The Conservation Reserve Enhancement Program is a program administered by the U.S. Department of Agriculture’s Farm Service Agency. The Secretary of Agriculture is required to submit an annual report to Congress on Conservation Reserve Enhancement Program agreements that, among other things, reports on the progress made towards fulfilling commitments outlined in the agreements. The U.S. Geological Survey developed an online reporting form designed to ensure that consistent information is submitted to the Farm Service Agency from Conservation Reserve Enhancement Program State partners. Combined with the automated importation of text from partner-provided forms to word-processing documents, individual State reports and annual reports to Congress can now be produced efficiently and in a standardized format. Use of a standardized reporting format will also assist the Farm Service Agency in collecting information needed to support ecosystem service quantifications that go beyond the quantifications required from partners to document progress towards meeting the specific purposes and objectives identified in each agreement. Addition of these overarching conservation effect quantifications builds upon past ecosystem services modeling efforts based on the Integrated Valuation of Ecosystem Services and Tradeoffs suite of open-source software models; these offer a spatially explicit means to quantify additional ecosystem services across diverse partners in a consistent manner. Data sources are currently available to provide much of the information needed to run these models and complete simulations that would facilitate the quantification and reporting of the societal values of conservation actions taken under the Conservation Reserve Enhancement Program. It is the aim of this report to provide the information needed to move towards widescale monitoring of the Nation’s ecosystem services in a natural accounting framework, similar to the framework used to value financial and human capital.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221104","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture’s Farm Production and Conservation Business Center and Farm Service Agency","usgsCitation":"Mushet, D.M., and McKenna, O.P., 2022, Development of an online reporting format to facilitate the inclusion of ecosystem services into Conservation Reserve Enhancement Program reports: U.S. Geological Survey Open-File Report 2022–1104, 19 p., https://doi.org/10.3133/ofr20221104.","productDescription":"Report: vi, 19 p.; 5 Appendixes","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-141507","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":409698,"rank":10,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221104/full","text":"Report"},{"id":409675,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1104/coverthb.jpg"},{"id":409676,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104.pdf","text":"Report","size":"725 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1104"},{"id":409677,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104.XML"},{"id":409678,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix1.pdf","text":"Appendix 1","description":"OFR 2022–1104, Appendix 1","linkHelpText":"—Farm Service Agency Notice Implementing Use of Online Reporting Form"},{"id":409679,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix2.pdf","text":"Appendix 2","description":"OFR 2022–1104, Appendix 2","linkHelpText":"—A Guide for Completing Conservation Reserve Enhancement Program Annual Reports Using the New Online Reporting Form"},{"id":409681,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix4.pdf","text":"Appendix 4","description":"OFR 2022–1104, Appendix 4","linkHelpText":"—Microsoft Word Mail Merge State Report Template"},{"id":409682,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix5.pdf","text":"Appendix 5","description":"OFR 2022–1104, Appendix 5","linkHelpText":"—Draft Text Produced for 2020 Report to Congress"},{"id":409683,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1104/ofr20221104_appendix6.pdf","text":"Appendix 6","description":"OFR 2022–1104, Appendix 6","linkHelpText":"—Draft Text Produced for 2021 Report to Congress"},{"id":409687,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1104/images"}],"contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
In this report, we consider evolutionary and ecological connectivity for westslope cutthroat trout (Oncorhynchus clarkii lewisi) and mountain whitefish (Prosopium williamsoni) within the Pend Oreille River in northeastern Washington State, northern Idaho, and adjacent portions of southeastern British Columbia, Canada. Specifically, we focused on the rationale for active translocation of individuals of these species upstream from Boundary Dam both in the context of natural patterns of pre-dam evolutionary connectivity as well as preserving contemporary ecological and evolutionary characteristics of local extant populations. Boundary Dam impounds the Pend Oreille River (called the Pend d’Oreille River in Canada) with the resulting reservoir inundating two historical barriers to upstream movement of fish (Metaline Falls and Z Canyon). Historically, it was thought these barriers impeded the upstream movement of westslope cutthroat trout and mountain whitefish, as well as Pacific salmon (Oncorhynchus spp.), steelhead trout (O. mykiss), and other resident species such as bull trout (Salvelinus confluentus). To address connectivity, we consider historical and contemporary processes and features. This review includes an assessment of postglacial processes within the Pend Oreille River and systems upstream that include Priest Lake, Lake Pend Oreille, the Clark Fork River, features of Boundary Reservoir and its tributaries, and areas downstream in the Pend Oreille River such as the Salmo River. Based on this information, we then give a more detailed review of existing genetic and ecological data to summarize what is known about connectivity for westslope cutthroat trout and mountain whitefish. Our assessment of the collective evidence leads us to conclude that moving fish upstream over Boundary Dam is not warranted if the management objective is to maintain natural patterns of evolutionary and ecological connectivity or to conserve unique ecological and evolutionary characteristics of extant local populations of these species in the system. These findings parallel that of a previous analysis of bull trout. Although we were able to arrive at well-supported conclusions in relation to Boundary Dam, we suggest that more work on connectivity further upstream in the Pend Oreille River would help to better understand the role of historical processes and dams further up in the system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221084","collaboration":"Prepared in cooperation with the University of British Columbia, Biodiversity Research Centre and Beaty Biodiversity Museum, and Idaho State University, Department of Biological Sciences, Fish Ecology Laboratory","usgsCitation":"Dunham, J.B., Taylor, E.B., and Keeley, E.R., 2022, Evolutionary and ecological connectivity in westslope cutthroat\ntrout (Oncorhynchus clarkii lewisi) and mountain whitefish (Prosopium williamsoni) in relation to the potential\ninfluences of Boundary Dam, Washington, Idaho, and parts of British Columbia: U.S. Geological Survey Open-File\nReport 2022–1084, 22 p., https://doi.org/10.3133/ofr20221084.","productDescription":"vii, 22 p.","onlineOnly":"Y","ipdsId":"IP-137003","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":409558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1084/coverthb.jpg"},{"id":409559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1084/ofr20221084.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1084"},{"id":409561,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1084/images"},{"id":409562,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1084/ofr20221084.XML"}],"country":"Canada, United States","state":"British Columbia, Idaho, Washington","otherGeospatial":"Boundary Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.81638376433206,\n 49.098372085467105\n ],\n [\n -117.81638376433206,\n 47.528691502768\n ],\n [\n -113.48236882623914,\n 47.528691502768\n ],\n [\n -113.48236882623914,\n 49.098372085467105\n ],\n [\n -117.81638376433206,\n 49.098372085467105\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
Flat Creek, a tributary to the Snake River in northwestern Wyoming, is an important source of irrigation water, fish and wildlife habitat, and local recreation. Since 1996, a section of Flat Creek within the town of Jackson has failed to meet Wyoming Department of Environmental Quality’s surface-water-quality standards for total suspended solids and turbidity required by its State water-use classification. Wyoming Department of Environmental Quality water-quality standards prohibit increases of greater than 10 nephelometric turbidity units (NTU) because of human activities in streambodies of Wyoming. Sediment loading from urban stormwater runoff is hypothesized in previous publications to be the primary cause of impairment, but the relative fine sediment contributions from various sources have not been quantified.
In cooperation with the Teton Conservation District, the U.S. Geological Survey began a pilot study in the Flat Creek drainage basin to investigate the use of continuous turbidity measurements to predict suspended-sediment concentrations, loads, and sources through the town of Jackson, Wyoming. The predictions were based on turbidity measurements collected every 15 minutes during parts of water years 2019 and 2020. Analysis of differences in the more than 15,000 turbidity measurements coincident between upstream and downstream streamgages indicated that differences of 10 formazin nephelometric units (FNU) or greater composed about 1 percent of the total accepted measurements during the 2019 and 2020 measurement periods. The median difference in measured turbidity between coincident records at the upstream and downstream streamgages in 2019 was 0.20 FNU and the median difference in 2020 was 0.0 FNU.
Calculations of mean total sediment loads in Flat Creek during 2019 and 2020 indicate substantially more suspended-sediment was in Flat Creek below the town of Jackson than above town. Mean total calculated suspended-sediment loads at the upstream streamgage were 26 percent in 2019 and 21 percent in 2020 of the mean total suspended-sediment loads at the downstream streamgage. For measurements occurring at the same time (coincident), mean calculated suspended-sediment loads entering the town of Jackson from Flat Creek were 39 percent in 2019 and 35 percent in 2020 of those loads exiting town in Flat Creek. Incorporating statistical model uncertainty, mean differences between predicted suspended-sediment loads could potentially be zero. The annual period of operations of the South Park Supply Ditch, which diverts water into Flat Creek from the Gros Ventre River, constituted between 91 and 90 percent of the total calculated suspended-sediment load at the upstream streamgage, and between 88 and 87 percent of the loads at the downstream streamgage for coincident periods of record in 2019 and 2020, respectively. However, in the absence of simultaneous continuous monitoring and resulting measurements at the outlet of the South Park Supply Ditch, no robust method was available to quantify suspended-sediment loads from the ditch.
A moving average filter was used to identify and isolate short-duration (minutes to hours) spikes in turbidity at the downstream streamgage that were likely caused by overland flow and urban runoff. Suspended-sediment loads during urban runoff constituted about 8 and 10 percent of the total calculated suspended-sediment loads at the downstream streamgage (Flat Creek below Cache Creek, near Jackson, Wyoming; U.S. Geological Survey streamgage 13018350), and 6 and 4 percent of the loads calculated for the record coincident with the upstream streamgage in 2019 and 2020, respectively. Estimated suspended-sediment loads at the upstream streamgage during urban runoff events for the coincident period of record constitute 32 and 40 percent of the total estimated suspended-sediment loads at the downstream streamgage in 2019 and 2020, respectively, indicating sediment loads from urban runoff may contribute less than 10 percent, even as little as 5 percent, of the total sediment load exiting the town of Jackson on Flat Creek. Estimation of the proportion of suspended-sediment loads at the upstream site that originate from the South Park Supply Ditch or Cache Creek can only be done with assumptions but have the potential to be equivalent to or greater than calculated suspended-sediment loads associated with urban runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221103","collaboration":"Prepared in cooperation with the Teton Conservation District","programNote":"Water Mission Area","usgsCitation":"Alexander, J.S., Girard, C., Campbell, J., Ellison, C., Gosselin, E., and Smith, E., 2022, Using continuous measurements of turbidity to predict suspended-sediment concentrations, loads, and sources in Flat Creek through the town of Jackson, Wyoming, 2019−20 — A pilot study: U.S. Geological Survey Open-File Report 2022–1103, 29 p., https://doi.org/10.3133/ofr20221103.","productDescription":"Report: viii, 29 p.; Dataset","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-136294","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":409367,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":409366,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1103/images"},{"id":409364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.pdf","text":"Report","size":"2.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1103"},{"id":409365,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1103/ofr20221103.XML"},{"id":409363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1103/coverthb.jpg"},{"id":501840,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113833.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Jackson","otherGeospatial":"Flat Creek drainage basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.72880406891166,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.5011735765672\n ],\n [\n -110.8241704639435,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.42146497765464\n ],\n [\n -110.72880406891166,\n 43.5011735765672\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
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Current time-invariant groundwater vulnerability assessments may not capture intermittent contamination events in landscape areas that experience rapid infiltration following precipitation or snowmelt. Occurrences of rapid infiltration and intermittent degradation of groundwater quality are frequently reported in fractured-rock aquifers. This investigation identifies landscape areas underlain by fractured rock within the conterminous United States (CONUS) that may be susceptible to rapid infiltration and where groundwater is a principal source of water supply to the population. Our analysis shows that approximately 27 percent of the CONUS, corresponding to a population of approximately 150 million people, is both underlain by fractured rock and denoted as an area of significant groundwater use.
