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.
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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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University","active":true,"usgs":false}],"preferred":false,"id":910614,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verhoeven, Michael R.","contributorId":343087,"corporation":false,"usgs":false,"family":"Verhoeven","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":910615,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hansen, Gretchen J.A.","contributorId":343090,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J.A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":910616,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910617,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70259615,"text":"70259615 - 2024 - Indications of preferential groundwater seepage feeding northern peatland pools","interactions":[],"lastModifiedDate":"2024-10-17T12:07:58.976979","indexId":"70259615","displayToPublicDate":"2024-06-20T07:05:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Indications of preferential groundwater seepage feeding northern peatland pools","docAbstract":"1. 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.
","language":"English","publisher":"Wiley","doi":"10.1002/aqc.4164","usgsCitation":"Huntsman, B., Palenscar, K., Russell, K., Mills, B., Jones, C., Ota, W., Anderson, K.E., Dyer, H., Abadi, F., and Wulff, M.L., 2024, Evaluation of extinction risk for stream fishes within an urban riverscape using population viability analysis: Aquatic Conservation: Marine and Freshwater Ecosystems, v. 34, no. 6, e4164, 15 p., https://doi.org/10.1002/aqc.4164.","productDescription":"e4164, 15 p.","ipdsId":"IP-155060","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":490042,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/aqc.4164","text":"Publisher Index Page"},{"id":430448,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Ana River drainage","geographicExtents":"{\n \"type\": 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Riverside, CA","active":true,"usgs":false}],"preferred":false,"id":904782,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, Kurt E.","contributorId":265545,"corporation":false,"usgs":false,"family":"Anderson","given":"Kurt","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":904783,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dyer, Heather","contributorId":297134,"corporation":false,"usgs":false,"family":"Dyer","given":"Heather","email":"","affiliations":[{"id":64298,"text":"San Bernardino Valley Municipal Water District","active":true,"usgs":false}],"preferred":false,"id":904784,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Abadi, Fitsum","contributorId":244779,"corporation":false,"usgs":false,"family":"Abadi","given":"Fitsum","affiliations":[{"id":48968,"text":"New Mexico State University, Department of Fish, Wildlife and Conservation 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wave erosion in Titan’s coasts","docAbstract":"In August 2020, the 3-m tall Pilchuck River Diversion Dam was removed from the Pilchuck River, allowing free fish passage to the upper third of the watershed for the first time in over a century. The narrow, 300-m long impoundment behind the dam was estimated to hold 4,000–7,500 m3 of sand and gravel, representing less than one year's typical bedload flux. Repeat cross section surveys, stage sensors, and time-lapse cameras were used to document the physical channel response over the first year following dam removal. A total of 7,400 m3 (effectively 100%) of impoundment sediment was eroded in the first year, with 25% accomplished by manual regrading during dam removal. Most river-caused erosion occurred during a sequence of modest flows in October 2020. Downstream deposition totaled 4,300 m3, predominately filling in the first 100 m downstream of the dam site. Deposition tapered below detectable levels within 350 m, and most downstream channel adjustments occurred before November 2020. Multiple high flows after December 2020 caused little upstream or downstream change. The physical river response to this dam removal then appears to have been largely accomplished within several months by modest flows, consistent with pre-removal modeling and observations from other regional dam removals. Efficient sediment evacuation was likely aided by the narrow and steep-walled impoundment geometry. Our observations support existing guidance that the physical river response to small dam removals is typically rapid and modest; the benefits of removal may then often be gained with minimal negative downstream geomorphic impacts.
