The use of wetlands to support native fish research and conservation efforts in the Sacramento–San Joaquin Delta (Delta) of California is a growing priority. The purpose of our study was to examine the physiochemical and biological characteristics of select managed ponds in the Delta to determine if they would be suitable habitats for research involving the conservation of delta smelt (Hypomesus transpacificus). We studied 10 managed ponds distributed across the central part of the Delta situated on Bacon Island and Bouldin Island in San Joaquin County, and Holland Tract and Webb Tract islands in Contra Costa County. The managed ponds had a diversity of physical habitat configurations and were not directly connected to waterways surrounding the islands and, therefore, not affected by tides. We studied the managed ponds from approximately November 2021 to December 2023 to assess water quality, zooplankton, fish, and pesticide metrics. Water levels in the managed ponds were managed to varying degrees and were mostly independent of climate-driven wet-dry seasonality. Water quality conditions varied among ponds and were independent of geographic location. Overall, mean monthly chlorophyll a concentration ranged from 15 to 57 (mean=30) micrograms per liter (μg/L), dissolved oxygen concentration ranged from 4 to 9 (mean=7) milligrams per liter (mg/L), pH was 8, salinity was 1 practical salinity units (PSU), specific conductance ranged from 1,202 to 1,839 (mean=1,471) microsiemens per centimeter (μS/cm), and turbidity ranged from 13 to 24 (mean=19) Formazin Nephelometric Units (FNU). Water temperature thresholds that contribute to stress (21 degrees Celsius [°C]) and mortality (28 °C) of delta smelt were often exceeded during summer and fall, though vertical stratification contributed to lower bottom temperatures in the deepest managed ponds, which could potentially provide thermal refugia for delta smelt so long as dissolved oxygen concentrations are suitable. Zooplankton populations were broadly similar among managed ponds and included calanoid and cyclopoid copepods that would be suitable prey for delta smelt. Overall average total zooplankton biomass, as measured with a Schindler-Patalas trap, was 0.6 μg/L (min=0, max=63.6) and peaked during spring at more than 4 μg/L. Fish populations highly varied among the managed ponds with potential predators of delta smelt such as largemouth bass (Micropterus salmoides) and black crappie (Pomoxis nigromaculatus) present in several of the managed ponds; predator distribution among ponds seemed to have been driven primarily by deliberate stocking to facilitate local fisheries. Measured pesticide concentrations were below U.S. Environmental Protection Agency Aquatic Life Benchmarks except for exceedances of three compounds (diuron [herbicide], clothianidin [insecticide], and deltamethrin [pyrethroid insecticide]) in samples collected from ponds on Bouldin Island and Webb Tract. Overall, most managed ponds seemed suitable to support delta smelt, though physical control of potential predators and summer temperature might be needed. The results provide guidance on how to engineer and manage new managed ponds to support research and conservation efforts for delta smelt and other native fishes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251040","collaboration":"Prepared in cooperation with Metropolitan Water District and State Water Contractors","usgsCitation":"Feyrer, F.V., Acuña, S., Buxton, J.M., Enos, E.R., Hladik, M.L., Orlando, J., and Young, M.J., 2025, Environmental characteristics of select managed ponds in the Sacramento–San Joaquin Delta—Implications\nfor native fish conservation and research: U.S. Geological Survey Open-File Report 2025–1040, 35 p., https://doi.org/10.3133/ofr20251040.","productDescription":"Report: viii, 35 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-168544","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":492747,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1040/ofr20251040.XML"},{"id":492746,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1040/images"},{"id":492745,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97GLG5I","text":"USGS data release","description":"USGS data release","linkHelpText":"Water quality and biological data from ponds on islands of the Sacramento–San Joaquin Delta"},{"id":492744,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251040/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1040"},{"id":492743,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1040/ofr20251040.pdf","text":"Report","size":"2.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1040"},{"id":492742,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1040/coverthb.jpg"}],"country":"United States","state":"California","county":"Contra Costa County, San Joaquin County","otherGeospatial":"Bacon Island, Bouldin Island, Holland Tract Island, Webb Tract Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.6667,\n 38.133333\n ],\n [\n -121.6667,\n 37.933333\n ],\n [\n -121.45,\n 37.933333\n ],\n [\n -121.45,\n 38.133333\n ],\n [\n -121.6667,\n 38.133333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Invasive carps, specifically silver carp (Hypophthalmichthys molitrix), bighead carp (H. nobilis), grass carp (Ctenopharyngodon idella), and black carp (Mylopharyngodon piceus), have proliferated in the Mississippi River Basin owing to escapes from aquaculture facilities and intentional releases. In the Water Resources and Development Act (WRDA) of 2020 Sec. 509, Congress directed the U.S. Army Corps of Engineers to work with the Tennessee Valley Authority and other relevant agencies with deterrent projects to implement as many as 10 deterrent projects intended to manage and prevent the spread of invasive carp in the Tennessee and Cumberland River subbasins. The WRDA was amended in 2022 to include that at least one location must be situated on the Tennessee–Tombigbee Waterway. This report documents a structured decision-making process that engaged State and Federal agencies to evaluate alternative deterrent site sequences at specified lock and dam complexes on the Tennessee River, Cumberland River, and the Tennessee–Tombigbee Waterway. State and Federal agencies participated in a series of virtual and face-to-face meetings to structure the problem, expand the models used in previous decision analyses for the Tennessee River, and define management objectives. Potential deterrent sites were restricted to the downstream locations on the Tennessee River (n=3), Cumberland River (n=2), and the Tennessee–Tombigbee Waterway (n=10). Only considering 15 sites allowed all feasible deterrent site combinations and sequences to be evaluated. Invasive carp relative abundance was projected for the Tennessee River, Cumberland River, and Tennessee–Tombigbee Waterway management units for 20 years using a simulation model. The deterrent site sequences were ranked based on the system-level invasive carp relative abundance and distribution in year 20. The unique downstream expansion of invasive carp through the Tennessee–Tombigbee Waterway was important to the interest group, but downstream movement rates were unknown; therefore, several downstream movement rates were evaluated, and the outcomes were used to rank deterrent site sequences. Additionally, the analysis incorporated two scenarios involving the retention and removal of an experimental deterrent at Barkley Lock on the Cumberland River. The results of the deterrent site sequences varied among downstream movement rates, with Tennessee–Tombigbee Waterway deterrent locations installed earlier in highly ranked sequences with increasing downstream movement rates. This analysis was time-limited owing to agency needs and represents Phase 1 of this project. Phase 2 expands Phase 1 to address additional uncertainties and more holistic management objectives and strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251039","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Colvin, M.E., Aldridge, C.A., Jackson, N., and Post van der Burg, M., 2025, Evaluating deterrent locations and sequence in the Tennessee and Cumberland Rivers and the Tennessee–Tombigbee Waterway to minimize invasive carp occupancy and abundance: U.S. Geological Survey Open-File Report 2025–1039, 27 p., https://doi.org/10.3133/ofr20251039.","productDescription":"vii, 27 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-171324","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":492704,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251039/full"},{"id":492703,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1039/images/"},{"id":492702,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1039/ofr20251039.XML"},{"id":492701,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1039/ofr20251039.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2-25–1039"},{"id":492700,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1039/coverthb.jpg"}],"country":"United States","state":"Alabama, Georgia, Kentucky, Mississippi, Tennessee, Virginia","otherGeospatial":"Cumberland River, Tennessee River, Tennessee-Tombigbee Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.25835232816404,\n 30.40221322680152\n ],\n [\n -87.74112738454285,\n 30.53409733966683\n ],\n [\n -86.28197353514268,\n 33.17664867905761\n ],\n [\n -84.58539276715948,\n 35.11174136013369\n ],\n [\n -84.00529754650283,\n 34.7785832881593\n ],\n [\n -83.35182994181118,\n 34.28883621944685\n ],\n [\n -83.19236665540257,\n 35.041055997522406\n ],\n [\n -80.2096850872316,\n 36.78640735388454\n ],\n [\n -80.86738805566942,\n 37.257953522126016\n ],\n [\n -82.13281736640333,\n 37.06950836241309\n ],\n [\n -83.02442148961904,\n 37.262219027957244\n ],\n [\n -83.54138832596139,\n 37.46692711167633\n ],\n [\n -84.33015340933808,\n 37.60749767579556\n ],\n [\n -85.06533697843895,\n 37.036511430167636\n ],\n [\n -85.5677502361562,\n 36.45362253430034\n ],\n [\n -85.87920757818353,\n 36.383379347391596\n ],\n [\n -86.6325463621631,\n 37.379506944709526\n ],\n [\n -87.72434869310914,\n 37.50907115621132\n ],\n [\n -88.41107734207077,\n 37.2244083095801\n ],\n [\n -88.42057356609506,\n 37.02794489656113\n ],\n [\n -89.00288659023786,\n 37.183779269350126\n ],\n [\n -88.75606773049479,\n 35.10788131292719\n ],\n [\n -89.05545157713219,\n 34.33758222980704\n ],\n [\n -88.86237269918561,\n 33.56728314668689\n ],\n [\n -88.61821473605681,\n 32.488997215417314\n ],\n [\n -88.31062051861113,\n 31.90405945387107\n ],\n [\n -88.25835232816404,\n 30.40221322680152\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
Invasive silver carp are spreading upstream in the Tennessee and Cumberland Rivers. This report details a collaborative effort among State and Federal agencies to evaluate potential sites for invasive carp deterrent projects along the Tennessee River, Cumberland River, and the Tennessee–Tombigbee Waterway. The findings highlight that project implementation timing could significantly impact their success, especially with increasing downstream movement rates of invasive carp.
