termini of Barter Island and Bernard Spit, which has accelerated since at least 2000. The 3.2 km long stretch of ocean-exposed coastal permafrost bluffs retreated on average 114 m and at a maximum of 163 m at an average long-term rate (70 year) of 1.6 ± 0.1 m/yr. The long-term retreat rate was punctuated by individual years with retreat rates up to four times higher (6.6 ± 1.9 m/yr; 2012–2013) and both long-term (multidecadal) and short-term (annual to semiannual) rates showed a steady increase in retreat rates through time, with consistently high rates since 2015. A best-fit polynomial trend indicated acceleration in retreat rates that was independent of the large spatial and temporal variations observed on an annual basis. Rates and patterns of bluff retreat were correlated to incident wave energy and air and water temperatures. Wave energy was found to be the dominant driver of bluff retreat, followed by sea surface temperatures and warming air temperatures that are considered proxies for evaluating thermo-erosion and denudation. Normalized anomalies of cumulative wave energy, duration of open water, and air and sea temperature showed at least three distinct phases since 1979: a negative phase prior to 1987, a mixed phase between 1987 and the early to late 2000s, followed by a positive phase extending to 2020. The duration of the open-water season has tripled since 1979, increasing from approximately 40 to 140 days. Acceleration in retreat rates at Barter Island may be related to increases in both thermodenudation, associated with increasing air temperature, and the number of niche-forming and block-collapsing episodes associated with higher air and water temperature, more frequent storms, and longer ice-free conditions in the Beaufort Sea.
","language":"English","publisher":"MDPI","doi":"10.3390/rs13214420","usgsCitation":"Gibbs, A.E., Erikson, L.H., Jones, B., Richmond, B., and Engelstad, A.C., 2021, Seven decades of coastal change at Barter Island, Alaska: Exploring the importance of waves and temperature on erosion of coastal permafrost bluffs: Remote Sensing, v. 13, no. 21, 4420, 25 p., https://doi.org/10.3390/rs13214420.","productDescription":"4420, 25 p.","ipdsId":"IP-127799","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450281,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs13214420","text":"Publisher Index Page"},{"id":391383,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Barter Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -143.82545471191406,\n 70.08547429861382\n ],\n [\n -143.4814453125,\n 70.08547429861382\n ],\n [\n -143.4814453125,\n 70.1478274118401\n ],\n [\n -143.82545471191406,\n 70.1478274118401\n ],\n [\n -143.82545471191406,\n 70.08547429861382\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"21","noUsgsAuthors":false,"publicationDate":"2021-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826380,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826381,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Benjamin M. 0000-0002-1517-4711","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":208625,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin M.","affiliations":[{"id":37848,"text":"Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":true,"id":826382,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richmond, Bruce M. 0000-0002-0056-5832","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":268302,"corporation":false,"usgs":false,"family":"Richmond","given":"Bruce M.","affiliations":[{"id":55619,"text":"USGS Pacific Coastal and Marine Science Center (emeritus, dec.)","active":true,"usgs":false}],"preferred":false,"id":826383,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Engelstad, Anita C 0000-0002-0211-4189","orcid":"https://orcid.org/0000-0002-0211-4189","contributorId":268303,"corporation":false,"usgs":true,"family":"Engelstad","given":"Anita","email":"","middleInitial":"C","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826384,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70226135,"text":"70226135 - 2021 - Expanding freshwater biologger studies to view fish as environmental sensing platforms","interactions":[],"lastModifiedDate":"2022-01-06T17:30:38.654159","indexId":"70226135","displayToPublicDate":"2021-11-03T07:01:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2681,"text":"Marine and Freshwater Research","active":true,"publicationSubtype":{"id":10}},"title":"Expanding freshwater biologger studies to view fish as environmental sensing platforms","docAbstract":"While recording fish habitat use by electronic sensors, biologgers can also be viewed as autonomous environmental monitoring systems with the organism as a vehicle. This dual perspective has provided novel results from marine ecosystems, but has not been applied to freshwater ecosystems. To understand limitations in fresh water, we evaluated miniature depth and temperature recorders as aquatic monitoring systems in a Laurentian Great Lake: Erie. As part of an acoustic telemetry study, biologgers were opportunistically implanted in a subsample of walleye Sander vitreus. Biologgers recorded temperature and depth at half-hour intervals for up to 1 year. Recaptures provided six biologgers for analysis of seasonal temperature patterns and lake stratification, key variables for understanding dimictic lakes. Depth-resolved temperature patterns showed close correspondence with independent weather buoy measurements. Because the buoy was deployed late in the season, biologger data provided improved estimates of the start of stratification, which had important implications for understanding development of hypoxia in the hypolimnion. Drawbacks to biologger data included imprecise knowledge of fish location and reliance on tag recoveries from the fishery. Optimistically, our results show how biologgers could be part of a monitoring approach that integrates limnological surveys with fisheries science.