","language":"English","publisher":"Northwest Scientific Association","doi":"10.3955/046.097.0113","usgsCitation":"Anderson, S.W., Shattuck, B., Shea, N., Seguin, C.M., Miles, J.J., Marks, D., and Coumou, N., 2024, River channel response to the removal of the Pilchuck River Diversion Dam, Washington State: Northwest Science, v. 97, no. 1-2, p. 134-145, https://doi.org/10.3955/046.097.0113.","productDescription":"12 p.","startPage":"134","endPage":"145","ipdsId":"IP-144271","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":427589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Pilchuck River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.904,\n 48.02\n ],\n [\n -121.916,\n 48.02\n ],\n [\n -121.916,\n 48.016\n ],\n [\n -121.904,\n 48.016\n ],\n [\n -121.904,\n 48.02\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":898313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shattuck, Brett","contributorId":335415,"corporation":false,"usgs":false,"family":"Shattuck","given":"Brett","email":"","affiliations":[{"id":80397,"text":"Tulalip Indian Tribe","active":true,"usgs":false}],"preferred":false,"id":898314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shea, Neil","contributorId":335416,"corporation":false,"usgs":false,"family":"Shea","given":"Neil","email":"","affiliations":[{"id":80397,"text":"Tulalip Indian Tribe","active":true,"usgs":false}],"preferred":false,"id":898315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seguin, Catherine M.","contributorId":332787,"corporation":false,"usgs":false,"family":"Seguin","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":898316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miles, Joe J. 0009-0003-4960-6783","orcid":"https://orcid.org/0009-0003-4960-6783","contributorId":337064,"corporation":false,"usgs":true,"family":"Miles","given":"Joe","email":"","middleInitial":"J.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":901867,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marks, Derek","contributorId":225112,"corporation":false,"usgs":false,"family":"Marks","given":"Derek","email":"","affiliations":[],"preferred":false,"id":898318,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Coumou, Natasha","contributorId":335418,"corporation":false,"usgs":false,"family":"Coumou","given":"Natasha","email":"","affiliations":[{"id":80397,"text":"Tulalip Indian Tribe","active":true,"usgs":false}],"preferred":false,"id":898319,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70255938,"text":"70255938 - 2024 - Demographics of a previously undocumented diamondback terrapin (Malaclemys terrapin) population","interactions":[],"lastModifiedDate":"2024-07-30T14:53:19.629068","indexId":"70255938","displayToPublicDate":"2024-06-18T10:33:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Demographics of a previously undocumented diamondback terrapin (Malaclemys terrapin) population","title":"Demographics of a previously undocumented diamondback terrapin (Malaclemys terrapin) population","docAbstract":"Coastal habitats are some of the most imperiled due to climate change and anthropogenic activities. As such, it is important to understand population dynamics of the species that may play a role in regulating coastal systems. Diamondback terrapins in Northwest Florida have been understudied, which has resulted in a gap in our knowledge for this region. To help fill this gap, we conducted a capture-mark-recapture study in St. Joseph Bay, Florida, from 2018 to 2021. Overall, we captured 518 individuals, including 146 recaptures, and we used several modeling frameworks to estimate apparent survival, recapture probability, population entrance, and population size. Our estimates of apparent survival were relatively low, especially for adult males (0.77) and adult females (0.83), but there is a considerable amount of uncertainty around our estimates. Our models indicated that the super-population consists of 1122 individuals (971–1327 95% CI), and the population is comprised of more adult males (753; 665–866 95% CI) than adult females (102; 85–130 95% CI) and juveniles (267; 221–331 95% CI). Estimates of population entrance varied by year throughout our study duration. This study is the first to document a Malaclemys terrapin population in this region of Florida, and we recommend long-term monitoring in order to gain inferences for the management of this declining coastal species.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-024-01380-5","usgsCitation":"Catizone, D.J., Thomas, T.M., Romagosa, C., and Lamont, M., 2024, Demographics of a previously undocumented diamondback terrapin (Malaclemys terrapin) population: Estuaries and Coasts, v. 47, p. 1684-1693, https://doi.org/10.1007/s12237-024-01380-5.","productDescription":"10 p.","startPage":"1684","endPage":"1693","ipdsId":"IP-151031","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":430976,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St. Joseph Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.44660816786433,\n 29.900893125154155\n ],\n [\n -85.44660816786433,\n 29.665660146459913\n ],\n [\n -85.25729815600472,\n 29.665660146459913\n ],\n [\n -85.25729815600472,\n 29.900893125154155\n ],\n [\n -85.44660816786433,\n 