Introduction: Terrestrial species in riverine ecosystems face unique constraints leading to diverging patterns of population structure, connectivity, and disease dynamics. Desert bighorn sheep (Ovis canadensis nelsoni) in Grand Canyon National Park, a large native population in the southwestern USA, offer a unique opportunity to evaluate population patterns and processes in a remote riverine system with ongoing anthropogenic impacts. We integrated non-invasive, invasive, and citizen-science methods to address questions on abundance, distribution, disease status, genetic structure, and habitat fragmentation.
Methods: We compiled bighorn sightings collected during river trips by park staff, commercial guides, and private citizens from 2000–2018 and captured bighorn in 2010–2016 to deploy GPS collars and test for disease. From 2011–2015, we non-invasively collected fecal samples and genotyped them at 9–16 microsatellite loci for individual identification and genetic structure. We used assignment tests to evaluate genetic structure and identify subpopulations, then estimated gene flow and recent migration to evaluate fragmentation. We used spatial capture-recapture to estimate annual population size, distribution, and trends after accounting for spatial variation in detection with a resource selection function model.
Results and discussion: From 2010–2018, 3,176 sightings of bighorn were reported, with sightings of 56–145 bighorn annually on formal surveys. From 2012–2016, bighorn exhibiting signs of respiratory disease were observed along the river throughout the park. Of 25 captured individuals, 56% were infected by Mycoplasma ovipneumoniae, a key respiratory pathogen, and 81% were recently exposed. Pellet sampling for population estimation from 2011–2015 yielded 1,250 genotypes and 453 individuals. We detected 6 genetic clusters that exhibited mild to moderate genetic structure (FST 0.022–0.126). The river, distance, and likely topography restricted recent gene flow, but we detected cross-river movements in one section via genetic recaptures, no subpopulation appeared completely isolated, and genetic diversity was among the highest reported. Recolonization of one large stretch of currently empty habitat appears limited by the constrained topology of this system. Annual population estimates ranged 536–552 (95% CrI range 451–647), lamb:ewe ratios varied, and no significant population decline was detected. We provide a multi-method sampling framework useful for sampling other wildlife in remote riverine systems.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fevo.2024.1377214","usgsCitation":"Epps, C.W., Holton, P.B., Monello, R.J., Crowhurst, R.S., Gaulke, S.M., Janousek, W.M., Creech, T.G., and Graves, T., 2024, Population and spatial dynamics of desert bighorn sheep in Grand Canyon during an outbreak of respiratory pneumonia: Frontiers in Ecology and Evolution, v. 12, 1377214, 22 p., https://doi.org/10.3389/fevo.2024.1377214.","productDescription":"1377214, 22 p.","ipdsId":"IP-137271","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":439348,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.3389/fevo.2024.1377214","text":"Publisher Index Page"},{"id":434937,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K89AA3","text":"USGS data release","linkHelpText":"Desert bighorn sheep (Ovis canadensis nelsoni) datasets from Grand Canyon National Park, 2010-2016"},{"id":430966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.5504498659519,\n 36.84244671894457\n ],\n [\n -114.04234802909026,\n 36.84244671894457\n ],\n [\n -114.04234802909026,\n 35.72909582502355\n ],\n [\n -111.5504498659519,\n 35.72909582502355\n ],\n [\n -111.5504498659519,\n 36.84244671894457\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Epps, Clinton W.","contributorId":198148,"corporation":false,"usgs":false,"family":"Epps","given":"Clinton","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":906239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holton, P. Brandon","contributorId":340119,"corporation":false,"usgs":false,"family":"Holton","given":"P.","email":"","middleInitial":"Brandon","affiliations":[],"preferred":false,"id":906240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monello, Ryan J.","contributorId":184143,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":906241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crowhurst, Rachel S.","contributorId":198153,"corporation":false,"usgs":false,"family":"Crowhurst","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":906242,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gaulke, Sarah Mccrimmon 0000-0002-2657-5844","orcid":"https://orcid.org/0000-0002-2657-5844","contributorId":225564,"corporation":false,"usgs":true,"family":"Gaulke","given":"Sarah","email":"","middleInitial":"Mccrimmon","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906243,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Janousek, William Michael 0000-0003-3978-1775","orcid":"https://orcid.org/0000-0003-3978-1775","contributorId":237980,"corporation":false,"usgs":true,"family":"Janousek","given":"William","email":"","middleInitial":"Michael","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906244,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Creech, Tyler G.","contributorId":198152,"corporation":false,"usgs":false,"family":"Creech","given":"Tyler","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":906245,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906246,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70255575,"text":"sir20245041 - 2024 - Representation of surface-water flows using Gradient-Related Discharge in an Everglades Network","interactions":[],"lastModifiedDate":"2026-02-03T19:22:10.1439","indexId":"sir20245041","displayToPublicDate":"2024-06-25T09:45:01","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5041","displayTitle":"Representation of Surface-Water Flows Using Gradient-Related Discharge in an Everglades Network","title":"Representation of surface-water flows using Gradient-Related Discharge in an Everglades Network","docAbstract":"The Everglades Depth Estimation Network interpolates water-level gage data to produce daily water-level elevations for the Everglades in south Florida. These elevations were used to estimate flow vectors (gradients and directions) and volumetric flow rates using the Gradient-Related Discharge in an Everglades Network (GARDEN) application developed by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers. Flow rates in both the east-west and north-south directions were computed on a 400-meter square grid using modified parameters in the Manning’s equation. The frictional resistance parameter in the Manning’s equation was calibrated to measured flow rates at coastal creeks fed by Everglades Depth Estimation Network boundary flows. Levees and other features that act as barriers to flow were defined as “no-flow” grid cells where vectors were set to zero.
The flow volume magnitudes were calibrated with 2020 daily values of coastal river flows, and verification was performed using 2021 data. Within a given day, the measured coastal river flows fluctuate more than the GARDEN boundary flows because of tidal and wind forcings. Because the GARDEN boundary flows were the upstream water source for the coastal rivers, calibration focused on matching average daily flow volumes rather than daily fluctuations. The Pearson’s correlation coefficient is 0.766 for the 2020 calibration period and 0.566 for the 2021 verification period.
Applying GARDEN to periods with hydraulic-control-structure releases allows the propagation of structure flows to be seen in the daily flow-vector maps along with the multiday response of flows farther downgradient. Flow vectors may be overestimated near control structures because of difficulties in resolving the water gradient downstream from the structure. Flow vectors farther from the structure are more accurate than those near the structure.
Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
We present a hydroclimate synthesis of the southern Great Basin over the last two glacial-interglacial cycles focused on paleolakes in Death Valley (core DV93-1), Searles Valley (core SLAPP-SRLS17), Owens Valley (core OL92), and the Devils Hole cave. There is close agreement between the occurrence of lakes in Death Valley and the height of the water table in the Devils Hole (50 km east of Death Valley) during the last 200 kyr. Death Valley and Devils Hole have adjacent, partly overlapping, drainage areas and most likely did over the last 200 kyr. When the water table in the Devils Hole was above the threshold level of ∼5 m higher than the modern, permanent lakes existed in Death Valley. At water table elevations less than 5 m above the modern, ephemeral lakes, saline pans, and mudflats occurred in Death Valley. The close temporal agreement between inferred paleoenvironments from the sediments in the Death Valley core and the paleowater table elevation in Devils Hole suggests a common forcing and provides insight into climate variability in the southwestern United States over the last 200 kyr. Owens Valley and Searles Valley, which derived inflow waters from the Sierra Nevada via the Owens River, contain paleohydrologic records which match those from Death Valley and the Devils Hole in terms of timing and direction of water availability over the last 200 kyr, indicating a similar paleohydrologic history for the entire southern Great Basin region. Near the end of Marine Oxygen Isotope Stage 6 (MIS 6), 140 ka - 130 ka, Lake Manly in Death Valley became shallow and hypersaline, and ultimately dried up at 127.1 ka ±4.3 ka. The transition from glacial to interglacial vegetation, which involved the loss of Juniperus pollen and an increase in Quercus (oak) pollen, occurred in Death Valley core DV93-1 at 131.3 ka ±4.0 ka. Following the glacial to interglacial pollen shift, a large alkaline lake formed in Death Valley. Similar conditions (freshwater, high productivity, and a mixed, deeply oxygenated water column indicated by biomarkers) existed in Searles Lake between 135.3 +2.7/-2.9 ka and 130.1+2.7/-2.6 ka, also following the juniper-oak pollen transition. Sr isotopes in calcite and sulfate minerals (gypsum, glauberite, thenardite), and the rare occurrence of the sodium carbonate mineral northupite with a low 87Sr/86Sr ratio in core DV93-1, together with organic geochemical proxies from Searles core SLAPP-SRLS17, all suggest that at this time, late MIS 6 Lake Manly in Death Valley received alkaline water via spillover from Searles Valley into Death Valley through Panamint Valley. The hydrologic connection between Searles Valley, Panamint Valley, and Death Valley at Termination II (130 ka) is documented here for this system of pluvial lakes for the first time. The Devils Hole water table decreased to +6.5 m at 140.8 ka ±3.2 ka, rose briefly to +8 m at 137.6 ka ±0.5 ka, and then dropped 8 m by 120.36 ka ±0.45 ka, when it reached an elevation similar to the modern. The pluvial lakes in Death Valley and Searles Valley may have coincided with the rise of the Devils Hole water table at ∼137.6 ka ±0.5 ka years ago, although the age models for core DV93-1 and core SLAPP-SLRS17 during the end of MIS 6 carry large uncertainties.