The Anza-Cahuilla groundwater basin located mainly in the semi-arid headwaters of the Santa Margarita River watershed in southern California is the principle source of groundwater for a rural disadvantaged community and two Native American Tribes, the Ramona Band of Cahuilla and the Cahuilla. Groundwater in the study area is derived entirely from precipitation and managing groundwater sustainably requires an accurate assessment of the water balance components, yet long-term estimates do not exist. Demand for groundwater in the region has increased and groundwater quality has decreased due to population growth and increased irrigated cropland. To characterize monthly long-term natural recharge and runoff estimates, a physically-based water balance model (Basin Characterization Model) was locally calibrated and validated using nearby streamgages and published estimates of climatic and hydrologic variables. The average modeled annual recharge and runoff from 1981 to 2010 was 5.4 × 106 and 1.2 × 107 m3, respectively, for the study area. Recharge and runoff do not reliably occur in large amounts every year and recharge rarely occurs in the groundwater basin footprint. These long-term estimates can be used by water managers, stakeholders, and Native American Tribes to develop plans for sustainable management of future water resources, and as inputs to a three-dimensional groundwater model.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12971","usgsCitation":"Stern, M.A., Flint, L.E., Flint, A.L., and Christensen, A.H., 2021, A basin-scale approach to estimating recharge in the desert: Anza-Cahuilla groundwater basin, CA: Journal of the American Water Resources Association, v. 57, no. 6, p. 990-1003, https://doi.org/10.1111/1752-1688.12971.","productDescription":"14 p.","startPage":"990","endPage":"1003","ipdsId":"IP-119217","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":450287,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1752-1688.12971","text":"Publisher Index Page"},{"id":436125,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BAMCP4","text":"USGS data release","linkHelpText":"Basin Characterization Model (BCMv8) monthly recharge and runoff for the Anza-Cahuilla Groundwater Basin, California"},{"id":391385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Anza-Cahuilla groundwater basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.9166,\n 33.3333\n ],\n [\n -116.25,\n 33.3333\n ],\n [\n -116.25,\n 33.75\n ],\n [\n -116.9166,\n 33.75\n ],\n [\n -116.9166,\n 33.3333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"57","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":826394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christensen, Allen H. 0000-0002-7061-5591 ahchrist@usgs.gov","orcid":"https://orcid.org/0000-0002-7061-5591","contributorId":1510,"corporation":false,"usgs":true,"family":"Christensen","given":"Allen","email":"ahchrist@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826395,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70225706,"text":"70225706 - 2021 - Modeling marsh dynamics using a 3-D coupled wave-flow-sediment model","interactions":[],"lastModifiedDate":"2021-11-04T13:24:32.427815","indexId":"70225706","displayToPublicDate":"2021-11-02T08:18:16","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Modeling marsh dynamics using a 3-D coupled wave-flow-sediment model","docAbstract":"Salt marshes are dynamic biogeomorphic systems that respond to external physical factors, including tides, sediment transport, and waves, as well as internal processes such as autochthonous soil formation. Predicting the fate of marshes requires a modeling framework that accounts for these processes in a coupled fashion. In this study, we implement two new marsh dynamic processes in the 3-D COAWST (coupled-ocean-atmosphere-wave sediment transport) model. The processes added are the erosion of the marsh edge scarp caused by lateral wave thrust from surface waves and vertical accretion driven by organic growth on the marsh platform. The sediment released from the marsh causes a change in bathymetry, thereby modifying the wave-energy reaching the