","publicationDate":"2025-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":943664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Caleb A.","contributorId":358407,"corporation":false,"usgs":false,"family":"Aldridge","given":"Caleb A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":943665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Neal","contributorId":203382,"corporation":false,"usgs":false,"family":"Jackson","given":"Neal","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":943666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Post van der Burg, Max 0000-0002-3943-4194","orcid":"https://orcid.org/0000-0002-3943-4194","contributorId":219400,"corporation":false,"usgs":true,"family":"Post van der Burg","given":"Max","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":943667,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70268814,"text":"ofr20251034 - 2025 - Preparation and analysis methods for fish tissue collected from Lake Koocanusa, Montana","interactions":[],"lastModifiedDate":"2026-02-03T14:19:50.914046","indexId":"ofr20251034","displayToPublicDate":"2025-07-08T12:33:51","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1034","displayTitle":"Preparation and Analysis Methods for Fish Tissue Collected from Lake Koocanusa, Montana","title":"Preparation and analysis methods for fish tissue collected from Lake Koocanusa, Montana","docAbstract":"Lake Koocanusa, a reservoir, receives mine wastes from metallurgical coal mines in the Elk River Valley of British Columbia, Canada. Selenium and other elements discharged by the mines into the waters of the United States can pose unknown risks to aquatic life. The U.S. Geological Survey Wyoming-Montana Water Science Center can collaborate with Montana Fish, Wildlife and Parks and other State and Federal agencies to design studies and to collect fish tissues to help fill this knowledge gap. This report describes the processes, techniques, and methods used to collect and analyze fish tissue collected from Lake Koocanusa; and procedures used to review and manage data, including quality assurance and quality control procedures used by the U.S. Geological Survey Wyoming-Montana Water Science Center and supporting analytical laboratories. These fish tissue collections began in 2021.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251034","usgsCitation":"Schmidt, T.S., Bussell, A.M., Moloney, M.A., Dunnigan, J.L., Selch, T.M., Brandt, J.E., Stricker, C.A., Stewart, A.R., Kocen, V.A., Cleveland, D., Blazer, V.S., Janssen, S.E., Ogorek, J.M., Dunn, M., McBride, T.L., Adams, K.B., Colman, B.P., Young, M., and Christensen, J., 2025, Preparation and analysis methods for fish tissue collected from Lake Koocanusa, Montana: U.S. Geological Survey Open-File Report 2025–1034, 16 p., https://doi.org/10.3133/ofr20251034.","productDescription":"vii, 16 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153220","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":491708,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251034/full"},{"id":491707,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1034/images/"},{"id":491706,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1034/ofr20251034.XML"},{"id":491705,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1034/ofr20251034.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025–1034"},{"id":491704,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1034/coverthb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Lake Koocanusa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.29104936748958,\n 50.23265651730222\n ],\n [\n -117.29104936748958,\n 48.55695721902586\n ],\n [\n -114.96658880253837,\n 48.55695721902586\n ],\n [\n -114.96658880253837,\n 50.23265651730222\n ],\n [\n -117.29104936748958,\n 50.23265651730222\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The purpose of this Wake Atoll Vessel Movement Biosecurity Program Efficacy document is to provide the United States Air Force (USAF) with an unbiased review of the current (2015; hereafter referred to as the 2015 Biosecurity Plan) biosecurity plan for the military base Wake Island Airfield (WIA) on Wake Atoll (hereafter Wake). Periodic reviews are an integral step for evaluating plan efficacy and updating plans with new information for improving plan effectiveness. The U.S. Geological Survey (USGS) acted as an external expert to provide the first unbiased assessment of the program and observe how it was being implemented. The USAF 2015 Wake Island Biosecurity Management Plan goes beyond sea vessel and container biosecurity; however, those aspects were not included in this evaluation.
We used several methods for a quality assurance evaluation of the 2015 sea vessel and shipping container biosecurity program specified in the Biosecurity Plan. Our evaluation included real-time observations in Hawai`i and at Wake. We surveyed cargo staging areas and empty shipping containers before supply shipment and the containers, barge, and marina at Wake after shipment. We used various detection tools and techniques (for example, visual encounter surveys, glue boards, chew cards, camera traps, and so on). We carried out an insect mortality experiment trial using one of the required shipping container biosecurity tools (dichlorvos impregnated pest strips). We also included a table-top review of documentation (largely the 2015 Biosecurity Plan) with respect to our observations to provide an assessment of how well the Biosecurity Plan protocols were carried out and how well they serve their intended purpose.
We observed biosecurity concerns in each focal area and stage of cargo handling (before and after barge movement) across all surveys of containers, flat racks, break bulk, warehouses, and dock areas. Using visual inspections, we recorded biosecurity concerns for every empty container we inspected before it was to be stuffed with cargo. Most containers had structural integrity issues (such as holes and damaged floorboards) and sanitation concerns, including live animals and plant matter or seeds. About one third of the containers had mold and a few had wet floorboards or standing water. We detected live animals on the break bulk, and flat racks were in poor condition. Next, we inspected cargo staging areas and noted extensive permeability of the building where cargo was staged for the 2018 resupply shipment and the building that had typically been used. We included the adjacent dock area used for staging break bulk, shipping containers and mooring the barge. We detected more than 5,000 individuals of 105 species. We also detected seeds in each location and scattered vegetation in the dock area, including growing in from the area outside separated by a chain link fence.
During surveys at Wake, we observed that 100 percent of the shipping containers, including all containers sent with required biosecurity tools, had live animals. The barge had only one unsecured snap trap for intercepting rodents aboard, we saw areas with fairly deep layers of dirt (or soil; we did not examine it to determine its properties), and there was plant matter with seed heads on the barge gangway that could easily be transported onto the barge. There was also only one snap trap station that was improperly placed on the dock. We also observed piled wood and vegetation nearby that could provide refuge to potential stowaway animals escaping.
Combined, surveys of the containers, staging areas, barges, and receiving area in Hawai`i and at Wake resulted in detection of more than 9,000 individuals of 131 animal species; nearly 4,000 individuals of 62 species were detected in surveys of containers once they had arrived at Wake. None of the species identified are known to be native to Wake. Our preliminary risk analysis of all species detected included eight species that we scored as high risk of potentially negative effects to biodiversity, infrastructure, or human health should they arrive at Wake and become established. Six of these species were only recorded using tools not clearly required by the Biosecurity Plan or being used to implement the plan.
We observed that the required biosecurity tools intended to intercept animals in the cargo staging area did not target the suite nor number of species present. Our analysis also indicated the required biosecurity tools intended to intercept animals in shipping containers were inadequate to handle the volume of organisms that were in the containers. The insect mortality trial experiment showed the pest strips were highly effective for only one of the three species tested, leaving uncertainty about how effective they are across the suite of potential species stowing away in cargo and containers.
Base Operating Support (BOS) did not carry out all Biosecurity Plan actions, but we also noted the document uses terminology such as “recommendation” as opposed to “requirement” which may lead contractors to consider those actions as optional. However, USAF provided evidence of BOS training and follow up; this included detailed identification of specific requirements for some of the biosecurity actions that we did not observe being carried out.
The 2015 Biosecurity Plan contains critical and useful components that seem to be well carried out. However, we also saw discrepancies, weaknesses, or both across methods and protocols currently used for Wake Atoll biosecurity. We observed shortcomings at each stage of our survey as well as in the plan as written, and we suggest general modifications to the Biosecurity Plan for consideration to potentially strengthen biosecurity overall.