Nutrient concentrations in many estuaries have increased over the past century due to increases in wastewater discharge and increased agricultural intensity, contributing to multiple environmental problems. Numerous biogeochemical and physical processes in estuaries influence nutrient concentrations during transport, resulting in complex spatial and temporal variability and challenges identifying predominant processes and their rates. Mechanistic models which require these rates to quantify biogeochemical processes become complex and difficult to calibrate as the number of processes and parameters grows, owing to the high dimensionality of the parameter space and the computational cost of simultaneously modeling the transport and transformations of constituents. We developed a modeling approach that decouples transport from transformations, enabling fast, data-driven exploration of the parameter space. The approach extracted information including water age, cumulative exposure to specific habitats, and mean water depth exposure from a hydrodynamic model. Using this information, a biogeochemical model was implemented to predict ammonium and nitrate concentrations in a Lagrangian frame. The model performed each simulation in milliseconds on a laptop computer, allowing the fitting of rate parameters for key transformations by optimization. The optimization used fixed station nitrate observations and the model was then validated against high-resolution mapping observations of ammonium and nitrate. The results suggest that the observed spatial and temporal variation can be largely represented with five transformation processes and their associated rates. Dissolved inorganic nitrogen (DIN) losses occurred only in shallow vegetated areas in the model, highlighting that biogeochemical processes in these areas should be included in DIN models.
The vertical accuracy of elevation data in coastal environments is critical because small variations in elevation can affect an area’s exposure to waves, tides, and storm-related flooding. Elevation data contractors typically quantify the vertical accuracy of lidar-derived digital elevation models (DEMs) on a per-project basis to gauge whether the datasets meet quality and accuracy standards. Here, we collated over 5200 contractor elevation checkpoints along the Atlantic and Gulf of Mexico coasts of the United States that were collected for project-level analyses produced for assessing DEMs acquired for the U.S. Geological Survey’s Three-Dimensional Elevation Program. We used land cover data to quantify non-vegetated vertical accuracy and vegetated vertical accuracy statistics (overall and by point spacing bins) and assessed elevation error by land cover class. We found the non-vegetated vertical accuracy had an overall root mean square error of 6.9 cm and vegetated areas had a 95th percentile vertical error of 22.3 cm. Point spacing was generally positively correlated to elevation accuracy, but sample size limited the ability to interpret results from accuracy by land cover, particularly in wetlands. Based on the specific questions a researcher may be asking, use of literature or fieldwork could assist with enhancing error statistics in underrepresented classes.
Spatial machine learning models can be developed from observations with substantial unexplainable variability, sometimes called ‘noise’. Traditional point-scale metrics (e.g., R2) alone can be misleading when evaluating these models. We present a multi-scale performance evaluation (MPE) using two additional scales (distributional and geostatistical). We apply the MPE framework to predictions of depth to bedrock (DTB) in the Delaware River Basin. Geostatistical analysis shows that approximately one third of the DTB variance is at spatial scale smaller than 2 km. Hence, we interpret our point-scale R2 of 0.3 (testing data) to be sufficient for regional-scale modelling. Bias-correction methods improve performance at two of the three MPE scales: point-scale change is negligible, while distributional and geostatistical performance improves. In contrast, bias correction applied to a global DTB model does not improve MPE performance. This work encourages scale-appropriate performance evaluations to enable effective model intercomparison.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2024.106124","usgsCitation":"Goodling, P.J., Belitz, K., Stackelberg, P.E., and Fleming, B.J., 2024, A spatial machine learning model developed from noisy data requires multiscale performance evaluation: Predicting depth to bedrock in the Delaware River Basin, USA: Environmental Modelling & Software, v. 179, 106124, 12 p., https://doi.org/10.1016/j.envsoft.2024.106124.","productDescription":"106124, 12 p.","ipdsId":"IP-160581","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":439361,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2024.106124","text":"Publisher Index Page"},{"id":430446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.88099946089724,\n 38.58741180591247\n ],\n [\n -74.71321333503417,\n 39.379784628066616\n ],\n [\n -74.91854009408658,\n 39.623906471535875\n ],\n [\n -74.56682974019151,\n 39.83490997578861\n ],\n [\n -74.83087158557463,\n 40.43445755432647\n ],\n [\n -74.69462804413362,\n 42.31099383658801\n ],\n [\n -75.89851464683143,\n 42.243461978517985\n ],\n [\n -76.67474108243883,\n 40.45538711590305\n ],\n [\n -76.4341425039691,\n 39.732367924983954\n ],\n [\n -75.81256791410406,\n 39.70992285882126\n ],\n [\n -75.68892404289328,\n 38.72600697054469\n ],\n [\n -74.88099946089724,\n 38.58741180591247\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"179","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goodling, Phillip J. 0000-0001-5715-8579","orcid":"https://orcid.org/0000-0001-5715-8579","contributorId":239738,"corporation":false,"usgs":true,"family":"Goodling","given":"Phillip","email":"","middleInitial":"J.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":904792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":904793,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stackelberg, Paul E. 0000-0002-1818-355X","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":204864,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","middleInitial":"E.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":904794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":904795,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255961,"text":"70255961 - 2024 - Back from the brink: Estimating daily and annual abundance of natural-origin salmon smolts from 30-years of mixed-origin capture-recapture data","interactions":[],"lastModifiedDate":"2024-07-11T14:25:45.706092","indexId":"70255961","displayToPublicDate":"2024-06-22T09:17:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Back from the brink: Estimating daily and annual abundance of natural-origin salmon smolts from 30-years of mixed-origin capture-recapture data","docAbstract":"Evaluating the status and trends of natural-origin anadromous fish populations over time requires robust estimates of out-migrating juvenile abundance. Information on abundance is typically acquired by capturing actively migrating fish as they pass stationary monitoring platforms. Challenges to estimation include protracted migration timing, temporally varying capture probabilities and the contemporaneous presence of unmarked hatchery-origin fish. The confounding effects of unmarked hatchery fish are especially pernicious in systems hosting multiple hatchery programs with variable mark-rates among releases. Here, we address this problem for a regionally and culturally important population of Chinook salmon (Oncorhynchus tshawytscha) supported by a hatchery-supplementation program implemented in response to the listing of this population under the U.S. Endangered Species Act. We developed a model to estimate daily and annual abundance of naturally produced age-0 fall Chinook salmon passing Lower Granite Dam (Snake River, USA) for each of the last 30 years. We accounted for variable hatchery marking rates by integrating two related data sources: 1) release-recapture data of fish with individually identifiable tags and 2) counts of marked and unmarked sample of fish captured each day. We fit joint parameters for daily fish arrival and capture probabilities to these data to estimate the daily abundance of hatchery- and natural-origin fish. Our results show that from 1992 to 2021, the annual abundance of juvenile natural-origin Snake River fall Chinook salmon increased by two orders of magnitude. These results are the first comprehensive evaluation of multi-decadal trends in abundance and run-timing for this population. Our approach can be adapted to other runs and locations within the Columbia River basin or similar systems where out-migrating fish are monitored at fixed