The results of this survey identified shallow fractured-rock aquifers underlying glacial sediments in the upper Midwest and northeastern United States as areas that may be subject to rapid infiltration events. Additionally, aquifers associated with the early Mesozoic basins located in the northeastern and mid-Atlantic United States and bands of carbonate aquifers in the southeastern United States show high susceptibility to rapid infiltration. Index values used in this investigation indicate isolated areas in the western half of the United States also show high susceptibility to rapid infiltration. The isolated areas in Oklahoma, Texas, Arkansas, and southwestern Missouri correspond to karst regions of carbonate aquifers. The isolated areas showing high susceptibility to rapid infiltration and contamination from agricultural sources are locations where more detailed investigations of transient contamination events are warranted.
This survey also addresses the potential for contaminant longevity in fractured-rock aquifers stemming from intermittent contamination events. Contaminants that can dissolve into the groundwater following infiltration may be introduced into fractures, and the dissolved constituents can diffuse from fractures into the porosity of the adjacent rock matrix. These constituents can then diffuse back into permeable fractures and adversely affect groundwater quality at downgradient locations over an extended time frame. Rock types with larger matrix porosities have the capacity to retain and then release larger quantities of dissolved constituents, resulting in longer residence times for dissolved groundwater contaminants. The magnitude of the dissolved contaminant concentration infiltrating to the water table will also dictate whether the contaminant concentration in the groundwater exceeds limits for human consumption over the duration of a contamination event.
In general, sedimentary- and carbonate-rock aquifers have larger matrix porosities in comparison to igneous- and metamorphic-rock aquifers, and thus, they are more susceptible to longer contaminant residence times. Aquifers composed of sedimentary or carbonate rock constitute approximately 51 percent of the CONUS, and 19 percent of the CONUS is associated with sedimentary- or carbonate-rock aquifers that are of significance for groundwater use. Depending on the contaminants of concern and the concentration of the contaminants introduced into the groundwater from infiltrating water, it would be beneficial for investigations of susceptibility to rapid infiltration to also consider the potential for contaminant longevity.
This investigation identifies areas of rapid infiltration into fractured rock using index values applied to the attributes (1) depth to the water table, (2) depth to bedrock, and (3) percentage of sand in soil, where larger index values indicate a greater susceptibility to rapid infiltration. These attributes are selected as the most likely factors that affect rapid infiltration to the water table. The combination of depth to water table and depth to bedrock highlight those aquifer settings that are characterized as shallow fractured-rock aquifers, where the water table may reside either in the bedrock or in overlying unconsolidated geologic materials. In addition, we consider the percentage of agricultural use as a land-use attribute when formulating an index of susceptibility to rapid infiltration and contamination. Agricultural areas are well recognized as nonpoint sources of contaminants that can affect groundwater quality because of seasonal amendments applied to the land surface. Rural agricultural areas are also characterized by septic tanks and leach fields for onsite treatment of wastewater, which may also be a source of contamination that may be introduced into the groundwater following precipitation or snowmelt events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221093","programNote":"National Water Quality Program","usgsCitation":"Shapiro, A.M., and Falcone, J.A., 2022, Mapping areas of groundwater susceptible to transient contamination events from rapid infiltration into shallow fractured-rock aquifers in agricultural regions of the conterminous United States: U.S. Geological Survey Open-File Report 2022–1093, 25 p., https://doi.org/10.3133/ofr20221093.","productDescription":"v, 25 p.","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-132538","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":501835,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113829.htm","linkFileType":{"id":5,"text":"html"}},{"id":409297,"rank":1,"type":{"id":31,"text":"Publication 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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Imaging sonar was used to assess the behavior, abundance, and timing of fish at the entrances to the Selective Water Withdrawal (SWW) intake structure located in the forebay of Round Butte Dam, Oregon during the spring of 2021. The purposes of the SWW are (1) to direct surface currents in the forebay to attract and collect downriver migrating juvenile salmonid smolts (Chinook salmon [Oncorhynchus tshawytscha], sockeye salmon [O. nerka], and steelhead [O. mykiss]) from Lake Billy Chinook and (2) to enable operators of the SWW to withdraw water from surface and benthic elevations in the reservoir to manage downriver water temperatures. Part of the evaluation, to determine how well the structure performs at collecting juvenile salmonids, needs (A) to regularly assess how fish are approaching the entrance, and (B) to determine if operational flows could be optimized to increase the attraction of smolts present in the forebay of Lake Billy Chinook. The primary goals of this study were (1) to assess the abundance and behaviors of smolt-size fish observed near the SWW and (2) to provide data of the effect of two-night generation operation timing conditions on movements and behaviors of fish near the entrance to the SWW structure. The purpose of this assessment is to improve downstream passage solutions.
Two imaging sonar units were deployed during the spring 2021 smolt out-migration period. One unit monitored fish movements near the south entrance and one unit monitored movements near the north entrance of the SWW. Both smolt and bull trout (Salvelinus confluentus)-size fish were regularly observed near the entrances with greater abundances observed during night, corresponding with greater discharge through the SWW than during the day when discharge was reduced. Differences in fish abundance were observed between the night generation operation timing conditions, with increased fish counts observed when elevated discharge was extended to 6:00 a.m., rather than when discharges have been traditionally reduced in the early morning at 4:00 a.m. Fish of all size groups were primarily observed near the center of the SWW, and greater abundances of fish were observed at the south entrance. Increased counts of bull trout-size fish coincided with the increased abundances of smolt-size fish. Overall, the results indicate that (A) smolt-size fish were more abundant near the entrance of the SWW during periods of increased discharge, (B) bull trout-size fish were present at the SWW, and (C) fish were more numerous at the SWW when night generation operation timing was extended later into the morning hours rather than the traditional operation timing flow reduction.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221098","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., and Hatton, T.W., 2022, Evaluation of fish behavior at the entrances to a Selective Water Withdrawal structure in Lake Billy Chinook, Oregon, 2021: U.S. Geological Survey Open-File Report 2022–1098, 28 p., https://doi.org/10.3133/ofr20221098.","productDescription":"viii, 28 p.","onlineOnly":"Y","ipdsId":"IP-139510","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409425,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1098/images"},{"id":409424,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221098/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1098"},{"id":409423,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.pdf","text":"Report","size":"36.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1098"},{"id":409422,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1098/coverthb.jpg"},{"id":409426,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1098/ofr20221098.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Billy Chinook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.5557866634069,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.38885839267408\n ],\n [\n -121.07886358532556,\n 44.75388913871075\n ],\n [\n -121.5557866634069,\n 44.75388913871075\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 Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at 33 locations along multiple drainages in San Diego County, including portions of Agua Hedionda Creek, Cottonwood Creek, Escondido Creek, Los Penasquitos Creek, Otay River, San Diego River, San Dieguito River, San Luis Rey River, Sweetwater River, and Tijuana River. Resident flycatchers were only found on two drainages in San Diego County, at San Dieguito and San Luis Rey Rivers, with 99 percent occurring on the San Luis Rey River. Resident flycatchers were detected at 18 percent of survey locations (Bonsall, Cleveland National Forest, Rey River Ranch, San Dieguito, and Vista Irrigation District [VID], and VID Lake Henshaw). Resident flycatchers were documented for the first time at Lake Henshaw, the only new location surveyed that supported flycatchers. We detected a minimum of 80 resident flycatchers from 2015 to 2019, most of these were upstream and downstream from Lake Henshaw. Transient flycatchers were found at 42 percent of survey locations; 38 transient individuals were detected at Agua Hedionda Creek, Otay River, San Diego River, San Dieguito River, and the San Luis Rey River.
Over the course of this study, 11 locations historically occupied by resident flycatchers were resurveyed; only 5 were found to have resident flycatchers: (1) Bonsall, (2) Cleveland National Forest, (3) Rey River Ranch, (4) San Dieguito, and (5) Vista Irrigation District. The number of resident flycatchers declined from previous high counts at all five locations. Collectively, the number of resident flycatcher territories within the historically occupied area of the upper San Luis Rey River downstream from Lake Henshaw (Cleveland National Forest, Rey River Ranch, and Vista Irrigation District) declined 71 percent between 1999 (48) and 2019 (14); 42 percent of the decline occurred between 1999 and 2016, with an additional decline (50 percent) occurring between 2016 and 2019. In 2016, the distribution of flycatcher territories at the historically occupied area of the upper San Luis Rey River changed relative to the distribution in 1999: the proportion of territories at Cleveland National Forest and Rey River Ranch decreased to 36 percent each, while Vista Irrigation District increased to 29 percent, creating a more equal distribution of territories across the historically occupied area. By 2019, the distribution changed relative to 2016, with most of the territories spread equally between Cleveland National Forest and Rey River Ranch (43 percent each), while the proportion of territories at Vista Irrigation District declined to 14 percent.
During countywide surveys, we documented the dispersal of two natal banded flycatchers; both were females that were originally banded as nestlings at Marine Corps Base Camp Pendleton and were seen for the first time as breeding adults. One of the females dispersed to San Dieguito, a distance of 41 kilometers, and a second female dispersed to Cleveland National Forest, a distance of 55 kilometers. We also documented the within-season movement of a uniquely banded male that was seen at the beginning of the 2017 breeding season at Bonsall and was later documented at San Dieguito, a movement distance of 31 kilometers.
We completed nest monitoring activities along the upper San Luis Rey River near Lake Henshaw in Santa Ysabel, California from 2016 to 2019. Monitoring occurred at three locations: (1) Cleveland National Forest, (2) Rey River Ranch, and (3) Vista Irrigation District, collectively the upper San Luis Rey River monitoring area. The number of flycatcher territories monitored each year ranged from 14 to 27. We observed polygynous pairings (one male paired with multiple females) in all years, with the lowest rate of polygyny (number of polygynous pairs/total number of pairs) observed in 2016 (10 percent) and the highest in 2017 (70 percent). The proportion of paired males that were polygynous ranged from 5 to 54 percent between 2016 and 2019.
