A major challenge in ecology is disentangling interactions of non-native, potentially invasive species on native species. Conditional two-species occupancy models examine the effects of dominant species (e.g., non-native) on subordinate species (e.g., native) while considering the possibility that occupancy of one species may affect occupancy and/ or detection of the other. Although conditional two-species models are useful for evaluating the influence of one species on presence of another, it is possible that species interactions are density dependent. Therefore, we developed a novel two-species occupancy model that incorporates multiple abundance states (i.e., absent, present, abundant) of the native species. We showcase the utility of this model with a case study that incorporates random effects and covariates on both occupancy and detection to help disentangle species interactions given varying occupancy and detection in different abundance states. We use snorkel survey data from the Umpqua basin, Oregon, where it is hypothesized that smallmouth bass Micropterus dolomieu, a non-native piscivore, exclude Umpqua chub Oregonichthys kalawatseti, a small endemic minnow. From our two-species multi-state (2SMS) model, we concluded that average occupancy was low for both fishes, and that when non-native bass were present, overall native chub occupancy in the present (0.18 ± 0.05 SD) and abundant (0.19 ± 0.03) states was higher than when non-natives were absent (0.14 ± 0.02/ 0.08 ± 0.02), indicating the non-native was not excluding the native species. By incorporating a species interaction factor, we found a positive association (6.75 ± 5.54 SD) between native chub and non-native bass. The covariates strongly related to occupancy were elevation, algae, and land cover type (urban and shrub). Detection probability for both species (0.21–0.82) was most strongly related to the covariates day of year, water temperature, gravel substrate, and stream order/ magnitude. Incorporation of detection probability and covariates enabled interpretation of interactions between the two species that may have been missed without their inclusion in the modeling process. Our new 2SMS occupancy model can be used by scientists and managers with a broad range of survey and covariate data to disentangle species interactions problems to help them inform management decisions.
Rising temperatures in the Arctic and subarctic are driving the rapid thaw of permafrost by reducing permafrost cooling, increasing active layer thickness, and promoting talik formation. In this study, the cyrohydrogeology of a permafrost mound located within the discontinuous permafrost zone near Umiujaq (Nunavik, Québec, Canada) is characterized through the analysis of a dataset covering more than two decades of monitoring. This dataset captures a high degree of interannual variability in air temperature and ground thermal conditions, as well as the formation and closure of a supra-permafrost talik. Data indicate that variable saturation and advective heat transport directly contribute to the expansion and contraction of the talik. Data further indicate the presence of two distinct thermo-hydrologic settings resulting from differences in surface conditions, as well as subsurface thermal and flow regimes. The first, found at the top of the mound feature, is characterized by very low moisture contents (< 0.05 m3/m3), while the second, found at the side of the mound feature, shows higher annual moisture contents that strongly influence the dynamics of heat and groundwater flow. The data were synthesized into a detailed conceptual model of the cyrohydrogeological dynamics that highlights the important role of hydrogeological characterization and long-term datasets in understanding the effects of groundwater flow on seasonal frost and permafrost dynamics. Specifically, the results presented here show that in the absence of long-term datasets, longer-period transient phenomena such as talik opening and closure may be misrepresented as uni-directional feedback loops, as opposed to highly-dynamic temporary phenomena.
The Federal Energy Regulatory Commission has been considering the approval to breach four dams on lower Klamath River in southern Oregon and northern California. Approval of this application would allow for Strikeouts indicate text deletion hereafter. decommissioning and dam removal, beginning as early as 2023. This action would affect Klamath River salmon (Oncorhynchus ssp.) populations, a critical food source for federally endangered Southern Resident Killer Whales (Orcinus orca). In the long run, reintroduction of salmon populations to the upper Klamath River Basin may increase salmon abundance available to Southern Resident Killer Whales, but in the near term, it is uncertain how changes in hatchery management and disease-caused mortality by the myxosporean parasite Ceratonova shasta will influence abundance of salmon populations entering the ocean. To assess this uncertainty, we used the Stream Salmonid Simulator (S3) to simulate population dynamics of juvenile Chinook salmon (Oncorhynchus tshawytscha) for nine different population sources that rear and migrate through the Klamath River.
S3 is a spatially explicit population model that runs on a daily time-step and simulates daily growth, survival, and movement of juvenile Chinook salmon from the time of spawning through ocean entry. The key features of this model relevant to this report include (1) a C. shasta disease submodel; (2) a temperature-dependent bioenergetics model that calculates daily growth rates; (3) size-dependent movement; (4) density-dependent dynamics that are influenced by the effect of flow on suitable habitat area; and (5) habitat, river flow, and water temperature specific to each scenario.
We constructed and ran four scenarios: two scenarios for dams in place (Dams In) and dams removed (Dams Out), and given these dam-removal conditions, a low- and high-spore scenario for C. shasta. Each scenario was run for nine water years representing a range of conditions from dry to wet. Previously published daily river flows and water temperatures for Dams In and Dams Out provided physical inputs for each scenario. Daily spore concentrations were simulated using a three-part mechanistic model that used river discharge, water temperature, and the prevalence of infection (POI) of hatchery-origin Chinook salmon juveniles with C. shasta in the previous year3. We constructed two spore scenarios for each Dams In and Dams Out scenario, a “Low Spore” scenario and a “High Spore” scenario resulting in four scenarios for comparison. Spore scenarios were established by setting the prior-year POI of hatchery fish to 0.15 and 0.75 in the estimation of spore concentrations. Hatchery releases under Dams Out differed from those under the current Dams In scenario. Hatchery releases under the Dams Out scenario were modified to emulate changes in hatchery production that would occur under Dams Out conditions. This included moving hatchery production and releases from Iron Gate Dam to a proposed hatchery at Fall Creek, which would be located about 11 kilometers (km) upstream of Iron Gate Dam. It is anticipated that the Fall Creek hatchery would produce fewer fish at smaller and larger sizes at different release timings. For salmon inputs, we used observed historical abundance of main-stem spawners from brood year 2009 and juvenile salmon entering from tributaries in water year 2010, which represented an average return year for the 2005–18 period. Main-stem spawning was allowed to shift upstream from Iron Gate Dam under the Dams Out scenario. We also included hatchery-origin fish as natural spawners that would have otherwise returned to Iron Gate Hatchery in the first 3 years following dam removal.
The S3 model simulated considerably higher total abundance for Dams Out relative to the respective Dams In scenarios, and higher abundance for the Low Spore scenario relative to the High Spore scenario. The difference in abundance between the four combinations of the dam-removal and spore scenarios varied among population groups. For main-stem natural production, juvenile abundance at ocean entry was 2–3 times higher for Dams Out scenarios than for Dams In scenarios, and juvenile abundance for High Spore scenarios was lower than that for the Dams Out Low Spores scenario. For hatchery releases, abundance at ocean entry was similar between Dams In and Dams Out scenarios for most water years, despite lower release sizes from Fall Creek Hatchery under Dams Out. For tributary populations, abundance for the High Spore scenarios was consistently lower than for the Low Spore scenarios, but differences between dam-removal scenarios varied among water years, with Dams Out scenarios having similar or higher abundance than Dams In scenarios, and dry water years having the largest difference between Dams In and Dams Out scenarios.