Prevention is the most efficient and cost-effective biosecurity measure. Based on our findings, we see possible solutions to improve existing preventative biosecurity efforts and reduce potential incursion at Wake. These potential solutions include creating and implementing the following:
Management of invasive species enhances capability to protect human health and the environment as well as to advance mission accomplishment. Biosecurity plans are an integral component for addressing invasive species. Periodic evaluation of the efficacy of these plans is useful for identifying elements that are working well and for illuminating those that can be improved. Evaluations encourage consideration of new tools and adaptation of processes to achieve better outcomes and accommodate potential future threats more efficiently and more cost effectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251026","collaboration":"Prepared in cooperation with the U.S. Air Force","programNote":"Ecosystems Mission Area—Biological Threats and Invasive Species Research Program","usgsCitation":"Hathaway, S.A., Molden, J.C., Peck, R., Rex, K.R., Brehme, C.S., Black, T., and Fisher, R.N., 2025, Wake Atoll vessel movement biosecurity program efficacy: U.S. Geological Survey Open-File Report 2025–1026, 130 p., https://doi.org/10.3133/ofr20251026","productDescription":"x, 130 p.","onlineOnly":"Y","ipdsId":"IP-155305","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":491323,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1026/ofr20251026.pdf","text":"Report","size":"22.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1026"},{"id":491324,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251026/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1026"},{"id":491326,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1026/ofr20251026.XML"},{"id":491325,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1026/images"},{"id":491322,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1026/coverthb.jpg"}],"otherGeospatial":"Wake Atoll","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 166.58609930546095,\n 19.335566334904826\n ],\n [\n 166.58609930546095,\n 19.259871066135005\n ],\n [\n 166.6712110656557,\n 19.259871066135005\n ],\n [\n 166.6712110656557,\n 19.335566334904826\n ],\n [\n 166.58609930546095,\n 19.335566334904826\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The Earth Resources Observation and Science Cal/Val Center of Excellence Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 8 and 9 for quarter 4 (October–December) of 2024. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251036","usgsCitation":"Haque, M.O., Hasan, M.N., Shrestha, A., Rengarajan, R., Lubke, M., Steinwand, D., Bresnahan, P., Shaw, J.L., Ruslander, K., Micijevic, E., Choate, M.J., Anderson, C., Clauson, J., Thome, K., Kaita, E., Levy, R., Miller, J., Ding, L., and Teixeira Pinto, C., 2025, ECCOE Landsat quarterly Calibration and Validation report—Quarter 4, 2024 (ver. 1.1, June 2026): U.S. Geological Survey Open-File Report 2025–1036, 56 p., https://doi.org/10.3133/ofr20251036.","productDescription":"Report: viii, 56 p.; Dataset","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-175052","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":505284,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2025/1036/versionHist.txt","text":"Version History","linkFileType":{"id":2,"text":"txt"}},{"id":505283,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251036/full","description":"OFR 2026-1036 HTML"},{"id":505281,"rank":5,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1036/ofr20251036.pdf","text":"Report","size":"6.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1036"},{"id":505273,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1036/coverthb2.jpg"},{"id":491624,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov/","text":"USGS database","linkHelpText":"- EarthExplorer"},{"id":491619,"rank":1,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1036/ofr20251036.XML"},{"id":491620,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1036/images/"}],"edition":"Version 1.0: July 2025; Version 1.1 June 2026","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Tungsten appears on the 2018 and 2022 U.S. Geological Survey critical mineral lists in part because of a very high global production concentration in China, which produces almost 83 percent of the world’s mined tungsten. Using known parameters and values from other tungsten mining operations, we created hypothetical scenarios in which three tungsten deposits in Uzbekistan are considered for development. Our results show that all three deposits are likely to be economically viable to develop under 2024 market conditions. If the three studied tungsten deposits were put into production, Uzbekistan could become the third-leading tungsten-producing country in the world and increase world output of tungsten by 2.7 percent. Putting these tungsten deposits in Uzbekistan into production could slightly reduce the tungsten global market concentration, therefore reducing the supply disruption potential for tungsten.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251032","usgsCitation":"Safirova, E., Golovko, Y., and Dulabova, N., 2025, Analysis of the potential effects of Uzbekistan’s mineral endowment on the critical mineral supply of tungsten: U.S. Geological Survey Open-File Report 1032, 14 p., https://doi.org/10.3133/ofr20251032.","productDescription":"v, 14 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-169634","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":491157,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1032/images/"},{"id":491156,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1032/ofr20251032.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1032 XML"},{"id":491155,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251032/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1032 HTML"},{"id":491154,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1032/ofr20251032.pdf","text":"Report","size":"840 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1032 PDF"},{"id":491153,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1032/coverthb.jpg"}],"country":"Uzbekistan","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[66.51861,37.36278],[66.54615,37.97468],[65.216,38.4027],[64.17022,38.89241],[63.51801,39.36326],[62.37426,40.05389],[61.88271,41.08486],[61.54718,41.26637],[60.46595,41.22033],[60.08334,41.42515],[59.97642,42.22308],[58.62901,42.75155],[57.78653,42.17055],[56.93222,41.82603],[57.09639,41.32231],[55.96819,41.30864],[55.92892,44.99586],[58.50313,45.5868],[58.68999,45.50001],[60.23997,44.78404],[61.05832,44.40582],[62.0133,43.50448],[63.18579,43.65007],[64.90082,43.72808],[66.09801,42.99766],[66.02339,41.99465],[66.51065,41.98764],[66.71405,41.16844],[67.98586,41.13599],[68.2599,40.66232],[68.63248,40.66868],[69.07003,41.38424],[70.38896,42.08131],[70.96231,42.26615],[71.25925,42.16771],[70.42002,41.52],[71.15786,41.14359],[71.87011,41.3929],[73.05542,40.86603],[71.77488,40.14584],[71.0142,40.24437],[70.60141,40.21853],[70.45816,40.49649],[70.66662,40.96021],[69.32949,40.72782],[69.01163,40.08616],[68.53642,39.53345],[67.70143,39.58048],[67.44222,39.14014],[68.17603,38.90155],[68.39203,38.15703],[67.83,37.14499],[67.07578,37.35614],[66.51861,37.36278]]]},\"properties\":{\"name\":\"Uzbekistan\"}}]}","contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
","tableOfContents":"Tungsten is a critical mineral used in many everyday products, from light bulbs to electronics and medical equipment. In 2024, China was the leading tungsten mining country, producing about 83 percent of all tungsten in the world. Uzbekistan has known tungsten deposits, so we investigated potential effects on the world supply of tungsten if three of those tungsten deposits were developed and produced tungsten and other minerals. Using market conditions from 2024 in our models, we determined that these tungsten deposits could be mined profitably. Our results suggest that if these deposits are developed, Uzbekistan could become the third-leading tungsten producer in the world, increasing global tungsten supply by 2.7 percent. Development of these tungsten deposits could help prevent possible shortages of tungsten.
","publicationDate":"2025-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Safirova, Elena 0000-0001-7121-3917 esafirova@usgs.gov","orcid":"https://orcid.org/0000-0001-7121-3917","contributorId":182020,"corporation":false,"usgs":true,"family":"Safirova","given":"Elena","email":"esafirova@usgs.gov","affiliations":[],"preferred":true,"id":941085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golovko, Yelena","contributorId":357290,"corporation":false,"usgs":false,"family":"Golovko","given":"Yelena","affiliations":[{"id":85400,"text":"Ministry of Mining Industry and Geology of the Republic of Uzbekistan","active":true,"usgs":false}],"preferred":false,"id":941086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dulabova, Nafisa","contributorId":351211,"corporation":false,"usgs":false,"family":"Dulabova","given":"Nafisa","affiliations":[{"id":83936,"text":"Ministry of Mining, Industry, and Geology of the Rebublic of Uzbekistan","active":true,"usgs":false}],"preferred":false,"id":941087,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70268444,"text":"ofr20251027 - 2025 - Grand Canyon River Alert System—Implementing an emergency alert system for wilderness recreation","interactions":[],"lastModifiedDate":"2025-06-26T15:27:39.55361","indexId":"ofr20251027","displayToPublicDate":"2025-06-25T09:50:06","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1027","displayTitle":"Grand Canyon River Alert System—Implementing an Emergency Alert System for Wilderness Recreation","title":"Grand Canyon River Alert System—Implementing an emergency alert system for wilderness recreation","docAbstract":"The Grand Canyon River Alert System (GCRAS) provides government-issued emergency alerts to wilderness recreationalists in the Grand Canyon, who are often outside the bounds of cellular signal reception. GCRAS is a collaboration between the U.S. Geological Survey (Grand Canyon Monitoring and Research Center), National Weather Service, Coconino County Emergency Management, and National Park Service. Technological advances in satellite communications have improved satellite signal availability in remote areas and increased the reliability of satellite communications using personal devices such as commercially available satellite messaging devices. These advancements have presented an opportunity to create a novel emergency alert system designed primarily for backcountry visitors to provide improved communications for periods of increased risk and potentially dangerous situations in the backcountry. GCRAS is designed specifically for the distinctive needs of satellite messaging devices and features reduced character count messages, short-code signup capability, and the ability to unsubscribe at any time. After a positive test of the system in March 2024, the system went live to the public and has been used more than two dozen times in 2024 to inform boaters and hikers of hazards (such as debris flows and flash floods) in the Grand Canyon. Satellite signal availability and device response time varies based on location and service provider, but initial testing showed messages arriving within 2–10 minutes. Although GCRAS was developed specifically for the Grand Canyon, the GCRAS framework could be applied to other wilderness areas. It can be used by emergency management authorities, land-management agencies, search and rescue units, and those concerned with public safety to help increase communication with people visiting or living in areas that are outside the signal of more traditional emergency-notification methods, such as cellular, wireless emergency alerts, and sirens.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251027","usgsCitation":"Thomas, J.E., Gushue, T.M., Byerley, E., and Grams, P., 2025, Grand Canyon River Alert System—Implementing an emergency alert system for wilderness recreation: U.S. Geological Survey Open-File Report 2025–1027, 9 p., https://doi.org/10.3133/ofr20251027.","productDescription":"vi, 9 p.","onlineOnly":"Y","ipdsId":"IP-166852","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":491300,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1027/images"},{"id":491297,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1027/coverthb.jpg"},{"id":491301,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1027/ofr20251027.XML"},{"id":491299,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251027/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1027"},{"id":491298,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1027/ofr20251027.pdf","text":"Report","size":"24.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1027"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.05083740896649,\n 36.823773492081415\n ],\n [\n -114.05083740896649,\n 35.58732870070932\n ],\n [\n -111.53233878502289,\n 35.58732870070932\n ],\n [\n -111.53233878502289,\n 36.823773492081415\n ],\n [\n -114.05083740896649,\n 36.823773492081415\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Southwest Biological Science Center
