Transient, acutely toxic concentrations of pesticides in streams can go undetected by fixed-interval sampling programs. Here we compare temporal patterns in occurrence of current-use pesticides in daily composite samples to those in weekly composite and weekly discrete samples of surface water from 14 small stream sites. Samples were collected over 10–14 weeks at 7 stream sites in each of the Midwestern and Southeastern United States. Samples were analyzed for over 200 pesticides and degradates by direct aqueous injection liquid chromatography with tandem mass spectrometry. Nearly 2 and 3 times as many unique pesticides were detected in daily samples as in weekly composite and weekly discrete samples, respectively. Based on exceedances of acute-invertebrate benchmarks (AIB) and(or) a Pesticide Toxicity Index (PTI) >1, potential acute-invertebrate toxicity was predicted at 11 of 14 sites from the results for daily composite samples, but was predicted for only 3 sites from weekly composites and for no sites from weekly discrete samples. Insecticides were responsible for most of the potential invertebrate toxicity, occurred transiently, and frequently were missed by the weekly discrete and composite samples. The number of days with benthic-invertebrate PTI ≥0.1 in daily composite samples was inversely related to Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness at the sites. The results of the study indicate that short-term, potentially toxic peaks in pesticides frequently are missed by weekly discrete sampling, and that such peaks may contribute to degradation of invertebrate community condition in small streams. Weekly composite samples underestimated maximum concentrations and potential acute-invertebrate toxicity, but to a lesser degree than weekly discrete samples, and provided a reasonable approximation of the 90th percentile total concentrations of herbicides, insecticides, and fungicides, suggesting that weekly composite sampling may be a compromise between assessment needs and cost.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.136795","usgsCitation":"Norman, J.E., Mahler, B., Nowell, L.H., Van Metre, P.C., Sandstrom, M.W., Corbin, M.A., Qian, Y., Pankow, J.F., Luo, W., Fitzgerald, N.B., Asher, W.E., and McWhirter, K.J., 2020, Daily stream samples reveal highly complex pesticide occurrence and potential toxicity to aquatic life: Science of the Total Environment, v. 715, 136795, 13 p., https://doi.org/10.1016/j.scitotenv.2020.136795.","productDescription":"136795, 13 p.","ipdsId":"IP-101574","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"links":[{"id":458098,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.136795","text":"Publisher Index Page"},{"id":437156,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N2A3LS","text":"USGS data release","linkHelpText":"Pesticides in Daily and Weekly Water Samples from the NAWQA Midwest and Southeast Stream Quality Assessments (2013-2014)"},{"id":371960,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ja/70208295/coverthb.jpg"}],"volume":"715","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Julia E. 0000-0002-2820-6225 jnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2820-6225","contributorId":3832,"corporation":false,"usgs":true,"family":"Norman","given":"Julia","email":"jnorman@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":781297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":781298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":781306,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corbin, Mark A.","contributorId":222126,"corporation":false,"usgs":false,"family":"Corbin","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":781300,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Qian, Yaorong","contributorId":176739,"corporation":false,"usgs":false,"family":"Qian","given":"Yaorong","email":"","affiliations":[],"preferred":false,"id":781301,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pankow, James F. 0000-0002-8602-9159","orcid":"https://orcid.org/0000-0002-8602-9159","contributorId":222127,"corporation":false,"usgs":false,"family":"Pankow","given":"James","email":"","middleInitial":"F.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781302,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luo, Wentai 0000-0003-3421-4958","orcid":"https://orcid.org/0000-0003-3421-4958","contributorId":222128,"corporation":false,"usgs":false,"family":"Luo","given":"Wentai","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781303,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fitzgerald, Nicholas B.","contributorId":222131,"corporation":false,"usgs":false,"family":"Fitzgerald","given":"Nicholas","email":"","middleInitial":"B.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781307,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Asher, William E.","contributorId":222129,"corporation":false,"usgs":false,"family":"Asher","given":"William","email":"","middleInitial":"E.