We determined that different factors affected the response of each population group. For main-stem natural production, survival from fry emergence to ocean entry was higher under Dams Out scenarios compared to Dams In scenarios because juveniles emerged later and tended to arrive at the ocean sooner and at larger sizes, causing the population to have less time-dependent in-river mortality. Owing to their late release timing, hatchery populations had high disease-caused mortality in Dams In and Dams Out High Spore scenarios. Furthermore, a high proportion of infected fish (those that would be expected to die at some future point) survived to the ocean. Iron Gate Hatchery fish had lower survival rates than releases from Fall Creek Hatchery because the last mid-June release group from the 2010 Iron Gate Hatchery release incurred nearly total mortality in most water years owing to water temperatures exceeding 24 degrees Celsius. Our analysis shows how the S3 model was able to track different populations and provide insights on how the differential response of each population combined to influence the simulated number of juvenile Chinook salmon arriving at the Pacific Ocean where they become available as a food source for Southern Resident Killer Whales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221106","collaboration":"Prepared in cooperation with the National Marine Fisheries Service and the U.S. Fish and Wildlife Service","usgsCitation":"Perry, R.W., Plumb, J.M., Dodrill, M.J., Som, N.A., Robinson, H.E., and Hetrick, N.J., 2023, Simulating post-dam removal effects of hatchery operations and disease on juvenile Chinook salmon (Oncorhynchus tshawytscha) production in the Lower Klamath River, California: U.S. Geological Survey Open-File Report 2022–1106, 33 p., https://doi.org/10.3133/ofr20221106.","productDescription":"vii, 33 p.","onlineOnly":"Y","ipdsId":"IP-137471","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":410980,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1106/coverthb2.jpg"},{"id":410983,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1106/images"},{"id":410981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1106/ofr20221106.pdf","text":"Report","size":"6.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1106"},{"id":499722,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114179.htm","linkFileType":{"id":5,"text":"html"}},{"id":410984,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1106/ofr20221106.XML"},{"id":410982,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221106/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1106"}],"country":"United States","state":"California","otherGeospatial":"Lower Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.36610471757332,\n 40.58470369882767\n ],\n [\n -120.32485220783963,\n 40.58470369882767\n ],\n [\n -120.32485220783963,\n 42.21557817118634\n ],\n [\n -124.36610471757332,\n 42.21557817118634\n ],\n [\n -124.36610471757332,\n 40.58470369882767\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
More than 2 million Californians rely on groundwater from privately owned domestic wells for drinking-water supply. This report summarizes a water-quality survey of domestic and small-system drinking-water supply wells in the Modesto, Turlock, and Merced subbasins of the San Joaquin Valley where more than 78,000 residents are estimated to use privately owned domestic wells. Results indicate that inorganic and organic constituents in groundwater were respectively present above regulatory (maximum contaminant level, MCL) benchmarks for public drinking-water quality in 37 percent and 9 percent of the aquifer area used for domestic drinking-water supplies (herein, “domestic groundwater resources”).
The most prevalent inorganic constituents exceeding regulatory benchmarks were nitrate, uranium, and arsenic. The only organic constituents exceeding regulatory benchmarks were the fumigant constituents 1,2,3-trichloropropane (1,2,3-TCP) and 1,2-dibromo-3-chloropropane (DBCP), but the herbicides atrazine and simazine were detected at low concentrations below one-tenth of regulatory benchmarks in 30 percent of domestic groundwater resources. Total dissolved solids (TDS) and manganese exceeded aesthetic-based (secondary maximum contaminant level [SMCL]) benchmarks for drinking water in 3 percent and 13 percent of domestic groundwater resources, respectively. Per- and polyfluoroalkyl substances (PFAS) were detected in 23 percent of domestic groundwater resources, with 4 percent exceeding California state notification or response levels for specific compounds. Total coliform bacteria were detected in 20 percent of domestic groundwater resources.
Elevated concentrations of nitrate, uranium, TDS, and pesticides (fumigant constituents and herbicides) are related to agricultural land use and were typically present at shallow depths up to 75 meters below land surface. Agriculturally derived constituents were detected in wells screened below the Corcoran Clay Member of the Tulare Formation (herein, “Corcoran Clay”) in the southeastern part of the study area, where the Corcoran Clay tends to be shallower and thinner than in areas to the northwest. Nitrate, uranium, and TDS were most prevalent in the northwest part of the study area proximal to the valley trough where soils are poorly drained and agricultural land uses are predominantly grain, alfalfa, and dairy farms. Pesticides tended to occur in groundwater below coarse-grained surficial deposits and within a northwest to southeast trending band along the eastern extent of the Corcoran Clay that typically demarcates the western extent of well-drained soils associated with perennial orchard crops. Elevated concentrations of arsenic tended to occur west of this band in reducing groundwater but also sometimes co-occurred with elevated nitrate in oxic groundwater, most likely because of geochemical conditions in agriculturally affected groundwater that can enhance the mobility of arsenic from aquifer sediments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221116","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"GAMA Program","usgsCitation":"Levy, Z.F., Balkan, M., and Shelton, J.L., 2023, Quality of groundwater used for domestic supply in the Modesto, Turlock, and Merced Subbasins of the San Joaquin Valley, California: U.S. Geological Survey Open-File Report 2022-1116, 13 p., https://doi.org/10.3133/ofr20221116.","productDescription":"Report: 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-139668","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":411493,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96R55KQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater-quality data in the Modesto-Turlock-Merced Domestic-Supply Aquifer Study Unit, 2020-2021: Results from the California GAMA Priority Basin Project"},{"id":411490,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1116/coverthb.jpg"},{"id":411494,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1116/images"},{"id":411491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1116/ofr20221116.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1116"},{"id":411492,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221116/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1116"},{"id":411495,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1116/ofr20221116.XML"},{"id":499725,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114178.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.79107113798727,\n 38.18457756338151\n ],\n [\n -121.79107113798727,\n 37.036293717738104\n ],\n [\n -119.63866490997714,\n 37.036293717738104\n ],\n [\n -119.63866490997714,\n 38.18457756338151\n ],\n [\n -121.79107113798727,\n 38.18457756338151\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"GAMA Project Chief
U.S. Geological Survey
California Water Science Center
6000 J Street
Placer Hall, Sacramento, CA 95819
Telephone number: (916) 278-3000
GAMA Program Unit Chief State Water Resources Control Board Division of Water Quality
PO Box 2231
Sacramento, CA 95812
Telephone number: (916) 341-5855
Models that assess the vulnerability of freshwater species to shifting environmental conditions do not always account for short-duration extremes, which are increasingly common. Life cycle models for Pacific salmon (Oncorhynchus spp.) generally focus on average conditions that fish experience during each life stage, yet many floods, low flows, and elevated water temperatures only last days to weeks. We developed a process-based life cycle model that links coho salmon (Oncorhynchus kisutch) abundance to daily streamflow and thermal regimes to assess: (1) “How does salmon abundance respond to short-duration floods, low flows, and high temperatures in glacier-, snow-, and rain-fed streams?” and (2) “How does the temporal resolution of flow and temperature data influence these responses?”. Our simulations indicate that short-duration extremes can reduce salmon abundance in some contexts. However, after daily flow and temperature data were aggregated into weekly and monthly averages, the impact of extreme events on populations declined. Our analysis demonstrates that novel modeling frameworks that capture daily variability in flow and temperature are needed to examine impacts of extreme events on Pacific salmon.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0129","usgsCitation":"Bellmore, J.R., Sergeant, C.J., Bellmore, R.A., Falke, J.A., and Fellman, J.B., 2023, Modeling coho salmon (Oncorhynchus kisutch) population response to streamflow and water temperature extremes, v. 80, no. 2, p. 243-260, https://doi.org/10.1139/cjfas-2022-0129.","productDescription":"18 p.","startPage":"243","endPage":"260","ipdsId":"IP-141126","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487894,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11122/14923","text":"External Repository"},{"id":485214,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Bellmore, J. Ryan","contributorId":104790,"corporation":false,"usgs":true,"family":"Bellmore","given":"J.