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The report focuses on the screening of previously published concentration data associated with 12 elements of concern (aluminum, arsenic, cadmium, chromium, copper, iron, mercury, manganese, lead, selenium, uranium, and zinc) measured in stream surface waters of three hydrologic basins (Delaware River Basin, Illinois River Basin, and the Upper Colorado River Basin). The purpose of this analysis is to determine what subsets of the original dataset (containing more than 1,500,000 observations) may be most suitable for each of two types of modeling efforts. The first type of modeling envisions a machine learning approach to determine which geospatial attributes are most significant in describing the spatial distribution of elemental concentrations within a basin. The second type of modeling envisions a stepwise regression approach to develop multivariable models that can be used to determine high resolution time-series estimates of elemental concentrations or loads at discrete U.S. Geological Survey real-time stream surface water sites. These site-specific temporal models are based on continuous measurements of available discharge and (or) in situ sensor data (temperature, pH, turbidity, dissolved oxygen, specific conductance, and (or) fluorescent dissolved organic matter) as the explanatory variables. The data screening for both model types considered historical trends in analytical methods and detection quantitation limits, the extent of censored data, data density, and environmental relevance with respect to three U.S. Environmental Protection Agency water quality thresholds (drinking water guidelines, human health criteria, and aquatic life criteria). The result of this analysis was the production of a final list of potential models deemed suitable for further development based upon the data exclusion (or inclusion) scheme developed herein for each model type. In both cases, the final models included mostly the three crustal elements (iron, manganese, and aluminum) that are found at comparatively high concentrations in surface water, whereas most of the more pernicious elements were excluded from the final model lists owing to various data limitations. The one exception to this was arsenic, for which the existing data were sufficient at three U.S. Geological Survey real-time sites for potential further development of time-series models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251033","programNote":"Water Quality Program","usgsCitation":"Marvin-DiPasquale, M.C., McCleskey, R.B., Sullivan, S.L., Root, J.C., Seawolf, S.M., Ransom, K.M., Wherry, S.A., Kakouros, E., and Baesman, S., 2025, Select elements of concern in surface water of three hydrologic basins (Delaware River, Illinois River, and Upper Colorado River)—Data screening for the development of spatial and temporal models: U.S. Geological Survey Open-File Report 2025–1033, 25 p., https://doi.org/10.3133/ofr20251033.","productDescription":"Report: v, 25 p.; 2 Data Releases","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-151463","costCenters":[{"id":37277,"text":"WMA - Earth System Processes 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Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Ave, Suite 1950
Portland, OR 97204
The range of the endangered black abalone (Haliotis cracherodii) is divided into the North Central California region, the Central California region, the Southern California Mainland region, the Channel Islands region, and the Baja California region by the National Marine Fisheries Service for management purposes. San Nicolas Island is one of eight subregions of the Channel Islands region. The black abalone recovery plan establishes five demographic criteria for the possible delisting or downlisting of the species. The U.S. Geological Survey monitors nine long-term intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. This report uses data collected between 2013 and 2022 and the delisting criteria to analyze and describe the density, recruitment, size structure, and population trends at the nine U.S. Geological Survey monitoring sites at San Nicolas Island.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251015","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2025, Black abalone (Haliotis cracherodii) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22: U.S. Geological Survey Open-File Report 2025–1015, 10 p., https://doi.org/10.3133/ofr20251015.","productDescription":"vi, 10 p.","onlineOnly":"Y","ipdsId":"IP-174146","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490728,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20251014","text":"Open-File Report 2025-1014","description":"OFR 2025-1014","linkHelpText":"- Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report"},{"id":486255,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1015/ofr20251015.XML"},{"id":486254,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1015/images"},{"id":486253,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251015/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1015"},{"id":486252,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1015/ofr20251015.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1015"},{"id":486251,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1015/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base Ventura County, San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.41565036125932,\n 33.22855822061233\n ],\n [\n -119.4322978602211,\n 33.233849792002204\n ],\n [\n -119.46292925831023,\n 33.2600242059834\n ],\n [\n -119.53051810409356,\n 33.29036557133239\n ],\n [\n -119.58545485066676,\n 33.281459107969354\n ],\n [\n -119.57180390151814,\n 33.25000088849947\n ],\n [\n -119.54217135336674,\n 33.228836776039614\n ],\n [\n -119.47857790733391,\n 33.21379600415082\n ],\n [\n -119.45160895901617,\n 33.21379600415082\n ],\n [\n -119.41565036125932,\n 33.22855822061233\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
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3020 State University Drive East
Sacramento, California 95819
The U.S. Geological Survey monitors a suite of intertidal black abalone (Haliotis cracherodii) sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential effect of translocated southern sea otters (Enhydra lutris nereis) on the intertidal black abalone population at San Nicolas Island. The sites were monitored, typically annually or biennially, from 1981 to 1997. Monitoring resumed in 2001 and has been completed annually thereafter. Since 2018, the monitoring has been carried out by the U.S. Geological Survey Western Ecological Research Center. The study sites became particularly important from a management perspective after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992, and during the next few years, withering syndrome reduced the black abalone population on San Nicolas Island by more than 99 percent. The black abalone was subsequently listed as endangered under the Endangered Species Act in 2009.
The subject of this report is the 2022 survey of the sites and the status of the measured population of black abalone in comparison to long-term patterns (based on data collected since 1981) at San Nicolas Island. Between the years 2000 and 2022, the total monitored black abalone population on the island has grown from roughly 200 to more than 2,000, approximately a ten-fold increase following the disease-related decline. Since it was first consistently measured in 2005, the distance between adjacent black abalone has decreased substantially from approximately 50 centimeters to less than 15 centimeters, indicating that black abalone are sufficiently close together at several of the sites to reproduce successfully. The total black abalone count in 2022 was 2,156, which was 7.9 percent lower than the total count in 2020 but 6.6 percent higher than in 2021. There were increases and decreases among the sites and transects within each site in 2022, but six of the nine sites had higher counts than in the previous year. The 2022 count is one of the highest since 1993, second only to the 2020 count. In 2022, the annual recruitment rate, defined as the percentage of measured black abalone with a shell length of 3 centimeters or less, was the second highest recorded, only slightly less than in 2017.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251014","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2025, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report: U.S. Geological Survey Open-File Report 2025–1014, 34 p., https://doi.org/10.3133/ofr20251014.","productDescription":"viii, 34 p.","onlineOnly":"Y","ipdsId":"IP-159889","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490412,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1014/images"},{"id":491626,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20251015","text":"Open-File Report 2025-1015","description":"OFR 2025-1015","linkHelpText":"- Black abalone (Haliotis cracherodii) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22"},{"id":490413,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1014/ofr20251014.XML"},{"id":490410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1014/ofr20251014.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1014"},{"id":490411,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251014/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1014"},{"id":490409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1014/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base, Ventura County, San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.41565036125932,\n 33.22855822061233\n ],\n [\n -119.4322978602211,\n 33.233849792002204\n ],\n [\n -119.46292925831023,\n 33.2600242059834\n ],\n [\n -119.53051810409356,\n 33.29036557133239\n ],\n [\n -119.58545485066676,\n 33.281459107969354\n ],\n [\n -119.57180390151814,\n 33.25000088849947\n ],\n [\n -119.54217135336674,\n 33.228836776039614\n ],\n [\n -119.47857790733391,\n 33.21379600415082\n ],\n [\n -119.45160895901617,\n 33.21379600415082\n ],\n [\n -119.41565036125932,\n 33.22855822061233\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The purpose of this report is to provide the Marine Corps with an annual summary of the distribution, abundance, and breeding activity of the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus; flycatcher) at Marine Corps Base Camp Pendleton (MCBCP or “Base”). Surveys for the flycatcher were conducted on Base between May 8 and July 24, 2024. All of MCBCP’s historically occupied riparian habitat (core survey area) was surveyed for flycatchers in 2024. None of the non-core survey areas were surveyed in 2024.
Three transient Willow Flycatchers of unknown subspecies were observed on two of the five drainages surveyed in 2024, the Santa Margarita River and San Mateo Creek. No Willow Flycatchers were detected at Fallbrook, Las Flores, or Pilgrim Creeks. Transients in 2024 occurred in riparian scrub habitat, dominated by mule fat (Baccharis salicifolia). Exotic vegetation, primarily poison hemlock (Conium maculatum), was present in all flycatcher locations. None of the transient flycatchers were banded.
In 2024, the resident Southwestern Willow Flycatcher population on Base consisted of one unpaired female occupying one territory in the Air Station breeding area along the Santa Margarita River. No territorial males were observed in 2024. The resident flycatcher territory was located in mixed willow riparian habitat, dominated by arroyo or red willow (Salix lasiolepis or S. laevigata). The female flycatcher was originally banded as a nestling in 2020 at MCBCP, making her 4 years old in 2024.
The resident female flycatcher returned to the same breeding area and territory she occupied in 2023. Nesting was initiated in late May and continued into early August. Three nesting attempts were documented; all were unsuccessful as a result of depredation and presumed infertile eggs. No instances of Brown-headed Cowbird (Molothrus ater) parasitism were observed. The flycatcher nests were placed in two native plants, sandbar willow (S. exigua) and stinging nettle (Urtica dioica).
Two measures were initiated in recent years to attract and retain breeding flycatchers on MCBCP: a conspecific attraction playback study (initiated in 2018) and an artificial seep study (initiated in 2019); both were repeated annually through 2024. The one resident flycatcher (female) detected in 2024 occupied a territory near an automated playback unit, and nested 5 meters from an artificial seep output.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251023","collaboration":"Prepared in cooperation with Assistant Chief of Staff, Environmental Security, Marine Corps Base Camp Pendleton","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2025, Distribution, abundance, and breeding activities of the Southwestern Willow Flycatcher at Marine Corps Base Camp Pendleton, California—2024 annual report: U.S. Geological Survey Open-File\nReport 2025–1023, 26 p., https://doi.org/10.3133/ofr20251023.","productDescription":"vi, 26 p.","onlineOnly":"Y","ipdsId":"IP-175198","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490243,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1023/ofr20251023.XML"},{"id":490242,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1023/images"},{"id":490241,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251023/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1023"},{"id":490240,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1023/ofr20251023.pdf","text":"Report","size":"8.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1023"},{"id":490239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1023/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Marine Corps Base Camp Pendleton","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.58338003323524,\n 33.45345643512407\n ],\n [\n -117.60222726717006,\n 33.386233650795276\n ],\n [\n -117.48331835489097,\n 33.30585564997955\n ],\n [\n -117.39614054579035,\n 33.19810587550057\n ],\n [\n -117.26283920032485,\n 33.29512730850755\n ],\n [\n -117.24244991997723,\n 33.33051403790782\n ],\n [\n -117.23302630300994,\n 33.410559433022755\n ],\n [\n -117.4911309974352,\n 33.508615342567545\n ],\n [\n -117.58338003323524,\n 33.45345643512407\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This report reflects our knowledge regarding the widespread landslide activity associated with Hurricane Helene observed during the U.S. Geological Survey’s (USGS) mission assignment to North Carolina in October 2024. The material in this report was originally prepared for the Federal Emergency Management Agency under mission assignment DR-4827-NC. The data and commentary in this report are reflective of a report provided to the Federal Emergency Management Agency (FEMA) on October 18, 2024, as well as information provided in briefings at the Buncombe County Emergency Operations Center. The report has been modified for public dissemination.