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781304,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"McWhirter, Kevin J.","contributorId":222130,"corporation":false,"usgs":false,"family":"McWhirter","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":781305,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70217377,"text":"70217377 - 2020 - The transformative impact of genomics on sage-grouse conservation and management","interactions":[],"lastModifiedDate":"2021-01-20T16:21:34.219524","indexId":"70217377","displayToPublicDate":"2020-01-18T10:16:17","publicationYear":"2020","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The transformative impact of genomics on sage-grouse conservation and management","docAbstract":"For over two decades, genetic studies have been used to assist in the conservation and management of both Greater Sage-grouse (Centrocercus urophasianus) and Gunnison Sage-grouse (C. minimus), addressing a wide variety of topics including taxonomy, parentage, population connectivity, and demography. The field of conservation genetics has been transformed by dramatic improvements in sequencing technology, facilitating genomic studies in many wildlife species. The quality and amount of data generated by genomic methods vastly exceed that of traditional genetic studies, allowing for increased precision in estimating genetic parameters of interest. Perhaps more importantly, genomic methods can provide insight into non-neutral evolution such as adaptive divergence. Here we recount the shift from genetic to genomic methods using two wildlife species of substantial conservation interest, focusing on the improved capabilities and advantages of genomic methods. For instance, reassessment of divergence in sage-grouse using genomic methods confirmed strong differentiation between the two species and revealed that a small population in the state of Washington was more genetically distinct than previously recognized. Further, new genomic resources and approaches have been used to identify a family of genes linked to local dietary adaptation suggesting that sage-grouse may possess digestive and metabolic adaptations that mitigate the effects of consuming plant secondary metabolites like those found in sagebrush. Genetic variation among populations in these gene regions is thought to be involved with local dietary adaptations, and therefore maintaining the tie between sage-grouse and the chemistry of local sagebrush may be an important management consideration. We posit that the integration of newly developed genomic resources combined with the vast wealth of ecological and behavioral data for sage-grouse has the potential to shed light on mechanistic relationships that ultimately are vital to the conservation and management of these species.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Population genomics: Wildlife","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/13836_2019_65","usgsCitation":"Oyler-McCance, S.J., Oh, K., Zimmerman, S., and Aldridge, C., 2020, The transformative impact of genomics on sage-grouse conservation and management, chap. of Population genomics: Wildlife, p. 523-546, https://doi.org/10.1007/13836_2019_65.","productDescription":"24 p.","startPage":"523","endPage":"546","ipdsId":"IP-094749","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":382323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2020-01-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":808550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oh, Kevin P","contributorId":223092,"corporation":false,"usgs":false,"family":"Oh","given":"Kevin P","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":808551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zimmerman, Shawna J","contributorId":139402,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Shawna J","affiliations":[{"id":6737,"text":"Colorado State University, Department of Ecosystem Science and Sustainability, and Natural Resource Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":808552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":213471,"corporation":false,"usgs":false,"family":"Aldridge","given":"Cameron L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":808553,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70229397,"text":"70229397 - 2020 - Effect of environmental factors on the movement of Rainbow Trout in the Deerfield Reservoir System","interactions":[],"lastModifiedDate":"2022-03-11T17:11:48.638861","indexId":"70229397","displayToPublicDate":"2020-01-18T09:49:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10384,"text":"Journal of FisheriesSciences.com","active":true,"publicationSubtype":{"id":10}},"title":"Effect of environmental factors on the movement of Rainbow Trout in the Deerfield Reservoir System","docAbstract":"Spawning movements and the factors affecting those movements are often of interest to fisheries managers and biologists. The objective of this study was to examine the influence of environmental factors on the movements of an adfluvial Rainbow Trout Oncorhynchus mykiss population in the Black Hills, South Dakota. Three unique strains of hatchery-reared Rainbow Trout and resident Rainbow Trout were implanted with passive integrated transponder (PIT) tags and movements between Deerfield Reservoir and the Castle Creek tributary system were monitored from August, 2010-July, 2011. Initial adfluvial movements of Rainbow Trout were detected using a stationary PIT tag reader deployed near the mouth of Castle Creek. Multiple linear regressions were used to model the relationship between PIT tagged Rainbow Trout movement and water temperature, photoperiod, and discharge. Using Akaike’s information criterion (AIC) to compare models, discharge was the top supported model explaining variation in Rainbow Trout movement. Additionally, models containing temperature and photoperiod were also supported. Supported models only explained moderate levels of variation (<23%) in Rainbow Trout movement. Understanding how environmental variables affect the movement patterns of this unique population is essential in determining the proper management strategy for the Deerfield Reservoir system.