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":934959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sergeant, Christopher J.","contributorId":140496,"corporation":false,"usgs":false,"family":"Sergeant","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":934960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bellmore, Rebecca A.","contributorId":275276,"corporation":false,"usgs":false,"family":"Bellmore","given":"Rebecca","email":"","middleInitial":"A.","affiliations":[{"id":39693,"text":"Southeast Alaska Watershed Coalition","active":true,"usgs":false}],"preferred":false,"id":934961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fellman, Jason B.","contributorId":198741,"corporation":false,"usgs":false,"family":"Fellman","given":"Jason","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":934963,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70246796,"text":"70246796 - 2023 - Out of the frying pan and into the fire: Effects of volcanic heat and other stressors on the conservation of a critically endangered plant in Hawaiʻi","interactions":[],"lastModifiedDate":"2023-07-19T13:36:39.868035","indexId":"70246796","displayToPublicDate":"2023-01-06T08:34:04","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1531,"text":"Environmental Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Out of the frying pan and into the fire: Effects of volcanic heat and other stressors on the conservation of a critically endangered plant in Hawaiʻi","docAbstract":"Loss of local biodiversity resulting from abrupt environmental change is a significant environmental problem throughout the world. Extinctions of plants are particularly important yet are often overlooked. Drawing from a case in Hawai‘i, a global hotspot for plant and other extinctions, we demonstrate an effort to better understand and determine priorities for the management of an endangered plant (‘Ihi makole or Portulaca sclerocarpa) in the face of rapid and extreme environmental change. Volcanic heat emissions and biological invasions have anecdotally been suggested as possible threats to the species. We integrated P. sclerocarpa outplanting with efforts to collect geological and ecological data to gauge the role of elevated soil temperatures and invasive grasses in driving P. sclerocarpa mortality and population decline. We measured soil temperature, soil depth, surrounding cover and P. sclerocarpa survivorship over three decades. The abundance of wild P. sclerocarpa decreased by 99.7% from the 1990s to 2021. Only 51% of outplantings persisted through 3–4 years. Binomial regression and structural equation modelling revealed that, among the variables we analysed, high soil temperatures were most strongly associated with population decline. Finding the niche where soil temperatures are low enough to allow P. sclerocarpa survival but high enough to limit other agents of P. sclerocarpa mortality may be necessary to increase population growth of this species.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0376892922000480","usgsCitation":"Gill, N.S., Stallman, J., Pratt, L., Lewicki, J.L., Elias, T., Nadeau, P.A., and Yelenik, S.G., 2023, Out of the frying pan and into the fire: Effects of volcanic heat and other stressors on the conservation of a critically endangered plant in Hawaiʻi: Environmental Conservation, v. 20, no. 2, p. 108-115, https://doi.org/10.1017/S0376892922000480.","productDescription":"8 p.","startPage":"108","endPage":"115","ipdsId":"IP-138767","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444933,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/s0376892922000480","text":"Publisher Index Page"},{"id":435520,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P1CA58","text":"USGS data release","linkHelpText":"Hawaii Volcanoes National Park, Puhimau Geothermal Area vegetation and abiotic data, 2011-2021"},{"id":419148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Hawai‘i Volcanoes National Park, Puhimau Thermal Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.2342961755231,\n 19.403837326641053\n ],\n [\n -155.2342961755231,\n 19.27954820153461\n ],\n [\n -155.0608186659034,\n 19.27954820153461\n ],\n [\n -155.0608186659034,\n 19.403837326641053\n ],\n [\n -155.2342961755231,\n 19.403837326641053\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Gill, Nathan S.","contributorId":211061,"corporation":false,"usgs":false,"family":"Gill","given":"Nathan","email":"","middleInitial":"S.","affiliations":[{"id":38177,"text":"Department of Integrative Biology, University of Wisconsin-Madison, Madison","active":true,"usgs":false}],"preferred":false,"id":878305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stallman, Jeff 0000-0003-4713-2193","orcid":"https://orcid.org/0000-0003-4713-2193","contributorId":245750,"corporation":false,"usgs":false,"family":"Stallman","given":"Jeff","email":"","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":878306,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pratt, Linda","contributorId":316790,"corporation":false,"usgs":false,"family":"Pratt","given":"Linda","affiliations":[{"id":68693,"text":"PIERC (Formerly)","active":true,"usgs":false}],"preferred":false,"id":878307,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":878308,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elias, Tamar 0000-0002-9592-4518 telias@usgs.gov","orcid":"https://orcid.org/0000-0002-9592-4518","contributorId":3916,"corporation":false,"usgs":true,"family":"Elias","given":"Tamar","email":"telias@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":878309,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nadeau, Patricia A. 0000-0002-6732-3686","orcid":"https://orcid.org/0000-0002-6732-3686","contributorId":215616,"corporation":false,"usgs":true,"family":"Nadeau","given":"Patricia","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":878310,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yelenik, Stephanie G. 0000-0002-9011-0769","orcid":"https://orcid.org/0000-0002-9011-0769","contributorId":256836,"corporation":false,"usgs":false,"family":"Yelenik","given":"Stephanie","email":"","middleInitial":"G.","affiliations":[{"id":51875,"text":"formerly U.S. Geological Survey; currently Rocky Mountain Research Station, U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":878311,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70248766,"text":"70248766 - 2023 - Intensified warming and aridity accelerate terminal lake desiccation in the Great Basin of the western United States","interactions":[],"lastModifiedDate":"2023-09-20T11:42:25.220554","indexId":"70248766","displayToPublicDate":"2023-01-06T06:40:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Intensified warming and aridity accelerate terminal lake desiccation in the Great Basin of the western United States","docAbstract":"Terminal lakes in the Great Basin (GB) of the western US host critical wildlife habitat and food for migrating birds and can be associated with serious human health and economic consequences when they desiccate. Water levels have declined dramatically in the last 100+ years due to diversion of inflows, drought and climate change. Satellite-derived environmental science data records (ESDRs) from the MODerate-resolution Imaging Spectroradiometer (MODIS) (snow cover, evapotranspiration (ET) and land surface temperature (LST)), enable a unique approach to evaluate the effects of aridification on terminal lakes and to study their individual vulnerabilities. Surface and air temperatures in the GB are rising dramatically, with a sharp rise in the rate of increase observed beginning around 2011, while the number of days of snow cover is declining especially in the western mountainous part of the GB as exemplified in Mono Basin, California. Rising temperatures coincide with fewer days of snow cover, a decrease of inflow to the lakes and greater evaporation of water from the lakes. MODIS ESDRs show strong and statistically significant increasing surface temperature (LST) in the GB, a reduction in the number of days of snow cover, and mixed results in ET. ET declined slightly in the more arid parts of the GB due to greater moisture restrictions to evaporation from extended drought, while ET increased in the more-vegetated, wetter, mountainous northeastern parts as temperatures have risen. Severe and costly ecological, human health and economic consequences are expected if the lakes continue to decline as predicted.
Xanthe Terra is a high-standing cratered plain located southeast of Lunae Planum and south of Chryse Planitia in the western equatorial region of Mars. It contains landforms shaped by diverse geologic processes, including various scales of channels and valleys, chaotic terrains, delta fan deposits, and landslides. An extensive outflow channel system is located within Xanthe Terra and the surrounding circum-Chryse region, including Shalbatana and Ravi Valles, thought to have formed by catastrophic flooding during the Hesperian to Amazonian Periods. The study region within Xanthe Terra is defined by Mars Transverse Mercator (MTM) quadrangles 00042 and 00047 (2.5° to −2.5° N, 310° to 320° E) and includes Orson Welles crater (124.5 km diameter, the source region for Shalbatana Vallis), the southernmost portion of Shalbatana Vallis, Aromatum Chaos (the source region for Ravi Vallis), the westernmost portion of Ravi Vallis, and the source area of Nanedi Valles. The Mars Odyssey Thermal Emission Image System (THEMIS) IR daytime mosaic (100 m/pixel) was used as the primary base map. We constructed the geologic map of the source region of Shalbatana Vallis at 1:750,000 scale. We defined 16 geologic units in the map area, which we divided into the following groups: plains units, channel units, crater units, chaos units, flow units, and surficial units. Mapped linear features include ridge crests, scarp crests, channels, crests of crater rims, crests of buried or degraded crater rims, graben traces, grooves, troughs, and faults. Surface features include secondary crater chains and dark ejecta material. The geologic history of the map region can be summarized as follows. During the Noachian Period, ancient highland materials in the Xanthe Terra region, including lava and any ancient sedimentary units present, were reworked by impacts during the heavy bombardment. In particular, the impact that formed a basin that later underwent widespread resurfacing, likely as a combination of lava flows, reworked crater materials, and sedimentary deposits resulting in the flat-lying, smooth plains of Chryse Planitia. The Hesperian Period was characterized by the impact that formed Orson Welles crater and the subsequent formation of Shalbatana Vallis, as well as Aromatum Chaos and Ravi Vallis. During this period, depressions were filled with smooth material that was subsequently modified by collapse, subsidence, and flooding. Water filled and overflowed the tops of Orson Welles crater and other depressions. The Amazonian Period was characterized by ongoing collapse, as well as the formation of flow and surficial materials, including a lava flow that extends from Aromatum Chaos.