This assessment was based on systematic visual examination and mapping of landslide locations from aerial and satellite imagery, visual and photographic observations from low-level helicopter overflights and conversations with local landslide experts from the North Carolina Geological Survey and Appalachian Landslide Consultants PLLC, and more than 50 years of combined landslide hazard professional experience of the mission-assigned field team. No systematic field investigations were done by the USGS.
While responding to the event, the USGS did not identify any landslides that posed an immediate major threat to recovery personnel in parts of nine counties in North Carolina (Avery, Buncombe, Henderson, McDowell, Mitchell, Polk, Rutherford, Watauga, and Yancey); however, threats from renewed landslide activity may remain heightened in localized areas for months or even years. Known areas of the most abundant landslide occurrence include Bat Cave, Lake Lure, Chimney Rock, Swannanoa, Black Mountain, Fairview, steep areas in Asheville, and the Blue Ridge Parkway. The USGS shared detailed locations of known landslides with the Emergency Operations Centers. The thousands of landslide scars on hillsides and landslide deposits on flatter ground may present some threat to recovery activities. Soil and rocks will continue to erode from newly exposed landslide scars and may pose a threat to people and infrastructure who are immediately nearby. In general, the steeper and taller the landslide scar, the greater the potential threat. This threat is heightened during periods of rainfall and increases with the duration and intensity of rainstorms. Very heavy rainfall, or repeated rainfall events during short periods, could also initiate new landslides on steep slopes. Excavation of landslide deposits, particularly excavation of those deposits directly adjacent to steep slopes, may also pose a threat to nearby people and equipment.
An interagency collaborative mapping effort led by the USGS that informed this assessment identified 1,155 landslide locations by the October 2024 briefings, but that number increased to 2,217 in a final reviewed version of the locations published in January 2025. Locations were mapped from satellite imagery, fixed-wing and helicopter surveys, media and social media, and field reports in the 3 weeks following the passage of the remnants of Hurricane Helene. USGS products outlined in this report are publicly available and include geotagged photographs from aerial reconnaissance, hazard models, an interactive view of mapped landslide locations, and landslide safety and education resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20251028","programNote":"Landslide Hazards Program","usgsCitation":"Allstadt, K.E., McBride, S.K., Godt, J.W., Slaughter, S.L., Baxstrom, K.W., Sobieszczyk, S., and Stull, A., 2025, Preliminary field report of landslide hazards following Hurricane Helene: U.S. Geological Survey Open-File Report 2025–1028, 15 p., https://doi.org/10.3133/ofr20251028.","productDescription":"Report vi, 15 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-175853","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":494134,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118637.htm","linkFileType":{"id":5,"text":"html"}},{"id":490259,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251028/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1028"},{"id":488392,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1028/ofr20251028.xml"},{"id":488391,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1028/images"},{"id":486657,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1C5W3PQ","text":"USGS data release","description":"USGS data release for OFR 2025-1028","linkHelpText":"Oblique Aerial Photographs from October 13 and 17, 2024, of Landslides and Flooding Caused by Hurricane Helene (ver 1.1, March 2025)"},{"id":486656,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1028/ofr20251028.pdf","text":"Report","size":"7.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1028"},{"id":486655,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1028/coverthb.jpg"}],"country":"United States","state":"North Carolina, South Carolina, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81,\n 36.667\n ],\n [\n -83.25,\n 36.667\n ],\n [\n -83.25,\n 35\n ],\n [\n -81,\n 35\n ],\n [\n -81,\n 36.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
A geometric accuracy assessment of lidar data collected in eastern Iowa in 2019 as part of the 3D Elevation Program (3DEP) was conducted. The assessment involved evaluating interswath accuracy, same surface precision, point density, absolute accuracy, and consistency with adjacent 3DEP datasets. The results demonstrate that the data meet or exceed the quality level 2 specifications outlined in the Lidar Base Specifications (LBS). Interswath and same surface precision values were within specified tolerances, with a root mean square difference of 0.03 meters for interswath vertical accuracy and 0.03 meters for same surface precision. Vertical accuracy in flat areas was excellent, with root mean square error values consistently below 0.10 meters. Horizontal accuracy assessments also showed good agreement between lidar and reference data. Point density generally exceeded the minimum requirement of 2 points per square meter, and the inter-project consistency assessment indicated good agreement between the Iowa lidar data and adjacent datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251017","usgsCitation":"Sampath, A., Irwin, J., and Kropuenske, T., 2025, Validation of the geometric accuracy of airborne light detection and ranging data for eastern Iowa, 2019: U.S. Geological Survey Open-File Report 2025–1017, 16 p., https://doi.org/10.3133/ofr20251017.","productDescription":"Report: v, 16 p.; Data Release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-167726","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":487536,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1017/ofr20251017.XML","text":"XML","size":"90.4 KB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1017 XML"},{"id":487523,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1017/images"},{"id":487518,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1017/ofr20251017.pdf","text":"Report","size":"3.15","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1017"},{"id":487578,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DI0G64","text":"USGS data release","linkHelpText":"2019 Eastern Iowa topographic lidar validation – USGS field survey data"},{"id":487546,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251017/full"},{"id":487511,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1017/coverthb.jpg"},{"id":494125,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118628.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.29294140522802,\n 43.01135367569728\n ],\n [\n -93.29294140522802,\n 40.35261453917326\n ],\n [\n -89.92207321354842,\n 40.35261453917326\n ],\n [\n -89.92207321354842,\n 43.01135367569728\n ],\n [\n -93.29294140522802,\n 43.01135367569728\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
No abstract available.
","language":"English","publisher":"Massachusetts Geological Survey","doi":"10.7275/ds6v-gy64","usgsCitation":"Stone, J.R., DiGiacomo-Cohen, M.L., Mabee, S.B., Brigham-Grette, J., Stone, B.D., Graham, B.L., and Yellen, B., 2025, Ice-lobe retreat, glacial lake levels and the North American varve chronology in the Deerfield basin of western Massachusetts: Open-File Report 25-01, 52 p., https://doi.org/10.7275/ds6v-gy64.","productDescription":"52 p.","ipdsId":"IP-179170","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":498338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Deerfield basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.50160195053968,\n 42.62009992849204\n ],\n [\n -72.76339223621905,\n 42.62009992849204\n ],\n [\n -72.76339223621905,\n 42.24421898621074\n ],\n [\n -72.50160195053968,\n 42.24421898621074\n ],\n [\n -72.50160195053968,\n 42.62009992849204\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Stone, Janet R. 0000-0003-0095-8238 jrstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0095-8238","contributorId":299644,"corporation":false,"usgs":true,"family":"Stone","given":"Janet","email":"jrstone@usgs.gov","middleInitial":"R.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":953323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiGiacomo-Cohen, Mary L. 0000-0003-2384-8912 mdicohen@usgs.gov","orcid":"https://orcid.org/0000-0003-2384-8912","contributorId":2527,"corporation":false,"usgs":true,"family":"DiGiacomo-Cohen","given":"Mary","email":"mdicohen@usgs.gov","middleInitial":"L.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":953324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mabee, Steven B.","contributorId":364850,"corporation":false,"usgs":false,"family":"Mabee","given":"Steven","middleInitial":"B.","affiliations":[{"id":35248,"text":"Massachusetts Geological Survey","active":true,"usgs":false}],"preferred":false,"id":953325,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brigham-Grette, Julie","contributorId":364853,"corporation":false,"usgs":false,"family":"Brigham-Grette","given":"Julie","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":953326,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stone, Byron D. 0000-0001-6092-0798 bdstone@usgs.gov","orcid":"https://orcid.org/0000-0001-6092-0798","contributorId":1702,"corporation":false,"usgs":true,"family":"Stone","given":"Byron","email":"bdstone@usgs.gov","middleInitial":"D.","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":953327,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graham, Brandon L. 0000-0002-7197-0413","orcid":"https://orcid.org/0000-0002-7197-0413","contributorId":340458,"corporation":false,"usgs":true,"family":"Graham","given":"Brandon","middleInitial":"L.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":953328,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yellen, Brian","contributorId":198491,"corporation":false,"usgs":false,"family":"Yellen","given":"Brian","email":"","affiliations":[{"id":33278,"text":"Department of Geosciences, University of Massachusetts, Amherst, MA","active":true,"usgs":false}],"preferred":false,"id":953329,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267734,"text":"ofr20251029 - 2025 - Restoration of Gavia immer (common loon) in Minnesota—2024 annual report","interactions":[],"lastModifiedDate":"2026-04-24T19:28:35.624822","indexId":"ofr20251029","displayToPublicDate":"2025-05-29T12:45:42","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1029","displayTitle":"Restoration of Gavia immer (Common Loon) in Minnesota—2024 Annual Report","title":"Restoration of Gavia immer (common loon) in Minnesota—2024 annual report","docAbstract":"In cooperation with the Minnesota Department of Natural Resources, the U.S. Geological Survey monitored 98 common loon (Gavia immer) focal territories and an additional 37 nonfocal territories in 2024 across 53 study lakes in Minnesota. Focal territories were those territories from which study inferences will be made, whereas nonfocal territories were observed to monitor common loon dynamics in territories adjacent to focal territories. In collaboration with lake associations and private citizens, we deployed 44 artificial nesting platforms within 44 treatment territories, and the remaining 54 focal territories were controls. We completed territorial surveys from April 29 to August 9, 2024, to evaluate occupancy, nest success, and chick survival. We attempted to visit each territory once a week. At least one nest attempt was observed in 41 of 54 control territories. Precisely one nest attempt was observed in 30 control territories, two nest attempts (first attempts failed) were observed in 9 control territories, and three nest attempts (first and second attempts failed) were observed in 2 control territories. At least one nest attempt was observed in 33 of 44 treatment territories. Precisely one nest attempt was observed in 25 treatment territories, two nest attempts (first attempts failed) were observed in 7 treatment territories, and three nest attempts (first and second attempts failed) were observed in 1 treatment territory. In treatment territories, 8 nests were on an artificial nesting platform; the remaining nest locations were natural. Chicks or other evidence of hatching were observed in 26 of 54 (48.1 percent) control territories and 21 of 44 (47.7 percent) treatment territories, with 7 of those successful treatment nests on an artificial nesting platform. This report includes no formal analysis, but we plan to analyze data after collection of all field data in subsequent years.
