The trophic ecology of lake charr Salvelinus namaycush morphotypes from small and large lakes within their native and introduced ranges is reviewed over the past 50 years. The lake charr is an apex predator in most habitats it occupies, where it plays a significant role in defining food webs. While often considered piscivores, lake charr feed on a range of aquatic prey throughout their life history, including zooplankton, benthic invertebrates, and fish, as well as terrestrial insects, mammals, birds, amphibians, and reptiles. Lake charr diets that vary within morphotypes among lakes and among sympatric morphotypes reflect differences in habitat use, prey availability, and individual preferences. Temporal variability in diet can result from seasonal prey pulses, thermal barriers, and long-term prey dynamics. Lake charr adapt quickly to consume invasive prey fishes, and often decimate native prey fishes and other piscivores in lakes into which they are introduced. Salient research topics in lake charr trophic ecology include: (1) how best to quantify spatial and temporal trophic niche space; and, (2) how changing environmental conditions, such as invasive species and lake warming, will influence lake charr feeding and broader lake food-web dynamics.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The lake charr Salvelinus namaycush: Biology, ecology, distribution, and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-62259-6_9","usgsCitation":"Vinson, M., Chavarie, L., Rosinski, C.L., and Swanson, H.K., 2021, Trophic ecology, chap. of The lake charr Salvelinus namaycush: Biology, ecology, distribution, and management, p. 287-314, https://doi.org/10.1007/978-3-030-62259-6_9.","productDescription":"28 p.","startPage":"287","endPage":"314","ipdsId":"IP-101993","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":385200,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":809627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chavarie, Louise","contributorId":156227,"corporation":false,"usgs":false,"family":"Chavarie","given":"Louise","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":809629,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosinski, Caroline Lynn 0000-0003-3635-2748","orcid":"https://orcid.org/0000-0003-3635-2748","contributorId":248618,"corporation":false,"usgs":true,"family":"Rosinski","given":"Caroline","email":"","middleInitial":"Lynn","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":814482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Swanson, Heidi K.","contributorId":203350,"corporation":false,"usgs":false,"family":"Swanson","given":"Heidi","email":"","middleInitial":"K.","affiliations":[{"id":6655,"text":"University of Waterloo","active":true,"usgs":false}],"preferred":false,"id":809628,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70221288,"text":"70221288 - 2021 - Distribution","interactions":[],"lastModifiedDate":"2021-06-09T15:51:04.676002","indexId":"70221288","displayToPublicDate":"2021-03-04T10:47:50","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Distribution","docAbstract":"The lake charr Salvelinus namaycush is restricted in its native distribution to oligotrophic fresh waters of northern North America largely within the extent of the Pleistocene glaciations. It is the only freshwater species in northwest North America that does not occur in Siberia. A GIS-based native occurrence map linked to the HydroLAKES database does not extend the lake charr range but provides more comprehensive occurrence data than previous maps. The total waterbody area of lakes occupied by lake charr (451,304 km2) is 40% of the total waterbody area across the range. Lake charr occur from 42.020901 latitude in the south to 74.420800 in the north and from −62.700000 longitude in the east to −161.173090 in the west. Lake charr lakes range in surface area from 3.4 to 8,210,000 ha (mean = 9715 ha; median = 191 ha), maximum depth from 2.7 to 614 m, and elevation from sea level to 2035 m ASL (mean = 381 m; median = 366 m). Glaciation, water temperature, dissolved oxygen, depth, and nutrient content are the main variables associated with lake charr native distribution in lakes. Life history variation, physiology, and ecological opportunity are the most likely drivers of lake charr dispersal and colonization.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The lake charr Salvelinus namaycush: Biology, ecology, distribution, and management","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-62259-6_2","usgsCitation":"Muir, A.M., Bennion, D., Hansen, M.J., Riley, S., and Gunn, J., 2021, Distribution, chap. 2 of The lake charr Salvelinus namaycush: Biology, ecology, distribution, and management, v. 39, p. 13-40, https://doi.org/10.1007/978-3-030-62259-6_2.","productDescription":"28 p.","startPage":"13","endPage":"40","ipdsId":"IP-116034","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":386348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","noUsgsAuthors":false,"publicationDate":"2021-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Muir, Andrew M.","contributorId":176177,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":817246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennion, David 0000-0003-4927-4195 dbennion@usgs.gov","orcid":"https://orcid.org/0000-0003-4927-4195","contributorId":149533,"corporation":false,"usgs":true,"family":"Bennion","given":"David","email":"dbennion@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":817247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Michael J","contributorId":260100,"corporation":false,"usgs":false,"family":"Hansen","given":"Michael","email":"","middleInitial":"J","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":817248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Riley, Stephen 0000-0002-8968-8416","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":236841,"corporation":false,"usgs":false,"family":"Riley","given":"Stephen","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":817249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gunn, John","contributorId":197606,"corporation":false,"usgs":false,"family":"Gunn","given":"John","affiliations":[],"preferred":false,"id":817250,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227736,"text":"70227736 - 2021 - Southwestern fish and aquatic systems: The climate challenge","interactions":[],"lastModifiedDate":"2022-01-28T16:29:16.917343","indexId":"70227736","displayToPublicDate":"2021-03-04T10:19:58","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"9","title":"Southwestern fish and aquatic systems: The climate challenge","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Standing between life and extinction: Ethics and ecology of conserving aquatic species in North American deserts","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of Chicago Press","usgsCitation":"Overpeck, J.T., and Bonar, S.A., 2021, Southwestern fish and aquatic systems: The climate challenge, chap. 9 of Standing between life and extinction: Ethics and ecology of conserving aquatic species in North American deserts, p. 137-152.","productDescription":"16 p.","startPage":"137","endPage":"152","ipdsId":"IP-088747","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395070,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Overpeck, Jonathan T.","contributorId":146162,"corporation":false,"usgs":false,"family":"Overpeck","given":"Jonathan","email":"","middleInitial":"T.