locations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107098","usgsCitation":"Hance, D., Plumb, J., Perry, R., and Tiffan, K., 2024, Back from the brink: Estimating daily and annual abundance of natural-origin salmon smolts from 30-years of mixed-origin capture-recapture data: Fisheries Research, v. 278, 107098, 18 p., https://doi.org/10.1016/j.fishres.2024.107098.","productDescription":"107098, 18 p.","ipdsId":"IP-160680","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":434942,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1EKDXW3","text":"USGS data release","linkHelpText":"Daily and annual abundances of natural- and hatchery-origin age-0 fall Chinook salmon (Oncorhynchus tshawytscha) passing Lower Granite Dam, Washington 1992 - 2021"},{"id":430961,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.97264940326166,\n 47.24310996536303\n ],\n [\n -118.075231715107,\n 47.27051186495126\n ],\n [\n -118.03216123599826,\n 44.88742975557119\n ],\n [\n -115.98127625140233,\n 44.90409917890665\n ],\n [\n -115.97264940326166,\n 47.24310996536303\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"278","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hance, Dalton 0000-0002-4475-706X","orcid":"https://orcid.org/0000-0002-4475-706X","contributorId":220179,"corporation":false,"usgs":true,"family":"Hance","given":"Dalton","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906151,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":220178,"corporation":false,"usgs":true,"family":"Plumb","given":"John","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906152,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906153,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tiffan, Kenneth 0000-0002-5831-2846","orcid":"https://orcid.org/0000-0002-5831-2846","contributorId":217812,"corporation":false,"usgs":true,"family":"Tiffan","given":"Kenneth","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":906154,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70256164,"text":"70256164 - 2024 - Modeling the mid-Piacenzian warm climate using the water isotope-enabled Community Earth System Model (iCESM1.2-ITPCAS)","interactions":[],"lastModifiedDate":"2025-01-17T15:55:36.342599","indexId":"70256164","displayToPublicDate":"2024-06-22T06:52:03","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1248,"text":"Climate Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the mid-Piacenzian warm climate using the water isotope-enabled Community Earth System Model (iCESM1.2-ITPCAS)","docAbstract":"The mid-Piacenzian Warm Period (MPWP, ~ 3.264–3.025 Ma) is the most recent example of a persistently warmer climate in equilibrium with atmospheric CO2 concentrations similar to today. Towards studying patterns and dynamics of a warming climate the MPWP is often compared to today. Following the Pliocene Model Intercomparison Project, Phase 2 (PlioMIP2) protocol we prepare a water isotope-enabled Community Earth System Model (iCESM1.2) simulation that is warmer and wetter than the PlioMIP2 multi-model ensemble (MME). While our simulation resembles PlioMIP2 MME in many aspects we find added insights. (1) Considerable warmth at high latitudes exceeds previous simulations. Polar amplification (PA) is comparable to proxies, enabled by iCESM1.2’s high climate sensitivity and a distinct method of ocean initialization. (2) Major driver of warmth is the downward component of clear-sky surface long-wave radiation (ΔTrlds_clearsky). (3) In iCESM1.2 modulated dominance of dynamic (δDY) processes causes different low-latitude (~ 30 S°–10°N) precipitation response than the PlioMIP2 MME, where thermodynamic processes (δTH) dominate. (4) Modulated local condensation leads to lower δ18Op across tropical Indian Ocean and surrounding Asian-African-Australian monsoon regions. (5) We find contrasting changes in tropical atmospheric circulations (Hadley and Walker cells). Anomalous regional meridional (zonal) circulation, forced by changes in tropical-subtropical (tropical) diabatic processes, presents a more comprehensive perspective than explaining weakened and expanded Hadley circulation (strengthened and westward-shifted Walker circulation) via static stability. (6) Enhanced Atlantic meridional overturning circulation owes to a closed Bering Strait.
","language":"English","publisher":"Springer","doi":"10.1007/s00382-024-07304-0","usgsCitation":"Sun, Y., Su, B., Dowsett, H.J., Wu, H., Hu, J., Stepanek, C., Xiong, Z., Yuan, X., and Ramstein, G., 2024, Modeling the mid-Piacenzian warm climate using the water isotope-enabled Community Earth System Model (iCESM1.2-ITPCAS): Climate Dynamics, v. 62, p. 7741-7761, https://doi.org/10.1007/s00382-024-07304-0.","productDescription":"21 p.","startPage":"7741","endPage":"7761","ipdsId":"IP-145565","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":439362,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00382-024-07304-0","text":"Publisher Index Page"},{"id":431436,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","noUsgsAuthors":false,"publicationDate":"2024-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Sun, Yong","contributorId":336900,"corporation":false,"usgs":false,"family":"Sun","given":"Yong","email":"","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":906957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Su, Baohuang","contributorId":338746,"corporation":false,"usgs":false,"family":"Su","given":"Baohuang","email":"","affiliations":[],"preferred":false,"id":907051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":907052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Haibin","contributorId":338744,"corporation":false,"usgs":false,"family":"Wu","given":"Haibin","email":"","affiliations":[],"preferred":false,"id":907053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hu, Jun","contributorId":340390,"corporation":false,"usgs":false,"family":"Hu","given":"Jun","email":"","affiliations":[],"preferred":false,"id":907054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stepanek, Christian","contributorId":220691,"corporation":false,"usgs":false,"family":"Stepanek","given":"Christian","email":"","affiliations":[{"id":40240,"text":"Alfred Wegener Institute-Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany","active":true,"usgs":false}],"preferred":false,"id":907055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xiong, Zhongyu","contributorId":340391,"corporation":false,"usgs":false,"family":"Xiong","given":"Zhongyu","email":"","affiliations":[],"preferred":false,"id":907056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yuan, Xiayu","contributorId":338747,"corporation":false,"usgs":false,"family":"Yuan","given":"Xiayu","email":"","affiliations":[],"preferred":false,"id":907057,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ramstein, Gilles","contributorId":269585,"corporation":false,"usgs":false,"family":"Ramstein","given":"Gilles","email":"","affiliations":[{"id":55994,"text":"Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France","active":true,"usgs":false}],"preferred":false,"id":907058,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70256471,"text":"70256471 - 2024 - Viability modeling for decision support with limited data: A lizard case study","interactions":[],"lastModifiedDate":"2024-12-10T15:01:27.166066","indexId":"70256471","displayToPublicDate":"2024-06-21T15:27:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17797,"text":"Journal of Fish and Wildlife Managment","active":true,"publicationSubtype":{"id":10}},"title":"Viability modeling for decision support with limited data: A lizard case study","docAbstract":"Plateau spot-tailed earless lizards, Holbrookia lacerata, are a species of ground lizard in central Texas that are under review for listing as endangered under the US Endangered Species Act, but heretofore no predictive models of population dynamics or viability have been developed. We used limited available data and published demographic rates in a PVA model to predict future status of these lizards under parametric and ecological uncertainty and temporal variability. Even in cases where data are sparse and life history information are limited, viability models can help clarify the consequences of management choices given the uncertainty. Our model predicted that on average populations will decline in in the future. Quasi-extinction probability was low 20 years into the future but up to 0.60. Extinction risk was highly dependent on the road mortality effect and the proportion of the population exposed to roadways, both of which are currently uncertain quantities. Despite these unknowns, our model enables managers to consider the future abundance and extinction risk for the species and make decisions about management to project the populations and also identifies key uncertainties for future research and monitoring.