marsh edge. Marsh vertical accretion due to biomass production is considered for a single vegetation species and is determined by the hydroperiod parameters (tidal datums) and the elevation of the marsh cells. Tidal datums are stored at user-defined intervals as a hindcast (on the order of days) and used to update the vertical growth formulation. Idealized domains are utilized to verify the lateral wave thrust formulation and show the dynamics of lateral wave erosion leading to horizontal retreat of marsh edge. The simulations of Reedy and Dinner Creeks within the Barnegat Bay estuary system demonstrate the model capability to account for both lateral wave erosion and vertical accretion due to organic growth in a realistic marsh complex. The simulations show that majority of accretion over the marsh complex occurs due to organic production while most estuarine sediment deposition occurs along the channel edges. The ability of the model to capture the fate of the sediment can be extended to model future storm and relative sea level rise (RSLR) scenarios.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2021.740921","usgsCitation":"Kalra, T., Ganju, N., Aretxabaleta, A., Carr, J., Defne, Z., and Moriarty, J., 2021, Modeling marsh dynamics using a 3-D coupled wave-flow-sediment model: Frontiers in Marine Science, v. 8, 740921, 20 p., https://doi.org/10.3389/fmars.2021.740921.","productDescription":"740921, 20 p.","ipdsId":"IP-131349","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":450291,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2021.740921","text":"Publisher Index Page"},{"id":436127,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9QO091Z","text":"USGS data release","linkHelpText":"COAWST model of Barnegat Bay creeks to demonstrate marsh dynamics"},{"id":436126,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94HYOGQ","text":"USGS data release","linkHelpText":"Idealized COAWST numerical model for testing marsh wave thrust and lateral retreat dynamics routines"},{"id":391380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2021-11-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":826399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826354,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":826355,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":826356,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moriarty, Julia 0000-0003-1087-6180","orcid":"https://orcid.org/0000-0003-1087-6180","contributorId":261307,"corporation":false,"usgs":false,"family":"Moriarty","given":"Julia","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":826357,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048926,"text":"sim3143 - 2021 - Geologic map of the State of Hawaii","interactions":[],"lastModifiedDate":"2021-11-02T15:48:34.21696","indexId":"sim3143","displayToPublicDate":"2021-11-02T08:01:21","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3143","displayTitle":"Geologic Map of the State of Hawaiʻi","title":"Geologic map of the State of Hawaii","docAbstract":"This geologic map and its digital databases present the geology of the eight major islands of the State of Hawaiʻi. The map should serve as a useful guide to anyone studying the geologic setting and history of Hawai‘i, including ground- and surface-water resources, economic deposits, and landslide or volcanic hazards. Its presentation in digital format allows the rapid application of geologic knowledge when conducting field work; analyzing land-use or engineering problems; studying onshore or nearshore biologic communities; or simply understanding the relation between the geology, scenery, and cultural history of the Hawaiian paradise.
The map includes a Description of Map Units, which describes the lithologic characteristics and distribution of the geologic deposits. A Correlation of Map Units shows how the different geologic formations are related to each other stratigraphically. A fairly complete geospatial database of the radiometric ages and geochemical analyses has been compiled from findings published over the past 100 years by numerous Earth scientists working across the island chain.