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":832149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":831987,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218709,"text":"70218709 - 2021 - Final report to SCEC on the October 27, 2020 SCEC workshop ‘dynamic rupture TAG – The 2020 ingredients workshop – Rock properties (SCEC rroject 20188)’","interactions":[],"lastModifiedDate":"2021-03-08T15:57:51.70109","indexId":"70218709","displayToPublicDate":"2021-03-04T09:57:39","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":251,"text":"Final Report","active":false,"publicationSubtype":{"id":4}},"title":"Final report to SCEC on the October 27, 2020 SCEC workshop ‘dynamic rupture TAG – The 2020 ingredients workshop – Rock properties (SCEC rroject 20188)’","docAbstract":"This workshop was the third in our series of four SCEC5 workshops designed to evaluate the importance of each of the four ingredients required for dynamic earthquake rupture simulations. The four ingredients are: fault geometry, fault friction, rock properties, and initial stress conditions (Figure 1). The previous two workshops in the ‘ingredients’ series were the November 2018 SCEC workshop that focused on ingredient #1, fault geometry, and the January 2020 SCEC workshop that focused on ingredient #2, fault friction. This October 2020 workshop focused on ingredient #3, rock properties. This workshop included presentations about how our choices of velocity structures and off-fault yielding affect computationally simulated earthquake rupture behavior and ground motion. We also had one presentation that introduced everyone to a new 3D rupture dynamics benchmark that simulates thermal pressurization, and we were shown the results from the 5 codes that had simulated this benchmark by the time of the workshop.","language":"English","publisher":"Southern California Earthquake Center","usgsCitation":"Harris, R.A., and Barall, M., 2021, Final report to SCEC on the October 27, 2020 SCEC workshop ‘dynamic rupture TAG – The 2020 ingredients workshop – Rock properties (SCEC rroject 20188)’: Final Report, 7 p.","productDescription":"7 p.","ipdsId":"IP-125500","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":384228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":384213,"type":{"id":15,"text":"Index Page"},"url":"https://files.scec.org/s3fs-public/reports/2020/20188_report.pdf?niPbPTKd7ZibCcpVhd7CXi30qVqS5i8X"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Ruth A. 0000-0002-9247-0768 harris@usgs.gov","orcid":"https://orcid.org/0000-0002-9247-0768","contributorId":786,"corporation":false,"usgs":true,"family":"Harris","given":"Ruth","email":"harris@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":811461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barall, Michael 0000-0001-7724-8563","orcid":"https://orcid.org/0000-0001-7724-8563","contributorId":198670,"corporation":false,"usgs":false,"family":"Barall","given":"Michael","affiliations":[],"preferred":false,"id":811462,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70218708,"text":"70218708 - 2021 - Reproduction","interactions":[],"lastModifiedDate":"2021-03-08T15:50:36.638472","indexId":"70218708","displayToPublicDate":"2021-03-04T09:41:54","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Reproduction","docAbstract":"Lake charr Salvelinus namaycush are typically fall spawners although one ecotype has populations that spawn during spring and fall (siscowets in Lake Superior). Lake charr are iteroparous (reproduce more than once in a lifetime) with group-synchronous ovarian development and typically spawn once per year. However, lake charr may not reproduce every year, a phenomenon known as skipped spawning. Free embryos are active on spawning reefs, make diurnal vertical movements from spawning substrate, and feed exogenously much earlier than previously assumed. The abundance of food and predators strongly affects the rate of development, yolk sac absorption, and duration of residence on spawning sites. The necessity for, and timing of, gas bladder inflation, and mechanisms for inflation without access to the surface, need further study. The low survival of free embryos due to thiamine deficiency has likely contributed to the lack of recruitment of lake charr in the Laurentian Great Lakes for decades. Thiaminase, a thiamine-degrading enzyme, appears to be the causal agent for thiamine deficiency in Great Lakes lake charr.
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These data reveal that debris flows have traveled ca. 30 km downslope, forming a seismic facies consisting of stacked, wedge-shaped, transparent units separated by high-amplitude continuous reflectors. Analysis of piston cores shows three distinct sedimentary units, throughout the basin. The lowest unit, I, is a debrite containing numerous mud clasts of varying size and color distributed in a mud-rich matrix; it is absent over elevated basinal highs or ridges, such as the Onnuri Ridge, suggesting that local topography controls its distribution. The debrite forms a recognizable acoustically transparent layer on subbottom chirp profiles (av. 7 m thick), covers approximately 500 km2, and has an estimated volume of ∼ 3.5 km3.
The overlying unit, II, contains normally graded beds composed of massive sand, laminated and cross-laminated sand and silt, and a thick cap of structureless mud. This unit is interpreted to be a megaturbidite deposited from turbidity currents that originated from the flow transformation of debris flows on the upper continental slope. The megaturbidite covers the entire basin (at least 650 km2), and has an average thickness of 2.8 m (maximum thickness of 4.35 m), and comprises a volume of 1.8 km3. Variations in grain size and sedimentary structures suggest that the megaturbidite was deposited by progressively waning flows that reflected off basin flanks and ridges. The thick (up to 3.65 m) structureless mud cap further indicates deposition in a confined basin. The sharp basal contact, together with the lack of hemipelagic sediments between debrite and overlying megaturbidite, suggest that both were deposited during the same flow event, likely to have originated from a single catastrophic slope failure. Collapsing slide material evolved into a debris flow, from which a turbidite formed by dilution of the debris flow. Radiocarbon dates suggest that the slope failure occurred about 13–11 ka, a time when sea level was ca. 50 m lower than at the present day. Hemipelagic sediments in the topmost unit, III-2, above the megaturbidite indicate that the basin has been stable since ca. 11 ka.