","language":"English","publisher":"IMed Pub LTD","usgsCitation":"Kientz, J., Davis, J., Chipps, S.R., and Simpson, G., 2020, Effect of environmental factors on the movement of Rainbow Trout in the Deerfield Reservoir System: Journal of FisheriesSciences.com, v. 14, no. 1, p. 1-6.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-124673","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":397026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":397024,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fisheriessciences.com/fisheries-aqua/effect-of-environmental-factors-on-the-movement-of-rainbow-trout-in-the-deerfield-reservoir-system.php?aid=26132"}],"country":"United States","state":"South Dakota","otherGeospatial":"Castle Creek, Deerfield Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.8398551940918,\n 44.00158219755276\n ],\n [\n -103.8017463684082,\n 44.00158219755276\n ],\n [\n -103.8017463684082,\n 44.02726038819847\n ],\n [\n -103.8398551940918,\n 44.02726038819847\n ],\n [\n -103.8398551940918,\n 44.00158219755276\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kientz, Jeremy","contributorId":205425,"corporation":false,"usgs":false,"family":"Kientz","given":"Jeremy","email":"","affiliations":[{"id":37104,"text":"South Dakota Department of Game, Fish and Parks","active":true,"usgs":false}],"preferred":false,"id":837832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Jacob L.","contributorId":275831,"corporation":false,"usgs":false,"family":"Davis","given":"Jacob L.","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":837833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":837273,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simpson, Gregory","contributorId":288393,"corporation":false,"usgs":false,"family":"Simpson","given":"Gregory","email":"","affiliations":[{"id":56698,"text":"South Dakota Department of Game, Fish, and Parks","active":true,"usgs":false}],"preferred":false,"id":837834,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207892,"text":"sim3449 - 2020 - High-resolution airborne geophysical survey of the Shellmound, Mississippi area","interactions":[],"lastModifiedDate":"2022-04-22T20:07:01.788312","indexId":"sim3449","displayToPublicDate":"2020-01-17T16:20:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3449","displayTitle":"High-Resolution Airborne Geophysical Survey of the Shellmound, Mississippi Area","title":"High-resolution airborne geophysical survey of the Shellmound, Mississippi area","docAbstract":"In late February to early March 2018, the U.S. Geological Survey acquired 2,364 line-kilometers (km) of airborne electromagnetic, magnetic, and radiometric data in the Shellmound, Mississippi study area. The purpose of this survey is to contribute high-resolution information about subsurface geologic structure to inform groundwater models, water resource infrastructure studies, and local decision making. The Shellmound region hosts a managed aquifer recharge (MAR) pilot project, developed by the Agricultural Research Service of the U.S. Department of Agriculture. The MAR pilot project is investigating the use of bank filtration along the Tallahatchie River as a source for recharge in areas of significant groundwater decline. Direct injection into the Mississippi River Valley Alluvial aquifer (MRVA) occurs about 3 km from the extraction gallery. Understanding the structure of the aquifer, including both shallow and deep confining units, is important for the success of this pilot MAR study and may be even more important for potential future large-scale MAR projects and groundwater model development efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3449","usgsCitation":"Burton, B.L., Minsley, B.J., Bloss, B.R., Kress, W.H., Rigby, J.R., and Smith, B.D., 2020, High-resolution airborne geophysical survey of the Shellmound, Mississippi area: U.S. Geological Survey Scientific Investigations Map 3449, 2 sheets, https://doi.org/10.3133/sim3449.","productDescription":"2 Sheets: 28.09 x 21.01 inches and 29.96 x 24.19 inches; Data Release; ReadMe","onlineOnly":"Y","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":399521,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109607.htm"},{"id":371340,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D4EA9W","text":"USGS data release","linkHelpText":"Airborne electromagnetic, magnetic, and radiometric survey, Shellmound, Mississippi, March 2018"},{"id":371339,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3449/sim3449_ReadMe.txt","text":"Read Me","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3449 Read Me"},{"id":371338,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3449/sim3449_sheet2.pdf","text":"Sheet 2—","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3449 Sheet 2","linkHelpText":"High-Resolution Airborne Geophysical Survey of the Shellmound, Mississippi Area"},{"id":371337,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3449/sim3449_sheet1.pdf","text":"Sheet 1—","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3449 Sheet 1","linkHelpText":"High-Resolution Airborne Geophysical Survey of the Shellmound, Mississippi Area"},{"id":371336,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3449/coverthb.jpg"}],"country":"United States","state":"Mississippi","county":"Leflore County","city":"Shellmound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.5333,\n 33.5242\n ],\n [\n -90.1628,\n 33.5242\n ],\n [\n -90.1628,\n 33.8\n ],\n [\n -90.5333,\n 33.8\n ],\n [\n -90.5333,\n 33.5242\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geology, Geophysics, and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS-973