Contact HVO
Hawaiian Volcano Observatory
U.S. Geological Survey
1266 Kamehameha Avenue
Suite A-8
Hilo, HI 96720
Excess nutrients transported by the Mississippi River (MR) contribute to hypoxia in the Gulf of Mexico. Nutrient balances are key drivers to river nutrient loads and represent inputs (fertilizer, manure, deposition, wastewater, N-fixation, and weathering) minus outputs (nutrient uptake and removal in harvest, and N emissions). Here, we quantified annual changes in nitrogen (N) and phosphorus (P) river loads and nutrient balances at the MR Outlet and documented that the river load response to watershed nutrient balances shifted between 1975 and 2017. Annual nutrient balances and river loads were positively correlated between 1975 and 1985, but after, a disconnect between both the N and P balances and river loads emerged, and the subsequent river load patterns were different for N versus P. We evaluated the relative impacts of legacy nutrients and other latent factors, for which data were not available, on river nutrient load trends. Our analysis showed that in the case of N, latent factors were potentially just as important in explaining changes in river nutrient loads over time as N balances, and in the case of P, they were even more important. We hypothesized that these factors included implementation of best management practices, changes in watershed buffering capacity, the effects of tile drainage, or increased precipitation. Our analytical approach shows promise for the investigation of drivers of water quality trends that are not well-represented in typical national scale geospatial datasets.
The Ziegler Reservoir fossil site near Snowmass Village, Colorado, provides a rare opportunity to examine environmental conditions in the Rocky Mountains during marine isotope stage (MIS) 4 (71–57 ka). Although recognized as a global-scale cold event, MIS 4 is typically absent from Rocky Mountain glacial chronologies because the geologic evidence was covered or destroyed during the subsequent, and more extensive, MIS 2 (Pinedale; 29–14 ka) glaciation. Ziegler Reservoir lies beyond the Pinedale glacial extent, which allowed for the preservation of a long-lived sequence of eolian sediments deposited in a lacustrine environment that spans from late MIS 6 (ca. 140 ka) through early MIS 3 (ca. 55 ka). Sediments dating to MIS 4 exhibit a significant increase in clay-sized particles, suggesting that the source areas, most likely nearby glacio-fluvial deposits, were enriched with fine-grained material at that time. We hypothesize that the elevated clay content was the result of rock flour production by nearby valley glaciers that were active in the Rocky Mountains during MIS 4. The results of our study illustrate how recognizing indirect evidence of glacial activity can result in a more complete record of past climate conditions than what could be achieved by the study of moraines alone.
No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Islands through time: A human and ecological history of California's northern Channel Islands","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Rowman & Littlefield","usgsCitation":"Muhs, D.R., 2021, Were humans and mammoths on the Channel Islands at the same time?, chap. of Islands through time: A human and ecological history of California's northern Channel Islands, p. 27-28.","productDescription":"2 p.","startPage":"27","endPage":"28","ipdsId":"IP-122621","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":397067,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"northern Channel Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.54473876953125,\n 33.8521697014074\n ],\n [\n -119.40216064453126,\n 33.8521697014074\n ],\n [\n -119.40216064453126,\n 34.093610452768715\n ],\n [\n -120.54473876953125,\n 34.093610452768715\n ],\n [\n -120.54473876953125,\n 33.8521697014074\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Muhs, Daniel R. 0000-0001-7449-251X dmuhs@usgs.gov","orcid":"https://orcid.org/0000-0001-7449-251X","contributorId":1857,"corporation":false,"usgs":true,"family":"Muhs","given":"Daniel","email":"dmuhs@usgs.gov","middleInitial":"R.