We monitored the nesting activity of 14–27 pairs annually during the course of the study. Most of the first nesting attempts were initiated during late May and early June. We monitored 18–41 Southwestern Willow Flycatcher nests per year from 2016 to 2019. Apparent nest success ranged from 11 to 37 percent and differed significantly by year, with higher success in 2016 and 2017 compared to 2018 and 2019. Predation was the presumed to be the primary source of nest failure, with 63–84 percent of failures annually attributed to predation. Although none of the failures were attributed to Brown-headed cowbird (Molothrus ater) parasitism, 4–27 percent of nests were parasitized annually from 2016 to 2019, with increased parasitism rates observed in 2018 and 2019 compared to 2016 and 2017. We “rescued” 11 parasitized nests between 2016 and 2019 by removing cowbird eggs; if those nests had been allowed to fail, apparent nest success would have been up to 45 percent lower annually.
Flycatcher egg clutch size ranged from 2.8±0.8 to 3.1±0.8 annually and did not vary significantly between years. The number of fledglings per pair ranged from 0.5±1.0 to 1.6±1.5 annually from 2016 to 2019. There was a significant difference in the number of young fledged per pair between years, with pairs in 2016 producing more than three times the number of fledglings compared to 2019. The percent of pairs fledging at least one young ranged from 18 to 62 percent annually but did not vary significantly by year.
Analysis of flycatcher daily nest survival rates suggested that both early and late winter precipitation influenced nest survival, with increases in early winter precipitation positively influencing nest survival and later winter precipitation negatively influencing nest survival. The second-best supported model included year, with the lowest daily nest survival occurring in 2018 and 2019.
A total of 119 flycatchers were newly banded over the course of this study; 36 adult flycatchers were banded with a unique color combination, and 83 nestlings (57 of which survived to fledging) were banded with a single band on the left or right leg. In addition, two adults that were banded before 2015 were observed in the monitoring area. Between 2015 and 2019, we accumulated 94 resights of 49 individual color-banded adult flycatchers that ranged in age from 1 to 8 years old.
Banding allowed us to examine differences in annual survivorship among flycatchers of different ages and sexes. We estimated annual survivorship of adult males to be 69±7 percent, which is higher than estimates of female survivorship (45±10 percent). Annual survivorship of first-year flycatchers ranged from 24 to 41 percent, which is roughly half the estimates calculated for adult flycatchers (52–75 percent). We found no evidence that precipitation in the previous breeding year had an effect on flycatcher survival.
We were also able to observe dispersal and movement among adults and first-year flycatchers. Average first-year dispersal distance was 3.1±2.6 kilometers, with the longest dispersal (8.5 kilometers) by a natal female dispersing from the monitoring area to Lake Henshaw. Of the first-year flycatchers, 65 percent returned to the monitoring area to establish an adult breeding territory, while the remaining 35 percent dispersed to Lake Henshaw.
Territory fidelity among adult flycatchers was high with 69±13 percent of returning adults occupying the same territory (or within 100 meters) from the previous year. There was no significant difference in territory fidelity between males and females, or across years. Nesting success in the previous year appeared to be a strong driver of territory fidelity, with adults more likely to return to the same territory following years when they successfully fledged young. The average between-year movement for returning adult flycatchers was 0.5±0.8 km. We documented the movement of two adult males from the monitoring area to Lake Henshaw. Between-year movement distances did not differ by sex or year.
Resident flycatchers in the upper San Luis Rey River monitoring area used five habitat types from 2016 to 2019: (1) willow-oak, (2) willow-ash, (3) oak-sycamore, (4) mixed willow riparian, and (5) willow-sycamore, with willow-oak the most commonly used habitat type. The most commonly recorded dominant species at flycatcher territories included coast live oak (Quercus agrifolia), red or arroyo willow (Salix laevigata or Salix lasiolepis), California sycamore (Platanus racemosa), and velvet ash (Fraxinus velutina).
In 2018, we anecdotally began to observe dead and dying oaks in the monitoring area, which we believe to be the result of goldspotted oak borer (Agrilus auroguttatus) infestation. At the conclusion of this study, we investigated the overall change in normalized difference vegetation index (NDVI) in flycatcher territories within the monitoring area. The greatest negative change in NDVI occurred in territories closest to Lake Henshaw, and many of the affected territories were no longer occupied in the later years of the study.
Flycatchers used 13 plant species for nesting at the monitoring area from 2016 to 2019; 70 percent of all nests were placed in coast live oak. None of the nest characteristics including host height, nest height, distance to the edge of the host, or distance to the edge of the vegetation clump where the nest was placed differed between years. In 2016, successful nests were placed higher than unsuccessful nests; no other within-year differences were observed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221082","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., Kus, B.E., and Mendia, S.M., 2022, Distribution and demography of Southwestern Willow Flycatchers in San Diego County, 2015–19: U.S. Geological Survey Open-File Report 2022–1082, 43 p., https://doi.org/10.3133/ofr20221082.","productDescription":"Report: ix, 43 p.; Data Release","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-139367","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":409362,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1082/images"},{"id":409388,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221082/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1082"},{"id":409359,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1082/ofr20221082.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1082"},{"id":409361,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1082/ofr20221082.xml"},{"id":409360,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96VC5Y4","text":"USGS data release","linkHelpText":"Southwestern Willow Flycatcher (Empidonax traillii extimus) surveys and nest monitoring in San Diego County, California"},{"id":409358,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1082/covrthb.jpg"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.57666896119845,\n 33.481188795657516\n ],\n [\n -117.57666896119845,\n 32.493491667261026\n ],\n [\n -116.14905258547724,\n 32.493491667261026\n ],\n [\n -116.14905258547724,\n 33.481188795657516\n ],\n [\n -117.57666896119845,\n 33.481188795657516\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir (hereinafter, Clear Lake), California, are experiencing long-term decreases in abundance. Upper Klamath Lake populations are decreasing not only because of adult mortality, which is relatively low, but also because they are not being balanced by recruitment of young adult suckers into known adult spawning aggregations.
Long-term monitoring of juvenile sucker populations is conducted to (1) determine if there are annual and species-specific differences in production, survival, and growth, (2) better understand when juvenile sucker mortality is greatest, and (3) help identify potential causes of high juvenile sucker mortality particularly in Upper Klamath Lake. The U.S. Geological Survey (USGS) monitoring program, begun in 2015, tracks cohorts through summer months and among years in Upper Klamath and Clear Lakes. Data on juvenile suckers captured in trap nets are used to provide information on annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, apparent growth, species composition, and health.
Upper Klamath Lake indices of year-class strength suggest that the 2020 age-0 cohort is one of the lowest since standardized monitoring began. Despite apparently low over-winter survival, the relatively large 2019 cohort persisted in our 2020 samples and continues to contribute to the populations. Although the 2019 cohort age-0 suckers were composed mainly of Lost River suckers, the age-1 suckers from the 2019 cohort were mainly shortnose suckers. Lost River suckers comprised the largest proportion of the 2020 year-class and were only captured in July and August. Shortnose suckers were mainly captured in August and September and comprised a smaller proportion of the 2020 year-class.
Age distribution of suckers captured in Clear Lake indicates greater juvenile survival than in Upper Klamath Lake. Most juvenile suckers captured were age-3 and age-4 suckers classified as the combination of Klamath largescale suckers (Catostomus snyderi) and shortnose suckers from the Lost River Basin, from the 2016 and 2017 cohorts. A lack of age-0 suckers captured in Clear Lake during years with the low inflow or lake levels initially lead us to believe that low water prevented spawning and year class formation. However, recent data indicate that some cohorts that were not captured as age-0 suckers were detected in later years at age-1 or age-2. This finding indicates that juvenile suckers in Clear Lake may spend one or more years in the tributaries or that sampling efficacy for age-0 suckers varies among years because of water depth.