Astrogeology Science Center
U.S. Geological Survey
2255 N. Gemini Dr.
Flagstaff, AZ 86001
In a system that uses supplemental stocking to enhance a fishery that serves a dual purpose, an understanding of the contributions from natural and hatchery-produced fish is important so that hatchery resources can be appropriately allocated. Kokanee Oncorhynchus nerka were first stocked in Flaming Gorge Reservoir (FGR), Wyoming–Utah, in 1963 and serve a dual purpose as a prey resource and sport fish. Although natural recruitment occurs in the reservoir, a supplemental stocking program was initiated in 1991. We sought to identify the natal origin (i.e., natural, hatchery) of kokanee in FGR using otolith microchemistry. We evaluated return to the creel, composition of spawning aggregates, and growth of kokanee in FGR and focused on differences associated with natal origin. We analyzed kokanee otoliths that we collected from hatcheries (n = 60) and FGR (n = 1,003) for the strontium isotope ratio, 87Sr/86Sr, using laser ablation and a multicollector inductively coupled plasma mass spectrometer. We conducted Kruskal–Wallis tests to compare the strontium isotope ratios from the otolith edge of kokanee that we sampled from hatcheries and FGR. Based on 87Sr/86Sr ratios, we could distinguish natural-origin kokanee from 11 of the 12 hatcheries (P < 0.01); however, the Wigwam Hatchery was not significantly different from FGR (P = 0.84). We used model-based discriminant function analysis to assign natal origins for kokanee caught in FGR. Hatchery contribution to the population at large varied from 21 to 50% among year classes from 2014 to 2018. The percentage of hatchery origin kokanee in the creel (18–50%) was similar to what we observed in the population. Hatchery-produced kokanee contributed a higher proportion to tributary-spawning aggregates (40–90%) than shoreline-spawning aggregates (19–58%) by sample year. Growth of natural and hatchery kokanee was similar, suggesting similar performance in the system. Results from this study identify that hatchery supplementation contributes to the population and recreational harvest of kokanee in FGR. This research also provides insight into the ecology of kokanee that is useful for better understanding kokanee population dynamics in reservoir systems.
","language":"English","publisher":"Allen Press","doi":"10.3996/JFWM-22-009","usgsCitation":"Black, A., Walrath, J., Willmes, M., and Quist, M.C., 2023, Natal contributions of Kokanee salmon to Flaming Gorge Reservoir, Wyoming–Utah: An evaluation using otolith microchemistry: Journal of Fish and Wildlife Management, v. 14, no. 1, p. 90-107, https://doi.org/10.3996/JFWM-22-009.","productDescription":"18 p.","startPage":"90","endPage":"107","ipdsId":"IP-134905","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":444961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3996/jfwm-22-009","text":"Publisher Index Page"},{"id":429872,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah, Wyoming","otherGeospatial":"Flaming Gorge Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -109.36367201626237,\n 41.43666565226448\n ],\n [\n -109.73395063659062,\n 41.43666565226448\n ],\n [\n -109.73395063659062,\n 40.835428277844755\n ],\n [\n -109.36367201626237,\n 40.835428277844755\n ],\n [\n -109.36367201626237,\n 41.43666565226448\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Black, Aaron","contributorId":288737,"corporation":false,"usgs":false,"family":"Black","given":"Aaron","email":"","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":902314,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walrath, John D.","contributorId":171507,"corporation":false,"usgs":false,"family":"Walrath","given":"John D.","affiliations":[],"preferred":false,"id":902315,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willmes, Marte","contributorId":337272,"corporation":false,"usgs":false,"family":"Willmes","given":"Marte","affiliations":[{"id":64417,"text":"University of California--Davis","active":true,"usgs":false}],"preferred":false,"id":902316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902317,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239827,"text":"70239827 - 2023 - Experimental infection of Mexican free-tailed bats (Tadarida brasiliensis) with SARS-CoV-2","interactions":[],"lastModifiedDate":"2023-03-01T17:12:26.997493","indexId":"70239827","displayToPublicDate":"2023-01-04T06:44:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5160,"text":"mSphere","active":true,"publicationSubtype":{"id":10}},"title":"Experimental infection of Mexican free-tailed bats (Tadarida brasiliensis) with SARS-CoV-2","docAbstract":"Groundwater in northwestern Louisiana is a valuable resource needed for expanding public-supply needs as well as possible energy development needs arising from Haynesville Formation natural-gas production. The Red River alluvial and the Carrizo-Wilcox aquifers are two of the most important and heavily pumped aquifers in northwestern Louisiana; however, little documentation of the regional hydrogeologic framework is available. The U.S. Geological Survey and the Louisiana Department of Transportation and Development have consolidated information from, and built upon, previous studies of the Red River alluvial and the Carrizo-Wilcox aquifers to characterize and document the regional hydrogeologic framework of northwestern Louisiana.
The study area has been tectonically modified and includes abundant structural features such as salt domes and areally extensive faulting in addition to minor folding related to these features, all of which impact the sedimentological and hydraulic characteristics of the freshwater-bearing strata. The hydrogeologic framework of northwestern Louisiana comprises a sequence of structurally modifi ed, complexly interbedded, varyingly interconnected, clayey, sandy, and gravelly alluvial sediments. The important freshwater hydrogeologic units include the Quaternary Red River alluvial and upland terrace aquifers, and the underlying Tertiary Sparta, Cane River, and Carrizo-Wilcox aquifers. The Midway confining unit underlies the Carrizo-Wilcox aquifer throughout the study area. No freshwater is present in or below the Midway Group.
Tertiary-age formations exposed at land surface in the study area have been incised by the Red River and are hydraulically connected to the Quaternary Red River alluvium in the Red River valley. In 2010, 7.73 million gallons per day (Mgal/d) of water were withdrawn from the Red River alluvial aquifer in the study area, representing an increase of 2.00 Mgal/d, or about 35 percent, over 2005 withdrawal rates.
The Tertiary Carrizo Sand and Wilcox Group crop out across much of the study area. The two units are hydraulically connected and function as a single hydrologic unit referred to as the Carrizo-Wilcox aquifer. In 2010, 19.33 Mgal/d of water were withdrawn from the Carrizo-Wilcox aquifer in the study area, representing an increase of nearly 1.8 Mgal/d, or about 10 percent, over 2005 withdrawal rates. Any expansion in energy development, as well as water needs of an increasing population, could result in an increased demand on groundwater in northwestern Louisiana.
","language":"English","publisher":"Louisiana Department of Transportation and Development","usgsCitation":"Hays, P.D., Nottmeier, A.M., Fendick, R.B., Daugherty, W.J., and Carter, K., 2023, Hydrogeologic framework of the Red River alluvial aquifer and Carrizo-Wilcox aquifer in northwestern Louisiana: Water Resources Technical Report of the Louisiana Department of Transportation and Development, Office of Public Works 82, 35 p.","productDescription":"35 p.","ipdsId":"IP-122443","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":427146,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427145,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://wise.er.usgs.gov/dp/pdfs/USGSDOTD_WRTR82.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.04836792990136,\n 33.02200760162475\n ],\n [\n -94.04836792990136,\n 31.205735114403552\n ],\n [\n -91.87339632735423,\n 31.205735114403552\n ],\n [\n -91.87339632735423,\n 33.02200760162475\n ],\n [\n -94.04836792990136,\n 33.02200760162475\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hays, Phillip D. 0000-0001-5491-9272 pdhays@usgs.gov","orcid":"https://orcid.org/0000-0001-5491-9272","contributorId":4145,"corporation":false,"usgs":true,"family":"Hays","given":"Phillip","email":"pdhays@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":836782,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nottmeier, Anna M. 0000-0002-0205-0955 anottmeier@usgs.gov","orcid":"https://orcid.org/0000-0002-0205-0955","contributorId":5283,"corporation":false,"usgs":true,"family":"Nottmeier","given":"Anna","email":"anottmeier@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":836783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fendick, Robert B.","contributorId":287472,"corporation":false,"usgs":false,"family":"Fendick","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":836784,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daugherty, William J.","contributorId":287473,"corporation":false,"usgs":false,"family":"Daugherty","given":"William","email":"","middleInitial":"J.","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":897434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Carter, Kayla kcarter@usgs.gov","contributorId":5681,"corporation":false,"usgs":true,"family":"Carter","given":"Kayla","email":"kcarter@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":897435,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70240147,"text":"70240147 - 2023 - Maximizing the water quality benefits of wetlands in croplands","interactions":[],"lastModifiedDate":"2023-01-31T16:09:46.160963","indexId":"70240147","displayToPublicDate":"2023-01-01T10:06:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13286,"text":"Conservation Insight","active":true,"publicationSubtype":{"id":1}},"title":"Maximizing the water quality benefits of wetlands in croplands","docAbstract":"Key Takeaways
Nutrient loads from croplands continue to negatively affect surface water quality, despite considerable investments in and adoption of agricultural conservation practices aimed at reducing nutrient losses.