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":true,"id":837630,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70225597,"text":"ofr20211082 - 2021 - Environmental DNA surveys of Burmese pythons in the Greater Everglades Ecosystem","interactions":[],"lastModifiedDate":"2021-11-02T10:28:55.496708","indexId":"ofr20211082","displayToPublicDate":"2021-11-01T11:42:44","publicationYear":"2021","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":"2021-1082","displayTitle":"Environmental DNA Surveys of Burmese Pythons in the Greater Everglades Ecosystem","title":"Environmental DNA surveys of Burmese pythons in the Greater Everglades Ecosystem","docAbstract":"Improving the probability of detecting invasive giant snakes is vital for the management of emerging or established populations. Burmese pythons occupy thousands of square kilometers of mostly inaccessible habitats in Florida. Environmental DNA (eDNA) methods have been shown to be time and cost effective in a number of systems and may be preferable to traditional detection methods for constrictor snakes, having been shown to be effective at detecting Burmese pythons where traditional and novel detection methods have failed. The purposes of this study were (1) to estimate Burmese python eDNA occurrence in the Greater Everglades Ecosystem based on land-use type; and (2) to conduct preliminary surveys within the Greater Everglades Ecosystem for positive eDNA detections. Twenty-eight sites were sampled in the Greater Everglades Ecosystem, with 5 field replicate samples per site, for a total of 140 water samples collected. Python eDNA was detected in samples from 25 of the 28 sites by using droplet digital polymerase chain reaction amplification. Abiotic parameters were collected and explored, but we found no conclusive relationship among them and python eDNA detections. eDNA monitoring of aquatic habitats can assist in identifying newly colonized areas where pythons have not been previously detected, as well as movement corridors and pathways of dispersal. This information could be used to delimit a population boundary as it expands further to the north in peninsular Florida.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211082","usgsCitation":"Beaver, C.E., Meigs-Friend, G., and Hunter, M.E., 2021, Environmental DNA surveys of Burmese pythons in the Greater Everglades Ecosystem: U.S. Geological Survey Open-File Report 2021–1082, 17 p., https://doi.org/10.3133/ofr20211082.","productDescription":"Report: vi, 17 p.; Data Releases","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-122212","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":390968,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HVM4VQ","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Droplet digital PCR data for environmental DNA surveys of Burmese pythons in the Greater Everglades Ecosystem"},{"id":390967,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1082/ofr20211082.pdf","text":"Report","size":"1.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1082"},{"id":390966,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1082/coverthb.jpg"},{"id":390969,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1082/images"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades Ecosystem","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.84814453125,\n 25.552353652165465\n ],\n [\n -80.87585449218749,\n 24.946219074360055\n ],\n [\n -80.2001953125,\n 25.199970890386\n ],\n [\n -79.8211669921875,\n 26.701452590314393\n ],\n [\n -82.15576171875,\n 26.598351182358265\n ],\n [\n -81.84814453125,\n 25.552353652165465\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