The first 5 years of this monitoring program indicated different patterns in recruitment and survival of juvenile suckers between Upper Klamath and Clear Lakes. Since the monitoring program began in 2015, age-0 sucker catch rates, interpreted as indices of year-class strength, were greatest in Upper Klamath Lake in 2016 and 2019. In those years Lost River suckers made up the majority of age-0 sucker catches; however, in 2017 and 2020 the age-1 sucker catches from these cohorts were mainly composed of shortnose suckers or suckers with genetic markers of both Klamath largescale and shortnose suckers, indicating a low overwinter survival for Lost River suckers even when the age-0 catches were high. Age-0 suckers do not fully recruit to our sampling gear in Upper Klamath Lake until August, experience high mortality by September, and are almost undetectable by the following July or August in most years. In Clear Lake, suckers frequently are not captured until age-1 or age-2 and annual survival appears much greater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221099","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Martin, B.A., Kelsey, C.M., Burdick, S.M., and Bart, R.J., 2022, Growth, survival, and cohort formation of juvenile Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2020 monitoring report: U.S. Geological Survey Open-File Report 2022–1099, 27 p., https://doi.org/10.3133/ofr20221099.","productDescription":"vi, 27 p.","onlineOnly":"Y","ipdsId":"IP-141866","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409276,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221099/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1099"},{"id":409274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1099/coverthb.jpg"},{"id":409278,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.XML"},{"id":409277,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1099/images"},{"id":409275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1099/ofr20221099.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1099"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Upper Klamath Lake, Clear Lake Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.23841270893135,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 41.77275507129002\n ],\n [\n -121.00794395893129,\n 42.66770378348696\n ],\n [\n -122.23841270893135,\n 42.66770378348696\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
Across the Pacific Northwest, there are many examples of artificial structures created to allow passage of upstream-migrating salmon over natural barriers. We studied upstream passage across three structures installed in 1989 to allow passage of salmon over Lake Creek Falls, a series of three natural waterfalls at the outlet of Triangle Lake on Lake Creek, in the central Oregon Coast Range (lat 123.57508°; long 44.15735°). To track upstream passage by adult coho salmon (Oncorhynchus kisutch), 87 fish were tagged using gastrically implanted radio tags. Tracking was accomplished with a series of stationary receivers installed to detect crossings at each of three structures—over Lake Creek Falls using two upstream Denil-type ladders and a bypass downstream constructed to mimic a natural side channel. Tracking spanned the upstream migration and spawn timing for adult coho salmon in the basin and extended from October 2019 to February 2020. A total of 15 coho salmon (17 percent) were tagged in October, 30 coho salmon (35 percent) were tagged in November, and 42 coho salmon (48 percent) were tagged in December. Later-than-normal precipitation and associated low discharge delayed upstream migrations. Accordingly, most fish arrived late in the season (late November and December) and in sudden flushes with the erratic rain events. Fish that were tagged earlier were more likely to cross all three ladders, with more than 93 percent of fish tagged in October compared to 46.7 and 19.0 percent of November and December fish passing, respectively. The decline in passage rate could be attributed to the overlapping influences of stream discharge and advanced stage of maturation (lower energy reserves) of fish later in the season. Near the end of the study, both fish that crossed and fish obstructed by barriers were observed in tributaries known to be used for spawning by coho salmon. Without a much longer-term study involving many more fish than the current study, more intensive tracking, and coverage of different flow years, firm conclusions are difficult to draw regarding the overall influences of the passage structures on the likelihood of upstream passage by adult coho salmon. However, substantial numbers of fish are capable of crossing during certain conditions. The population-level consequences of the barriers on spawning distribution and the production of coho salmon in the watershed are not clear. Additional empirical study or population modeling could be used to address this question in more detail.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221083","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Fischer, R.B., Dunham, J., Scheidt, N., Hansen, A.C., and Heaston, E.D., 2022, Passage of adult coho salmon (Oncorhynchus kisutch) over Lake Creek Falls, Oregon, 2019: U.S. Geological Survey Open-File Report 2022–1083, 19 p., https://doi.org/10.3133/ofr20221083.","productDescription":"vii, 19 p.","onlineOnly":"Y","ipdsId":"IP-130393","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":409177,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1083/coverthb.jpg"},{"id":409181,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.XML"},{"id":409180,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1083/images"},{"id":409179,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221083/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1083"},{"id":409178,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1083/ofr20221083.pdf","text":"Report","size":"21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1083"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Creek Falls","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.61844237310005,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.131057340436286\n ],\n [\n -123.5593908594283,\n 44.17170307975459\n ],\n [\n -123.61844237310005,\n 44.17170307975459\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
The seagrasses eelgrass (Zostera marina) and widgeongrass (Ruppia maritima) are prominent features of coastal lagoons along the Pacific coast of Baja California, Mexico, supporting a rich diversity of marine life. Yet little is known about their spatial distribution in this region. This is a concern because of declining trends in the abundance and distribution of seagrass in parts of northern Baja California and southern California. We used 7-band satellite imagery, 4-band digital multispectral videography, and 3-band color aerial photography to map the distribution of eelgrass and widgeongrass in six embayments along the central Pacific coast of Baja California. The total spatial extent of seagrass was estimated to be 42,697 hectares, of which about 70 percent was eelgrass. This seagrass was primarily lower in the intertidal than widgeongrass in all embayments. Eelgrass and widgeongrass composed the greatest proportion (47 percent) of the spatial extent in the two largest embayments, Lagunas Ojo de Liebre and San Ignacio, and these two embayments accounted for 85 percent of all seagrass in the study area. The native cordgrass (Spartina foliosa) and pickleweed (Salicornia spp.) were the predominate vegetation cover type of marshes in the three northern and three southern embayments, respectively. The three southern embayments contained mangrove (Rhizophora spp.) and the three northern embayments did not, thus marking the northern edge of mangroves along the Pacific coast of North America. This study establishes an embayment-wide baseline for continuing investigations and monitoring future changes in the spatial abundance of seagrasses in central Baja California.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221004","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., Morton, A., Markon, C.J., and Hogrefe, K.R., 2022, Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000: U.S. Geological Survey Open-File Report 2022–1004, 13 p., https://doi.org/10.3133/ofr20221004.","productDescription":"Report: vi, 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-128315","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":409029,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4LBP3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Point sampling data for eelgrass (Zostera marina) and widgeongrass (Ruppia maritima) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409030,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release.","linkHelpText":"Mapping data of eelgrass (Zostera marina) distribution, Alaska and Baja California, Mexico"},{"id":409032,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1004/ofr20221004.XML"},{"id":409031,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1004/images"},{"id":409026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1004/coverthb.jpg"},{"id":409041,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221078","text":"OFR 2022-1078 —","description":"OFR 2022-1078","linkHelpText":"Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409028,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221004/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1004"},{"id":409027,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1004/ofr20221004.pdf","text":"Report","size":"6.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1004"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.34490212994275,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 28.246325178662076\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
Trends in the abundance and distribution of eelgrass (Zostera marina), the primary winter forage of black brant (Branta bernicla nigricans), was evaluated at three major wintering sites for black brant along the northern Pacific coast of Baja California, Mexico. This region of northwestern Mexico contains significant beds of eelgrass that were showing signs of decline, which may negatively affect the Pacific flyway population of black brant. Embayment-wide surveys of eelgrass were conducted at Bahia San Quintin (BSQ), Laguna Ojo de Liebre (LOL), and Laguna San Ignacio (LSI) between 1998 and 2012 to estimate baselines and trends in the distribution and abundance of this seagrass in Mexico. Eelgrass was the most abundant and frequently encountered seagrass in each site across survey years. Density and aboveground biomass of eelgrass was greater in BSQ than in LOL and LSI while abundance of widgeongrass (Ruppia maritima), a secondary source of food for brant, was greatest in LSI across survey years. Widgeongrass occurred higher in the intertidal zone than did eelgrass in all embayments, and both seagrasses generally shifted to lower water depths along a southward latitudinal gradient. A negative temporal trend in abundance of seagrasses was detected in BSQ that appeared linked to impacts of climate warming and an increase in macroalgae populations. Decreases in abundance of seagrasses were also detected in LOL and LSI, although long-term trends were less certain in LOL. Overall, declines in abundance of eelgrass in Baja California may be influencing the ongoing shift in the winter distribution of brant to areas north of the Mexican border.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221078","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., 2022, Abundance of eelgrass (Zostera marina) at key Black Brant (Branta bernicla nigricans) wintering sites along the northern Pacific coast of Baja California, Mexico, 1998–2012: U.S. Geological Survey Open-File Report 2022–1078, 15 p., https://doi.org/10.3133/ofr20221078.","productDescription":"Report: vi, 15 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-135227","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":409019,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release.","linkHelpText":"Mapping data of eelgrass (Zostera marina) distribution, Alaska and Baja California, Mexico"},{"id":409018,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H4LBP3","text":"USGS data release","description":"USGS data release.","linkHelpText":"Point sampling data for eelgrass (Zostera marina) and widgeongrass (Ruppia maritima) abundance in embayments of the north Pacific coast of Baja California, Mexico, 1998–2012"},{"id":409021,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.XML"},{"id":409020,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1078/images"},{"id":409042,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221004","text":"OFR 2022-1004 —","description":"OFR 2022-1004","linkHelpText":"Spatial extent of seagrasses (Zostera marina and Ruppia maritima) along the central Pacific coast of Baja California, Mexico, 1999–2000"},{"id":409015,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1078/coverthb2.jpg"},{"id":409017,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221078/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1078"},{"id":409016,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1078/ofr20221078.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1078"}],"country":"Mexico","otherGeospatial":"Baja California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.34490212994275,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 26.352495017715754\n ],\n [\n -111.76335916119284,\n 28.246325178662076\n ],\n [\n -115.34490212994275,\n 28.246325178662076\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
In 2015, U.S. Geological Survey scientists in collaboration with scientists from other institutions began a study of the Queen Charlotte fault—the first systematic study of the fault in more than three decades. The primary goal of the study was to gain a better understanding of the earthquake, tsunami, and underwater-landslide hazards throughout southeastern Alaska, as well as gather data to develop geologic models that can be applied to similar plate boundaries around the globe, such as the San Andreas fault system in southern California, the Alpine fault in New Zealand, and the North Anatolian fault in Turkey. A bathymetric terrain model was compiled from six different multibeam surveys of the previously unmapped Queen Charlotte fault offshore of southeastern Alaska and Haida Gwaii archipelago.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221085","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"Andrews, B.D., Brothers, D.S., Dartnell, P., Barrie, J.V., Haeussler, P.J., Green, K.M., Greene, H.G., Miller, N.C., Kluesner, J.W., and ten Brink, U.S., 2022, Systematic mapping of the ocean-continent transform plate boundary of the Queen Charlotte fault system, southeastern Alaska and western British Columbia—A preliminary bathymetric terrain model: U.S. Geological Survey Open-File Report 2022–1085, 2 sheets, 7-p. pamphlet, https://doi.org/10.3133/ofr20221085.","productDescription":"Pamphlet: iii, 7 p.; 2 Sheets: 60.50 × 42.50 inches and 60.00 × 42.00 inches; Data Release","numberOfPages":"7","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-128196","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501832,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113792.htm","linkFileType":{"id":5,"text":"html"}},{"id":408793,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_sheet2.pdf","text":"Sheet 2","size":"101 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Contents of sheet replicated in the HTML version of the report linked to above"},{"id":408792,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_sheet1.pdf","text":"Sheet 1","size":"72.3 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Contents of sheet replicated in the HTML version of the report linked to above"},{"id":408791,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1085/images/"},{"id":408787,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1085/coverthb.jpg"},{"id":408788,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085_pamphlet.pdf","text":"Pamphlet","size":"5.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1085"},{"id":408790,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1085/ofr20221085.XML"},{"id":408789,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221085/full","text":"Pamphlet","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1085"},{"id":408794,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YGDHIQ","text":"USGS data release","linkHelpText":"A bathymetric terrain model of multibeam sonar data collected between 2005 and 2018 along the Queen Charlotte fault system in the eastern Gulf of Alaska from Cross Sound, Alaska, to Queen Charlotte Sound, Canada"}],"country":"Canada, United States","state":"Alaska, British Columbia","otherGeospatial":"Queen Charlotte Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -140.92029001527425,\n 58\n ],\n [\n -140.92029001527425,\n 46.46240819189495\n ],\n [\n -124.69923324285543,\n 46.46240819189495\n ],\n [\n -124.69923324285543,\n 58\n ],\n [\n -140.92029001527425,\n 58\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543–1598
The Mount Blue Sky (formerly Mount Evans) 7.5’ quadrangle lies in Park and Clear Creek counties, Colorado, about 60 km west of Denver. The highest elevation in the quadrangle is 14,265 ft (4,348 m) at the top of Mount Blue Sky. The lowest is at about 9,200 ft (2,804 m) on Guanella Pass Road at the southern edge of the quadrangle. Bedrock directly underlies most of the map area, with surficial deposits primarily in the valleys. The geology of the quadrangle was previously mapped at 1:100,000 scale as part of a regional compilation by Kellogg and others (2008). The oldest rocks in the Mount Blue Sky 7.5-minute quadrangle are Paleoproterozoic metasedimentary rocks, and mafic to felsic metaigneous rocks (all units starting with ‘X’ on Plate 1). These rocks were metamorphosed under upper amphibolite facies conditions and intruded by Mesoproterozoic felsic igneous rocks of the ~1442 Ma Mount Blue Sky (YgR, Yt, Ygdm, Ymgm and ~1424 Ma Silver Plume (Yg) batholiths (Spurr and others, 1908; Tweto, 1897; Aleinikoff and others, 1993; du Bray and others, 2018) and, in the southern part of the quadrangle, by rocks that may also be part of the Mount Blue Sky batholith, but may alternatively interpreted as part of the ~1115 Ma to ~1066 Ma Pikes Peak batholith (Unruh and others, 1995; Guitreau and others, 2016). Four generations of folds affected the area. The oldest, F1 folds are isoclinal of various orientations, but primarily northerly-plunging in the southern part of the quadrangle (Mahatma, 2019; Mahatma and others, 2022). In the northern part of the quadrangle (Powell, 2020), open to close F2 chevron folds exist with various orientations. F3 folds in the northern part of the quadrangle are open to close with upright axial planes and plunges to the north and south, and in the southern part of the quadrangle they are open centimeter- to meter- scale northerly-plunging folds, possibly overprinted by another generation of northerly-plunging folds based on orientations of axial planes (F2 and F3 of Mahatma and others, 2022). F4 folds throughout the quadrangle are open to gentle with upright axial planes and shallow plunges to the east and west. The Mount Blue Sky batholith displays a pervasive moderately NW-dipping biotite-hornblende foliation (Fig. 1) in addition to a flow foliation near the margins, indicating NW-directed shortening after ~1442 Ma (Powell, 2020). The relationship between this foliation and the folds is not clear. Various joint sets are present in the area. The most pervasive joint set strikes 355°-020° and is subvertical. It is best developed in the western to southwestern part of the map area, and may be related to late Cenozoic extension associated with the Rio Grande Rift. Joint orientations are generally consistent with the trends of topographical lineaments. Surficial deposits include two series of glacial till deposits (Qtb and Qtp), and outwash (Qgp) deposits. They correlate with the Bull Lake (170-120 ka) and Pinedale (30-12 ka) glacial periods (Dahms, 2004) based on original depositional morphology, geomorphic and topographic position, deposit weathering and pedogenic properties. Possible older glacial deposits (Qti) have been observed along topographically higher surfaces.