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\"}}]}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
Director, National Civil Applications Center
National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 562
Reston, VA 20192
Email: cac@usgs.gov
","tableOfContents":"The U.S. Geological Survey and the U.S. Fish and Wildlife Service have developed a three-tiered strategy for monitoring eelgrass (Zostera marina) beds at Izembek Lagoon, Alaska, that targets different spatial and temporal scales. The broadest-scale monitoring (tier-1) uses satellite imagery about every 5 years to delineate the spatial extent of eelgrass beds throughout the lagoon. This report describes the most recent (mid-2020s) tier-1 eelgrass monitoring at Izembek Lagoon. The monitoring effort began by canvasing all satellite imagery collected during summer, under clear daytime skies and at low-tide, since the last tier-1 effort in 2006. Two eelgrass maps of Izembek Lagoon were generated by first creating maps of spectrally unique classes from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing those spectral classes with information about eelgrass conditions based on field data. Specifically, maps depicting various eelgrass metrics, such as percentage of cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons of the 2016 and 2020 Sentinel-2 maps showing eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined during 2006–20 were most prevalent in the central part of Izembek Lagoon. More recently, during 2016-20, areas of possible biomass decline were more prevalent in the southern part of the lagoon. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data allows conditions to be compared over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251007","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","programNote":"Land Management Research Program","usgsCitation":"Douglas, D.C., Fleming, M.D., Patil, V.P., and Ward, D.H., 2025, Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery: U.S. Geological Survey Open-File Report 2025–1007, 30 p., https://doi.org/10.3133/ofr20251007. [Supersedes preprint https://doi.org/10.1101/2024.08.07.607047.]","productDescription":"Report: vii, 30 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-169599","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":485960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1007/coverthb2.jpg"},{"id":485963,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1HLTAHD","text":"USGS data release","description":"USGS data release","linkHelpText":"Eelgrass (Zostera marina) maps from 2016 and 2020, at Izembek Lagoon, Alaska"},{"id":485961,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1007/ofr20251007.pdf","text":"Report","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1007"},{"id":485962,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251007/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1007"},{"id":485964,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1007/images"},{"id":485965,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1007/ofr20251007.XML"}],"country":"United States","state":"Alaska","otherGeospatial":"Izembek Lagoon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -163.098854980302,\n 55.171004418891414\n ],\n [\n -162.87580882559715,\n 55.150219377165826\n ],\n [\n -162.79513255687405,\n 55.2819754305454\n ],\n [\n -162.63219813180595,\n 55.3494888427272\n ],\n [\n -162.52937543637472,\n 55.342292888511395\n ],\n [\n -162.47875503247008,\n 55.40162041992025\n ],\n [\n -162.50248334680037,\n 55.47879257840398\n ],\n [\n -162.74767592913727,\n 55.39443394016618\n ],\n [\n -162.92959300566955,\n 55.31259575418295\n ],\n [\n -163.098854980302,\n 55.171004418891414\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The Trinity River is managed in two sections: (1) from the upper 64-kilometer “restoration reach” downstream from Lewiston Dam to the confluence with the North Fork Trinity River, and (2) the 120-kilometer lower Trinity River downstream from the restoration reach. The Stream Salmonid Simulator (S3) has been previously applied to these reaches and the Klamath River. To estimate fish growth, past S3 calibration efforts in the Trinity and Klamath Rivers used maximum likelihood methods that considered only the abundance of juvenile Chinook salmon (Oncorhynchus tshawytscha) passing a fish trap to estimate survival and movement parameters, but not fish consumption. Previous calibrations did not estimate the average proportion of maximum consumption (Cy) when estimating survival (Sy) and movement (M0y) parameters across years (y) of data, but because no other information was available in the literature a fixed value of Cy=0.66 was assumed. Therefore, the goal of this report is to present an alternative approach that calibrates the S3 model to multivariate data (that is, abundance and size), enabling the estimation of the average proportion of maximum consumption, in conjunction with survival and movement parameters for a particular migration year. We fit the S3 model to individual years of weekly trap abundance estimates and mean fish sizes (fork length) at the Pear Tree Gulch (hereafter referred to as Pear Tree) fish trap representing the restoration reach. We used the Earth Mover’s Distance (EMD) as the objective value to be minimized in parameter optimization. This approach estimated survival, movement, and consumption parameters for each migration year. Because we had information on the abundance of natural and hatchery produced juvenile salmon at the fish traps, we estimated survival and movement for natural and hatchery fish.
S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile Chinook Salmon. A key theme of the model is that river discharge affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units.
The physical template of the restoration reach of the Trinity River was classified into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily discharge, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity time series were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg maturation and survival, and in turn, juvenile movement, growth, and survival.
We estimated movement, survival, and consumption parameters by calibrating the model to 12 years of weekly juvenile abundance estimates and fish sizes at the Pear Tree fish trap near the downstream end of the restoration reach. We estimated parameters for 12 years that included a wide range of female spawner abundances (1,414–11,494) and water year types (critically dry–extremely wet). We contrast the estimated parameters to the corresponding number of female spawners and the total annual volume of water discharged for the Trinity River (Trinity River Restoration Program; https://www.trrp.net/restoration/flows/summary/).
The calibration consisted of replicating historical conditions as closely as possible (for example, discharge; temperature; spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location from each brood year of adults and subsequent migration year of their juvenile progeny. Because density-dependent movement was favored in past evaluations, we estimated S3 parameters based on density-independent survival and density-dependent movement. Likewise, each year’s estimated survival parameter for natural (SNy) and hatchery (SHy) fish may be interpreted as the mean daily survival probability from emergence or hatchery release to the Pear Tree fish trap. Under density dependence, the estimated movement parameter for natural (M0Ny) and hatchery (M0Hy) fish represents the intercept of the Beverton-Holt model; the probability of remaining in a habitat at near-zero abundance.
We estimated Cy by using EMD and incorporating abundance and fish size into model calibration. Average daily proportions of maximum consumption, , across the years were generally high (=0.640; standard deviation (SD) SD=0.176), suggesting that fish were feeding at about two-thirds of expected maximum consumption rates. This average proportion of maximum consumption,is very similar to what has been assumed (=0.66) in previous Trinity and Klamath River S3 calibration and simulation efforts. In 2017, we estimated the lowest Cy, suggesting lower average consumption for juvenile salmon in high-discharge water years. When this high discharge year was excluded, there was no apparent trend in Cy with annual water volume. Estimates of survival showed little trend over the range in spawner abundances, but a trend towards higher natural and hatchery fish survival with higher annual volumes of water was apparent. Over the 12 years, the average survival of hatchery fish was =0.888 (SD=0.079) and the average survival natural fish was=0.969 (SD=0.01).
With respect to fish movement, we estimated higher M0Ny and M0Hy with higher annual volumes of water in the Trinity River. Higher MN0y or MH0y suggest greater probability of remaining in a habitat at low fish densities, with potential for density-dependent processes in movement to occur. The highest M0Ny = 0.676 was estimated during brood year 2012, and the overall average for natural fish was =0.276 (SD=0.188) and for hatchery fish was=0.467 (SD=0.235). Under the Beverton-Holt model, as M0Ny or M0Hy approach zero, there is less capacity for change in fish movement as fish density increases.
The S3 model was initialized with only the spatiotemporal distribution of spawners, so it performed well at capturing the essential outmigration features that are ultimately governed by rates of growth, movement, and mortality. We used a new optimization method that could accommodate multivariate data on abundance and fish size collected at the Pear Tree fish trap, enabling the calibration of S3 to estimate five parameters for 12 separate years of data. Incorporating weekly fish size data for each year in our parameter optimization process made the estimation of Cy possible and represents a step forward in the fitting of the S3 model to fish trap data for the purposes of parameter calibration and the estimation of growth parameters with respect to annual conditions. We identified lack of fit and adding important effects into the S3 model may improve the S3 estimation and simulation of water scenarios.