29.900893125154155\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","noUsgsAuthors":false,"publicationDate":"2024-06-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Catizone, Daniel J. 0000-0002-7030-4208","orcid":"https://orcid.org/0000-0002-7030-4208","contributorId":248817,"corporation":false,"usgs":true,"family":"Catizone","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":906082,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Travis M.","contributorId":289917,"corporation":false,"usgs":false,"family":"Thomas","given":"Travis","email":"","middleInitial":"M.","affiliations":[{"id":62286,"text":"Nature Coast Biological Station, Cedar Key, FL","active":true,"usgs":false}],"preferred":false,"id":906083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romagosa, Christina 0000-0003-1900-5648","orcid":"https://orcid.org/0000-0003-1900-5648","contributorId":299306,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":906084,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":222403,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":906085,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255886,"text":"70255886 - 2024 - Spatial patterns as long transients in submersed-floating plant competition with biocontrol","interactions":[],"lastModifiedDate":"2024-09-23T16:11:40.232139","indexId":"70255886","displayToPublicDate":"2024-06-18T06:44:25","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3592,"text":"Theoretical Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Spatial patterns as long transients in submersed-floating plant competition with biocontrol","docAbstract":"A cellular automata model was developed and parameterized to test the effectiveness of application of biological control insects to water hyacinth (Pontederia crassipes), which is an invasive floating plant species in many parts of the world and outcompetes many submersed native aquatic species in southern Florida. In the model, P. crassipes was allowed to compete with Nuttall’s waterweed (Elodea nuttallii). In the absence of biocontrol acting on the P. crassipes, E. nuttallii excluded P. crassipes at low concentrations of the limiting nutrient (nitrogen), and the reverse occurred at high nutrient concentrations. At intermediate values, alternative stable states could occur; either P. crassipes alone or a mixture of the two species. When the biocontrol agent, the weevil Neochetina eichhorniae, was applied in the model, there was initially a rapid reduction of the P. crassipes, however, over time a regular striped pattern of moving spatially alternating stripes of P. crassipes and E. nuttallii emerged. -This pattern of moving stripes emerged and persisted over thousands of days but could quickly transform into an irregular pattern at some apparently random time, when either external stochasticity (added adult weevils) or only the weak internal stochasticity of weevil movements occurred. The cause of the end of the long transient can be traced to a single slightly irregular pixel within the striped pattern. Model parameters were varied to study effects of plant growth rate, nutrient concentration and nutrient diffusion rate on the dynamics of the system.
Understanding controls on solute export to streams is challenging because heterogeneous catchments can respond uniquely to drivers of environmental change. To understand general solute export patterns, we used a large-scale inductive approach to evaluate concentration–discharge (C–Q) metrics across catchments spanning a broad range of catchment attributes and hydroclimatic drivers. We leveraged paired C–Q data for 11 solutes from CAMELS-Chem, a database built upon an existing dataset of catchment and hydroclimatic attributes from relatively undisturbed catchments across the contiguous USA. Because C–Q relationships with Q thresholds reflect a shift in solute export dynamics and are poorly characterized across solutes and diverse catchments, we analysed C–Q relationships using Bayesian segmented regression to quantify Q thresholds in the C–Q relationship. Threshold responses were rare, representing only 12% of C–Q relationships, 56% of which occurred for solutes predominantly sourced from bedrock. Further, solutes were dominated by one or two C–Q patterns that reflected vertical solute–source distributions. Specifically, solutes predominantly sourced from bedrock had diluting C–Q responses in 43%–70% of catchments, and solutes predominantly sourced from soils had more enrichment responses in 35%–51% of catchments. We also linked C–Q relationships to catchment and hydroclimatic attributes to understand controls on export patterns. The relationships were generally weak despite the diversity of solutes and attribute types considered. However, catchment and hydroclimatic attributes in the central USA typically drove the most divergent export behaviour for solutes. Further, we illustrate how our inductive approach generated new hypotheses that can be tested at discrete, representative catchments using deductive approaches to better understand the processes underlying solute export patterns. Finally, given these long-term C–Q relationships are from minimally disturbed catchments, our findings can be used as benchmarks for change in more disturbed catchments.