","language":"English","publisher":"Colorado Geological Survey","usgsCitation":"Powell, L., Mahatma, A.A., Kuiper, Y., and Ruleman, C.A., 2022, Geologic map of the Mount Blue Sky (formerly Mount Evans) quadrangle, Clear Creek and Park Counties, Colorado: Open-File Report OF-22-11, 2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files.","productDescription":"2 Plates: 33.00 x 31.50 inches and 41.00 x 31.00 inches: Data Files","ipdsId":"IP-139573","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":413293,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":413292,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://coloradogeologicalsurvey.org/publications/geologic-map-mount-evans-quadrangle-clear-creek-park-colorado/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Mount Evans quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.75,\n 39.625\n ],\n [\n -105.75,\n 39.5\n ],\n [\n -105.625,\n 39.5\n ],\n [\n -105.625,\n 39.625\n ],\n [\n -105.75,\n 39.625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Powell, Logan 0000-0002-0528-3092 ljpowell@usgs.gov","orcid":"https://orcid.org/0000-0002-0528-3092","contributorId":299647,"corporation":false,"usgs":false,"family":"Powell","given":"Logan","email":"ljpowell@usgs.gov","affiliations":[{"id":64912,"text":"Colorado School of Mines MS Graduate","active":true,"usgs":false}],"preferred":false,"id":858245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahatma, Asha A.","contributorId":299648,"corporation":false,"usgs":false,"family":"Mahatma","given":"Asha","email":"","middleInitial":"A.","affiliations":[{"id":64913,"text":"Colorado School of Mines PhD Graduate","active":true,"usgs":false}],"preferred":false,"id":858246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuiper, Yvette 0000-0002-8506-8180","orcid":"https://orcid.org/0000-0002-8506-8180","contributorId":299649,"corporation":false,"usgs":false,"family":"Kuiper","given":"Yvette","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":858247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":858248,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70237964,"text":"ofr20221096 - 2022 - Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","interactions":[],"lastModifiedDate":"2023-09-18T20:04:08.872815","indexId":"ofr20221096","displayToPublicDate":"2022-11-01T08:50:41","publicationYear":"2022","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":"2022-1096","displayTitle":"Assessing the Efficacy of Using a Parentage-Based Tagging Survival Model to Evaluate Two Sources of Mortality for Juvenile Chinook Salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","title":"Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon","docAbstract":"We conducted a study to assess the efficacy of using a parentage-based tagging survival model (PBT N-mixture model) to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon. The model was originally developed to evaluate reservoir mortality because of predation from piscivorous fish. However, recent studies have also found that juvenile Chinook salmon experience high infection rates from parasitic copepods (Salmincola californiensis), which are known to negatively affect performance and survival. Our study was conducted to determine if the PBT N-mixture model could separately estimate mortality because of predation from non-native fish and mortality resulting from copepod infection. This assessment was conducted in two parts: (1) data collected in Lookout Point Reservoir during 2018 were re-analyzed; and (2) a simulation was conducted to evaluate a multi-year study that included inter-annual variation in copepod infection rate and two subsampling strategies (10 fish per month, 30 fish per month) to characterize monthly copepod infection rate. Results from each of these efforts suggest that the survival model is unlikely to provide reliable survival estimates for the two mortality sources that we evaluated. The re-analysis of 2018 data showed that “predation only” and “copepod only” models estimated a negative coefficient for the respective covariate, but the model that included both covariates provided coefficient estimates that differed from the other models and were highly uncertain. Similarly, the simulation results showed that most models failed to correctly estimate the magnitude and direction of mortality due to predation and copepods. These results suggest that additional data will be required if a model is desired that can separately estimate mortality effects due to both predation and copepods in the future. The existing data are limited by factors including low detection probabilities from previous field studies, existing uncertainties about copepod effects on mortality in a natural setting and expected limitations in the number of years that a field study could realistically be expected to receive funding.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221096","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hance, D.J., Kock, T.J., Perry, R.W., and Pope, A.C., 2022, Assessing the efficacy of using a parentage-based tagging survival model to evaluate two sources of mortality for juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon: U.S. Geological Survey Open-File Report 2022–1096, 14 p., https://doi.org/10.3133/ofr20221096.","productDescription":"v, 14 p.","onlineOnly":"Y","ipdsId":"IP-141621","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":408997,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1096/ofr20221096.XML"},{"id":408996,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1096/images"},{"id":408995,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221096/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1096"},{"id":408994,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1096/ofr20221096.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1096"},{"id":408993,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1096/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Lookout Point Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.84577497588536,\n 43.952222617898286\n ],\n [\n -122.84577497588536,\n 43.78093867902544\n ],\n [\n -122.51343855010415,\n 43.78093867902544\n ],\n [\n -122.51343855010415,\n 43.952222617898286\n ],\n [\n -122.84577497588536,\n 43.952222617898286\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
A collaborative acoustic telemetry study was conducted to describe behavior and movement patterns of juvenile green sturgeon (Acipenser medirostris) in the lower Sacramento River, California during 2016–19. For the study, juvenile green sturgeon were collected, tagged, and released in the Sacramento River between river kilometer (rkm) 467 and rkm 419 near Red Bluff, California. Telemetry monitoring sites were located between rkm 464 and rkm 1 to detect tagged fish that moved downstream. In this report, we describe movement patterns of juvenile green sturgeon in the lower Sacramento River between rkm 167 and rkm 52. In total, 98 juvenile green sturgeon were tagged and released during the study and 46 of these fish moved downstream and were detected in the lower Sacramento River. Downstream movement appeared to be associated with periods of increasing river flow, and the greatest percentage of tagged fish were detected moving downstream during the first period of increased streamflow each autumn. The number of tagged fish that were detected decreased in lower reaches of the study area, but it’s not clear if this was because fish experienced mortality while moving downstream, stopped moving downstream to rear in study reaches, or their transmitters stopped working due to battery life limitations. We did find that several fish were detected moving upstream between telemetry monitoring sites in the lower reaches of the study area. This study provides new insights into movement patterns and behavior of juvenile green sturgeon in the lower Sacramento River, but additional research will be required to better understand factors such as survival and how fish respond to estuarine conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221091","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansen, A.C., Chase, R.D., Kock, T.J., Perry, R.W., Gruber, J.J., and Poytress, W.R., 2022, Juvenile green sturgeon (Acipenser medirostris) movement during autumn and winter in the lower Sacramento River, California, 2016–20: U.S. Geological Survey Open-File Report 2022–1091, 17 p., https://doi.org/10.3133/ofr20221091.","productDescription":"vii, 17 p.","onlineOnly":"Y","ipdsId":"IP-139543","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":408893,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1091/ofr20221091.XML"},{"id":408892,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1091/images"},{"id":408890,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1091/ofr20221091.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1091"},{"id":408889,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1091/coverthb.jpg"},{"id":408891,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221091/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1091"}],"country":"United States","state":"California","otherGeospatial":"Lower Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.22303530664792,\n 37.892351455555556\n ],\n [\n -121.08045718164777,\n 37.892351455555556\n ],\n [\n -121.08045718164777,\n 38.64643627131957\n ],\n [\n -122.22303530664792,\n 38.64643627131957\n ],\n [\n -122.22303530664792,\n 37.892351455555556\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
A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 60th annual report of the River Master of the Delaware River. It covers the 2013 River Master report year, the period from December 1, 2012 to November 30, 2013.
During the report year, precipitation in the upper Delaware River Basin was 44.50 inches or 100 percent of the long-term average. Combined storage in the Pepacton, Cannonsville, and Neversink Reservoirs remained high until October 2013 when it decreased below 80 percent combined capacity. The lowest combined storage of the report year was 70.2 percent of combined capacity on November 26, 2013. Delaware River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program.
Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the Montague flow objective for the Delaware River at the Montague, New Jersey streamgage on 71 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were also made during the report year. An agreement was signed on July 16, 2013 to temporarily increase releases to provide thermal protection below Cannonsville Reservoir.
The quality of water in the Delaware River estuary between streamgages at Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at several locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221068","isbn":"978-1-4113-4486-0","usgsCitation":"DiFrenna, V.J., Andrews, W.J., Russell, K.L., Norris, J.M., and Mason, R.R., Jr., 2022, Report of the River Master of the Delaware River for the period December 1, 2012–November 30, 2013: U.S. Geological Survey Open-File Report 2022–1068, 99 p., https://doi.org/10.3133/ofr20221068.","productDescription":"xii, 99 p.","numberOfPages":"99","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-123834","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":501821,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113786.htm","linkFileType":{"id":5,"text":"html"}},{"id":408577,"rank":4,"type":{"id":31,"text":"Publication 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Office of the Delaware River Master
U.S. Geological Survey
120 Route 209 South
Milford, PA 18337
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) 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 ECCOE 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 7–8 for quarter 2 (April–June), 2022. 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.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was the lowering of the Landsat 7 orbit. On April 6, 2022, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor was placed into standby mode, and a series of spacecraft burns was completed throughout the month of April to lower the satellite’s orbit by 8 kilometers. Imaging resumed at the lower orbit of 697 kilometers on May 5, 2022, extending the science mission to allow for essential data to be acquired during the 2022 Northern Hemisphere fire and growing season. Additional information about the Landsat 7 orbit lowering is here:
https://www.usgs.gov/centers/eros/news/landsat-7-lowered-standard-landsat-orbit#:~:text=The%20satellite's%20primary%20science%20mission%20has%20ended&text=On%20April%206%2C%202022%2C%20the,satellite's%20orbit%20by%208%20kilometers.
Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Water, bed sediment, and invertebrate tissue were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the Clark Fork Basin. The sampling program was completed by the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, to characterize aquatic resources in the Clark Fork Basin and monitor trace elements associated with historical mining and smelting activities. Sampling sites were on the Clark Fork River and a subset of its tributaries. Water samples were collected periodically at 22 sites from October 2019 through September 2020. Bed-sediment and tissue samples were collected once at 12 sites during July 2020.
Water-quality data included concentrations of major ions, dissolved organic carbon, nitrogen (nitrate plus nitrite), trace elements, and suspended sediment. Daily values of turbidity were determined at four sites. Bed-sediment data included trace-element concentrations in the fine-grained (less than 0.063 millimeter) fraction. Biological data included trace-element concentrations in whole-body tissue of selected aquatic benthic invertebrates. Statistical summaries of water-quality, bed-sediment, and invertebrate tissue trace-element data for sites in the Clark Fork Basin were provided for the period of record: March 1985–September 2020.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221090","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Clark, G.D., Hornberger, M.I., Hepler, E.J., and Heinert, T.L., 2022, Water-quality, bed-sediment, and invertebrate tissue trace-element concentrations for tributaries in the Clark Fork Basin, Montana, October 2019–September 2020: U.S. Geological Survey Open-File Report 2022–1090, 17 p., https://doi.org/10.3133/ofr20221090.","productDescription":"Report: vii, 17 p.; Data Release; Dataset","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-138065","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":501834,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113781.htm","linkFileType":{"id":5,"text":"html"}},{"id":408546,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221090/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":408387,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":408386,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93BP9P8","text":"USGS data release","linkHelpText":"Results of water-quality, bed-sediment, and invertebrate tissue trace-element concentrations for tributaries in the Clark Fork Basin, Montana, October 2019– September 2020"},{"id":408385,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1090/images"},{"id":408384,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1090/ofr20221090.XML"},{"id":408383,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1090/ofr20221090.pdf","text":"Report","size":"0.97 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1090"},{"id":408381,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1090/coverthb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.67714251796224,\n 47.58172589143089\n ],\n [\n -115.67714251796224,\n 45.00795879114483\n ],\n [\n -111.56647259158387,\n 45.00795879114483\n ],\n [\n -111.56647259158387,\n 47.58172589143089\n ],\n [\n -115.67714251796224,\n 47.58172589143089\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
In this report, we apply the stream salmonid simulator (S3) to coho salmon (Oncorhynchus kisutch) in the Klamath River Basin by extending the original model to account for life history and disease dynamics specific to coho salmon. This version of S3 includes tracking of three separate life-history strategies representing the different time periods and ages at which fish leave natal tributaries such as the Scott and Shasta Rivers (age-0 spring, age-0 fall, or age-1 smolt). Once fish leave their natal tributaries and enter the Klamath River, the deterministic life-stage-structured population model simulates daily growth, movement, and survival. We extend the model to include non-natal tributary dynamics, where spring age-0 fish entry to non-natal tributaries is simulated based on environmental conditions in the main-stem Klamath River. Fish that use non-natal tributaries then reenter the Klamath River during the winter or spring as smolts and actively migrate downstream. We also consider the life history strategy where fish rear in natal tributaries and enter the Klamath River as age-1 smolts. In addition to simulating different life history pathways that coho salmon may take, we model disease dynamics, incorporating new information on Ceratonova shasta related infection and mortality. We incorporate competitive interactions between juvenile coho and Chinook salmon (Oncorhynchus tshawytscha) by simulating density-dependent movement dynamics in response to Chinook salmon abundance.
Model simulations suggest that total abundance and survival to the ocean differed between life-history strategies. In general, spring age-0 fish that leave their natal tributaries in their first spring had lower survival compared with fish that remained in natal tributaries and out-migrated later. Spring age-0 fish also had higher disease related mortality, owing to their residence in the main-stem Klamath River overlapping with periods of elevated C. shasta spore concentrations. Age-0 fish leaving their natal tributaries in the fall had near-zero disease related mortality. Most non-natal tributary use occurred at upstream tributary locations and was variable between the brood years depending on passage timing and environmental conditions. The inclusion of Chinook salmon in simulations resulted in decreased abundance and survival of Coho salmon reaching the ocean. In addition, we developed an R package to facilitate use of and continued development of S3 as a tool to guide management of juvenile salmonid populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221071","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Bureau of Reclamation","usgsCitation":"Dodrill, M.J., Perry, R.W., Som, N.A., Manhard, C.V., and Alexander, J.D., 2022, Extending the Stream Salmonid Simulator to accommodate the life history of coho salmon (Oncorhynchus kisutch) in the Klamath River Basin, Northern California: U.S. Geological Survey Open-File Report 2022–1071, 70 p., https://doi.org/10.3133/ofr20221071.","productDescription":"viii, 70 p.","onlineOnly":"Y","ipdsId":"IP-129401","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":408507,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1071/ofr20221071.XML"},{"id":408506,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1071/images"},{"id":408505,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221071/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1071"},{"id":408503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1071/coverthb.jpg"},{"id":408504,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1071/ofr20221071.pdf","text":"Report","size":"10.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1071"}],"country":"United States","state":"California","otherGeospatial":"Klamath River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.16748046874999,\n 41.071069130806414\n ],\n [\n -121.915283203125,\n 41.071069130806414\n ],\n [\n -121.915283203125,\n 42.037054301883806\n ],\n [\n -124.16748046874999,\n 42.037054301883806\n ],\n [\n -124.16748046874999,\n 41.071069130806414\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The Navajo (N) aquifer is an extensive aquifer and the primary source of groundwater in the 5,400-square-mile Black Mesa area in northeastern Arizona. Water availability is an important issue in the Black Mesa area because of the arid climate, past industrial water use, and continued water requirements for municipal use by a growing population. Precipitation in the area typically ranges from less than 6 to more than 16 inches per year depending on location.
The U.S. Geological Survey water-monitoring program in the Black Mesa area began in 1971 and provides information about the long-term effects of groundwater withdrawals from the N aquifer for industrial and municipal uses. This report presents results of data collected as part of the monitoring program in the Black Mesa area from calendar year 2019, and additionally uses streamflow statistics from November and December 2018. The monitoring program includes measurements of (1) groundwater withdrawals (pumping), (2) groundwater levels, (3) spring discharge, (4) surface-water discharge, and (5) groundwater chemistry.
In calendar year 2019, total groundwater withdrawals were estimated to be 3,070 acre-feet (acre-ft), industrial withdrawals were 670 acre-ft, and municipal withdrawals were estimated to be 2,400 acre-ft. Total withdrawals during 2019 were about 58 percent less than total withdrawals in 2005 because of Peabody Western Coal Company’s discontinued use of water to transport coal in a coal slurry pipeline after 2005 and cessation of mining operations in 2019.
Water levels measured in 2019 from wells completed in the unconfined areas of the N aquifer within the Black Mesa area showed a decline in 10 of 16 wells when compared with water levels from the prestress period (prior to 1965). The changes in water levels across all 16 wells ranged from +8.2 feet (ft) to −40.0 ft, and the median change was −1.7 ft. Water levels also showed decline in 16 of 18 wells measured in the confined area of the aquifer when compared to the prestress period. The median change for the confined area of the aquifer was −38.8 ft, with changes across all 18 wells ranging from +12.9 ft to −185.0 ft.
Spring flow was measured at four springs in 2019. Flow fluctuated during the period of record for Burro Spring and Pasture Canyon Spring, but a decreasing trend was statistically significant (p<0.05) at Moenkopi School Spring and Unnamed Spring near Dennehotso. Discharge at Burro Spring has remained relatively constant since it was first measured in the 1980s and discharge at Pasture Canyon Spring has fluctuated for the period of record.
Continuous records of surface-water discharge in the Black Mesa area were collected from streamflow-gaging stations at the following sites: Moenkopi Wash at Moenkopi 09401260 (1976 to 2019), Dinnebito Wash near Sand Springs 09401110 (1993 to 2019), Polacca Wash near Second Mesa 09400568 (1994 to 2019), and Pasture Canyon Springs 09401265 (2004 to 2019). Median winter flows (November through February) of each winter were used as an estimate of the amount of groundwater discharge at the above-named sites. For the period of record, the median winter flows have generally remained constant at Polacca Wash and Pasture Canyon Springs, whereas a decreasing trend was indicated at Moenkopi Wash and Dinnebito Wash.
In 2019, water samples collected from four springs and three wells in the Black Mesa area were analyzed for selected chemical constituents. Results from the four springs were compared with previous analyses from the same springs. Concentrations of dissolved solids, chloride, and sulfate increased at Moenkopi School Spring during the more than 30 years of record at that site. Concentrations of dissolved solids, chloride, and sulfate at Pasture Canyon Spring have not varied significantly (p>0.05) since the early 1980s, and there is no increasing or decreasing trend in those data. Concentrations of dissolved solids, chloride, and sulfate at Unnamed Spring near Dennehotso have varied for the period of record, but there is no statistical trend in the data. Concentrations of dissolved solids and chloride at Burro Spring have varied for the period of record, but there is no statistical trend in the data; however, concentrations of sulfate from Burro Spring now show a trend towards lower concentrations. No statistical trend tests were performed for the three wells sampled in 2019 since less historical water-quality data were available for comparison.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221086","collaboration":"Prepared in cooperation with the Navajo Nation and Peabody Western Coal Company","usgsCitation":"Mason, J.P., 2022, Groundwater, surface-water, and water-chemistry data, Black Mesa area, northeastern Arizona—2018–2019: U.S. Geological Survey Open-File Report 2022–1086, 47 p., https://doi.org/10.3133/ofr20221086.","productDescription":"vii, 47 p.","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-119897","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":501833,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113767.htm","linkFileType":{"id":5,"text":"html"}},{"id":408436,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211124","text":"Open-File Report 2021-1124","linkHelpText":"- Groundwater, Surface-Water, and Water-Chemistry Data, Black Mesa Area, Northeastern Arizona—2016–2018"},{"id":408427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1086/covrthb.jpg"},{"id":408428,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1086/ofr20221086.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022-1086"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.06054687499999,\n 34.94899072578227\n ],\n [\n -109.390869140625,\n 34.94899072578227\n ],\n [\n -109.390869140625,\n 36.96744946416934\n ],\n [\n -112.06054687499999,\n 36.96744946416934\n ],\n [\n -112.06054687499999,\n 34.94899072578227\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Bathymetric and topographic data were collected from May 2013 to February 2016 along the 15.84-mile reach of the Colorado River spanning from Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona. Channel bathymetry was mapped using multibeam and singlebeam echo sounders; subaerial topography was mapped using a combination of ground-based total stations and aerial photogrammetry. These data were combined to produce a digital elevation model (DEM), spatially variable estimates of DEM uncertainty, and bed-substrate distribution maps. This project is part of a larger effort to monitor the status and trends of sand storage along the Colorado River in Glen Canyon National Recreation Area and Grand Canyon National Park. This report documents the study methodologies (survey methods and post-processing procedures, DEM production and uncertainty assessment, and bed-substrate classification) and presents the resulting datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221057","collaboration":"Prepared in cooperation with Northern Arizona University and Marda Science LLC","usgsCitation":"Kaplinski, M., Hazel, J.E., Jr., Grams, P.E., Gushue, T., Buscombe, D.D., and Kohl, K., 2022, Channel mapping of the Colorado River from Glen Canyon Dam to Lees Ferry in Glen Canyon National Recreation Area, Arizona: U.S. Geological Survey Open-File Report 2022-1057, 20 p., https://doi.org/10.3133/ofr20221057.","productDescription":"Report: v, 20 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-120853","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":408061,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1057/ofr20221057.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 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The reservoir, located under a semi-tropical climate, is the principal water supply for the city of Charleston, South Carolina, and the surrounding areas including the Bushy Park Industrial Complex. Although there was an adequate supply of freshwater in the reservoir in 2022, water-quality concerns are present over taste-and-odor and saltwater-intrusion issues. From 2013 to 2015, the U.S. Geological Survey (USGS), in cooperation with the Charleston Water System, engaged in a multi-year study of the hydrology and hydrodynamics of Bushy Park Reservoir to better understand factors affecting water-quality conditions in the reservoir. As part of this study, Charleston Water System worked with Tetra Tech, Inc., a consulting and engineering firm, to develop a Bushy Park Reservoir hydrodynamic and water-quality modeling framework, built upon earlier efforts by both Tetra Tech and the U.S. Army Corps of Engineers. At the completion of the new modeling framework, the USGS was requested to evaluate the calibrated hydrodynamic and water-quality model.