","language":"English","publisher":"US Fish and Wildlife Service","doi":"10.3996/JFWM-23-024","usgsCitation":"Goode, A.B., Allan, N., and McGowan, C., 2024, Viability modeling for decision support with limited data: A lizard case study: Journal of Fish and Wildlife Managment, v. 15, no. 1, p. 70-86, https://doi.org/10.3996/JFWM-23-024.","productDescription":"17 p.","startPage":"70","endPage":"86","ipdsId":"IP-152348","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":487513,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-23-024","text":"Publisher Index Page"},{"id":432057,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Goode, Ashley B.C.","contributorId":340756,"corporation":false,"usgs":false,"family":"Goode","given":"Ashley","email":"","middleInitial":"B.C.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":907519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allan, Nathan","contributorId":340757,"corporation":false,"usgs":false,"family":"Allan","given":"Nathan","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":907520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":3381,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor P.","email":"cmcgowan@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":907521,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273359,"text":"70273359 - 2024 - Alaskan glacial dust is an important iron source to surface waters of the Gulf of Alaska","interactions":[],"lastModifiedDate":"2026-01-09T17:22:33.919542","indexId":"70273359","displayToPublicDate":"2024-06-21T11:17:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Alaskan glacial dust is an important iron source to surface waters of the Gulf of Alaska","docAbstract":"This work evaluates glacial dust as a source of sediment, and associated iron (Fe), to the Fe-limited Gulf of Alaska (GoA). A reanalysis of GoA sediment data, using rare earth elements and thorium as provenance tracers, suggests a flux to the ocean surface of Copper River (AK) glacial dust, and associated Fe, that is comparable to the flux of dust from Asia, at least 1,000 km from the narrow mountain valley glacial dust source area. This work suggests dust from Asia may not be the largest source of Fe to the GoA. Dust models fail to accurately simulate this glacial dust transport because their coarse resolution underestimates wind speeds, and the dust flux. This work suggests that glacial dust fluxes may have been important in the geologic past (e.g., the last glacial maximum) from locations where there was more extensive coverage by glaciers than at present.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GL106778","usgsCitation":"Crusius, J., Lao, C., Holmes, T.M., and Murray, J.W., 2024, Alaskan glacial dust is an important iron source to surface waters of the Gulf of Alaska: Geophysical Research Letters, v. 51, no. 12, e2023GL106778, 10 p., https://doi.org/10.1029/2023GL106778.","productDescription":"e2023GL106778, 10 p.","ipdsId":"IP-144402","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":498678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gl106778","text":"Publisher Index Page"},{"id":498516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -166,\n 61\n ],\n [\n -166,\n 48\n ],\n [\n -136,\n 48\n ],\n [\n -136,\n 61\n ],\n [\n -166,\n 61\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"51","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":953433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lao, Carsten","contributorId":364912,"corporation":false,"usgs":false,"family":"Lao","given":"Carsten","affiliations":[{"id":87012,"text":"UW Dept of Chemistry","active":true,"usgs":false}],"preferred":false,"id":953434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holmes, Thomas M. 0000-0001-8061-4325","orcid":"https://orcid.org/0000-0001-8061-4325","contributorId":364913,"corporation":false,"usgs":false,"family":"Holmes","given":"Thomas","middleInitial":"M.","affiliations":[{"id":87014,"text":"U. Tasmania","active":true,"usgs":false}],"preferred":false,"id":953435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murray, J. W. 0000-0002-8577-7964","orcid":"https://orcid.org/0000-0002-8577-7964","contributorId":364914,"corporation":false,"usgs":false,"family":"Murray","given":"J.","middleInitial":"W.","affiliations":[{"id":87015,"text":"UW School of Oceanography","active":true,"usgs":false}],"preferred":false,"id":953436,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255896,"text":"70255896 - 2024 - Thermo-hydrologic processes governing supra-permafrost talik dynamics in discontinuous permafrost near Umiujaq (Québec, Canada)","interactions":[],"lastModifiedDate":"2024-07-10T15:28:12.262442","indexId":"70255896","displayToPublicDate":"2024-06-21T10:23:23","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Thermo-hydrologic processes governing supra-permafrost talik dynamics in discontinuous permafrost near Umiujaq (Québec, Canada)","docAbstract":"Widespread supra-permafrost talik formation is\ncurrently recognized as a critical mechanism that\ncould accelerate permafrost thaw in the Arctic\n(e.g., Connon et al. 2018; Farquharson et al. 2022).\nHowever, the trajectory of permafrost dynamics\nfollowing talik formation may prove difficult to predict.\nPhysically-based cryohydrogeologic models provide\na powerful tool for understanding processes and\nfactors controlling talik dynamics and, ultimately, how\npermafrost will respond to climate change. Such\nmodels are typically used to represent multiple\nnon-linear processes relevant for groundwater\nsystems in cold regions, such as coupled heat and\ngroundwater movement, including freeze-thaw\ndynamics and the effects on the surface energy\nbalance and the subsurface thermal and hydraulic\nproperties (Lamontagne-Hallé et al. 2020). Though\ncryohydrogeologic modeling advances have been\nmade in simulating talik dynamics, few applications\nhave been tested against robust long-term\nhydrometeorological and subsurface observations.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Permafrost","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Permafrost (ICOP 2024)","conferenceDate":"June 16-20, 2024","conferenceLocation":"Whitehorse, Canada","language":"English","usgsCitation":"Fortier, P., Young, N., Walvoord, M.A., Lemieux, J., and Mohammed, A., 2024, Thermo-hydrologic processes governing supra-permafrost talik dynamics in discontinuous permafrost near Umiujaq (Québec, Canada), in Proceedings of the 12th International Conference on Permafrost, v. 2, Whitehorse, Canada, June 16-20, 2024, p. 374-375.","productDescription":"2 p.","startPage":"374","endPage":"375","ipdsId":"IP-160074","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":430899,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430859,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.uspermafrost.org/conference-proceedings"}],"country":"Canada","state":"Quebec","otherGeospatial":"Umiujaq","volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fortier, Philippe","contributorId":300757,"corporation":false,"usgs":false,"family":"Fortier","given":"Philippe","email":"","affiliations":[{"id":39893,"text":"Laval University","active":true,"usgs":false}],"preferred":false,"id":905929,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Nathan","contributorId":215062,"corporation":false,"usgs":false,"family":"Young","given":"Nathan","affiliations":[{"id":39169,"text":"University of Ottawa","active":true,"usgs":false}],"preferred":false,"id":905930,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":905931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lemieux, Jean-Michel","contributorId":300758,"corporation":false,"usgs":false,"family":"Lemieux","given":"Jean-Michel","email":"","affiliations":[{"id":65253,"text":"University Laval","active":true,"usgs":false}],"preferred":false,"id":905932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Aaron","contributorId":340028,"corporation":false,"usgs":false,"family":"Mohammed","given":"Aaron","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":905933,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70255897,"text":"70255897 - 2024 - A history of cryohydrogeology modeling and recent advancements through the integration of solute transport","interactions":[],"lastModifiedDate":"2024-07-10T15:22:41.762515","indexId":"70255897","displayToPublicDate":"2024-06-21T10:22:08","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A history of cryohydrogeology modeling and recent advancements through the integration of solute transport","docAbstract":"Groundwater flow systems and permafrost are interrelated because permafrost thaw enhances permeability, while groundwater flow can advect heat and accelerate permafrost thaw (McKenzie et al. 2021). Given amplified climate change in cold regions, there is renewed interest in ‘cryohydrogeology’, the study of groundwater in cold regions. Many data-driven studies have shown that permafrost thaw is leading to activated aquifers and increased baseflow across the pan-Arctic region (e.g. Walvoord and Striegl 2007, Evans et al. 2020). Empirical evidence of a subsurface ‘replumbing’ (Walvoord and Kurylyk 2016) in permafrost regions raises questions about the fate of sequestered contaminants in the North (Langer et al. 2023). We will discuss the history of and emerging opportunities in cryohydrogeological modeling, with a focus on recent contaminant transport modeling.