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L.","contributorId":152225,"corporation":false,"usgs":false,"family":"Li","given":"L.","affiliations":[],"preferred":false,"id":906559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seybold, Erin C. 0000-0002-0365-2333","orcid":"https://orcid.org/0000-0002-0365-2333","contributorId":340201,"corporation":false,"usgs":false,"family":"Seybold","given":"Erin","email":"","middleInitial":"C.","affiliations":[{"id":35641,"text":"Kansas Geological Survey","active":true,"usgs":false}],"preferred":false,"id":906560,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Bryn 0000-0002-3199-0129","orcid":"https://orcid.org/0000-0002-3199-0129","contributorId":340202,"corporation":false,"usgs":false,"family":"Stewart","given":"Bryn","email":"","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":906561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rizzo, Donna M.","contributorId":171679,"corporation":false,"usgs":false,"family":"Rizzo","given":"Donna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":906562,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ul Haq, Ijaz","contributorId":340203,"corporation":false,"usgs":false,"family":"Ul Haq","given":"Ijaz","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":906563,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Perdrial, Julia N.","contributorId":177340,"corporation":false,"usgs":false,"family":"Perdrial","given":"Julia","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":906564,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70255606,"text":"70255606 - 2024 - Visualizing wading bird optimal foraging decisions with aggregation behaviors using individual-based modeling","interactions":[],"lastModifiedDate":"2024-06-26T13:38:24.914144","indexId":"70255606","displayToPublicDate":"2024-06-17T08:36:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Visualizing wading bird optimal foraging decisions with aggregation behaviors using individual-based modeling","docAbstract":"Foragers on patchy landscapes must efficiently balance time between searching for and consuming resources to meet their daily energetic requirements. Spatial aggregation foraging behaviors may improve foraging efficiency by sharing information on locations of resource hotspots. Wading birds are an example of patch foragers that form colonial aggregations during the breeding season to obtain sufficient prey energy to sustain themselves and their offspring each day. Here, we describe a spatially-explicit simulation model of wading bird optimal foraging that represents information sharing through visual cues. The overall purpose of the model is to describe how wading bird daily foraging and reproductive success may change with alternative water control management practices that determine spatial availability of prey for wading birds on the landscape, throughout their breeding seasons. Wading birds are simulated as individuals that operate independently, sampling and selecting among patches based on a prey density tolerance threshold, but also use information from other birds to inform their selection decisions. Foraging success is evaluated against the fundamental objectives of (a) fulfilling daily energetic demands and (b) minimizing predation exposure, by tracking individual daily energetic intake and time spent foraging. In this way, the model approximates population level dynamics of wading bird aggregations that emerge through collective decision making of birds simulated at the lower individual level. Key results of this study suggest that aggregation behaviors may improve population-level foraging success rates, and the optimal settling threshold may modulate when resources become more scarce or difficult to find. Thus, the model addresses ecological theory on the advantages of foraging in groups versus independently. This technique is appropriate for evaluating wading bird populations that forage on patchy landscapes, such as seasonally-pulsed wetlands, wherever sufficient information is available to describe (1) foraging behavior (e.g., feeding rate, flight speeds, patch selection decisions), (2) key landscape characteristics, (3) spatial distributions of prey densities among foraging patches, and (4) changes in prey densities through time. The model was designed to predict qualitative, testable spatial patterns of wading bird foraging movements which can be compared with empirical observations and empirically-derived habitat suitability models. These techniques can also be applied to other bird species, such as shorebirds, or more generally to any species that transits between discrete foraging patches.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2024.110702","usgsCitation":"Yurek, S., DeAngelis, D.L., Lee, H.W., and Tennenbaum, S., 2024, Visualizing wading bird optimal foraging decisions with aggregation behaviors using individual-based modeling: Ecological Modelling, v. 493, 110702, 15 p., https://doi.org/10.1016/j.ecolmodel.2024.110702.","productDescription":"110702, 15 p.","ipdsId":"IP-153166","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2024.110702","text":"Publisher Index Page"},{"id":430522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"493","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yurek, Simeon 0000-0002-6209-7915","orcid":"https://orcid.org/0000-0002-6209-7915","contributorId":216738,"corporation":false,"usgs":true,"family":"Yurek","given":"Simeon","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":904925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":904926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Hyo Won","contributorId":292184,"corporation":false,"usgs":false,"family":"Lee","given":"Hyo","email":"","middleInitial":"Won","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":904927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tennenbaum, Stephen","contributorId":292180,"corporation":false,"usgs":false,"family":"Tennenbaum","given":"Stephen","email":"","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":904928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70255277,"text":"sir20235064B - 2024 - Peak streamflow trends in Illinois and their relation to changes in climate, water years 1921–2020","interactions":[{"subject":{"id":70255277,"text":"sir20235064B - 2024 - Peak streamflow trends in Illinois and their relation to changes in climate, water years 1921–2020","indexId":"sir20235064B","publicationYear":"2024","noYear":false,"chapter":"B","displayTitle":"Peak Streamflow Trends in Illinois and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in Illinois and their relation to changes in climate, water years 1921–2020"},"predicate":"IS_PART_OF","object":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"id":1}],"isPartOf":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"lastModifiedDate":"2024-06-17T22:21:15.873668","indexId":"sir20235064B","displayToPublicDate":"2024-06-17T07:11:12","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":"2023-5064","chapter":"B","displayTitle":"Peak Streamflow Trends in Illinois and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in Illinois and their relation to changes in climate, water years 1921–2020","docAbstract":"This report characterizes changes in peak streamflow in Illinois and the relation of these changes to climatic variability, and provides a foundation for future studies that can address nonstationarity in peak-flow frequency analysis in Illinois. Records of annual peak and daily streamflow at streamgages and gridded monthly climatic data (observed and modeled) were examined across four trend periods (100 years, water years 1921–2020; 75 years, 1946–2020; 50 years, 1971–2020; 30 years 1991–2020) for trends, change points, and other statistical properties indicative of changing conditions. Median peak streamflows generally exhibit upward trends across the State for the 100- and 75-year trend periods and in northern and southern Illinois for the 50- and 30-year trend periods. The medians of the trend magnitudes (normalized by median peak streamflow) range from a 23-percent increase during the 30-year trend period to a 41-percent increase during the 100-year trend period. Streamgages with trends in peak streamflow often also have change points, or abrupt changes, in streamflow magnitude. More than two-thirds of streamgages at the 100- and 75-year trend periods exhibit a trend and change point in median peak streamflow in the same direction. Temporally, clusters of change points are observed in the late 1960s through early 1980s for the 100- and 75-year trend periods and around 2006 for the 50- and 30-year trend periods. Trends in the 90-percent quantile of peak streamflow, which correspond to the 10-percent exceedance probability often used for the design of drainage structures, increased about the same amount as the 50-percent quantile peak streamflows, except at the 100-year trend period, where the 50-percent quantile peak flow increased more for almost all streamgages. The frequency of high flows has also increased in Illinois, with increases in peaks-over-threshold observed across much of the State for the 100- and 75-year trend periods and in northern and southern Illinois for the 50- and 30-year trend periods.
Upward trends in observed temperature and observed annual precipitation dominate in all trend periods, with clusters of likely upward trends observed in northern and southern Illinois at the 50- and 30-year trend periods. As expected in response to increasing temperature, the modeled proportion of precipitation falling as snow has largely decreased in the study basins across the State, and modeled potential evapotranspiration has increased. Upward trends in modeled annual runoff, which in this report incorporates only the effects of climatic variation, are observed in the same geographic areas where there are increases in observed annual precipitation.
The widespread upward trends in the magnitude of median peak streamflows and the frequency with which high flows occur across the State at the 100- and 75-year trend periods and in northern and southern Illinois at the 50- and 30-year trend periods appear to be driven largely by increases in precipitation based on spatial patterns of these changes and statistical relations between streamflow and climate metrics. Other effects not considered in this report, like urbanization, may be important drivers for certain streamgages in the State.
The prevalence of nonstationarity in peak streamflow in Illinois has important implications for peak-flow frequency analysis. Average annual precipitation and the occurrence of extreme precipitation events are expected to increase across the State. If precipitation continues to increase as expected, peak-flow frequency estimates based on older records may no longer represent the hydrologic regime of today, and methods for nonstationary peak-flow frequency analysis may be needed.
Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
Effect concentrations of ammonia, nickel, sodium chloride, and potassium chloride from short-term 7-day tests were compared to those from standard chronic 28-day toxicity tests with juvenile mussels (fatmucket, Lampsilis siliquoidea) to evaluate the sensitivities of the 7-day tests. The effect concentrations for nickel (59 µg Ni/L), chloride (316–519 mg Cl/L, a range from multiple tests), and potassium (15 mg K/L) obtained from the 7-day tests were within a range of effect concentrations for each corresponding chemical in the 28-day tests (41–91 µg Ni/L, 251–>676 mg Cl/L, 15–23 mg K/L), whereas the 7-day ammonia effect concentration (0.40 mg/L total ammonia nitrogen; TAN) was up to 3.3-fold greater than the 28-day effect concentrations (0.12–0.36 mg TAN/L) but with overlapped 95% confidence limits. These results indicate that the 7-day tests produced similar estimates compared to the 28-day tests. Further studies are needed to evaluate the 7-day test sensitivity using additional chemicals with different modes of toxic action. Environ Toxicol Chem 2024;00:1–6. Published 2024. This article is a U.S. Government work and is in the public domain in the USA.