We provide robust evidence that submarine slope failures evolve downslope into slides, debris flows, and finally, thick megaturbidites. This contribution highlights the importance of seafloor morphology on the distribution and stratigraphy of submarine flows in confined basins.
","language":"English","publisher":"SEPM Society for Sedimentary Geology","doi":"10.2110/jsr.2020.115","usgsCitation":"Cukur, D., Um, I., Chun, J., Lee, G., Kong, G., Johnson, S., and Horozal, S., 2021, Deepwater debrites and linked megaturbidites in confined basins: An example from the Onnuri Basin, East Sea of Korea: Journal of Sedimentary Research, v. 91, no. 1, p. 1-20, https://doi.org/10.2110/jsr.2020.115.","productDescription":"20 p.","startPage":"1","endPage":"20","ipdsId":"IP-120291","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":384225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"South Korea","otherGeospatial":"Onnuri Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 128.29833984375,\n 37.37888785004527\n ],\n [\n 131.3525390625,\n 37.37888785004527\n ],\n [\n 131.3525390625,\n 38.75408327579141\n ],\n [\n 128.29833984375,\n 38.75408327579141\n ],\n [\n 128.29833984375,\n 37.37888785004527\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"91","issue":"1","noUsgsAuthors":false,"publicationDate":"2021-03-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Cukur, Deniz","contributorId":216636,"corporation":false,"usgs":false,"family":"Cukur","given":"Deniz","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":811463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Um, In-Kwon","contributorId":216640,"corporation":false,"usgs":false,"family":"Um","given":"In-Kwon","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":811464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chun, Jong-Hwa","contributorId":216638,"corporation":false,"usgs":false,"family":"Chun","given":"Jong-Hwa","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":811465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lee, Gwang-Soo","contributorId":254937,"corporation":false,"usgs":false,"family":"Lee","given":"Gwang-Soo","email":"","affiliations":[{"id":24820,"text":"Korea Institute of Geoscience and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":811466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kong, Gee-Too","contributorId":254938,"corporation":false,"usgs":false,"family":"Kong","given":"Gee-Too","email":"","affiliations":[{"id":24820,"text":"Korea Institute of Geoscience and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":811467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Samuel Y. 0000-0001-7972-9977","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":221270,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":811468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Horozal, Senay","contributorId":254939,"corporation":false,"usgs":false,"family":"Horozal","given":"Senay","email":"","affiliations":[{"id":24820,"text":"Korea Institute of Geoscience and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":811469,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227101,"text":"70227101 - 2021 - Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model","interactions":[],"lastModifiedDate":"2021-12-29T14:14:01.03095","indexId":"70227101","displayToPublicDate":"2021-03-04T08:10:44","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2043,"text":"International Journal of Forestry Research","active":true,"publicationSubtype":{"id":10}},"title":"Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model","docAbstract":"Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied (r2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple (Acer rubrum), and eastern hemlock (Tsuga canadensis) where soil moisture was sufficient. On drier sandy soils, eastern white pine (Pinus strobus), red pine (P. resinosa), northern red oak (Quercus rubra), and white oak (Q. alba) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.
","language":"English","publisher":"Hindawi","doi":"10.1155/2021/6650821","usgsCitation":"Odom, R.H., and Ford, W., 2021, Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model: International Journal of Forestry Research, v. 2021, 6650821, 16 p., https://doi.org/10.1155/2021/6650821.","productDescription":"6650821, 16 p.","ipdsId":"IP-111053","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":453196,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://doi.org/10.1155/2021/6650821","text":"Publisher Index Page"},{"id":393572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fort Drum","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.0089111328125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 43.95921358836687\n ],\n [\n -75.509033203125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 44.209772586984485\n ],\n [\n -76.0089111328125,\n 43.95921358836687\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2021","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Odom, Richard H.","contributorId":171659,"corporation":false,"usgs":false,"family":"Odom","given":"Richard","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":829633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":829632,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70219538,"text":"70219538 - 2021 - Monitoring Tamarix changes using WorldView-2 satellite imagery in Grand Canyon National Park, Arizona","interactions":[],"lastModifiedDate":"2021-04-13T13:06:06.096863","indexId":"70219538","displayToPublicDate":"2021-03-04T08:04:32","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":"Monitoring Tamarix changes using WorldView-2 satellite imagery in Grand Canyon National Park, Arizona","docAbstract":"The U.S. Geological Survey assists the Federal Emergency Management Agency in its mission to identify flood hazards and zones for risk premiums for communities nationwide, by creating flood insurance rate maps through updating hydraulic models that use river geometry data. The data collected consist of elevations of river channels, banks, and structures, such as bridges, dams, and weirs that can affect flow. To account for the model complexity of river structure hydraulics and the fidelity between river channel and structure geometry, two distinct standards for collecting geometry data are presented, both using global navigation satellite system real-time network surveying. This method is adapted from U.S. Geological Survey manuals and is foundational in hydraulic surveying for flood insurance rate maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201146","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Taylor, N.J., and Simeone, C.E., 2021, Practical field survey operations for flood insurance rate maps: U.S. Geological Survey Open-File Report 2020–1146, 8 p., https://doi.org/10.3133/ofr20201146.","productDescription":"iv, 8 p.","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114316","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":383741,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/tm11D1","text":"Techniques and Methods 11-D1","linkHelpText":"- Methods of practice and guidelines for using survey-grade global navigation satellite systems (GNSS) to establish vertical datum in the United States Geological Survey"},{"id":383723,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1146/coverthb.jpg"},{"id":383724,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1146/ofr20201146.pdf","text":"Report","size":"662 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1146"},{"id":383725,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/tm11D3","text":"Techniques and Methods 11-D3","linkHelpText":"- Procedures and Best Practices for Trigonometric Leveling in the U.S. Geological Survey"}],"contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Groundwater discharge generates streamflow and influences stream thermal regimes. However, the water quality and thermal buffering capacity of groundwater depends on the aquifer source-depth. Here, we pair multi-year air and stream temperature signals to categorize 1729 sites across the continental United States as having major dam influence, shallow or deep groundwater signatures, or lack of pronounced groundwater (atmospheric) signatures. Approximately 40% of non-dam stream sites have substantial groundwater contributions as indicated by characteristic paired air and stream temperature signal metrics. Streams with shallow groundwater signatures account for half of all groundwater signature sites and show reduced baseflow and a higher proportion of warming trends compared to sites with deep groundwater signatures. These findings align with theory that shallow groundwater is more vulnerable to temperature increase and depletion. Streams with atmospheric signatures tend to drain watersheds with low slope and greater human disturbance, indicating reduced stream-groundwater connectivity in populated valley settings.