As the human footprint upon the landscape expands, wildlife seeking to avoid human contact are losing the option of altering their spatial distribution and instead are shifting their daily activity patterns to be active at different times than humans. In this study, we used game cameras to evaluate how human development and activity were related to the daily activity patterns of the nine-banded armadillo (Dasypus novemcinctus) along an urban to rural gradient in Arkansas, USA during the winter of 2020–2021. We found that armadillos had substantial behavioral plasticity in regard to the timing of their activity patterns; >95% of armadillo activity was nocturnal at six of the study sites, whereas between 30% and 60% of activity occurred during the day at three other sites. The likelihood of diurnal armadillo activity was best explained by the distance to downtown Fayetteville (the nearest population center) and estimated ambient sound level (both indices of human activity) with armadillos being most active during the day at quiet sites far from Fayetteville. Furthermore, armadillo activity occurred later during the night period (minutes after sunset) at sites near downtown and with higher anthropogenic sound. Anecdotal evidence suggests that the observed activity shift may be in response to not only human activity but also the presence of domestic dogs. Our results provide further evidence that human activity has subtle nonlethal impacts on even common, widespread wildlife species. Because armadillos have low body temperatures and basal metabolism, being active during cold winter nights likely has measurable fitness costs. Nature reserves near human population centers may not serve as safe harbors for wildlife as we intend, and managers could benefit from considering these nonlethal responses in how they manage recreation and visitation in these natural areas.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8257","usgsCitation":"DeGregorio, B.A., Gale, C., Lassiter, E.V., Massey, A., Roberts, C.P., and Veon, J., 2021, Nine-banded armadillo (Dasyrus novemcinctus) activity patterns are influenced by human activity: Ecology and Evolution, v. 11, no. 22, p. 15874-15881, https://doi.org/10.1002/ece3.8257.","productDescription":"8 p.","startPage":"15874","endPage":"15881","ipdsId":"IP-130809","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":450298,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8257","text":"Publisher Index Page"},{"id":397186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","city":"Elkins, Fayetteville","otherGeospatial":"Bear Hollow Nature Preserve, Devil's Den State Park, Devil's Eyebrow Nature Preserve, Hyland Park, Kessler Mountain Regional Park, Lake Wilson, Markham Hill, Sequoyah Woods, Wilson Springs Nature Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.01412963867188,\n 35.99856302536764\n ],\n [\n -94.00314331054688,\n 35.99856302536764\n ],\n [\n -94.00314331054688,\n 36.00786740304298\n ],\n [\n -94.01412963867188,\n 36.00786740304298\n ],\n [\n -94.01412963867188,\n 35.99856302536764\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.1433048248291,\n 36.062387023360785\n ],\n [\n -94.13562297821045,\n 36.062213564390795\n ],\n [\n -94.13527965545654,\n 36.06960257766082\n ],\n [\n -94.13884162902832,\n 36.06956788907914\n ],\n [\n -94.13901329040526,\n 36.06609895366221\n ],\n [\n -94.14317607879639,\n 36.06609895366221\n ],\n [\n -94.1433048248291,\n 36.062387023360785\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.1934084892273,\n 36.10046934925393\n ],\n [\n -94.18853759765625,\n 36.10046934925393\n ],\n [\n -94.18834447860716,\n 36.10282721094111\n ],\n [\n -94.18712139129639,\n 36.10289655874305\n ],\n [\n -94.1862416267395,\n 36.10306992798007\n ],\n [\n -94.18529748916626,\n 36.103416665306405\n ],\n [\n -94.18458938598633,\n 36.10372872759166\n ],\n [\n -94.18252944946289,\n 36.10397144184545\n ],\n [\n -94.18282985687256,\n 36.105306356837275\n ],\n [\n -94.18270111083984,\n 36.10587845631836\n ],\n [\n -94.1823148727417,\n 36.106485223942386\n ],\n [\n -94.181649684906,\n 36.10683194619472\n ],\n [\n -94.18068408966064,\n 36.10705731483805\n ],\n [\n -94.18049097061157,\n 36.10742137051141\n ],\n [\n -94.18441772460938,\n 36.1074560423923\n ],\n [\n -94.18446063995361,\n 36.10894691879306\n ],\n [\n -94.1879153251648,\n 36.10764673746366\n ],\n [\n -94.18797969818114,\n 36.11036842575149\n ],\n [\n -94.18896675109862,\n 36.11040309633153\n ],\n [\n -94.1899538040161,\n 36.110333755156155\n ],\n [\n -94.18986797332764,\n 36.1099697129811\n ],\n [\n -94.19008255004883,\n 36.10924162356909\n ],\n [\n -94.18986797332764,\n 36.10776808863165\n ],\n [\n -94.19008255004883,\n 