Features of landscape morphology—including slope, curvature, and drainage dissection—are important controls on runoff generation in upland landscapes. Over long timescales, runoff plays an essential role in shaping these same features through surface erosion. This feedback between erosion and runoff generation suggests that modeling long-term landscape evolution together with dynamic runoff generation could provide insight into hydrological function. Here we examine the emergence of variable source area runoff generation in a new coupled hydro-geomorphic model that accounts for water balance partitioning between surface flow, subsurface flow, and evapotranspiration as landscapes evolve over millions of years. We derive a minimal set of dimensionless numbers that provide insight into how hydrologic and geomorphic parameters together affect landscapes. Across the parameter space we investigated, model results collapsed to a single inverse relationship between the dimensionless relief and the ratio of catchment quickflow to discharge. Furthermore, we found an inverse relationship between the Hillslope number, which describes topographic relief relative to aquifer thickness, and the proportion of the landscape that was variably saturated. While the model generally produces fluvial topography visually similar to simpler landscape evolution models, certain parameter combinations produce wide valley bottom wetlands and non-dendritic, trellis-like drainage networks, which may reflect real conditions in some landscapes where aquifer gradients become decoupled from topography. With these results, we demonstrate the power of hydro-geomorphic models for generating new insights into hydrological processes, and also suggest that subsurface hydrology may be integral for modeling aspects of long-term landscape evolution.
The eruption of Hunga volcano on 15 January 2022 produced a higher plume and faster-growing umbrella cloud than has ever been previously recorded. The plume height exceeded 58 km, and the umbrella grew to 450 km in diameter within 50 min. Assuming an umbrella thickness of 10 km, this growth rate implied an average volume injection rate into the umbrella of 330–500 km3 s−1. Conventional relationships between plume height, umbrella-growth rate, and mass eruption rate suggest that this period of activity should have injected a few to several cubic kilometers of rock particles (tephra) into the plume. Yet tephra fall deposits on neighboring islands are only a few centimeters thick and can be reproduced using ash transport simulations with only 0.1–0.2 km3 erupted volume (dense-rock equivalent). How could such a powerful eruption contain so little tephra? Here, we propose that seawater mixing at the vent boosted the plume height and umbrella growth rate. Using the one-dimensional (1-D) steady plume model Plumeria, we find that a plume fed by ~90% water vapor at a temperature of 100 °C (referred to here as steam) could have exceeded 50 km height while keeping the injection rate of solids low enough to be consistent with Hunga’s modest tephra-fall deposit volume. Steam is envisaged to rise from intense phreatomagmatic jets or pyroclastic density currents entering the ocean. Overall, the height and expansion rate of Hunga’s giant plume is consistent with the total mass of fall deposits plus underwater density current deposits, even though most of the erupted mass decoupled from the high plume. This example represents a class of high (> 10 km), ash-poor, steam-driven plumes, that also includes Kīlauea (2020) and Fukutoku-oka-no-ba (2021). Their height is driven by heat flux following well-established relations; however, most of the heat is contained in steam rather than particles. As a result, the heights of these water-rich plumes do not follow well-known relations with the mass eruption rate of tephra.
Wildlife populations near the periphery of a species’ range are vulnerable to changes in habitat conditions and climate. However, habitat management and maintenance can help with the persistence of these susceptible populations. Snowshoe hare (Lepus americanus) populations near the southern extent of their range are at risk of extirpation because of changing winter conditions, coupled with reduced early-successional habitat. Prescribed fire has been used to restore and maintain early-successional habitat in the southern range of snowshoe hares, but previous research suggests that burned areas might initially be unsuitable for hares. Therefore, more information is needed on the time required for hares to start using an area post-burning, and the long-term effects of prescribed fire on hare survival. We studied snowshoe hare habitat use and survival in northeastern Pennsylvania, where prescribed fire has been used for scrub oak barrens restoration. We used GPS locations from 71 hares and used resource selection functions to analyze hare selection for burned habitats of varying ages (0–12 years post-burn) and known-fate survival models to evaluate the effects of burning on survival. Hares started using burned areas ≥7 years post-burning but avoided areas burned 0–6 years prior. In addition, hare survival was positively associated with the amount of old burn habitat (≥7 years post-burn) used by an individual. Our results indicate that prescribed burning can be beneficial for hares, but that a time lag of ≥7 years is necessary for positive responses to occur. Planning burns within a mosaic of unburned areas could allow hares to persist during the 0–6 years post-burn when areas are not suitable for hares, which in turn could benefit the persistence of southern snowshoe hare populations. Collectively, our results highlight the importance of long-term demographic monitoring to understand wildlife population responses to management actions.