We concur with Azizi‐Rad et al. (2021) that it is vital to critically evaluate and compare different soil carbon models, and we welcome the opportunity to further describe the unique contribution of the PROMISE model (Waring et al. 2020) to this literature. The PROMISE framework does share many features with established biogeochemical models, as our original manuscript highlighted in Table 1, and our work builds upon model innovations developed by many different groups, including that of Azizi‐Rad and colleagues. Yet, the PROMISE framework is distinctive due to where it places mechanistic emphasis, and how these mechanisms are formalized in the mathematical model structure.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.15580","usgsCitation":"Waring, B.G., Sulman, B.N., Reed, S., Smith, A.P., Averill, C., Creamer, C., Cusack, D.F., Hall, S.J., Jastrow, J.D., Jilling, A., Kemner, K.M., Kleber, M., Allen Liu, X., Pett-Ridge, J., and Schulz, M., 2021, Response to ‘Stochastic and deterministic interpretation of pool models’: Global Change Biology, v. 27, no. 11, p. e11-e12, https://doi.org/10.1111/gcb.15580.","productDescription":"2 p.","startPage":"e11","endPage":"e12","ipdsId":"IP-127051","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":453205,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/gcb.15580","text":"Publisher Index Page"},{"id":384273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"11","noUsgsAuthors":false,"publicationDate":"2021-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Waring, Bonnie G. 0000-0002-8457-5164","orcid":"https://orcid.org/0000-0002-8457-5164","contributorId":245284,"corporation":false,"usgs":false,"family":"Waring","given":"Bonnie","email":"","middleInitial":"G.","affiliations":[{"id":49130,"text":"Utah State University, Department of Biology and Ecology Center, Logan UT 84322","active":true,"usgs":false}],"preferred":false,"id":811560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":811561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reed, Sasha C. 0000-0002-8597-8619","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":205372,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":811562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, A. Peyton","contributorId":245298,"corporation":false,"usgs":false,"family":"Smith","given":"A.","email":"","middleInitial":"Peyton","affiliations":[],"preferred":false,"id":811563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Averill, Colin","contributorId":245299,"corporation":false,"usgs":false,"family":"Averill","given":"Colin","email":"","affiliations":[],"preferred":false,"id":811564,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creamer, Courtney 0000-0001-8270-9387","orcid":"https://orcid.org/0000-0001-8270-9387","contributorId":201952,"corporation":false,"usgs":true,"family":"Creamer","given":"Courtney","email":"","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":811565,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cusack, Daniela F. 0000-0003-4681-7449","orcid":"https://orcid.org/0000-0003-4681-7449","contributorId":245300,"corporation":false,"usgs":false,"family":"Cusack","given":"Daniela","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":811566,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hall, Steven J. 0000-0002-7841-2019","orcid":"https://orcid.org/0000-0002-7841-2019","contributorId":244336,"corporation":false,"usgs":false,"family":"Hall","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":811567,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jastrow, Julie D.","contributorId":254970,"corporation":false,"usgs":false,"family":"Jastrow","given":"Julie","email":"","middleInitial":"D.","affiliations":[{"id":51371,"text":"Environmental Science Division, Argonne National Laboratory, Lemont IL 60439","active":true,"usgs":false}],"preferred":false,"id":811568,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jilling, Andrea","contributorId":254971,"corporation":false,"usgs":false,"family":"Jilling","given":"Andrea","email":"","affiliations":[{"id":51372,"text":"Department of Plant and Soil Sciences, Oklahoma State University, Stillwater OK 74078","active":true,"usgs":false}],"preferred":false,"id":811569,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kemner, Kenneth M.","contributorId":245301,"corporation":false,"usgs":false,"family":"Kemner","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":811570,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kleber, Markus","contributorId":254972,"corporation":false,"usgs":false,"family":"Kleber","given":"Markus","affiliations":[{"id":51374,"text":"Department of Crop and Soil Science, Oregon State University, Corvallis OR 97331","active":true,"usgs":false}],"preferred":false,"id":811571,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Allen Liu, Xiao-Jun","contributorId":254973,"corporation":false,"usgs":false,"family":"Allen Liu","given":"Xiao-Jun","affiliations":[{"id":51375,"text":"Department of Microbiology, University of Massachusetts, Amherst MA 01003","active":true,"usgs":false}],"preferred":false,"id":811572,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pett-Ridge, Jennifer","contributorId":254974,"corporation":false,"usgs":false,"family":"Pett-Ridge","given":"Jennifer","affiliations":[{"id":51376,"text":"Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore CA 94551","active":true,"usgs":false}],"preferred":false,"id":811573,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":811574,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70219458,"text":"70219458 - 2021 - Characterization of groundwater recharge and flow in California's San Joaquin Valley from InSAR-observed surface deformation","interactions":[],"lastModifiedDate":"2021-04-08T12:47:24.059845","indexId":"70219458","displayToPublicDate":"2021-03-04T07:44:25","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Characterization of groundwater recharge and flow in California's San Joaquin Valley from InSAR-observed surface deformation","docAbstract":"Surface deformation in California's Central Valley (CV) has long been linked to changes in groundwater storage. Recent