The Bushy Park Reservoir Environmental Fluid Dynamics Code (EFDC) model was calibrated for the time period from January 1, 2012, to December 31, 2015. The general modeling approach for the newly revised modeling framework, as briefly detailed in this report, was developed with EFDC. The EFDC is a grid-based modeling package that can simulate three-dimensional flow, transport, and water quality in surface-water systems. This report evaluated the capacity of Tetra Tech’s Bushy Park EFDC model to simulate water discharge, water circulation, surface elevations, temperature, salinity, and other water-quality parameters.
The USGS model review focused specifically on the following criteria: (1) determine if the model, with additional effort, could be developed into an adequate planning tool for Bushy Park Reservoir; (2) assess the capacity of the model to specifically address water-quality issues in the reservoir related to taste-and-odor and saltwater intrusions; and, (3) evaluate three preliminary water-management scenarios related to reduced water withdrawals in the reservoir and the effect on saltwater intrusion.
Overall, the model was able to simulate discharge, flow velocity, and water-surface elevations with generally good agreement between the simulated and measured values. Specifically, the model was able to demonstrate good agreement for discharge at two USGS continuous discharge locations (USGS station 02172002; USGS station 02172040), with Wilmott index of agreements of 0.86 and 0.75, respectively. A total of seven USGS streamgages, located on the West Branch of the Cooper River, Durham Canal, and the Cooper River, were available for water-surface elevations, with index of agreements ranging from 0.74 to 0.99. However, model-simulated water-surface elevation ranges were appreciably high (compared to measured ranges) for two locations near Pinopolis Dam, farthest upstream on the West Branch of the Cooper River. This result may indicate that too much simulated tidal energy propagated through the model domain.
For water temperature, 16 calibration stations were available for at least part of the 4-year simulation. The index of agreement range for temperature comparisons was from 0.95 to 1.00, indicating excellent agreement between the measured and simulated results. One of the primary future applications for the Bushy Park Reservoir EFDC model is to determine the extent of saltwater intrusions. A wide range in the salinity prediction quality was simulated with the model. The prediction quality ranged from an index of agreement of 0.15 at Cooper River approximately 2.75 miles southeast of the Tee, South Carolina, to 0.92 at West Branch Cooper River near Moncks Corner, South Carolina. Although the model did not accurately simulate some of the larger salinity deviations resulting during individual hydrologic events, the seasonal salinity trends were adequately simulated with the model during the study period (2012–15). Therefore, it may be difficult to simulate extreme hydrologic events, such as during large storms, where high salinity water is exchanged with Bushy Park Reservoir. There was agreement in model simulation with the measured data either on the quantitative index of agreement values or qualitative agreement in the seasonal salinity data trends.
For water quality, the index of agreement values were generally low for total nitrogen, ammonia, nitrate, total Kjeldahl nitrogen, total phosphorus, and orthophosphate. Although general trends were adequately simulated at specific stations, particularly for Bushy Park Reservoir, the model-simulated fit was low across all the constituents described above with index of agreements usually below 0.50. A limitation for simulating nutrient concentrations across the model domain was the lack of characterization for the constituents directly entering Bushy Park Reservoir, or the lack of data directly attributed to the boundary condition (for example, the Cooper River). The other two calibrated water-quality constituents (besides the nutrients mentioned above) were dissolved oxygen and chlorophyll a. Dissolved oxygen varied from index of agreement values from 0.58 to 0.94 for 11 stations, generally indicating agreement with the available measured data. Chlorophyll a, calibrated for seven stations, had a wider range from 0.11 to 0.74 for the index of agreement.
With the current modeling framework, taste-and-odor events, related to cyanobacterial blooms, cannot be directly simulated. However, indirect estimates of cyanobacteria concentrations may be obtained by using the chlorophyll a model outputs, which represent total phytoplankton biomass, and the phytoplankton biovolume data by group (diatoms, green algae, cyanobacteria and others) collected from 2012 to 2015. For the Bushy Park Reservoir modeling framework to be used directly for taste-and-odor issues, cyanobacteria must be simulated and calibrated based on observations of cyanobacteria biomass concentrations. In addition to the cyanobacteria sampling conducted within the reservoir between 2012 and 2015, the new model calibration would also require new algae biomass data-collection efforts to characterize the external sources of cyanobacteria entering the Bushy Park Reservoir from tributaries, as well as the internal cycling, production, and decay of cyanobacteria in the hydrologic system.
Further improvements to the EFDC model would include expanding the collection of boundary condition datasets, such as water-quality monitoring to determine improved nutrient loads into the model domain. Along with improved water-quality monitoring for the major boundary conditions, continuous discharge, for both Foster Creek and the Back River, would further constrain the flow balance and the loads into Bushy Park Reservoir. In addition to better boundary-condition characterization, it is important to better characterize possible shortcomings specifically to the model domain, such as the grid resolution, bathymetry, and numerical hydrodynamic errors. Further consideration of the model may involve a sensitivity analysis to determine if errors in the simulation outputs, such as discharge, water-surface elevations, and salinity, were more likely caused by poor boundary condition characterization or, specifically, the model setup.
Three model scenarios were run with the revised Bushy Park Reservoir model: (1) reduced withdrawals from one of the large intake-discharge locations for Bushy Park Reservoir, the Williams Station; (2) elevated (above background levels) ocean water level causing saltwater intrusion from the ocean through Durham Canal into Bushy Park Reservoir; and (3) overtopping of the Back River Dam at the southernmost end of Bushy Park Reservoir. For the reduced withdrawals scenarios, the largest shift in flow resulted near the Williams Station intake, with the next largest flow change at the southern end of Bushy Park Reservoir, and a net increase in flow out of the Bushy Park Reservoir to the Cooper River by way of the Durham Canal. The effect resulting from scenario 3 on water quality and salinity was small, with larger increases for dissolved oxygen than other constituents at several monitoring stations. For the two scenarios related to saltwater intrusion (including dam overtopping), the changes in salinity generally were found to dissipate in the following 2 weeks and generally back to baseline salinity conditions within 3 months. This result did vary depending on the severity of the storm or length of the dam overtopping event.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221079","collaboration":"Prepared in cooperation with Charleston Water System","usgsCitation":"Smith, E.A., Akasapu-Smith, M., Petkewich, M.D., and Conrads, P.A., 2022, Evaluation of the Bushy Park Reservoir three-dimensional hydrodynamic and water-quality model, South Carolina, 2012–15: U.S. Geological Survey Open-File Report 2022–1079, 35 p., https://doi.org/10.3133/ofr20221079.","productDescription":"Report: ix, 35 p.; Data Release","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087955","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501828,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113612.htm","linkFileType":{"id":5,"text":"html"}},{"id":407629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1079/coverthb.jpg"},{"id":407630,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1079/ofr20221079.pdf","text":"Report","size":"5.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1079"},{"id":407632,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1079/ofr20221079.XML"},{"id":407633,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1079/images/"},{"id":407634,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NG4NVX","text":"USGS data release","linkHelpText":"Water quality data for Bushy Park Reservoir, South Carolina 2013–2015"},{"id":407631,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221079/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1079"}],"country":"United States","state":"South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.39794921875,\n 32.676372772089806\n ],\n [\n -79.661865234375,\n 32.676372772089806\n ],\n [\n -79.661865234375,\n 33.458942753687616\n ],\n [\n -80.39794921875,\n 33.458942753687616\n ],\n [\n -80.39794921875,\n 32.676372772089806\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
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720 Gracern Road, Suite 129
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Landslide hazards are present in all 50 States and most U.S. territories, and they affect lives, property, infrastructure, and the environment. Landslides are the downslope movement of earth materials under the force of gravity. They can occur without any obvious trigger. Widespread or severe landslide events are often driven by such hazards as hurricanes, earthquakes, volcanic eruptions, heavy rain events, flooding, and wildfires. Landslides can also cause their own cascading consequences, such as the spread of hazardous materials or the creation of devastating local tsunamis.
This strategy document describes goals and strategic actions of a comprehensive strategy to meet key challenges to reducing the Nation’s risk from landslide hazards equitably and effectively. The document follows the direction of the National Landslide Preparedness Act (Public Law 116–323) by presenting a strategy for addressing landslide hazards, including risk reduction and response. The act directs the Department of the Interior to establish a program that will work with State, Tribal, and local governments as well as with academia, the private sector, community-based groups, and nonprofit organizations to identify landslide hazards and risk and improve communication, coordination, and emergency preparedness, with the objective of reducing landslide losses. As the only Federal program dedicated to landslide hazard science, the U.S. Geological Survey’s Landslide Hazards Program will lead and coordinate many of the efforts described in this strategy document. Landslide hazard risk reduction must be undertaken collectively and collaboratively across the Federal Government. This strategy document will provide a framework for the creation of an interagency management plan that describes the programs, projects, workforce, and budgets required to carry out the national strategy.