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\"}}]}","noUsgsAuthors":false,"publicationDate":"2024-06-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Gigliotti, Laura C.","contributorId":204828,"corporation":false,"usgs":false,"family":"Gigliotti","given":"Laura C.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":912757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyd, Emily S.","contributorId":342971,"corporation":false,"usgs":false,"family":"Boyd","given":"Emily","email":"","middleInitial":"S.","affiliations":[{"id":12891,"text":"Pennsylvania Game Commission","active":true,"usgs":false}],"preferred":false,"id":910550,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910551,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256001,"text":"70256001 - 2024 - Uncertainty in ground-motion-to-intensity conversions significantly affects earthquake early warning alert regions","interactions":[],"lastModifiedDate":"2024-07-12T11:58:11.727858","indexId":"70256001","displayToPublicDate":"2024-06-16T06:56:13","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10542,"text":"The Seismic Record","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty in ground-motion-to-intensity conversions significantly affects earthquake early warning alert regions","docAbstract":"We examine how the choice of ground‐motion‐to‐intensity conversion equations (GMICEs) in earthquake early warning (EEW) systems affects resulting alert regions. We find that existing GMICEs can underestimate observed shaking at short rupture distances or overestimate the extent of low‐intensity shaking. Updated GMICEs that remove these biases would improve the accuracy of alert regions for the ShakeAlert EEW system for the West Coast of the United States. ShakeAlert uses ground‐motion prediction equations (GMPEs), which calculate spatial distributions of peak ground acceleration (PGA) and peak ground velocity (PGV) from earthquake source estimates, combined with GMICEs to translate GMPE output into modified Mercalli intensity (MMI). We find significant epistemic uncertainty in alert distances; near‐source MMI estimates from different GMICEs can differ by over 1 MMI unit, and MMI extents used for public EEW alerts can differ by hundreds of kilometers for larger magnitude earthquakes (M ∼6.5+). We use a catalog of “Did You Feel It?” shaking reports to evaluate how well GMICEs predict observed shaking. Our preferred GMICE is the one that computes MMI using PGV for high intensities and transitions to using PGA for nondamaging intensities. These results motivate updating GMICE relationships more generally, including in ShakeMap applications.
Understanding genetic structure and diversity among remnant populations of rare species can inform conservation and recovery actions. We used a population genetic framework to spatially delineate gene pools and estimate gene flow and effective population sizes for the endangered California Freshwater Shrimp Syncaris pacifica. Tissues of 101 individuals were collected from 11 sites in 5 watersheds, using non-lethal tissue sampling. Single Nucleotide Polymorphism markers were developed de novo using ddRAD-seq methods, resulting in 433 unlinked loci scored with high confidence and low missing data. We found evidence for strong genetic structure across the species range. Two hierarchical levels of significant differentiation were observed: (i) five clusters (regional gene pools, FST = 0.38–0.75) isolated by low gene flow were associated with watershed limits and (ii) modest local structure among tributaries within a watershed that are not connected through direct downstream flow (local gene pools, FST = 0.06–0.10). Sampling sites connected with direct upstream-to-downstream water flow were not differentiated. Our analyses suggest that regional watersheds are isolated from one another, with very limited (possibly no) gene flow over recent generations. This isolation is paired with small effective population sizes across regional gene pools (Ne = 62.4–147.1). Genetic diversity was variable across sites and watersheds (He = 0.09–0.22). Those with the highest diversity may have been refugia and are now potential sources of genetic diversity for other populations. These findings highlight which portions of the species range may be most vulnerable to future habitat fragmentation and provide management consideration for maintaining local effective population sizes and genetic connectivity.