Numerous studies indicate that effective restoration and management of wetlands in and adjacent to cultivated croplands could reduce surface and subsurface nutrient loads to downstream waters.
Current drainage basin-scale models do not effectively account for the local-scale processes that are important in understanding the functional variability of wetlands and their potential as conservation practices across different spatial and temporal scales.
Findings presented here from a literature review and simulation modeling study help inform bottom-up field-scale modeling of nitrogen and phosphorus dynamics and improve our understanding of the capacity for wetlands to provide nutrient retention services in agricultural drainage basins to inform strategic agricultural wetland restoration
","language":"English","publisher":"U.S. Department of Agriculture","usgsCitation":"McKenna, O.P., Ross, C.D., and Prenger, J., 2023, Maximizing the water quality benefits of wetlands in croplands: Conservation Insight, 4 p.","productDescription":"4 p.","ipdsId":"IP-123979","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":412507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412472,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nrcs.usda.gov/sites/default/files/2023-01/CEAP-Wetlands-2023-ConservationInsight-WetlandsWaterQuality.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKenna, Owen P. 0000-0002-5937-9436 omckenna@usgs.gov","orcid":"https://orcid.org/0000-0002-5937-9436","contributorId":198598,"corporation":false,"usgs":true,"family":"McKenna","given":"Owen","email":"omckenna@usgs.gov","middleInitial":"P.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":862766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Caryn D 0000-0002-9125-1424","orcid":"https://orcid.org/0000-0002-9125-1424","contributorId":300667,"corporation":false,"usgs":true,"family":"Ross","given":"Caryn","email":"","middleInitial":"D","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":862767,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prenger, Joseph","contributorId":301843,"corporation":false,"usgs":false,"family":"Prenger","given":"Joseph","email":"","affiliations":[{"id":65354,"text":"USDA Natural Resources Conservation Service","active":true,"usgs":false}],"preferred":false,"id":862768,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70250602,"text":"70250602 - 2023 - Geologic map of Okmok Volcano","interactions":[],"lastModifiedDate":"2023-12-21T15:32:24.005778","indexId":"70250602","displayToPublicDate":"2023-01-01T09:28:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5492,"text":"Report of Investigations of the Alaska Department of Natural Resources, Division of Geological & Geophysical Surveys","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"2023-1","title":"Geologic map of Okmok Volcano","docAbstract":"The geologic map and description of map units presented here cover approximately 880 km2 of northeastern Umnak Island, Aleutian Islands, Alaska. This report focuses on Okmok Volcano and its eruptive products and updates the mid-20th-century geologic map of Byers (1959). Mapped deposits reflect the state of the volcano just prior to the 2008 eruption. Published information about other portions of Umnak Island geology, including Mount Recheshnoi and Mount Vsevidof, can be found in Byers (1959). The 2008 eruption and its deposits are described in Larsen and others (2009, 2013, 2015).
Okmok Volcano is one of 54 historically active volcanoes in the Alaska–Aleutian volcanic arc that stretches across southern mainland Alaska and the Aleutian Islands (fig. 1; Wood and Kienle, 1990; Miller and others, 1998; Cameron and others, 2020). The highest point of the modern Okmok Caldera is along the caldera’s northern rim, 967 m in elevation, and formally named “Mount Okmok” (U.S. Board on Geographic Names, www.usgs.gov/core-science-systems/ngp/boardon-geographic-names/domestic-names). Okmok Volcano dominates the northeastern portion of Umnak Island, which is 100 km southwest of Unalaska/Dutch Harbor and 1,400 km southwest of Anchorage (figs. 1, 2). The Port of Dutch Harbor on Unalaska Island produces the highest volume of seafood for any port in the United States (see fisheries.noaa.gov/resource/document/fisheries-united-states-2018-report). Unalaska city and the Port of Dutch Harbor have been impacted by ash fall and drifting ash clouds from Okmok Volcano’s explosive eruptions as recently as 2008. Holocene and late Pleistocene volcanic rocks and deposits of Okmok Volcano rest upon glaciated Tertiary volcanic and sedimentary rocks (Byers, 1959).
The first geologic mapping expedition to Okmok Volcano was by the U.S. Geological Survey (USGS) after the 1945 eruption, largely in response to concerns about volcanic hazards to U.S. military activities in the Aleutians Islands (Byers and others, 1947, 1959; Byers and Brannock, 1949; Byers, 1955, 1959, 1961). The State of Alaska conducted further mapping and geochemical studies as part of its geothermal exploration program in the 1980s (Nye, 1983; Nye and Reid, 1986; Motyka and others, 1993). Additional modern geological work focused on Okmok Volcano and the rest of Umnak Island to address the geochemistry and origin of primary Aleutian arc magmas and subduction zone mass recycling (Marsh, 1982; Brophy and Marsh, 1986; Nye and Reid, 1986; Myers and Marsh, 1987; Miller and others, 1992; Fournelle and others, 1994; Kay and Kay, 1994).
In 1998, the Alaska Volcano Observatory (AVO) began a multi-year effort to expand geophysical monitoring in the central Aleutians Islands, including at Okmok Volcano. As part of this effort, AVO geologists from the University of Alaska Fairbanks Geophysical Institute (UAF/GI), the Alaska Division of Geological & Geophysical Surveys (DGGS), and USGS also began a renewed effort to document Okmok Volcano’s recent eruption products. The project started with reconnaissance fieldwork to document and sample products from the 1997 eruption within Okmok Caldera. This evolved into an effort to produce an updated geologic map of Okmok Volcano and gather more information about its eruptive history and hazards. Three significant eruptions occurred at Okmok Volcano in 1958, 1997, and 2008—after fieldwork had been conducted for the original 1:63,360-scale geologic map produced by Byers (1959)—resulting in new volcanic deposits not previously described.
Okmok Volcano is one of the most frequently active volcanoes in the Aleutian volcanic arc. Seismic and geodetic monitoring indicate ongoing unrest at Okmok Volcano since at least 1997. Geodetic observations of inflation before and after the 1997 and 2008 eruptions indicate a nearly continuous input of new magma from a depth consistent with frequent eruptions of basalt and basaltic andesite magmas over the past 200 years (Larsen and others, 2013; Lu and others, 2000, 2003, 2005; Mann, 2002; Mann and others, 2002). To better understand the likelihood and character of future eruptions from Okmok Volcano, it is necessary to understand its past behavior, including eruptions since the first geologic map was published by Byers (1959).