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Permafrost","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Permafrost (ICOP 2024)","conferenceDate":"June 16-20, 2024","conferenceLocation":"Whitehorse, Canada","language":"English","publisher":"International Permafrost Association","usgsCitation":"Kurylyk, B.L., Guimond, J., Mohammed, A., Bense, V.F., McKenzie, J.M., Walvoord, M.A., Jamieson, R., and Strong, R.B., 2024, A history of cryohydrogeology modeling and recent advancements through the integration of solute transport, in Proceedings of the 12th International Conference on Permafrost, v. 2, Whitehorse, Canada, June 16-20, 2024, p. 568-569.","productDescription":"2 p.","startPage":"568","endPage":"569","ipdsId":"IP-159997","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":430898,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430860,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.uspermafrost.org/conference-proceedings"}],"volume":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kurylyk, Barret L.","contributorId":176296,"corporation":false,"usgs":false,"family":"Kurylyk","given":"Barret","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":905934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guimond, Julia","contributorId":266043,"corporation":false,"usgs":false,"family":"Guimond","given":"Julia","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":905935,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mohammed, Aaron","contributorId":340028,"corporation":false,"usgs":false,"family":"Mohammed","given":"Aaron","email":"","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":905936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bense, Victor F.","contributorId":248636,"corporation":false,"usgs":false,"family":"Bense","given":"Victor","email":"","middleInitial":"F.","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":905937,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenzie, Jeffrey M.","contributorId":176299,"corporation":false,"usgs":false,"family":"McKenzie","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":905938,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":905939,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jamieson, Rob","contributorId":340029,"corporation":false,"usgs":false,"family":"Jamieson","given":"Rob","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":905940,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Strong, R. Bailey","contributorId":340030,"corporation":false,"usgs":false,"family":"Strong","given":"R.","email":"","middleInitial":"Bailey","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":905941,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70255720,"text":"70255720 - 2024 - Thermal and hydrological limitations on modeling carbon dynamics at wetland sites of discontinuous and continuous permafrost extent","interactions":[],"lastModifiedDate":"2024-07-02T14:31:18.244161","indexId":"70255720","displayToPublicDate":"2024-06-21T09:30:39","publicationYear":"2024","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Thermal and hydrological limitations on modeling carbon dynamics at wetland sites of discontinuous and continuous permafrost extent","docAbstract":"Accurate representation of cryohydrological processes is fundamental for biosphere models, particularly at high-latitudes, given their influence on carbon and permafrost dynamics in carbon-rich peatlands and wetlands. This study analyzes site-level simulations in moist and wet drainage conditions in continuous or discontinuous permafrost regions, using a terrestrial ecosystem model DVM-DOS-TEM. Functional benchmarking was conducted against eddy covariance flux alongside soil temperature, moisture, and thaw depth observations. Thermal and hydrological analysis reveals parameter sensitivity and uncertainty concerning carbon cycling and permafrost dynamics. Flux representation is markedly consistent at sites characterized by continuous permafrost with less seasonal variation, owing to longer soil freezing duration. Sites in discontinuous permafrost, exhibiting active permafrost degradation and talik formation, pose considerable challenges in accurately depicting thaw depth. Underprediction of soil moisture across all sites has more pronounced effects on boreal wetlands characterized by thick organic layers up to 1 m. These results illustrate the limitations of terrestrial ecosystem models to represent environmental and ecological dynamics in wetlands. Attempts to adjust model hydrology have yielded marginal improvements in thaw depth prediction, but revealed large effects of abrupt phase changes for poorly drained sites on discontinuous permafrost. Our analysis suggests the importance of gradual phase change representation, particularly in ice-rich wetlands with thick organic layers, which will be crucial when evaluating the permafrost carbon-climate feedback in model projections.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Permafrost","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Permafrost","conferenceDate":"June 16-20, 2024.","conferenceLocation":"Whitehorse, Yukon, Canada","language":"English","publisher":"International Permafrost Association","usgsCitation":"Maglio, B.C., Rutter, R., Carman, T., Edgar, C.W., Euskirchen, E., Genet, H., Mullen, A., Briones, V., Jafarov, E., and Manies, K.L., 2024, Thermal and hydrological limitations on modeling carbon dynamics at wetland sites of discontinuous and continuous permafrost extent, in Proceedings of the 12th International Conference on Permafrost, Whitehorse, Yukon, Canada, June 16-20, 2024., p. 248-256.","productDescription":"9 p.","startPage":"248","endPage":"256","ipdsId":"IP-162209","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":430724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":430702,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.permafrost.org/proceedings-of-the-12th-international-conference-on-permafrost-icop/"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -142.6808844305595,\n 69.84467566186115\n ],\n [\n -151.89695276969454,\n 69.84467566186115\n ],\n [\n -151.89695276969454,\n 63.137459294385934\n ],\n [\n -142.6808844305595,\n 63.137459294385934\n ],\n [\n -142.6808844305595,\n 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Hélène","contributorId":195179,"corporation":false,"usgs":false,"family":"Genet","given":"Hélène","affiliations":[],"preferred":false,"id":905425,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mullen, Andrew","contributorId":339864,"corporation":false,"usgs":false,"family":"Mullen","given":"Andrew","email":"","affiliations":[{"id":56085,"text":"Woodwell Climate Research Center","active":true,"usgs":false}],"preferred":false,"id":905426,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Briones, Valeria","contributorId":339865,"corporation":false,"usgs":false,"family":"Briones","given":"Valeria","email":"","affiliations":[{"id":56085,"text":"Woodwell Climate Research Center","active":true,"usgs":false}],"preferred":false,"id":905427,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jafarov, Elchin","contributorId":195182,"corporation":false,"usgs":false,"family":"Jafarov","given":"Elchin","affiliations":[],"preferred":false,"id":905428,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":905429,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70255562,"text":"70255562 - 2024 - Iron oxyhydroxide-rich hydrothermal deposits at the high-temperature Fåvne vent field, Mohns Ridge","interactions":[],"lastModifiedDate":"2024-06-24T14:00:38.413451","indexId":"70255562","displayToPublicDate":"2024-06-21T08:43:28","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Iron oxyhydroxide-rich hydrothermal deposits at the high-temperature Fåvne vent field, Mohns Ridge","docAbstract":"The recently discovered Fåvne vent field, located at 3,040 m depth on the slow-spreading Mohns mid-ocean ridge between Greenland and Norway, is a high-temperature (≥250°C) vent field that is characterized by Fe oxyhydroxide-rich and S-poor chimneys and mounds. The vent field is located on both the hanging wall and footwall of a normal fault with a ∼1.5 km throw that forms the western edge of the ∼20 km wide ridge axial valley. Data collected during exploration of the site using a remotely operated vehicle as well as mineralogical and geochemical analyses of rock samples and sediments are used to characterize the geological setting of the vent field and composition of the hydrothermal deposits. The chimney walls are highly porous and lack defined chalcopyrite lined conduits, typical of high-temperature chimneys. Overall, abundant Fe oxyhydroxide precipitation at high-temperature vents at Fåvne reflects an excess of Fe over reduced S in the fluid, leading to precipitation of Fe oxide and oxyhydroxide minerals at high to moderate temperature vents (>100°C), and as microbially mediated and abiotic precipitation of Fe oxyhydroxide minerals at low-temperature diffuse vents (<100°C). The mounds and chimneys exhibit low base metal and reduced S concentrations relative to globally averaged seafloor deposits and suggest subseafloor mixing of hydrothermal fluid with seawater, causing metal sulfide precipitation. Cobalt enrichment at Fåvne may reflect a subsurface influence of an ultramafic substrate on circulating fluids, although ultramafic rocks are absent on the seafloor and no other elements typical of ultramafic deposits are present.