36.10705731483805\n ],\n [\n -94.190833568573,\n 36.10700530674698\n ],\n [\n -94.19143438339233,\n 36.10658924077877\n ],\n [\n -94.19197082519531,\n 36.10641587930827\n ],\n [\n -94.19255018234253,\n 36.105826447446795\n ],\n [\n -94.19317245483398,\n 36.105739765917654\n ],\n [\n -94.19317245483398,\n 36.10662391302697\n ],\n [\n -94.19433116912842,\n 36.10662391302697\n ],\n [\n -94.19437408447266,\n 36.10544504800317\n ],\n [\n -94.19321537017822,\n 36.10542771162082\n ],\n [\n -94.1934084892273,\n 36.10046934925393\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.46422576904295,\n 35.58501397284422\n ],\n [\n -94.28878784179688,\n 35.57998806651504\n ],\n [\n -94.28604125976562,\n 35.66733803249021\n ],\n [\n -94.23248291015625,\n 35.66594341573466\n ],\n [\n -94.22698974609375,\n 35.78746239087127\n ],\n [\n -94.23625946044922,\n 35.78718388978009\n ],\n [\n -94.23625946044922,\n 35.797487780189684\n ],\n [\n -94.27814483642578,\n 35.79832317220566\n ],\n [\n -94.2791748046875,\n 35.76991491635478\n ],\n [\n -94.28775787353516,\n 35.7696363537892\n ],\n [\n -94.28775787353516,\n 35.76685067447143\n ],\n [\n -94.29668426513672,\n 35.766293526899965\n ],\n [\n -94.29634094238281,\n 35.76295055951789\n ],\n [\n -94.3014907836914,\n 35.76295055951789\n ],\n [\n -94.30217742919922,\n 35.756264203297114\n ],\n [\n -94.4937515258789,\n 35.75988604933661\n ],\n [\n -94.46422576904295,\n 35.58501397284422\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.12618160247801,\n 36.06887411423356\n ],\n [\n -94.11334991455077,\n 36.06887411423356\n ],\n [\n -94.11334991455077,\n 36.075620815001415\n ],\n [\n -94.12618160247801,\n 36.075620815001415\n ],\n [\n -94.12618160247801,\n 36.06887411423356\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.21892166137694,\n 36.02119713497088\n ],\n [\n -94.21767711639404,\n 36.02123184487143\n ],\n [\n -94.21759128570555,\n 36.020468223527565\n ],\n [\n -94.21098232269287,\n 36.02036409277097\n ],\n [\n -94.21085357666016,\n 36.02206487789787\n ],\n [\n -94.20540332794188,\n 36.02206487789787\n ],\n [\n -94.20540332794188,\n 36.02012112047045\n ],\n [\n -94.20257091522217,\n 36.02022525154813\n ],\n [\n -94.20179843902586,\n 36.02005169967559\n ],\n [\n -94.20128345489502,\n 36.02255080976299\n ],\n [\n -94.20051097869872,\n 36.02366149991602\n ],\n [\n -94.19978141784668,\n 36.024390381820304\n ],\n [\n -94.199481010437,\n 36.02543162998694\n ],\n [\n -94.19939517974854,\n 36.02737525641319\n ],\n [\n -94.19780731201172,\n 36.02734054921891\n ],\n [\n -94.19699192047119,\n 36.02865941185233\n ],\n [\n -94.19883728027342,\n 36.029596485042966\n ],\n [\n -94.20085430145264,\n 36.02883294476566\n ],\n [\n -94.20493125915527,\n 36.02900647729672\n ],\n [\n -94.20578956604004,\n 36.02942295381161\n ],\n [\n -94.20681953430176,\n 36.02956177882728\n ],\n [\n -94.20673370361327,\n 36.03154000871768\n ],\n [\n -94.2063045501709,\n 36.03178294580541\n ],\n [\n -94.20613288879395,\n 36.03372641553364\n ],\n [\n -94.20493125915527,\n 36.03487165202541\n ],\n [\n -94.20960903167725,\n 36.03494105976244\n ],\n [\n -94.20973777770996,\n 36.03320584798705\n ],\n [\n -94.21166896820067,\n 36.03320584798705\n ],\n [\n -94.21166896820067,\n 36.03511457883741\n ],\n [\n -94.21870708465576,\n 36.035183986360344\n ],\n [\n -94.21862125396729,\n 36.03341407541855\n ],\n [\n -94.2208957672119,\n 36.03341407541855\n ],\n [\n -94.22093868255615,\n 36.03136648176773\n ],\n [\n -94.22098159790039,\n 36.029596485042966\n ],\n [\n -94.22059535980225,\n 36.028728825063546\n ],\n [\n -94.2207670211792,\n 36.02799998329553\n ],\n [\n -94.22492980957031,\n 36.028034690199284\n ],\n [\n -94.22497272491455,\n 36.025049840590285\n ],\n [\n -94.2238998413086,\n 36.024980424137595\n ],\n [\n -94.2233419418335,\n 36.02470275771518\n ],\n [\n -94.22329902648926,\n 36.024216839121344\n ],\n [\n -94.21892166137694,\n 36.024078004686984\n ],\n [\n -94.21892166137694,\n 36.02119713497088\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.13759708404541,\n 36.00422216200329\n ],\n [\n -94.13802623748778,\n 35.993215983301525\n ],\n [\n -94.12901401519775,\n 35.99297292732201\n ],\n [\n -94.1291856765747,\n 