","language":"English","publisher":"Alaska Division of Geological and Geophysical Surveys","doi":"10.14509/31015","usgsCitation":"Larsen, J., Neal, C.A., Schaefer, J., and Nye, C., 2023, Geologic map of Okmok Volcano: Report of Investigations of the Alaska Department of Natural Resources, Division of Geological & Geophysical Surveys 2023-1, 63 p., https://doi.org/10.14509/31015.","productDescription":"63 p.","ipdsId":"IP-142905","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":444978,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14509/31015","text":"Publisher Index Page"},{"id":423837,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Okmok Volcano, Umnak Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.4940614057107,\n 53.01297120722842\n ],\n [\n -167.799296762778,\n 53.38973492849598\n ],\n [\n -167.78079711252238,\n 53.5365823869877\n ],\n [\n -168.09734668356276,\n 53.57077373403283\n ],\n [\n -168.38306350417713,\n 53.49991813616461\n ],\n [\n -168.7222237588632,\n 53.274349397005494\n ],\n [\n -169.14976831531723,\n 52.810922775693314\n ],\n [\n -168.97504939623653,\n 52.78979597004388\n ],\n [\n -168.4940614057107,\n 53.01297120722842\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Larsen, Jessica 0000-0003-1171-129X","orcid":"https://orcid.org/0000-0003-1171-129X","contributorId":242808,"corporation":false,"usgs":false,"family":"Larsen","given":"Jessica","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":890527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neal, Christina A. 0000-0002-7697-7825 tneal@usgs.gov","orcid":"https://orcid.org/0000-0002-7697-7825","contributorId":131135,"corporation":false,"usgs":true,"family":"Neal","given":"Christina","email":"tneal@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":890528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schaefer, Janet","contributorId":199547,"corporation":false,"usgs":false,"family":"Schaefer","given":"Janet","affiliations":[],"preferred":false,"id":890529,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nye, Christopher J.","contributorId":332578,"corporation":false,"usgs":false,"family":"Nye","given":"Christopher J.","affiliations":[{"id":79497,"text":"Alaska Division of Geological & Geophysical Surveys (retired)","active":true,"usgs":false}],"preferred":false,"id":890530,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70240926,"text":"70240926 - 2023 - Inferring geologic structure from gravity anomalies: Proceed with caution","interactions":[],"lastModifiedDate":"2026-03-19T14:29:29.206183","indexId":"70240926","displayToPublicDate":"2023-01-01T09:28:09","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Inferring geologic structure from gravity anomalies: Proceed with caution","docAbstract":"Characterization of key geologic structures within a study region, such as basin depths, fault offsets, and fault dip, are often derived from gravity data. Gravity modeling of such subsurface geologic structure generally assumes either homogeneous or spatially uncorrelated densities within modeled rock bodies and overlying sediments. This assumption allows modeling to focus on the shape of the subsurface bodies, for example, body depth or fault dip, which then underpin subsequent structural interpretations. However, both surface and drill-hole samples from rock bodies and sediments show a range of density values that exhibit spatial correlation, The spatially-correlated densities add low-frequency noise to the models that is difficult to detect and characterize which can lead to misinterpretations of the subsurface structure.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic mapping forum 22/23 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"Phelps, G., 2023, Inferring geologic structure from gravity anomalies: Proceed with caution, in Geologic mapping forum 22/23 abstracts, p. 39-40.","productDescription":"2 p.","startPage":"39","endPage":"40","ipdsId":"IP-147435","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":501306,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501305,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/256180"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phelps, Geoffrey 0000-0003-1958-2736 gphelps@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-2736","contributorId":127489,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey","email":"gphelps@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":865326,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70252806,"text":"70252806 - 2023 - 2021–2022 Statewide Abundance Estimates for the Florida Manatee","interactions":[],"lastModifiedDate":"2024-04-05T14:14:20.517907","indexId":"70252806","displayToPublicDate":"2023-01-01T09:10:24","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":138,"text":"Technical Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"TR-27","title":"2021–2022 Statewide Abundance Estimates for the Florida Manatee","docAbstract":"Knowing the population size of Florida manatees (Trichechus manatus latirostris) is critical for conservation and management of this threatened species. Martin et al. (2015) and Hostetler et al. (2018) applied statistical models that incorporated multiple data sources to estimate the statewide abundance of manatees from aerial surveys f lown in 2011–2012 and 2015–2016. We conducted additional aerial surveys in 2021–2022 and applied similar models to provide an updated abundance estimate. This report serves as an update to Hostetler et al. (2018), with most of the text and methodology adapted from the previous report, and provides updated population estimates based on the newly available data. We estimate that the number of manatees in Florida in 2021–2022 was 9,790 (95% Bayesian credible interval 8,350–11,730), of which 4,630 (3,960–5,420) were on the west coast of Florida and 5,160 (3,940–6,980) were on the east coast. These estimates and the associated uncertainty, in addition to being of immediate value to wildlife managers, are essential new data for incorporation into integrated population models and population viability analyses. We also provide context for interpreting the new estimates and perspectives for future modeling improvements.
","language":"English","publisher":"Florida Fish and Wildlife Conservation Commission","usgsCitation":"Gowan, T., Edwards, H.H., Krzystan, A.M., Martin, J., and Hostetler, J.A., 2023, 2021–2022 Statewide Abundance Estimates for the Florida Manatee: Technical Report TR-27, 14 p.","productDescription":"14 p.","ipdsId":"IP-153497","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":427511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":427508,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://myfwc.com/research/publications/technical-reports/"}],"country":"United States","state":"Florida","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"id\":10,\"properties\":{\"name\":\"Florida\",\"nation\":\"USA 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Commission","active":true,"usgs":false}],"preferred":false,"id":898280,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":898281,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":898282,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241524,"text":"70241524 - 2023 - Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities","interactions":[],"lastModifiedDate":"2023-03-22T13:52:48.219679","indexId":"70241524","displayToPublicDate":"2023-01-01T08:44:46","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13626,"text":"DWH MDBC Data Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"DR-23-01","title":"Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities","docAbstract":"This report is part of the NOAA Mesophotic and Deep Benthic Communities (MDBC) Series of \npublications that share the results of work conducted by the Deepwater Horizon MDBC restoration projects. \n \nThe 2010 Deepwater Horizon oil spill was an unprecedented event. Approximately 3.2 million barrels of oil were released into the deep ocean over nearly three months. The plume of oil moved throughout the water column, formed surface slicks that cumulatively covered an area the size of Virginia, and washed oil onto at least 1,300 miles of shoreline habitats. More than 770 square miles (2,000 square kilometers) of deep benthic habitat surrounding the Deepwater Horizon wellhead and 4-square miles of the Pinnacles mesophotic reef complex, located at the edge of the continental shelf, were injured by the oil spill. \n \nUnder the Oil Pollution Act, state and federal natural resource trustees conducted a Natural Resource Damage Assessment (NRDA). The Trustees assessed damages, quantifying the unprecedented injuries to natural resources and lost services. They also developed a programmatic restoration plan to restore injured resources and compensate the public for lost services. \n \nIn April 2016, a settlement was finalized that included up to $8.8 billion in funding for the Deepwater Horizon Trustees to restore the natural resource injuries caused by the oil spill as described in their programmatic restoration plan, Final Programmatic Damage Assessment and Restoration Plan and Final Programmatic Environmental Impact Statement. The Deepwater Horizon Open Ocean Trustee Implementation Group is responsible for restoring natural resources and their services within the Open Ocean Restoration Area that were injured by the oil spill. The Open Ocean Trustees include NOAA, Department of the Interior, U.S. Environmental Protection Agency, and U.S. Department of Agriculture. \n \nIn 2019, the Open Ocean Trustee Implementation Group committed more than $126 million to \nimplement four restoration projects to address the injury to MDBC. The MDBC projects are: mapping, Ground-truthing, and Predictive Habitat Modeling; Habitat Assessment and Evaluation; Coral Propagation Technique Development; and Active Management and Protection. NOAA and the Department of the Interior are implementing the projects, in cooperation with a range of partners, over eight years. \n \nTogether, the projects take a phased approach to meet the challenges involved in restoring deep-sea habitats. Challenges to restoration include a limited scientific understanding of these communities, limited experience with restoration at the depths at which these communities occur, and remote locations that limit accessibility. \n \nMore information about Deepwater Horizon restoration and the