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GC011481","usgsCitation":"Gini, C., Jamieson, J., Reeves, E., Gartman, A., Barreyre, T., Babechuk, M.G., Jorgensen, S.L., and Robert, K., 2024, Iron oxyhydroxide-rich hydrothermal deposits at the high-temperature Fåvne vent field, Mohns Ridge: Geochemistry, Geophysics, Geosystems, v. 25, no. 6, e2024GC011481, 29 p., https://doi.org/10.1029/2024GC011481.","productDescription":"e2024GC011481, 29 p.","ipdsId":"IP-162095","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439365,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gc011481","text":"Publisher Index Page"},{"id":430445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Fåvne Vent Field, Mohns Ridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -14.945593530960565,\n 74.30569199847616\n ],\n [\n -14.945593530960565,\n 66.9804124151006\n ],\n [\n 3.9250034267149374,\n 66.9804124151006\n ],\n [\n 3.9250034267149374,\n 74.30569199847616\n ],\n [\n -14.945593530960565,\n 74.30569199847616\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Gini, Caroline","contributorId":334026,"corporation":false,"usgs":false,"family":"Gini","given":"Caroline","email":"","affiliations":[{"id":40744,"text":"Memorial University","active":true,"usgs":false}],"preferred":false,"id":904676,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jamieson, John","contributorId":339557,"corporation":false,"usgs":false,"family":"Jamieson","given":"John","affiliations":[{"id":40744,"text":"Memorial University","active":true,"usgs":false}],"preferred":false,"id":904677,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Eoghan P.","contributorId":339559,"corporation":false,"usgs":false,"family":"Reeves","given":"Eoghan P.","affiliations":[{"id":28158,"text":"University of Bergen","active":true,"usgs":false}],"preferred":false,"id":904678,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":904679,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barreyre, Thibaut","contributorId":339562,"corporation":false,"usgs":false,"family":"Barreyre","given":"Thibaut","email":"","affiliations":[{"id":28158,"text":"University of Bergen","active":true,"usgs":false}],"preferred":false,"id":904680,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Babechuk, Michael G.","contributorId":339563,"corporation":false,"usgs":false,"family":"Babechuk","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":40744,"text":"Memorial University","active":true,"usgs":false}],"preferred":false,"id":904681,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jorgensen, Steffen L.","contributorId":339565,"corporation":false,"usgs":false,"family":"Jorgensen","given":"Steffen","email":"","middleInitial":"L.","affiliations":[{"id":28158,"text":"University of Bergen","active":true,"usgs":false}],"preferred":false,"id":904682,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Robert, Katleen","contributorId":339567,"corporation":false,"usgs":false,"family":"Robert","given":"Katleen","email":"","affiliations":[{"id":40744,"text":"Memorial University","active":true,"usgs":false}],"preferred":false,"id":904683,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70258117,"text":"70258117 - 2024 - Prediction of regional broadband strong ground motions using a teleseismic source model of the 18 April 2014 Mw 7.3 Papanoa, Mexico, earthquake","interactions":[],"lastModifiedDate":"2024-10-07T16:18:18.502647","indexId":"70258117","displayToPublicDate":"2024-06-21T08:34:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Prediction of regional broadband strong ground motions using a teleseismic source model of the 18 April 2014 MW 7.3 Papanoa, Mexico, earthquake","title":"Prediction of regional broadband strong ground motions using a teleseismic source model of the 18 April 2014 Mw 7.3 Papanoa, Mexico, earthquake","docAbstract":"To estimate predicted ground motion from a teleseismic slip model, we use a low‐ and high‐frequency hybrid method to simulate the regional, strong ground motions observed following the 18 April 2014 moment magnitude (Mw) 7.3 Papanoa, Mexico, earthquake. To generate the regional ground motion at low frequencies (<1 Hz), a teleseismically derived, finite‐fault, kinematic model is used to define the earthquake source, taking into account slip‐model variations identified with a parameter sampling approach that considers possible errors in the fault geometry, the hypocenter depth, and the rupture velocity. A 3D crustal model is used to calculate the low‐frequency ground motions using a finite‐element calculation that includes topography and considers variations in the source model to estimate the uncertainty in the calculations. High frequencies (>1 Hz) are added using a 1D full‐wave propagation code that estimates uncertainties by considering multiple random distributions of slip with different spatial correlation lengths. The synthetic, broadband (0.05–10.0 Hz) ground motions are obtained by combining the low‐ and high‐frequency portions match filtered at 1 Hz. These synthetic ground motions are compared with the regional observations using velocity records, peak ground acceleration, and medians of the orientation‐independent response spectra of the horizontal components (RotD50) calculated at periods of 0.2, 0.3, 0.5, 1.0, 2.0, 3.0, 5.0, 7.5, and 10.0 s. The results indicate that ground motions estimated at these periods using our hybrid approach based primarily on a teleseismically derived source model are comparable to the values observed for the 2014 Papanoa earthquake at regional distances. The approach could be used to estimate strong‐motion spectral levels expected for regions with limited local and regional recordings and could also fill in magnitude or distance gaps in ground‐motion prediction relations utilized in the assessment of seismic hazard.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230311","usgsCitation":"Mendoza, C., Hartzell, S.H., Ramirez-Guzman, L., and Martinez-Lopez, R., 2024, Prediction of regional broadband strong ground motions using a teleseismic source model of the 18 April 2014 Mw 7.3 Papanoa, Mexico, earthquake: Bulletin of the Seismological Society of America, v. 14, no. 5, p. 2524-2545, https://doi.org/10.1785/0120230311.","productDescription":"22 p.","startPage":"2524","endPage":"2545","ipdsId":"IP-156741","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":433492,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","city":"Papanoa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102,\n 18.5\n ],\n [\n -102,\n 16.833\n ],\n [\n -99,\n 16.833\n ],\n [\n -99,\n 18.5\n ],\n [\n -102,\n 18.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Mendoza, Carlos 0000-0002-2428-7064","orcid":"https://orcid.org/0000-0002-2428-7064","contributorId":343872,"corporation":false,"usgs":false,"family":"Mendoza","given":"Carlos","email":"","affiliations":[{"id":18923,"text":"Universidad Nacional Autonoma de Mexico","active":true,"usgs":false}],"preferred":false,"id":912251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":912252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramirez-Guzman, Leonardo","contributorId":151026,"corporation":false,"usgs":false,"family":"Ramirez-Guzman","given":"Leonardo","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":912253,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martinez-Lopez, R.","contributorId":343875,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"R.","email":"","affiliations":[{"id":18923,"text":"Universidad Nacional Autonoma de Mexico","active":true,"usgs":false}],"preferred":false,"id":912254,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255527,"text":"sir20245029 - 2024 - Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California","interactions":[],"lastModifiedDate":"2024-06-21T16:00:45.438369","indexId":"sir20245029","displayToPublicDate":"2024-06-21T06:46:09","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5029","displayTitle":"Dissolved Arsenic Concentrations in Surface Waters Within the Upper Portions of the Klamath River Basin, Oregon and California","title":"Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California","docAbstract":"Arsenic toxicity is an environmental health problem. Levels of arsenic in surface waters at some locations in the Klamath River Basin in southern Oregon and northern California can exceed the U.S. Environmental Protection Agency (EPA) standard for drinking water. There are both anthropogenic and natural sources of arsenic. The Klamath River Basin consists primarily of volcanic deposits and contains an underground geothermal system with hot springs and warm water wells, all known natural sources of arsenic. Anthropogenic sources of arsenic are related to the agricultural use of herbicides, fungicides, and insecticides. Surface water arsenic levels can also be affected by fertilizer amendments, evaporative concentration, oxygen-level depletion, and various geochemical transformations that can increase arsenic mobilization.
In this study by the U.S. Geological Survey and the Bureau of Reclamation, dissolved concentrations of arsenic, copper, and lead were measured in surface waters at 39 unique sites within the upper portions of the Klamath River Basin between 2018 and 2022. In every year, except 2022, sites were sampled four times between April and November. Surface-water arsenic concentrations varied up to four-orders of magnitude among sites. Median arsenic concentration was lowest at Cherry Creek (0.03 micrograms per liter [μg/L]) and highest at Wood Kimball Spring (36.7 μg/L), two sites located north of Upper Klamath Lake. The highest arsenic concentrations (17.4±4.9 μg/L, n=3) were found in drain sites (defined here as a waterbody returning used irrigation water) while the lowest arsenic concentrations were found in an artesian well (0.8 μg/L, n=1). The elevated arsenic concentrations of the drain sites suggest that arsenic might be concentrated or mobilized by agricultural activities, water re-use practices, and (or) by geochemical processes occurring around water stored in drains (that is, in the water column and across sediment water boundaries). A source of arsenic in drain water in the Klamath Strait Drain area includes water used for irrigation originating from Ady Canal. Other potential sources include groundwater, geothermal water, and local soils and sediments.