The Trinity River Restoration Program (TRRP) Science Advisory Board recommended that the TRRP focus on developing core elements of a decision support system (DSS; Buffington and others, 2014). Toward that end, the habitat and S3 models described in this report are both core elements of the DSS. The structure of S3 makes it a particularly useful fish production model for the DSS because population dynamics are sensitive to (1) water temperature, (2) daily discharge management, and (3) habitat quality and quantity. Each of these variables are key management parameters under consideration in the TRRP. As such, the S3 model may provide valuable insights into the potentially variable effects of different management decisions on the Trinity River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241070","collaboration":"Prepared in cooperation with U.S. Bureau of Reclamation","usgsCitation":"Plumb, J.M., Perry, R.W., and De Juilio, K., 2025, Calibration of the Stream Salmonid Simulator (S3) model to estimate annual survival, movement, and food consumption by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the restoration reach of the Trinity River, California, 2006–18: U.S. Geological Survey Open-File Report 2024–1070, 21 p., https://doi.org/10.3133/ofr20241070.","productDescription":"vii, 22 p.","onlineOnly":"Y","ipdsId":"IP-156648","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":485969,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1070/images"},{"id":485968,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241070/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1070"},{"id":485967,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1070/ofr20241070.pdf","text":"Report","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1070"},{"id":485966,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1070/coverthb.jpg"},{"id":485970,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1070/ofr20241070.XML"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.1406578585185,\n 40.785753827016435\n ],\n [\n -123.1406578585185,\n 40.69151845163566\n ],\n [\n -122.79146166523228,\n 40.69151845163566\n ],\n [\n -122.79146166523228,\n 40.785753827016435\n ],\n [\n -123.1406578585185,\n 40.785753827016435\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at the Mojave River Dam study area near Hesperia, California, in 2024. Four vireo surveys were completed between April 17 and July 2, 2024, and three flycatcher surveys were completed between May 23 and July 2, 2024.
We detected three territorial male vireos, all of which were paired. No juveniles were observed during surveys. Vireo territories were reported in two habitat types: riparian scrub and willow-cottonwood. Red or arroyo willow (Salix laevigata or lasiolepis) was the dominant plant species in most vireo territories. No territorial or transient flycatchers were observed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251025","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2025, Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2024 data summary: U.S. Geological Survey Open-File Report 2025–1025, 8 p., https://doi.org/10.3133/ofr20251025.","productDescription":"vi, 8 p.","onlineOnly":"Y","ipdsId":"IP-172384","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":485895,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1025/ofr20251025.XML"},{"id":485894,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1025/images"},{"id":485893,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251025/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1025"},{"id":485892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1025/ofr20251025.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1025"},{"id":485891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1025/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Mojave River Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.2768615020681,\n 34.370295162773715\n ],\n [\n -117.2768615020681,\n 34.31872800675019\n ],\n [\n -117.21059336313478,\n 34.31872800675019\n ],\n [\n -117.21059336313478,\n 34.370295162773715\n ],\n [\n -117.2768615020681,\n 34.370295162773715\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Gravity data require submeter elevation accuracy for data processing, and differential global navigation satellite system (dGNSS) equipment is commonly used to acquire three-dimensional positional data to achieve such accuracy. However, lidar (light detection and ranging) data are commonly used to develop digital elevation models (DEMs) of Earth’s surface. Therefore, using elevations from lidar-derived DEMs for gravity-data acquisition and reduction may improve field efficiency and reduce cost. This study examines the feasibility of using DEMs for gravity-data reduction by comparing dGNSS elevation data from 435 gravity stations in Michigan, Wyoming, and Colorado with their respective DEM elevations. The results show that the average difference between DEM and dGNSS elevations is 13 centimeters (cm) and that 93 percent of those differences are less than 50 cm, even in areas with steep terrain. Because an elevation discrepancy of 50 cm corresponds to an error of roughly 0.1 milligals (mGal) in the simple Bouguer gravity anomaly, the results suggest that lidar-derived DEMs are a viable source for acquiring the elevation data needed to process gravity data, thus improving both the cost and efficiency of data collection for regional surveys where an accuracy of less than 1.0 mGal is desired.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251019","programNote":"Mineral Resources Program","usgsCitation":"Murchek, J.T., Drenth, B.J., Reitman, J.J., Anderson, E.D., Magnin, B.P., and DeGraff, J.M., 2025, The feasibility of using lidar-derived digital elevation models for gravity data reduction (ver. 1.1, July 2025): U.S. Geological Survey Open-File Report 2025–1019, 33 p., https://doi.org/10.3133/ofr20251019.","productDescription":"vii, 33 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-163043","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":491565,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1019/coverthb2.jpg"},{"id":491633,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118572.htm"},{"id":491634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1019/ofr20251019.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1019 PDF"},{"id":491636,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1019/ofr20251019.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1019 XML"},{"id":491635,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251019/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1019 HTML"},{"id":491638,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2025/1019/versionHist.txt","size":"654 B","linkFileType":{"id":2,"text":"txt"}},{"id":491637,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1019/images/"}],"edition":"Version 1.0: May 12, 2025; Version 1.1: July 1, 2025","contact":"Director, Energy and Minerals Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192-0002
The Clear Lake Hitch (Lavinia exilicauda chi) is a minnow endemic to Clear Lake, Lake County, California. This species is listed as a threatened species under the California Endangered Species Act and has been petitioned for listing under the United States Endangered Species Act. In 2017, the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, initiated a Clear Lake Hitch monitoring program to generate information annually on relative abundance and size structure. The monitoring program was organized around a conceptual life cycle diagram, focused on life stages approximately ≥1 year of age, and incorporated a probabilistic study design involving approximately 10 days of short-duration (approximately 40 minutes) gillnet sampling undertaken during daytime. This report documents monitoring program activities from 2017 to 2023 and presents the results of an evaluation of the monitoring program. The evaluation was done after the 2023 sampling event, following 6 years of implementation, which is the approximate generation cycle of Clear Lake Hitch. The results of the evaluation indicated the following: (1) gillnets used in the monitoring program were effective at capturing Clear Lake Hitch aged 1 year or more; (2) the study design was effective at generating the information needed to characterize Clear Lake Hitch relative abundance and size structure, and meaningful operational efficiencies can be obtained by implementing simple changes; and (3) future sampling can be scaled to approximately 4–7 days of effort and maintain at least 80-percent confidence in detecting at least a 25-percent change in abundance, assuming past work productivity is maintained and future data are typical of previous data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251018","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","programNote":"Water Resources Mission Area","usgsCitation":"Feyrer, F., Young, M.J., Huntsman, B., Violette, V., Clause, J.K., Buxton, J., Palm, D., Wulff, M., Gronemyer, J., and Santana, L., 2025, Gillnet sampling methods for monitoring status and trends of Clear Lake Hitch in Clear Lake, Lake County, California: U.S. Geological Survey Open-File Report 2025–1018, 26 p., https://doi.org/10.3133/ofr20251018.","productDescription":"Report: viii, 26 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-168545","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":484873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1018/coverthb.jpg"},{"id":484874,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1018/ofr20251018.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1018"},{"id":484875,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251018/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1018"},{"id":484876,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KXAMKP","text":"USGS data release","description":"USGS data release","linkHelpText":"Abundance and distribution of fishes in Clear Lake, Lake County, California"},{"id":484877,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1018/images"},{"id":484878,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1018/ofr20251018.XML"}],"country":"United States","state":"California","county":"Lake County","otherGeospatial":"Clear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.65917771122702,\n 39.01735284231793\n ],\n [\n -122.72999697064151,\n 39.029142588016896\n ],\n [\n -122.751242748466,\n 39.044466317884144\n ],\n [\n -122.76945341517263,\n 39.038965874124074\n ],\n [\n -122.78108800779074,\n 39.076281906791024\n ],\n [\n -122.83015563752795,\n 39.12142755641764\n ],\n [\n -122.8807408228241,\n 39.123782188115115\n ],\n [\n -122.90046904508966,\n 39.101017451759986\n ],\n [\n -122.91311534141363,\n 39.076281906791024\n ],\n [\n -122.91665630438428,\n 39.031107354476376\n ],\n [\n -122.892881267295,\n 39.02285496831968\n ],\n [\n -122.83673171161647,\n 39.024033939613446\n ],\n [\n -122.80688645229174,\n 39.014994657245325\n ],\n [\n -122.79727526708535,\n 38.99887828791458\n ],\n [\n -122.77653534111394,\n 39.007133472381724\n ],\n [\n -122.7628773410841,\n 39.00123701034022\n ],\n [\n -122.74820763734814,\n 38.99298113784059\n ],\n [\n -122.73960815584789,\n 38.98275824692357\n ],\n [\n -122.74466667437748,\n 38.972533879655856\n ],\n [\n -122.72999697064151,\n 38.95955467222447\n ],\n [\n -122.72240919284712,\n 38.96152137166055\n ],\n [\n -122.71633897061167,\n 38.95916132578665\n ],\n [\n -122.71077460022903,\n 38.96584791826234\n ],\n [\n -122.70217511872879,\n 38.95444099821404\n ],\n [\n -122.69357563722826,\n 38.94499939981313\n ],\n [\n -122.66980060013927,\n 38.941065029307254\n ],\n [\n -122.65361334084434,\n 38.94735991731659\n ],\n [\n -122.65563674825637,\n 38.93949121997264\n ],\n [\n -122.6404611926676,\n 38.93437609838975\n ],\n [\n -122.63236756302015,\n 38.942638803709116\n ],\n [\n -122.64754311860891,\n 38.9627013651191\n ],\n [\n -122.65361334084434,\n 38.96899433164984\n ],\n [\n -122.66271867419766,\n 38.972533879655856\n ],\n [\n -122.69104637796346,\n 38.98236502932696\n ],\n [\n -122.69812830390507,\n 38.98039890858698\n ],\n [\n -122.69205808166961,\n 38.985903909070544\n ],\n [\n -122.7133038594938,\n 39.0043818512562\n ],\n [\n -122.68194104461014,\n 38.99455375924509\n ],\n [\n -122.66929474828619,\n 38.99848515986562\n ],\n [\n -122.66929474828619,\n 39.009098850512345\n ],\n [\n -122.65766015566808,\n 39.011457232184966\n ],\n [\n -122.65917771122702,\n 39.01735284231793\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
This report documents the system characterization of the Indian Space Research Organisation Resourcesat-2A Advanced Wide Field Sensor (AWiFS) and is part of a series of system characterization reports produced by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports describe the methodology and procedures used for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2A was launched in 2016 on the Polar Satellite Launch Vehicle-C36; it is identical to Resourcesat-2, and together, they decrease imaging revisit time from 5 days to 2–3 days, providing data continuity and improved temporal resolution. Resourcesat-2 and -2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-4 medium-resolution imaging sensors, continuing the legacy of the Indian Space Research Organisation’s Indian Remote Sensing-1C/1D/P3 satellite programs. More information about Indian Space Research Organisation satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium and from the Indian Space Research Organisation at https://www.isro.gov.in/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team assessed the geometric, radiometric, and spatial performance of the Resourcesat-2A AWiFS sensor. Geometric performance is divided into the interior geometric performance of band-to-band registration and the exterior geometric performance of geolocation accuracy. The interior geometric performance had offsets in the range of −1.10 meters (m; −0.020 pixel) to 3.67 m (0.066 pixel) in easting and −5.68 m (−0.101 pixel) to 10.38 m (0.185 pixel) in northing with root mean square error values from 5.60 m (0.100 pixel) to 11.31 m (0.202 pixel) in easting and from 3.00 m (0.054 pixel) to 13.52 m (0.241 pixel) in northing.