MDBC restoration projects is available at: www.gulfspillrestoration.noaa.gov.","language":"English","publisher":"NOAA","doi":"10.25923/kz7t-4674","usgsCitation":"Bassett, R., Herting, J., Frometa, J., Sharuga, S.M., Howell, J., Siceloff, L., Bourque, J.R., Cromwell, M., Francis, K., Clark, R., Demopoulos, A., David, A., Benson, K., and Harter, S.L., 2023, Comprehensive inventory of habitat assessment and evaluation datasets to support Deepwater Horizon mesophotic and deep benthic communities: DWH MDBC Data Report DR-23-01, 68 p., https://doi.org/10.25923/kz7t-4674.","productDescription":"68 p.","ipdsId":"IP-143985","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":414549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.4738402663695,\n 27.73976270326594\n ],\n [\n -88.43668753646247,\n 28.377487555215865\n ],\n [\n -87.08865291012629,\n 29.215833830999557\n ],\n [\n -87.79750143247816,\n 30.10517365534068\n ],\n [\n -88.52009799635897,\n 30.199023526767235\n ],\n [\n -89.11487834086316,\n 30.0687140895985\n ],\n [\n -89.42838914695855,\n 29.569401260101472\n ],\n [\n -89.06685117410953,\n 29.1845830007817\n ],\n [\n -89.02359871978788,\n 28.964173359471857\n ],\n [\n -89.57102082101116,\n 29.108470712158947\n ],\n [\n -91.61652997779979,\n 28.32580643304547\n ],\n [\n -92.09126902602307,\n 28.00138024651494\n ],\n [\n -92.01917703089228,\n 27.72672931065955\n ],\n [\n -91.4738402663695,\n 27.73976270326594\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bassett, Rachel","contributorId":302194,"corporation":false,"usgs":false,"family":"Bassett","given":"Rachel","email":"","affiliations":[{"id":65431,"text":"CSS Inc, under contract to NOAA/NOS","active":true,"usgs":false}],"preferred":false,"id":867102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herting, Jennifer","contributorId":302201,"corporation":false,"usgs":false,"family":"Herting","given":"Jennifer","email":"","affiliations":[{"id":65436,"text":"Tech Global, Inc., Under contract to NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frometa, Janessy","contributorId":200722,"corporation":false,"usgs":false,"family":"Frometa","given":"Janessy","email":"","affiliations":[],"preferred":false,"id":867104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sharuga, Stephanie M.","contributorId":301148,"corporation":false,"usgs":false,"family":"Sharuga","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[{"id":65319,"text":"Genwest Systems","active":true,"usgs":false}],"preferred":false,"id":867105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howell, Jacob","contributorId":218500,"corporation":false,"usgs":false,"family":"Howell","given":"Jacob","affiliations":[{"id":39855,"text":"NOAA contractor","active":true,"usgs":false}],"preferred":false,"id":867106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Siceloff, Laughlin","contributorId":303301,"corporation":false,"usgs":false,"family":"Siceloff","given":"Laughlin","email":"","affiliations":[{"id":65431,"text":"CSS Inc, under contract to NOAA/NOS","active":true,"usgs":false}],"preferred":false,"id":867107,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bourque, Jill R. 0000-0003-3809-2601","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":215719,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":867108,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cromwell, Megan","contributorId":303303,"corporation":false,"usgs":false,"family":"Cromwell","given":"Megan","email":"","affiliations":[{"id":65754,"text":"NOAA/NCEI","active":true,"usgs":false}],"preferred":false,"id":867109,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Francis, Kirstie","contributorId":303304,"corporation":false,"usgs":false,"family":"Francis","given":"Kirstie","email":"","affiliations":[{"id":65754,"text":"NOAA/NCEI","active":true,"usgs":false}],"preferred":false,"id":867110,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Clark, Randy","contributorId":218497,"corporation":false,"usgs":false,"family":"Clark","given":"Randy","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":867111,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222192,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":867112,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"David, Andy","contributorId":302199,"corporation":false,"usgs":false,"family":"David","given":"Andy","email":"","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867113,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Benson, Kristopher","contributorId":302200,"corporation":false,"usgs":false,"family":"Benson","given":"Kristopher","email":"","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867114,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Harter, Stacey L.","contributorId":302195,"corporation":false,"usgs":false,"family":"Harter","given":"Stacey","email":"","middleInitial":"L.","affiliations":[{"id":62397,"text":"NOAA/NMFS","active":true,"usgs":false}],"preferred":false,"id":867115,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70240778,"text":"70240778 - 2023 - Skeletal indicators of locomotor adaptations in shrews","interactions":[],"lastModifiedDate":"2023-02-22T14:24:43.331761","indexId":"70240778","displayToPublicDate":"2023-01-01T08:21:19","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13293,"text":"Therya","active":true,"publicationSubtype":{"id":10}},"title":"Skeletal indicators of locomotor adaptations in shrews","docAbstract":"The Soricidae (Mammalia: Eulypotyphla) comprises more than 450 species inhabiting a variety of habitats on five continents. As a family, shrews employ a variety of locomotor modes that incorporate ambulatory, fossorial, aquatic, and scansorial behaviors, illustrating an ability to exploit a variety of natural substrates and their associated resources. In this study, the association of skeletal morphology and three of the dominant locomotor modes in the family—ambulatory, semi-fossorial, and semi-aquatic behaviors—was investigated in up to 52 species of 12 genera representing all three subfamilies of Soricidae. From skeletal measures, 34 morphological indices were calculated, most of which have been used previously to characterize substrate use among shrews, rodents, and other mammals, and analyzed for their individual effectiveness for discriminating the three locomotory modes. To assess their effectiveness in combination, subsets of locomotor indices were analyzed using 1) mean percentile ranks, 2) the first principal component from principal components analysis, and 3) plots and classifications from discriminant function analyses. In general, the three methods effectively identified and grouped the three locomotor modes and identified smaller subsets. Additional analyses were then used to classify the locomotor behaviors of five species whose locomotor modes were unknown or ambiguous. The analyses reinforce and broaden the scope of a previously identified observation of the wide range of grades of morphological variation that may permit an equally diverse range of locomotor abilities among the Soricidae.
","language":"English","publisher":"Asociación Mexicana de Mastozoología A. C.","doi":"10.12933/therya-23-2218","usgsCitation":"Woodman, N., 2023, Skeletal indicators of locomotor adaptations in shrews: Therya, v. 14, no. 1, p. 15-37, https://doi.org/10.12933/therya-23-2218.","productDescription":"23 p.","startPage":"15","endPage":"37","ipdsId":"IP-147190","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444989,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.12933/therya-23-2218","text":"Publisher Index Page"},{"id":413281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Woodman, Neal 0000-0003-2689-7373 nwoodman@usgs.gov","orcid":"https://orcid.org/0000-0003-2689-7373","contributorId":3547,"corporation":false,"usgs":true,"family":"Woodman","given":"Neal","email":"nwoodman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":864803,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70239356,"text":"70239356 - 2023 - Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation","interactions":[],"lastModifiedDate":"2023-01-10T13:18:25.464452","indexId":"70239356","displayToPublicDate":"2023-01-01T07:17:05","publicationYear":"2023","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":"Improving the operational simplified surface energy balance evapotranspiration model using the forcing and normalizing operation","docAbstract":"Watershed resilience is the ability of a watershed to maintain its characteristic system state while concurrently resisting, adapting to, and reorganizing after hydrological (for example, drought, flooding) or biogeochemical (for example, excessive nutrient) disturbances. Vulnerable waters include non-floodplain wetlands and headwater streams, abundant watershed components representing the most distal extent of the freshwater aquatic network. Vulnerable waters are hydrologically dynamic and biogeochemically reactive aquatic systems, storing, processing, and releasing water and entrained (that is, dissolved and particulate) materials along expanding and contracting aquatic networks. The hydrological and biogeochemical functions emerging from these processes affect the magnitude, frequency, timing, duration, storage, and rate of change of material and energy fluxes among watershed components and to downstream waters, thereby maintaining watershed states and imparting watershed resilience. We present here a conceptual framework for understanding how vulnerable waters confer watershed resilience. We demonstrate how individual and cumulative vulnerable-water modifications (for example, reduced extent, altered connectivity) affect watershed-scale hydrological and biogeochemical disturbance response and recovery, which decreases watershed resilience and can trigger transitions across thresholds to alternative watershed states (for example, states conducive to increased flood frequency or nutrient concentrations). We subsequently describe how resilient watersheds require spatial heterogeneity and temporal variability in hydrological and biogeochemical interactions between terrestrial systems and down-gradient waters, which necessitates attention to the conservation and restoration of vulnerable waters and their downstream connectivity gradients. To conclude, we provide actionable principles for resilient watersheds and articulate research needs to further watershed resilience science and vulnerable-water management.