Seasonal differences in surface-water arsenic concentrations were detected at 13 sites, 10 of which had higher arsenic concentrations in summer than in either spring or fall. The sites sampled around Upper Klamath Lake, the impounded rivers, one of the two canal sites, and 5 of the 14 river sites had higher surface-water arsenic concentrations in the summer than in either spring or fall. Surface-water arsenic concentrations from groundwater sources (that is, springs and in the artesian well) did not vary significantly among seasons (p-values greater than 0.1).
Median surface-water concentrations of copper and lead ranged from 0.03 to 3.7 μg/L, and from 0.013 to 0.175 μg/L (n=2–18), respectively. Dissolved concentrations of both metals were below acute toxicity endpoints reported by the EPA for freshwater animals. Surface-water arsenic concentrations varied independently from corresponding changes in surface-water lead or copper concentrations. However, arsenic concentrations measured in bed-sediment samples collected from a subset of sites located north of Upper Klamath Lake correlated strongly and significantly with the corresponding sedimentary lead concentrations (p=0.015).
Aqueous arsenic speciation measured in a subset of sites in 2019 and 2022 showed that all the arsenic existed as arsenic (V), the most oxidized arsenic species, and presumably, the least toxic. The highest proportions of arsenite (As(III)), the presumably most toxic arsenic species, relative to total arsenic concentrations were found at drain sites.
Our assessment of dissolved arsenic concentrations in various surface-water bodies in the Upper Klamath River Basin reveals geographical areas of consistently low (below 2.1 μg/L), moderate (below 10 μg/L) and high (above 10 μg/L) surface-water arsenic concentrations. South of Upper Klamath Lake, surface-water arsenic concentrations were consistently higher than 20 μg/L at two drain sites located in an area of predominant agricultural land use with extensive water re-use practices. North of Upper Klamath Lake, surface-water arsenic concentrations greater than 20 μg/L were consistently measured at sites with limited nearby agricultural activities, suggesting a geogenic source. The consistently high arsenic levels from the Wood River at Jackson F. Kimball State Park, Fort Creek, and Crooked Creek, which are sites located at or near headwater spring sources, suggest a natural background source of arsenic. Water flowing downstream from this area could be a potential source of arsenic to Upper Klamath Lake and the Upper Klamath River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20245029","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Croteau, M.N., Topping, B.R., and Carlson, R.A., 2024, Dissolved arsenic concentrations in surface waters within the upper portions of the Klamath River Basin, Oregon and California: U.S. Geological Survey Scientific Investigations Report 2024–5029, 42 p., https://doi.org/10.3133/sir20245029.","productDescription":"Report: viii, 38 p.; Data Release","ipdsId":"IP-149938","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":430399,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P943CWH1","text":"USGS Data Release","description":"Hill, K.L., Croteau, M.N., Topping, B.R., Caro, D.A., Parris, J.L., Zierdt Smith, E.L., and Baesman, S.M., 2021, Dissolved arsenic, copper and lead concentrations in surface water within the Klamath Basin (ver 4.0, April 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P943CWH1.","linkHelpText":"Dissolved arsenic, copper and lead concentrations in surface water within the Klamath Basin (ver 4.0, April 2023)"},{"id":430404,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245029/full"},{"id":430403,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5029/images"},{"id":430402,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5029/sir20245029.xml"},{"id":430401,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5029/sir20245029.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":430400,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5029/covrthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.44639737545533,\n 43\n ],\n [\n -122.44639737545533,\n 41.66727944834608\n ],\n [\n -120.85711312398831,\n 41.66727944834608\n ],\n [\n -120.85711312398831,\n 43\n ],\n [\n -122.44639737545533,\n 43\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Gaofen-6 represents a series of Chinese high-resolution Earth observation satellites. More than 12 satellites have been launched in the Gaofen series, beginning with Gaofen-1 in 2013. Satellites within the series have varying infrared, radar, and optical imaging capabilities. The primary goal for the satellites in this series is to provide near real-time observations for climate change monitoring, geographical mapping, precision agriculture support, environmental and resource surveying, and disaster prevention. More information on Chinese satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium.”
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances of Gaofen-6. Results of these analyses indicate that Gaofen-6 has an interior geometric performance root mean square error ranging from 2.84 meters (m; 0.18 pixel) to 7.42 m (0.46 pixel) in easting and from 2.84 m (0.18 pixel) to 11.57 m (0.72 pixel) in northing in band-to-band registration, an exterior geometric performance root mean square error ranging from 154.50 m (8.80 pixels) in easting to 14.65 m (0.80 pixel) in northing in comparison to a corresponding Sentinel-2 scene, a radiometric performance ranging from 0.018 to 0.055 (in offset) and from 0.620 to 0.858 (in slope), and a spatial performance ranging from 2.10 to 2.30 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency ranging from 0.040 to 0.055.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030M","usgsCitation":"Sampath, A., Christopherson, J., Park, S., Kim, M., Stensaas, G.L., and Anderson, C., 2024, System characterization report on the Gaofen-6, chap. M of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 9 p., https://doi.org/10.3133/ofr20211030M.","productDescription":"iv, 9 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-133753","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":430388,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/m/coverthb.jpg"},{"id":430389,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/m/ofr20211030m.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–M"},{"id":430390,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/m/ofr20211030m.XML"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The purpose of this report is to provide the Marine Corps with an annual summary of abundance, breeding activity, demography, and habitat use of endangered Least Bell’s Vireos (Vireo bellii pusillus) at Marine Corps Base Camp Pendleton (MCBCP, or Base). Surveys for the Least Bell's Vireo were conducted at MCBCP, California, between April 1 and July 10, 2020. Core survey areas and a subset of non-core areas in drainages containing riparian habitat suitable for vireos were surveyed 3–4 times. We detected 669 territorial male vireos and 16 transient vireos in core survey areas. An additional 156 territorial male vireos were detected in non-core survey areas. Territorial vireos were detected on all 10 drainages/sites surveyed (core and non-core areas). Of the vireo territories in core areas, 88 percent were on the 4 most populated drainages, with the Santa Margarita River containing 69 percent of all territories. In core areas, 79 percent of male vireos were confirmed as paired; 83 percent of male vireos in non-core areas were confirmed as paired.
The number of documented Least Bell’s Vireo territories in core survey areas on MCBCP (669) increased 39 percent from 2019 to 2020. The number of territories in all core survey area drainages increased by one or more between 2019 and 2020. The substantial increase in vireo numbers on MCBCP (39 percent) was consistent with population changes in surrounding areas, including the lower San Luis Rey River (26 percent), Marine Corps Air Station, Camp Pendleton (58 percent), and the middle San Luis Rey River (7 percent).
Most core-area vireo territories (69 percent of males) occurred in willow (Salix spp.) riparian habitat. An additional 4 percent of birds occupied willow habitat co-dominated by Western sycamores (Platanus racemosa) or Fremont cottonwoods (Populus fremontii). Eighteen percent of territories were found in riparian scrub dominated by mule fat (Baccharis salicifolia) or sandbar willow (S. exigua). Upland scrub was used by 7 percent or fewer vireos; 1 percent of territories occurred in non-native vegetation, and less than 1 percent of vireo territories occurred in habitat co-dominated by coast live oak (Quercus agrifolia) and sycamore.
In 2019, MCBCP began operating an artificial seep along the Santa Margarita River. The artificial seep pumped water to the surface from March through August each year during daylight hours and was designed to increase the amount of surface water present to enhance Southwestern Willow Flycatcher (Empidonax traillii extimus; flycatcher) breeding habitat. Although this enhancement was designed to benefit flycatchers, few flycatchers have inhabited the seep and proposed seep areas within the past several years. Therefore, vireos were selected as a surrogate species to determine effects of the habitat enhancement. This report presents preliminary analyses of vireo and vegetation response to the existing artificial seep.
We sampled vegetation in the Seep site and three Reference sites to determine the effects of a new water diversion dam that was completed in 2019 and a surface water enhancement seep pump installed along the Santa Margarita River. We found minor differences in non-native vegetation cover between Reference sites and the Seep site. However, soil moisture was higher at the Reference sites compared to the Seep site. The effect of the seep pump may have been masked by high precipitation in the bio-year (July 1‒June 30) before 2020, limited time for the water diversion to have an effect, well-draining soil, and the non-operation of two to three of the six seep outlets.