35.98943116951363\n ],\n [\n -94.1244649887085,\n 35.989292273810364\n ],\n [\n -94.12412166595459,\n 36.000403157297654\n ],\n [\n -94.13300514221191,\n 36.00057675243315\n ],\n [\n -94.13296222686768,\n 36.004187444611766\n ],\n [\n -94.13759708404541,\n 36.00422216200329\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.2033863067627,\n 36.05666267544504\n ],\n [\n -94.18012619018555,\n 36.05666267544504\n ],\n [\n -94.18012619018555,\n 36.07275917455547\n ],\n [\n -94.2033863067627,\n 36.07275917455547\n ],\n [\n -94.2033863067627,\n 36.05666267544504\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.23385620117188,\n 36.41914137852475\n ],\n [\n -94.21398639678954,\n 36.41914137852475\n ],\n [\n -94.21398639678954,\n 36.432608386568795\n ],\n [\n -94.23385620117188,\n 36.432608386568795\n ],\n [\n -94.23385620117188,\n 36.41914137852475\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.01674747467041,\n 36.438926715882836\n ],\n [\n -93.97868156433105,\n 36.438926715882836\n ],\n [\n -93.97868156433105,\n 36.45960442572789\n ],\n [\n -94.01674747467041,\n 36.45960442572789\n ],\n [\n -94.01674747467041,\n 36.438926715882836\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"22","noUsgsAuthors":false,"publicationDate":"2021-11-03","publicationStatus":"PW","contributors":{"authors":[{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":838088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gale, C.","contributorId":288233,"corporation":false,"usgs":false,"family":"Gale","given":"C.","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":838089,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lassiter, E. V.","contributorId":288228,"corporation":false,"usgs":false,"family":"Lassiter","given":"E.","email":"","middleInitial":"V.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":838090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Massey, A.","contributorId":288235,"corporation":false,"usgs":false,"family":"Massey","given":"A.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":838091,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":838093,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Veon, J.","contributorId":288245,"corporation":false,"usgs":false,"family":"Veon","given":"J.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":838092,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226952,"text":"70226952 - 2021 - Mapping multivariate ore occurrence data with correspondence analysis","interactions":[],"lastModifiedDate":"2022-01-20T17:02:47.589658","indexId":"70226952","displayToPublicDate":"2021-11-01T10:55:44","publicationYear":"2021","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Mapping multivariate ore occurrence data with correspondence analysis","docAbstract":"Correspondence analysis is a multivariate method that can be applied to mineral abundance data. Ore mineral assemblages from broadly underutilized prospect and occurrence data can be treated as geochemical anomalies, projected to low-dimensional space, and returned into map view. This approach could have applications for mineral prospectivity mapping and delineation of permissive areas during mineral assessments.","largerWorkTitle":"Abstract proceedings: Mineral prospectivity and exploration targeting – MinProXT 2021 webinar","conferenceTitle":"Mineral Prospectivity and Exploration Targeting – MinProXT 2021 Webinar","conferenceDate":"Oct 12-13, 2021 & Oct 26-27, 2021","language":"English","publisher":"Geological Survey of Finland","usgsCitation":"Rosera, J.M., 2021, Mapping multivariate ore occurrence data with correspondence analysis, in Abstract proceedings: Mineral prospectivity and exploration targeting – MinProXT 2021 webinar, Oct 12-13, 2021 & Oct 26-27, 2021, p. 63-66.","productDescription":"4 p.","startPage":"63","endPage":"66","ipdsId":"IP-130325","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":394592,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":393282,"type":{"id":15,"text":"Index Page"},"url":"https://tupa.gtk.fi/raportti/arkisto/57_2021.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":828922,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}