advances in remote sensing have enabled the mapping of CV deformation and associated changes in groundwater resources at increasingly higher spatiotemporal resolution. Here, we use interferometric synthetic aperture radar (InSAR) from the Sentinel‐1 missions, augmented by continuous Global Positioning System (cGPS) positioning, to characterize the surface deformation of the San Joaquin Valley (SJV, southern two‐thirds of the CV) for consecutive dry (2016) and wet (2017) water years. We separate trends and seasonal oscillations in deformation time series and interpret them in the context of surface and groundwater hydrology. We find that subsidence rates in 2016 (mean −42.0 mm/yr; peak −345 mm/yr) are twice that in 2017 (mean −20.4 mm/yr; peak −177 mm/yr), consistent with increased groundwater pumping in 2016 to offset the loss of surface‐water deliveries. Locations of greatest subsidence migrated outwards from the valley axis in the wetter 2017 water year, possibly reflecting a surplus of surface‐water supplies in the lowest portions of the SJV. Patterns in the amplitude of seasonal deformation and the timing of peak seasonal uplift reveal entry points and potential pathways for groundwater recharge into the SJV and subsequent groundwater flow within the aquifer. This study provides novel insight into the SJV aquifer system that can be used to constrain groundwater flow and subsidence models, which has relevance to groundwater management in the context of California's 2014 Sustainable Groundwater Management Act (SGMA).
Prassack et al. (2020) analyzed dental microwear in a sample of canids from the Gravettian site of Předmostí that had been identified as either Paleolithic dogs or Pleistocene wolves (n = 10 in each group), accepting that the morphological differences between the groups validly distinguished the (self-domesticating) protodogs from wolves. The authors then concluded that differences in one m2 microwear pattern separated those groups and indicated enhanced anthropogenic based durophagy in the putative protodogs. The study also inferred protodog diets from another isotope study.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jas.2020.105160","usgsCitation":"Janssens, L.A., Boudadi-Maligne, M., Mech, L.D., and Lawler, D., 2021, The enigma of the Předmostí protodogs. A comment on Prassack et al. 2020: Journal of Archaeological Science, v. 126, 105160, 4 p., https://doi.org/10.1016/j.jas.2020.105160.","productDescription":"105160, 4 p.","ipdsId":"IP-117731","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":453214,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.jas.2020.105160","text":"External Repository"},{"id":422137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Janssens, Luc A. A.","contributorId":331208,"corporation":false,"usgs":false,"family":"Janssens","given":"Luc","email":"","middleInitial":"A. A.","affiliations":[{"id":79148,"text":"Ghent University, Department of Archaeology, UFO, Sint Pietersniewstraat 35, 9000 Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":886927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boudadi-Maligne, Myriam","contributorId":331209,"corporation":false,"usgs":false,"family":"Boudadi-Maligne","given":"Myriam","email":"","affiliations":[{"id":79149,"text":"2 Department of Archaeology, University of Leiden, Einsteinweg 2, 2333 CC Leiden, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":886928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":886929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawler, Dennis","contributorId":331210,"corporation":false,"usgs":false,"family":"Lawler","given":"Dennis","email":"","affiliations":[{"id":79151,"text":"Center for American Archaeology, Kampsville IL 62053 USA Illinois State Museum, Springfield IL 62703 USA. Pacific Marine Mammal Center, Laguna Beach CA 92651","active":true,"usgs":false}],"preferred":false,"id":886930,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218747,"text":"70218747 - 2021 - Greenhouse gas emissions from an arid-zone reservoir and their environmental policy significance: Results from existing global models and an exploratory dataset","interactions":[],"lastModifiedDate":"2021-03-10T13:48:59.529423","indexId":"70218747","displayToPublicDate":"2021-03-04T07:22:33","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1563,"text":"Environmental Science and Policy","active":true,"publicationSubtype":{"id":10}},"title":"Greenhouse gas emissions from an arid-zone reservoir and their environmental policy significance: Results from existing global models and an exploratory dataset","docAbstract":"Reservoirs in arid regions often provide critical water storage but little is known about their greenhouse gas (GHG) footprint. While there is growing appreciation of the role reservoirs play as GHG sources, there is a lack of understanding of GHG emission dynamics from reservoirs in arid regions and implications for environmental policy. Here we present initial GHG emission measurements from Lake Powell, a large water storage reservoir in the desert southwest United States. We report CO2-eq emissions from the shallow (< 15 m) littoral regions of the reservoir that are higher than the global average areal emissions from reservoirs (9.4 vs. 5.8 g CO2-eq m−2 d−1) whereas fluxes from the main reservoir were two orders of magnitude lower (0.09 g CO2-eq m−2 d−1). We then compared our measurements to modeled CO2 + CH4 emissions from the reservoir using four global scale models. Factoring these emissions into hydropower production at Lake Powell yielded low GHG emissions per MWh−1 as compared to fossil-fuel based energy sources. With the exception of one model, the estimated hydropower emissions for Lake Powell ranged from 10−32 kg CO2-eq MWh−1, compared to ∼400−1000 kg CO2-eq MWh−1 for natural gas, oil, and coal. We also estimate that reduced littoral habitat under low water levels leads to ∼50% reduction in the CO2 equivalent emissions per MWh. The sensitivity of GHG emissions to reservoir water levels suggests that the interaction will be an important policy consideration in the design and operation of arid region systems.