We color banded and resighted color banded Least Bell’s Vireos to evaluate adult site fidelity, between-year movement, and the effect of surface water enhancement on vireo site fidelity and between-year movement. We banded 146 Least Bell's Vireos for the first time during the 2020 season. Birds banded included 27 adult vireos and 119 juvenile vireos. All adult vireos were banded with unique color combinations. The juvenile vireos (all nestlings) were banded with a single gold numbered federal band on the left leg.
We resighted and identified 85 Least Bell's Vireos banded before the 2020 breeding season on Base in 2020. Of the 85, 13 vireos were originally banded on the San Luis Rey River, 2 were banded in Baja California Sur, 1 was banded at Marine Corps Air Station, Camp Pendleton, and the remaining birds were banded at MCBCP. Adult birds of known age ranged from 1 to 8 years old.
Most returning adult vireos showed strong between-year site fidelity. Of the adults present in 2019 and 2020, 74 percent, (79 percent of males; 40 percent of females) returned to within 100 m of their previous territory. The average between-year movement for returning adult vireos was 0.3 plus or minus (±) 0.8 kilometer (km). The average movement of first-year vireos detected in 2020 that fledged from a known nest on MCBCP in 2019 was 4.7±7.0 km. One first-year vireo that originated at MCBCP moved off Base and was detected at Murrieta Creek, 23.0 km from his natal territory.
We monitored Least Bell's Vireo pairs to evaluate the effects of surface water enhancement on nest success and breeding productivity. Vireos were monitored at one Seep site and three Reference sites. Base personnel plan to install a second seep pump at one of the Reference sites in the future, at which time the status of the monitoring site will change from Reference to Seep.
Nesting activity was monitored between March 31 and July 28 in 52 territories within the Seep and Reference sites (12 at the Seep site and 40 at Reference sites). All territories were occupied by pairs, and all but one territory was fully monitored, meaning all nesting attempts were monitored at these territories. One vireo territory within a Reference site was partially monitored. During the monitoring period, 94 nests (25 in the Seep site and 69 in Reference sites) were monitored.
Breeding productivity was similar at the Seep site and Reference sites (3.7 and 2.9 young per pair, respectively), with 75 percent of Seep pairs and 79 percent of Reference pairs successfully fledging at least 1 young in 2020. Compared to Reference sites, the Seep site had a higher proportion of all eggs that hatched and also a higher proportion of nests with eggs that hatched. Conversely, a lower proportion of hatchlings and nests that had hatchlings fledged at the Seep site than at Reference sites. According to the best model, nest survival in 2020 was not affected by treatment (Seep versus Reference), although the second best model that included treatment was also well supported.
Completed nests at the Seep site were likely to be as successful as nests at Reference sites in 2020 (57 percent and 59 percent, respectively). Predation was believed to be the primary source of nest failure at both sites. Predation accounted for 90 percent and 73 percent of nest failures at Seep and Reference sites, respectively. Failure of the remaining eight nests was attributed to the collapse of the nesting substrate, exposure to rain and flooding, and other unknown reasons.
Fourteen plant species were used as hosts for vireo nests in 2020. In 2020, we found that at the Seep site, successful nests were placed in taller host plants and further from the edge of host plants (closer to the center) than unsuccessful nests. We found no difference in nest placement between the Seep site and the Reference sites.
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The wild to domestic bird interface is an important nexus for emergence and transmission of highly pathogenic avian influenza (HPAI) viruses. Although the recent incursion of HPAI H5N1 Clade 2.3.4.4b into North America calls for emergency response and planning given the unprecedented scale, readily available data-driven models are lacking. Here, we provide high resolution spatial and temporal transmission risk models for the contiguous United States. Considering virus host ecology, we included weekly species-level wild waterfowl (Anatidae) abundance and endemic low pathogenic avian influenza virus prevalence metrics in combination with number of poultry farms per commodity type and relative biosecurity risks at two spatial scales: 3 km and county-level. Spillover risk varied across the annual cycle of waterfowl migration and some locations exhibited persistent risk throughout the year given higher poultry production. Validation using wild bird introduction events identified by phylogenetic analysis from 2022 to 2023 HPAI poultry outbreaks indicate strong model performance. The modular nature of our approach lends itself to building upon updated datasets under evolving conditions, testing hypothetical scenarios, or customizing results with proprietary data. This research demonstrates an adaptive approach for developing models to inform preparedness and response as novel outbreaks occur, viruses evolve, and additional data become available.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-64912-w","usgsCitation":"Prosser, D., Kent, C.M., Sullivan, J.D., Patyk, K.A., McCool, M., Torchetti, M.K., Lantz, K., and Mullinax, J.M., 2024, Using an adaptive modeling framework to identify avian influenza spillover risk at the wild-domestic interface: Scientific Reports, v. 14, 14199, 13 p., https://doi.org/10.1038/s41598-024-64912-w.","productDescription":"14199, 13 p.","ipdsId":"IP-160406","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466992,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-64912-w","text":"Publisher Index Page"},{"id":465191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"contiguous United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n 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M.","contributorId":265823,"corporation":false,"usgs":false,"family":"Kent","given":"Cody","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":921227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":921228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Patyk, Kelly A.","contributorId":139696,"corporation":false,"usgs":false,"family":"Patyk","given":"Kelly","email":"","middleInitial":"A.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":921229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCool, Mary-Jane","contributorId":347273,"corporation":false,"usgs":false,"family":"McCool","given":"Mary-Jane","email":"","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":921230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torchetti, Mia K.","contributorId":252830,"corporation":false,"usgs":false,"family":"Torchetti","given":"Mia","email":"","middleInitial":"K.","affiliations":[{"id":50437,"text":"US Department of Agriculture – Veterinary Services, Ames, Iowa, USA","active":true,"usgs":false}],"preferred":false,"id":921231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lantz, Kristina","contributorId":317920,"corporation":false,"usgs":false,"family":"Lantz","given":"Kristina","email":"","affiliations":[{"id":69192,"text":"National Veterinary Services Laboratories, Animal and Plant Health Inspection Service, USDA","active":true,"usgs":false}],"preferred":false,"id":921232,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":921233,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70257521,"text":"70257521 - 2024 - Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model","interactions":[],"lastModifiedDate":"2024-09-06T15:17:44.893598","indexId":"70257521","displayToPublicDate":"2024-06-20T08:11:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model","docAbstract":"Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold-adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.
","language":"English","publisher":"Wiley","doi":"10.1002/ecy.4362","usgsCitation":"Custer, C.A., North, J.S., Schliep, E., Verhoeven, M.R., Hansen, G.J., and Wagner, T., 2024, Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model: Ecology, v. 105, no. 8, e4362, 16 p., https://doi.org/10.1002/ecy.4362.","productDescription":"e4362, 16 p.","ipdsId":"IP-159528","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":439371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.4362","text":"Publisher Index Page"},{"id":433556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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The Santa Ana River in the Los Angeles region of California demonstrates common habitat degradation symptoms that are characteristic of the urban stream syndrome. These impacts have altered the Santa Ana River community structure, with few species as impacted as the native Santa Ana sucker (sucker; Pantosteus santaanae). 2. Consequently, a recovery plan developed for sucker identified the need for a population viability analysis (PVA) to assess sucker extirpation risk. However, PVAs can be data-intensive and are subject to several sources of bias when standardized protocols are absent. 3. More than 20 years of sucker and arroyo chub (chub; Gila orcuttii) surveys using different methods were compiled to build an integrated hierarchical multi-population PVA to estimate trends in abundance and extirpation probability of these native fishes from the Santa Ana River. 4. PVA modelling indicated similar patterns in sucker and chub abundance along the Santa Ana River, with the highest abundance of both species in the upper regions of the river during the early 2000s and downstream in recent years (2018–2022). Extirpation risk was estimated to be greatest near wastewater treatment facilities, where native fish abundance estimates have been zero since 2018. Extirpation risk was lower downstream of the wastewater treatment facilities for both species, although extinction risk was higher for sucker than chub throughout the river. 5. As the model evolves and more data are collected, the PVA could be used to assess the effects of various management actions, such as non-native predator removals and native fish re-introductions, on sucker and chub persistence.
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