The exterior geometric performance had mean offsets of −25.29 m in easting and 16.22 m northing with root mean square error values of 26.07 m in easting and 17.60 m in northing compared to the Landsat 8 Operational Land Imager sensor. The radiometric performance had offsets from −0.002 to 0.029 and slopes from 0.733 to 1.012. Spatial performance was in the range of 1.354 to 1.639 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.108 to 0.174.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030V","usgsCitation":"Shrestha, M., Kim, M., Sampath, A., and Clausen, J., 2025, System characterization report on Resourcesat-2A Advanced Wide Field Sensor, chap. V of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 18 p., https://doi.org/10.3133/ofr20211030V.","productDescription":"v, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-170096","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":485174,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030V/full"},{"id":485170,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/v/coverthb.jpg"},{"id":485171,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/v/ofr20211030v.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-V"},{"id":485172,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/v/ofr20211030v.XML"},{"id":485173,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/v/images/"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Captive breeding and release programs aimed at recovery of rare species can be informed by genetic data to help select high-diversity source populations, make pairing decisions to minimize inbreeding, and manage release strategies. We developed a set of 54 microsatellite loci to assess genetic structure and diversity across the United States range of the Light-footed Ridgway’s Rail (Rallus obsoletus levipes), a federally endangered marsh bird for which populations have been augmented by a captive breeding program annually since 2001. We identified three regional genetic clusters, with the highest genetic diversity reported in the central cluster, which included all sampled wetlands in north San Diego County. Recent (2019–24) captive-breeding adults all clustered within the northernmost cluster (Orange and Ventura Counties), which was expected given that this cluster included the source wetland for the captive breeding program. Gene flow rates, which approximate the proportions of individuals in a population originating from other populations, were relatively high among clusters (4–24 percent) and may have been enhanced through the release of captive-bred rails. Based on the genetic data analyzed in a genetic rescue decision framework, sourcing new breeding birds from the north San Diego County cluster could provide the greatest genetic diversity benefits. The northernmost cluster, which included Mugu Lagoon and all sampled Orange County wetlands, was considered the most in need of genetic rescue. Recent breeding pairs in the captive breeding program have comparatively low diversity and high interrelatedness. Sourcing birds from wetlands with high genetic diversity and population sizes, assessing genetic relatedness before pairing, and focusing releases in areas that have low estimates of genetic diversity could improve the distribution of genetic diversity across wild populations in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251011","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service, Carlsbad Fish and Wildlife Office","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Vandergast, A.G., Smith, J.G., Mitelberg, A., Wood, D.A., Sawyer, K.A., and Conway, C.J., 2025, Genetic structure and diversity in wild populations of the Light-footed Ridgway’s Rail reflect 20 years of augmentation through captive breeding and release: U.S. Geological Survey Open-File Report 2025–1011, 24 p., https://doi.org/10.3133/ofr20251011.","productDescription":"Report: viii, 24 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-169671","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":485012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1011/coverthb.jpg"},{"id":485013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1011/ofr20251011.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1011"},{"id":485015,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14CYDJC","text":"USGS data release","description":"USGS data release","linkHelpText":"Microsatellite genotypes for light-footed Ridgway's rail (Rallus obsoletus levipes) sampled in southern California"},{"id":485017,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1011/ofr20251011.XML"},{"id":485014,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251011/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1011"},{"id":485016,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1011/images"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.10331263380175,\n 34.10687099022617\n ],\n [\n -118.03807861620402,\n 33.46101273577156\n ],\n [\n -117.15926055168606,\n 32.54485080859107\n ],\n [\n -116.83812382579282,\n 32.56519890177364\n ],\n [\n -117.45219990652568,\n 33.65951802680661\n ],\n [\n -118.60202603728568,\n 34.09630540323134\n ],\n [\n -119.10331263380175,\n 34.10687099022617\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-3 sensor and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence since 2021. These reports present and detail the methodology and procedures for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 for continuity of data and improved temporal resolution. The Resourcesat-2 platform (which includes Resourcesat-2A) is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Linear Imaging Self Scanning-3 and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/.
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.
To summarize the results, we have determined that this sensor provides an interior geometric performance with mean offsets in the range of 1.75 meters (m; 0.06 pixel) to 6.83 m (0.23 pixel) in easting and −1.83 m (−0.06 pixel) to 1.81 m (0.06 pixel) in northing in band-to-band registration and a root mean square error in the range of 3.81 m (0.13 pixel) to 8.19 m (0.27 pixel) in easting and 2.21 m (0.09 pixel) to 4.72 m (0.16 pixel) in northing.
We have measured an exterior geometric error offset in the range of −21.29 to 6.88 m in easting and −7.35 to −2.63 m in northing, and the root mean square error is in the range of 7.19 to 21.43 m in easting and 3.64 to 8.19 m in northing in comparison to the Landsat 8 Operational Land Imager.
The measured radiometric performance was in the range of −0.002 to 0.031 in offset and 0.701 to 0.940 in slope, and the spatial performance was in the range of 1.204 to 1.265 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.251 to 0.277.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030T","usgsCitation":"Park, S., Shrestha, M., Kim, M., Sampath, A., and Clauson, J., 2025, System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor, chap. T of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 17 p., https://doi.org/10.3133/ofr20211030T.","productDescription":"v, 17 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-170097","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":484900,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/t/images/"},{"id":484899,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/t/ofr20211030t.XML"},{"id":484898,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/t/ofr20211030t.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-T"},{"id":484897,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/t/coverthb.jpg"},{"id":484901,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030T/full"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The hydrogeologic framework at closed-loop geothermal sites in the Erie-Ontario Lowlands and Allegheny Plateau of central and western New York is the result of the complex interaction of bedrock geology, glacial geology, and groundwater hydrology, and the occurrence of petroleum and gas. Considerations for closed-loop geothermal bore installation include the thickness and character of glacial deposits, bedrock solubility and depth to competent rock, karst development, the distribution of highly permeable zones and their hydraulic heads, and the presence of saline water, gas, and oil. The hydrogeology of the Erie-Ontario Lowlands and Allegheny Plateau poses challenges to closed-loop geothermal bore drilling and casing; managing drill cuttings, discharge water, and gas; and grouting. The potential to encounter severe challenges typically increases with bore depth. This report highlights hydrogeologic considerations for closed-loop geothermal bore installation in New York’s Erie-Ontario Lowlands and Allegheny Plateau to help guide the efficient and safe development of geothermal resources in the regions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251013","usgsCitation":"Williams, J.H., Kappel, W.M., and Woda, J.C., 2025, Hydrogeologic framework and considerations for drilling and grouting of closed-loop geothermal bores in the Erie-Ontario Lowlands and Allegheny Plateau of New York State: U.S. Geological Survey Open-File Report 2025–1013, 11 p., https://doi.org/10.3133/ofr20251013.","productDescription":"v, 11 p.","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-160254","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":484773,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1013/coverthb.jpg"},{"id":484774,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1013/ofr20251013.pdf","text":"Report","size":"3.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1013 PDF"},{"id":484776,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1013/ofr20251013.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1013 XML"},{"id":484775,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251013/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1013 HTML"},{"id":484777,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1013/images/"},{"id":493765,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118544.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Allegheny Plateau, Erie-Ontario Lowlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.81166805859044,\n 42.45817957611891\n ],\n [\n -79.70949328319377,\n 41.9887101346182\n ],\n [\n -75.25480564049155,\n 41.98783382644345\n ],\n [\n -74.87533808065217,\n 41.42844676638893\n ],\n [\n -74.68982238759088,\n 44.66640491894796\n ],\n [\n -75.55631580076837,\n 44.66459292990035\n ],\n [\n -76.3423531557645,\n 44.2288156067778\n ],\n [\n -76.41053068058827,\n 43.979744421465796\n ],\n [\n -76.30005176487545,\n 43.60034279040653\n ],\n [\n -76.88563948226266,\n 43.34164590639\n ],\n [\n -77.46843046198688,\n 43.34036285729903\n ],\n [\n -78.42846779801299,\n 43.474518439670874\n ],\n [\n -79.08970961322291,\n 43.31146453979213\n ],\n [\n -78.97892018115594,\n 42.958836576630915\n ],\n [\n -78.81395126277387,\n 42.855237313375795\n ],\n [\n -79.81166805859044,\n 42.45817957611891\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349