The contamination of coastal ecosystems from a variety of toxins of marine algal origin is a common and well-documented situation along the coasts of the United States and globally. The occurrence of toxins originating from cyanobacteria along marine coastlines is much less studied, and little information exists on whether toxins from marine and freshwater sources co-occur regularly. The current study focused on the discharge of cyanotoxins from a coastal lagoon (Santa Clara River Estuary) as a consequence of an extreme tide event (King Tides; December 3–5, 2017) resulting in a breach of the berm separating the lagoon from the ocean. Monthly monitoring in the lagoon throughout 2017 documented more than a dozen co-occurring cyanobacterial genera, as well as multiple algal and cyanobacterial toxins. Biotoxin monitoring before and following the King Tide event using Solid Phase Adsorption Toxin Tracking (SPATT) in the lagoon and along the coast revealed the co-occurrence of microcystins, anatoxin, domoic acid, and other toxins on multiple dates and locations. Domoic acid was ubiquitously present in SPATT deployed in the lagoon and along the coast. Microcystins were also commonly detected in both locations, although the beach berm retained the lagoonal water for much of the year. Mussels collected along the coast contained microcystins in approximately half the samples, particularly following the King Tide event. Anatoxin was observed in SPATT only in late December, following the breach of the berm. Our findings indicate both episodic and persistent occurrence of both cyanotoxins and marine toxins may commonly contaminate coastlines in proximity to cyanobacteria-laden creeks and lagoons.
Fire transforms, fragments and sometimes maintains forests, creating mosaics of burned and unburned patches. Highly mobile animals respond to resources in the landscape at a variety of spatial scales, yet we know little about their landscape-scale relationships with fire.
We aimed to identify drivers of bat richness in a landscape mosaic of forested and burned areas while identifying spatial scales at which bat richness was most strongly related to extent, configuration, and diversity measures of landscape-level habitat.
We used multi-species hierarchical occupancy modelling to relate bat richness to landscape variables at 10 spatial scales, based on acoustic data collected in the Sierra Nevada, United States. We also assessed redundancy among landscape variable type (extent, configuration, and diversity) and between focal patch types (forested and burned).
Bat richness was positively associated with heterogenous landscapes, shown by positive associations with pyrodiversity, extent and mean area of burned patches, burned and forested edge density and patch density and relationships were generally consistent across scales. Extent of forest cover and burned areas were highly correlated, but configuration and diversity of these patch types diverged.
Bat communities of our study area appear to be largely resilient to wildfire and adapted to more heterogenous forests and shorter-interval fire regimes that likely predominated before the fire suppression era.
","language":"English","publisher":"Springer Link","doi":"10.1007/s10980-021-01204-y","usgsCitation":"Blakey, R.V., Webb, E.B., Kesler, D.C., Siegel, R.B., Corcoran, D., Cole, J.S., and Johnson, M., 2021, Extent, configuration and diversity of burned and forested areas predict bat richness in a fire-maintained forest: Landscape Ecology, v. 36, p. 1101-1115, https://doi.org/10.1007/s10980-021-01204-y.","productDescription":"15 p.","startPage":"1101","endPage":"1115","ipdsId":"IP-114645","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":453221,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-021-01204-y","text":"Publisher Index Page"},{"id":395689,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Plumas National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.53649902343749,\n 39.72197606377427\n ],\n [\n -120.00915527343749,\n 39.825413103424786\n ],\n [\n -120.00915527343749,\n 39.96449067924025\n ],\n [\n -120.30029296875,\n 40.212440718286466\n ],\n [\n -120.59967041015624,\n 40.371658891506094\n ],\n [\n -120.82489013671875,\n 40.348637376031725\n ],\n [\n -121.0748291015625,\n 40.24389506699777\n ],\n [\n -121.28082275390625,\n 39.953964380766394\n ],\n [\n -120.53649902343749,\n 39.72197606377427\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","noUsgsAuthors":false,"publicationDate":"2021-03-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Blakey, R. 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C.","contributorId":275326,"corporation":false,"usgs":false,"family":"Kesler","given":"D.","email":"","middleInitial":"C.","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":833997,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Siegel, R. B.","contributorId":216846,"corporation":false,"usgs":false,"family":"Siegel","given":"R.","email":"","middleInitial":"B.","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":833998,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corcoran, D.","contributorId":275327,"corporation":false,"usgs":false,"family":"Corcoran","given":"D.","email":"","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":833999,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cole, J. S.","contributorId":275328,"corporation":false,"usgs":false,"family":"Cole","given":"J.","email":"","middleInitial":"S.","affiliations":[{"id":37290,"text":"The Institute for Bird Populations","active":true,"usgs":false}],"preferred":false,"id":834000,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Matthew mjjohnson@usgs.gov","contributorId":257370,"corporation":false,"usgs":false,"family":"Johnson","given":"Matthew","email":"mjjohnson@usgs.gov","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":834001,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70254661,"text":"70254661 - 2021 - Evidence of economical territory selection in a cooperative carnivore","interactions":[],"lastModifiedDate":"2024-06-06T13:48:49.302663","indexId":"70254661","displayToPublicDate":"2021-03-03T08:30:30","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Evidence of economical territory selection in a cooperative carnivore","docAbstract":"As an outcome of natural selection, animals are probably adapted to select territories economically by maximizing benefits and minimizing costs of territory ownership. Theory and empirical precedent indicate that a primary benefit of many territories is exclusive access to food resources, and primary costs of defending and using space are associated with competition, travel and mortality risk. A recently developed mechanistic model for economical territory selection provided numerous empirically testable predictions. We tested these predictions using location data from grey wolves (Canis lupus) in Montana, USA. As predicted, territories were smaller in areas with greater densities of prey, competitors and low-use roads, and for groups of greater size. Territory size increased before decreasing curvilinearly with greater terrain ruggedness and harvest mortalities. Our study provides evidence for the economical selection of territories as a causal mechanism underlying ecological patterns observed in a cooperative carnivore. Results demonstrate how a wide range of environmental and social conditions will influence economical behaviour and resulting space use. We expect similar responses would be observed in numerous territorial species. A mechanistic approach enables understanding how and why animals select particular territories. This knowledge can be used to enhance conservation efforts and more successfully predict effects of conservation actions.