Body condition indices are commonly used in the management of fish populations and are a surrogate to physiological attributes such as tissue-energy reserves. Relative condition factor (Kn) describes the condition of species relative to populations in a geographic area. We developed models to allow for the calculation of Kn in Montana, USA by using the weight–length data collected by Montana Fish, Wildlife & Parks. We generated log10weight–log10length relationships to obtain Montana specific parameter estimates for relative condition equations (W′) for 51 species and three subspecies. We developed separate models by water type (e.g., lotic and lentic) and sex for five species due to varying growth based on sexual dimorphism and varying ecosystem types. Relative condition offers the advantage of describing body condition relative to species in Montana, provides a condition index for species that do not have standard-weight models developed for relative weight (Wr), and affords more information for the global database on weight–length relationships of fishes.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes8010028","usgsCitation":"Eckelbecker, R.W., Heili, N.M., Guy, C.S., and Schmetterling, D.A., 2023, Relative-condition parameters for fishes of Montana, USA: Fishes, v. 8, no. 1, 28, 8 p., https://doi.org/10.3390/fishes8010028.","productDescription":"28, 8 p.","ipdsId":"IP-139822","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":445003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes8010028","text":"Publisher Index Page"},{"id":429875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Eckelbecker, Robert W.","contributorId":338225,"corporation":false,"usgs":false,"family":"Eckelbecker","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903026,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heili, Nathaniel M.","contributorId":338227,"corporation":false,"usgs":false,"family":"Heili","given":"Nathaniel","email":"","middleInitial":"M.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":903027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Guy, Christopher S. 0000-0002-9936-4781 cguy@usgs.gov","orcid":"https://orcid.org/0000-0002-9936-4781","contributorId":2876,"corporation":false,"usgs":true,"family":"Guy","given":"Christopher","email":"cguy@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true}],"preferred":true,"id":903028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmetterling, David A.","contributorId":338230,"corporation":false,"usgs":false,"family":"Schmetterling","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":52338,"text":"Montana Fish, Wildlife & Parks","active":true,"usgs":false}],"preferred":false,"id":903029,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239219,"text":"70239219 - 2023 - Assessment of cropland inundation due to the operation of the Reelfoot Lake spillway in West Tennessee","interactions":[],"lastModifiedDate":"2023-08-07T16:55:22.918741","indexId":"70239219","displayToPublicDate":"2022-12-30T06:51:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of cropland inundation due to the operation of the Reelfoot Lake spillway in West Tennessee","docAbstract":"Running Reelfoot Bayou (RRB) is the outlet canal of Reelfoot Lake, the largest natural lake in Tennessee. RRB is not able to contain discharge from Reelfoot Lake greater than the bankfull discharge of 28 m3/s (1000 ft3/s), which typically occurs at the beginning of the growing season (April–June). Historically, the planting of crops has been delayed until flooding subsides and cropland has drained. The objective of this study is a preliminary quantification of cropland inundation to determine its spatial distribution in the RRB floodplain. Inundated croplands in the RRB floodplain were delineated over a range of spillway discharges from 2 to 57 m3/s (70–2000 ft3/s), using one-dimensional–two-dimensional hydrodynamic modeling and multispectral satellite images (Landsat 8 and Sentinel-2). The composite maps made by combining the simulated and image-derived flood maps were overlaid on the United States Department of Agriculture CropScape layer to determine the inundation of individual summer crops during the growing season. About 25% of the inundated croplands are flooded at discharges of RRB less than 28 m3/s, implying wetland hydrology. The results of this analysis can be used to inform operational management of the Reelfoot Lake spillway.
Gizzard shad (Dorosoma cepedianum) is a common freshwater fish species found throughout the central and eastern portions of North America. Within these regions, gizzard shad play several critical roles in the freshwater community such as serving as prey for other fish species and translocating nutrients from substrates into the water column. Because of this, it is important to understand gizzard shad population dynamics. Here, we introduce an integral projection model (IPM) for gizzard shad that incorporates empirical information from sources including Long Term Resource Monitoring (LTRM) upper Mississippi River restoration data. IPMs are a generalization of stage-based, matrix population models that have been used to describe a wide range of organisms, and as such are a natural choice for gizzard shad because many aspects of their life cycle have been studied. We tested model outputs against empirical patterns reported for gizzard shad from a different location along the Illinois River (La Grange Reach). Results of our work indicate that our model could serve as an important tool for predicting patterns within gizzard shad populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2022.110260","usgsCitation":"Peirce, J.P., Sandland, G., Bennie, B., and Erickson, R.A., 2023, An integral projection model for gizzard shad (Dorosoma cepedianum) utilizing density-dependent age-0 survival: Ecological Modelling, v. 477, 110260, 7 p., https://doi.org/10.1016/j.ecolmodel.2022.110260.","productDescription":"110260, 7 p.","ipdsId":"IP-138963","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":445013,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2022.110260","text":"Publisher Index Page"},{"id":427558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"477","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peirce, James P 0000-0002-7147-3695","orcid":"https://orcid.org/0000-0002-7147-3695","contributorId":316559,"corporation":false,"usgs":false,"family":"Peirce","given":"James","email":"","middleInitial":"P","affiliations":[{"id":47908,"text":"University of Wisconsin - La Crosse","active":true,"usgs":false}],"preferred":false,"id":898309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sandland, Gregory","contributorId":332579,"corporation":false,"usgs":false,"family":"Sandland","given":"Gregory","email":"","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":898310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennie, Barb","contributorId":244792,"corporation":false,"usgs":false,"family":"Bennie","given":"Barb","email":"","affiliations":[{"id":48977,"text":"UW-La Crosse","active":true,"usgs":false}],"preferred":false,"id":898311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":898312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70239211,"text":"70239211 - 2023 - Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data","interactions":[],"lastModifiedDate":"2023-01-04T13:31:11.765279","indexId":"70239211","displayToPublicDate":"2022-12-29T07:29:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data","docAbstract":"The success of long-term wildlife monitoring programs can be influenced by many factors and study designs often represent compromises between spatial scales and costs. Adaptive monitoring programs can iteratively manage this tension by adopting new cost-efficient technologies, which can provide projects the opportunity to reallocate costs to address new hypotheses, adapt to changing ecological conditions, or adjust sampling scale or resolution. If there is interest in longer time series of monitoring data, methodological transitions may necessitate integrated models to link newer data with historical data. However, data integration can be difficult if spatial or temporal scales are mismatched. Here, we develop an integrated multistate site-occupancy model and resolve sample unit spatial mismatch to link datasets from two northern spotted owl (Strix occidentalis caurina) monitoring schemes that broadly overlapped during a methodological transition. The first dataset was obtained from a decades-long spotted owl monitoring program using call-playback and mark-resight surveys on historical territories of varying size and shape. This monitoring program has recently transitioned to passive acoustic monitoring of randomly selected 5-km2 hexagons over larger spatial extents. Both monitoring datasets overlapped with areas in which barred owl (Strix varia), an invasive competitor that has played an important role in northern spotted owl declines, were being removed experimentally. Reconciling spatial mismatch substantially increased the representation of the call-playback dataset and integrating the two datasets increased precision of spotted owl use and paired occupancy estimates relative to single dataset estimates. Estimates of spotted owl pair occupancy across the study area were lower than previous territory-based estimates based on call-playback surveys. Our integrated model further showed that a concurrent barred owl removal experiment increased landscape use and site occupancy by pairs of spotted owls. Our empirical application of an integrated modelling approach demonstrates a useful analytical framework for long-term monitoring efforts undergoing methodological transitions (e.g. mark-recapture to non-invasive population monitoring). This framework allows monitoring programs to maintain continuity of monitoring objectives across methodological transitions, rigorously incorporate previous findings, and adaptively respond to changing ecological conditions.
The Sukari gold deposit (>15 Moz Au) in the Eastern Desert of Egypt is hosted by a deformed granitoid stock (Sukari tonalite-trondhjemite intrusion) and mainly occurs as a network of crosscutting sulfide-bearing quartz (± carbonate) veins and intensely sulfidized-silicified-sericitized wall rock. Emplacement of the Sukari intrusion into a tectonized Neoproterozoic accretionary complex was controlled by a system of NE- to NNE-trending oblique faults that are related to a deep-seated positive flower structure. A robust genetic model has been hampered by the poorly understood relationships between gold mineralization and host rocks. In this study, zircon U-Pb ages of three samples from the Sukari intrusion define a crystallization age of ~695 ± 2 Ma. In contrast, hydrothermal sericite from the ore zone yields an 40Ar/39Ar age of ~625 ± 3 Ma, which coincides with the onset of major sinistral transpression in the region.
Features including sigmoidal morphology of gold quartz veins and abundant subhorizontal tension gashes alongside widespread brecciation and recrystallization suggest that quartz veining occurred during renewed shortening and exhumation through the brittle-ductile transition. Petrographic and micro-X-ray fluorescence (µXRF) studies indicate that disseminated gold and sulfides, commonly associated with sericite and carbonate alteration, are mostly confined to stylolitic bands in the quartz veins. Oscillatory and sector zoning patterns, irregular As-rich bands, and truncations between early- and late-genetic pyrites reflect variations in temperature and mechanism of ore deposition, demonstrated by variable As/S and Co/Ni ratios in the different pyrite generations. Laser ablation-inductively coupled plasma-mass spectrometry analysis pinpoints the covariance of gold and arsenic contents in pyrite, but free milling gold inclusions in microfractures consistently have a mercury-bearing electrum composition, depicting different ore formation stages.
Ore fluids with δ34