The strategy outlined in this document presents a vision of how to equitably produce, communicate, and apply landslide data and science to support a broad range of land management, infrastructure, planning, and emergency response decisions. These decisions are made by a variety of actors, including private and nonprofit landholders; State, Tribal, territorial, city, and county planners; emergency managers; engineers; infrastructure managers; Federal agencies and their partners; and community leaders and individuals. Supporting those decisions and reducing the Nation’s vulnerability to landslides requires overcoming three main challenges: (1) gaps in basic information needed to describe and understand landslide occurrence and societal risk, (2) difficulty in accurately mapping and forecasting landslide hazards, and (3) communication and coordination among the many jurisdictions and sectors that have responsibility for and interest in reducing landslide losses. To address those challenges, this strategy document puts forward a series of strategic actions to achieve four goals:
These strategic actions focus on expanding the knowledge of societal risk posed by landslides as well as better understanding of where, when, and why they occur. They focus on applying that knowledge to support landslide risk reduction efforts and decisions, including the establishment of new advisory, coordination, and working groups focused on landslide hazard and risk. They take into account that supporting landslide loss reduction decisions also requires new guidance, tools, and training codeveloped with the entities, organizations, and individuals faced with making those decisions. Finally, they address actions needed to support and expand landslide warning information and improve the technical response to landslide emergencies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221075","programNote":"USGS Landslide Hazards Program","usgsCitation":"Godt, J.W., Wood, N.J., Pennaz, A.B., Dacey, C.M., Mirus, B.B, Schaefer, L.N., and Slaughter, S.L., 2022, National strategy for landslide loss reduction: U.S. Geological Survey Open-File Report 2022–1075, 36 p., https://doi.org/10.3133/ofr20221075.","productDescription":"viii, 36 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-136128","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":405658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1075/ofr20221075.pdf","text":"Report","size":"3.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Natural Hazards Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Collection of accurate suspended-sediment data using depth-integrating samplers requires that they operate isokinetically, that is, that they sample at the local stream velocity unaffected by the presence of the suspended-sediment sampler. Sub-isokinetic suspended-sediment sampling causes grain-size dependent positive biases in the suspended-sediment concentration measured by the suspended-sediment sampler. Collapsible bag suspended-sediment samplers like the US D-96 and the lighter US D-96-A1 depth-integrating samplers have shown a tendency to sample sub-isokinetically under low stream velocities (below ~3.5 feet per second), colder water temperatures, and longer sampling durations. Previous work concluded that the time-dependent decrease in the intake efficiency of the US D-96-type sampler could be partially overcome by increasing the venting of water from the sampler cavity by shortening the sampler tray. The standard-length sampler tray partially blocks the rear vent hole; shortening the sampler tray effectively increases the area of the sampler-cavity rear vent hole. This previous work showed that removing the partial blockage of the rear vent hole caused by the sampler tray resulted in both an increase in intake efficiency and a decrease in the positive bias in measured suspended-sand concentration.
Herein, a series of tests were conducted on the Colorado River in Arizona using different modifications to a US D-96-A1 sampler to see if physical enlargement of the rear vent hole would produce further improvements in intake efficiency. Results from these tests show that physical enlargement of the rear vent hole, beyond that already effectively achieved by shortening the sampler tray, did not result in any further improvement in intake efficiency. However, these tests also indicated that physically increasing the area of the rear vent hole did not affect the suspended-sediment data collected by the US D-96-A1 sampler. Furthermore, comparisons of suspended-sediment data collected using the US D-96-A1 sampler and the isokinetic US P-61-A1 point-integrating sampler show that the suspended-sediment data collected by the US D-96-type sampler can be accurate in certain circumstances despite the tendency of this sampler to sample sub-isokinetically over the entire depth of a sampling vertical. We surmise that this result could arise from the US D-96-A1 sampler collecting sample isokinetically when the water-sediment mixture enters the nozzle, but that the water-sediment mixture only enters the nozzle intermittently while the sampler transits a sampling vertical.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221077","usgsCitation":"Sabol, T.A., Topping, D.J., Griffiths, R.E., and Dramais, G., 2022, Field investigation of sub-isokinetic sampling by the US D-96-type suspended-sediment sampler and its effect on suspended-sediment measurements: U.S. Geological Survey Open-File Report 2022-1077, 14 p., https://doi.org/10.3133/ofr20221077.","productDescription":"v, 14 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-127691","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501827,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113586.htm","linkFileType":{"id":5,"text":"html"}},{"id":407352,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1077/ofr20221077.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1077"},{"id":407351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1077/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.58950805664062,\n 36.830722025409784\n ],\n [\n -111.54144287109375,\n 36.830722025409784\n ],\n [\n -111.54144287109375,\n 36.88236678807325\n ],\n [\n -111.58950805664062,\n 36.88236678807325\n ],\n [\n -111.58950805664062,\n 36.830722025409784\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.38714599609375,\n 35.755149755962755\n ],\n [\n -113.33358764648438,\n 35.755149755962755\n ],\n [\n -113.33358764648438,\n 35.777435736805614\n ],\n [\n -113.38714599609375,\n 35.777435736805614\n ],\n [\n -113.38714599609375,\n 35.755149755962755\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Passive membrane samplers—semipermeable membrane devices and polar organic chemical integrative samplers—were deployed for 22 continuous days at 7 sites along the West Maui, Hawaiʻi, coastline in February and March 2017 to assess organic contaminants at shallow coral reef ecosystems from diverse upstream inputs. The distribution of organic compounds observed at these coastal sites showed considerable variability; high concentrations of microbially sourced organic compounds observed at all sites, with pentadecane as the predominant normal alkane, showed the relative importance of marine and microbial organic matter to the coastal carbon pool. Pharmaceuticals and personal care products, as well as flame retardants, were also detected at all sites. Of the seven sites sampled, the Kahekili Beach Park site had the highest number of unique contaminants and the Honokōwai Stream site had the highest concentrations of compounds. Two individual compounds, a flame retardant and a fragrance, were ubiquitous across the studied West Maui reefs, including at the least-developed site. A direct correlation to upstream land-use practices or legacy agricultural inputs was not readily observed since polychlorinated biphenyls, pesticides, herbicides, or insecticides were not detected. Results provide a snapshot of relative contaminant abundances as well as inputs to select nearshore environments along the West Maui coastline captured during the 2017 wet season, which was drier than expected. These data can be useful for understanding the range of stressors potentially affecting nearshore ecosystems, such as groundwater inputs and watershed runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221065","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the State of Hawai‘i Department of Health","usgsCitation":"Campbell, P.L., Prouty, N.G., and Storlazzi, C.D., 2022, Pharmaceuticals and personal care products in passive samplers at seven coastal sites off West Maui, Hawaiʻi: U.S. Geological Survey Open-File Report 2022–1065, 14 p., https://doi.org/10.3133/ofr20221065.","productDescription":"Report: vii, 12 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-132890","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501819,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113585.htm","linkFileType":{"id":5,"text":"html"}},{"id":435674,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZFE0OP","text":"USGS data release","linkHelpText":"Pharmaceuticals and personal care products measured in passive samplers at seven coastal sites off West Maui during February and March 2017"},{"id":407356,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1065/ofr20221065.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1065"},{"id":407355,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1065/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.708984375,\n 20.78693059257028\n ],\n [\n -156.5826416015625,\n 20.78693059257028\n ],\n [\n -156.5826416015625,\n 21.04349121680354\n ],\n [\n -156.708984375,\n 21.04349121680354\n ],\n [\n -156.708984375,\n 20.78693059257028\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Coastal communities in Alaska are undergoing rapid environmental change from increasing temperatures and baseline data are needed to monitor potential impacts. We conducted the first surveys of the abundance and distribution of eelgrass (Zostera marina) and seaweeds in the western part of Izembek National Wildlife Refuge at the end of the Alaska Peninsula. Six embayments and two offshore islands were surveyed in August–September of 2012. Biotic (percent cover of eelgrass/seaweeds, presence/absences of five sessile invertebrates), and abiotic (water temperature, salinity, and depth) data were recorded at 257 survey points (range =9–74 points per site) across all sites. Twenty-two genera/species of seaweeds were identified at the six embayments. New seaweed species for the offshore islands of Sanak and Caton were added to an existing seaweed collection accessioned at the University of British Columbia Herbarium. We also collected samples of eelgrass to be accessioned at U.S. Geological Survey, Alaska Science Center-Molecular Ecology Laboratory, for future genetic analyses. Fifty-three species of birds and 13 species of mammals were observed and recorded during the survey period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211034","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., Hogrefe, K.R., Donnelly, T.F., Dau, N.C., Lind, O., Payne, K.J., and Lindstrom, S.C., 2022, Inventory of eelgrass (Zostera marina) and seaweeds at the end of the Alaska Peninsula, August–September 2012: U.S. Geological Survey Open-File Report 2021–1034, 14 p., https://doi.org/10.3133/ofr20211034.","productDescription":"Report: iv, 14 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-118597","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":405872,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K1ZOMY","text":"USGS data release","description":"USGS data release","linkHelpText":"Point sampling data from eelgrass (Zostera marina), seaweeds and selected invertebrates at six embayments and two islands at the end of the Alaska Peninsula"},{"id":405873,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201035","text":"OFR 2020-1035 —","description":"OFR 2020-1035","linkHelpText":"Abundance and distribution of eelgrass (Zostera marina) and seaweeds at Izembek National Wildlife Refuge, Alaska, 2007–10"},{"id":405874,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201080","text":"OFR 2020-1080 —","description":"OFR 2020-1080","linkHelpText":"Distribution of eelgrass (Zostera marina) in coastal waters adjacent to Togiak National Wildlife Refuge, Alaska"},{"id":405870,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1034/coverthb.jpg"},{"id":405871,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1034/ofr20211034.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1034"},{"id":405875,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201144","text":"OFR 2020-1144 —","description":"OFR 2020-1144","linkHelpText":"Eelgrass (Zostera marina) and seaweed assessment Alaska Peninsula-Becharof National Wildlife Refuges, 2010"},{"id":405876,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201114","text":"OFR 2020-1114 —","description":"OFR 2020-1114","linkHelpText":"Eelgrass (Zostera marina) and Seaweed Abundance along the Coast of Togiak National Wildlife Refuge, Alaska, 2008–10"},{"id":405877,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201143","text":"OFR 2020-1143 —","description":"OFR 2020-1143","linkHelpText":"Eelgrass (Zostera marina) and seaweed abundance along the coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165.10253906249997,\n 53.98193516209167\n ],\n [\n -161.0595703125,\n 53.98193516209167\n ],\n [\n -161.0595703125,\n 56.19448087726972\n ],\n [\n -165.10253906249997,\n 56.19448087726972\n ],\n [\n -165.10253906249997,\n 53.98193516209167\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508