","language":"English","publisher":"Royal Society Publishing","doi":"10.1098/rspb.2021.0108","usgsCitation":"Sells, S., Mitchell, M.S., Podruzny, K.M., Gude, J., Keever, A., Boyd, D.K., Smucker, T., Nelson, A.A., Parks, T.W., Lance, N.J., Ross, M.S., and Inman, R.M., 2021, Evidence of economical territory selection in a cooperative carnivore: Proceedings of the Royal Society B: Biological Sciences, v. 288, no. 1946, 20210108, 10 p., https://doi.org/10.1098/rspb.2021.0108.","productDescription":"20210108, 10 p.","ipdsId":"IP-117340","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":453222,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2021.0108","text":"Publisher Index Page"},{"id":429567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": 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M.","contributorId":85865,"corporation":false,"usgs":true,"family":"Podruzny","given":"Kevin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":902247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gude, Justin A.","contributorId":95780,"corporation":false,"usgs":true,"family":"Gude","given":"Justin A.","affiliations":[],"preferred":false,"id":902248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keever, Allison","contributorId":187743,"corporation":false,"usgs":false,"family":"Keever","given":"Allison","email":"","affiliations":[],"preferred":false,"id":902249,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyd, Diane K.","contributorId":337179,"corporation":false,"usgs":false,"family":"Boyd","given":"Diane","email":"","middleInitial":"K.","affiliations":[{"id":80987,"text":"fwp","active":true,"usgs":false}],"preferred":false,"id":902250,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smucker, T.D.","contributorId":32404,"corporation":false,"usgs":true,"family":"Smucker","given":"T.D.","email":"","affiliations":[],"preferred":false,"id":902251,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nelson, Abigail A.","contributorId":69042,"corporation":false,"usgs":true,"family":"Nelson","given":"Abigail","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":902252,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Parks, Tyler W.","contributorId":337252,"corporation":false,"usgs":false,"family":"Parks","given":"Tyler","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":902253,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lance, Nathan J.","contributorId":337253,"corporation":false,"usgs":false,"family":"Lance","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":902254,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ross, Michael S.","contributorId":45406,"corporation":false,"usgs":true,"family":"Ross","given":"Michael","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":902255,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Inman, Robert M.","contributorId":337254,"corporation":false,"usgs":false,"family":"Inman","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":902256,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70218768,"text":"70218768 - 2021 - Preconditioning by sediment accumulation can produce powerful turbidity currents without major external triggers","interactions":[],"lastModifiedDate":"2021-03-12T14:09:09.118235","indexId":"70218768","displayToPublicDate":"2021-03-03T08:07:42","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Preconditioning by sediment accumulation can produce powerful turbidity currents without major external triggers","docAbstract":"Turbidity currents dominate sediment transfer into the deep ocean, and can damage critical seabed infrastructure. It is commonly inferred that powerful turbidity currents are triggered by major external events, such as storms, river floods, or earthquakes. However, basic models for turbidity current triggering remain poorly tested, with few studies accurately recording precise flow timing. Here, we analyse the most detailed series of measurements yet made of powerful (up to 7.2 m s−1) turbidity currents, within Monterey Canyon, offshore California. During 18-months of instrument deployment, fourteen turbidity currents were directly monitored. No consistent triggering mechanism was observed, though flows did cluster around enhanced seasonal sediment supply. We compare turbidity current timing at Monterey Canyon (a sandy canyon-head fed by longshore drift) to the only other systems where numerous (>10-100) flows have been measured precisely via direct monitoring; the Squamish Delta (a sandy fjord-head delta), and the Congo Canyon (connected to the mud-dominated mouth of the Congo River). A common seasonal pattern emerges, leading to a new model for preconditioning and triggering of turbidity currents initiating through slope failure in areas of sediment accumulation, such as canyon heads or river mouths. In this model, rapid or sustained sediment supply alone can produce elevated pore pressures, which may persist, thereby predisposing slopes to fail. Once preconditioned, a range of minor external perturbations, such as moderate storm-waves, result in local pore pressure variation, and thus become effective triggers. Major external triggers are therefore not always a prerequisite for triggering of powerful turbidity currents.
Mobile hydroacoustic surveys are routinely used to estimate pelagic fish abundance. In the Great Lakes, alewife are commonly surveyed with mobile hydroacoustics, however, their behavior often has them associated with epilimnetic habitats which increases the potential for vessel avoidance to bias hydroacoustic observations. Abundance estimates from mobile hydroacoustic surveys are typically made using depth and size thresholds to classify targets to species. In hydroacoustic surveys, fish can appear to be smaller when oriented off horizontal axis, as is common with fish displaying vessel avoidance behaviour. This presents a problem where alewives that are diving may appear too small to be correctly classified. We compared alewife swimming behaviours and target strength distributions between stationary up-looking and mobile down-looking hydroacoustics to quantify how vessel avoidance may bias hydroacoustic observations. Alewives from the mobile survey were found to be diving away from the surface, moving faster and in more linear paths than the undisturbed fish from the stationary survey. In the mobile survey, alewives were observed at smaller target strength values than would be expected if boat avoidance was not occurring. Our results suggest that alewife behavioral changes associated with vessel avoidance affect the number and size of targets classified as alewife from mobile hydroacoustic surveys in Lake Ontario.
Introduced species often disrupt established food webs, but some native predators can come to rely on introduced prey. Understanding the net effects of the non-natives on imperiled predators is crucial for planning conservation measures. The invasive American bullfrog (Lithobates catesbeianus) can be prey, predator, and competitor for the critically endangered San Francisco garter snake (Thamnophis sirtalis tetrataenia). We examined the seasonal prey use of a San Francisco garter snake population that co-occurs with American bullfrogs to examine intraguild predation between these species. Juvenile and adult snakes mainly consumed native anurans instead of American bullfrogs, and this diet pattern peaked in spring, a critical foraging period for the snakes. In spring, large adult American bullfrogs also foraged heavily on native anurans and displayed a high degree of diet overlap with San Francisco garter snakes. Invasive American bullfrogs are detrimental to San Francisco garter snakes mainly through seasonal competition rather than reciprocal predation. Removal of invasive species provided further evidence that eliminating American bullfrogs can benefit San Francisco garter snakes by reducing predation pressure on their shared amphibian prey. Better understanding the interactions of invasive species with native species of conservation concern informs management practices and improves conservation outcomes.
This study examines the use of organic petrology techniques to quantify the amount of coal and carbonaceous combustion by-products (i.e., coke, coal tar/pitch, cenospheres) in sediments taken from the Kinnickinnic River adjacent to the former site of the Milwaukee Solvay Coke and Gas Company. These materials are of concern as contaminants like polycyclic aromatic hydrocarbons (PAHs) are known to readily adsorb to coal and combustion byproducts. Kinnickinnic River sediment samples (n = 36) ranging in depth (1–11 ft.) were collected from eight core locations to quantify and characterize carbonaceous material in the sediments. To determine the amount (vol%) of organic particulates, U.S. Geological Survey (USGS) modified the existing ASTM D2799 using the following categories: coal, coke, coal tar/pitch, inertinite organics, plant material, cenospheres, and mineral matter. Coal fragments were subdivided by rank using vitrinite reflectance (Ro, %) and organic components were further subdivided into the size fractions of coarse (250–1000 μm), fine (63–250 μm), and very fine (<63 μm). Of the 36 samples analyzed, concentrations of coal, coke, and coal tar/pitch ranged from 0 to 18.2 vol%, 0 to 32.0 vol%, and 0 to 2.6 vol%, respectively, with the highest concentrations occurring near point sources (e.g. discharge pipe and coal unloading operations). Samples that were furthest upstream and downstream from the Solvay site exhibited a marked decrease in particulate organics, with exception of one upstream location which had 19.8 vol% coke. Overall, the modified ASTM method provided a means to quantify the abundance of carbonaceous material present in the sediments. Petrography and total PAH concentrations did not provide a clear correlation to organic matter type or size fraction but the samples with the highest vol% organic matter in each core generally corresponded to the sample with the highest bulk PAH content.
Continuous movement monitoring is a powerful tool for evaluating reintroduction techniques and assessing how well reintroduced animals are adjusting to the wild. However, to date, continuous monitoring has only occurred for large-bodied species capable of carrying heavy tracking devices. In this study we used an automated VHF radio telemetry array to investigate the exploratory behavior and movement patterns of critically endangered ʻAlalā (Corvus hawaiiensis), reintroduced to the Island of Hawaiʻi in 2017. The 11 juvenile ʻAlalā we tracked exhibited high site fidelity and initial survival. Over time the birds showed decreased time spent at the supplemental feeders, and transitioned to more focused use of the landscape, suggesting increased foraging on wild food items. Birds with seemingly less spatial neophobia at release also made larger post-release exploratory movements. This study provides the first evidence that 1) supplemental feeding can support site fidelity for reintroduced ʻAlalā without restricting a transition to independent foraging, and 2) that pre-release personality metrics may be useful predictors for predicting post-release movements of ʻAlalā. Our work is the first to demonstrate the utility and power of automated telemetry for monitoring the reintroduction of small species.
Livestock diseases have devastating consequences economically, socially and politically across the globe. In certain systems, pathogens remain viable after host death, which enables residual transmissions from infected carcasses. Rapid culling and carcass disposal are well-established strategies for stamping out an outbreak and limiting its impact; however, wait-times for these procedures, i.e. response delays, are typically farm-specific and time-varying due to logistical constraints. Failing to incorporate variable response delays in epidemiological models may understate outbreak projections and mislead management decisions. We revisited the 2001 foot-and-mouth epidemic in the United Kingdom and sought to understand how misrepresented response delays can influence model predictions. Survival analysis identified farm size and control demand as key factors that impeded timely culling and disposal activities on individual farms. Using these factors in the context of an existing policy to predict local variation in response times significantly affected predictions at the national scale. Models that assumed fixed, timely responses grossly underestimated epidemic severity and its long-term consequences. As a result, this study demonstrates how general inclusion of response dynamics and recognition of partial controllability of interventions can help inform management priorities during epidemics of livestock diseases.
Migratory marine species cross political borders and enter the high seas, where the lack of an effective global management framework for biodiversity leaves them vulnerable to threats. Here, we combine 10,108 tracks from 5775 individual birds at 87 sites with data on breeding population sizes to estimate the relative year-round importance of national jurisdictions and high seas areas for 39 species of albatrosses and large petrels. Populations from every country made extensive use of the high seas, indicating the stake each country has in the management of biodiversity in international waters. We quantified the links among national populations of these threatened seabirds and the regional fisheries management organizations (RFMOs) which regulate fishing in the high seas. This work makes explicit the relative responsibilities that each country and RFMO has for the management of shared biodiversity, providing invaluable information for the conservation and management of migratory species in the marine realm.
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