Denver, CO 80225-0046
Dams can alter the chemical and physical conditions of downstream environments by increasing stream temperatures, altering nutrient limitation, reducing flow variability, and reducing fine sediment deposition. However, little is known about how fundamental stream ecosystem processes like productivity and respiration respond to dams. Nutrient diffusing substrates were installed in three dam streams and three control streams to evaluate the effect of dams on benthic gross primary productivity (GPP), respiration (R), and chlorophyll α production. Dam streams were an average of 5.6 °C warmer than control streams but GPP, R and chlorophyll α were not different between control and dam streams. Phosphorus enrichment increased heterotrophic R relative to controls (~1.8×) but not autotrophic GPP, R or chlorophyll α. Stream nutrient concentrations and nutrient limitation of heterotrophic R were similar in dam and control streams, suggesting that the dams had limited effects on nutrient transport downstream. Autotrophic GPP, R and chlorophyll α were limited by light and varied within and across streams, potentially masking our ability to detect differences caused solely by dams. Dams may alter stream ecosystem function but consideration of other factors associated with and independent of dams is critical for predicting ecosystem responses to dams.
","language":"English","publisher":"Schweizerbart Science Publishers","doi":"10.1127/fal/2020/1260","usgsCitation":"Ludlam, J.P., and Roy, A.H., 2020, Understanding effects of small dams on benthic metabolism and primary production in temperate forested streams: Fundamental and Applied Limnology, v. 193, no. 3, p. 227-237, https://doi.org/10.1127/fal/2020/1260.","productDescription":"11 p.","startPage":"227","endPage":"237","ipdsId":"IP-098905","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":395238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"193","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ludlam, John P.","contributorId":272885,"corporation":false,"usgs":false,"family":"Ludlam","given":"John","email":"","middleInitial":"P.","affiliations":[{"id":56402,"text":"Fitchburg State University","active":true,"usgs":false}],"preferred":false,"id":832363,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832362,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70212551,"text":"70212551 - 2020 - Use of visual surveys and radiotelemetry reveals sources of detection bias for a cryptic snake at low densities","interactions":[],"lastModifiedDate":"2020-08-20T14:18:36.641214","indexId":"70212551","displayToPublicDate":"2020-01-17T09:13:28","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Use of visual surveys and radiotelemetry reveals sources of detection bias for a cryptic snake at low densities","docAbstract":"Transect surveys are frequently used to estimate distribution and abundance of species across a landscape, yet a proportion of individuals present will be missed because either they were out of view and unavailable for detection or they were available but not detected because the surveyors missed them. These situations lead to availability and perception bias, respectively, and can result in misleading estimates of abundance and habitat use. In this study, we examined potential biases of visual surveys used for the brown tree snake (Boiga irregularis), a cryptic invasive snake responsible for the extirpation of at least 15 vertebrates on Guam. We simultaneously executed visual surveys and radiotelemetry in a low‐density population of brown tree snakes with two goals in mind: to assess the efficacy of visual surveys in detecting subjects at low densities and to identify sources of perception and availability bias in such surveys. Results indicated that with considerable effort, visual surveys can predict the presence of this cryptic reptile even at low densities (0.4 animals/ha) but perform poorly at predicting areas of high use resulting in inaccurate estimates of relative habitat importance. Telemetered snakes used densely foliated plants including Pandanus tectorius and ferns (epiphytic and terrestrial species) for nearly half of their time, yet <9% of visual survey observations occurred in these microhabitats. Visibility of snakes decreased as they perched higher in the canopy mirroring the disparity between visual survey and telemetry detections but was also surprisingly low near the forest floor (0–1 m). Microhabitats identified in this study are likely to disproportionately affect visual surveys and would be appropriate resources to target for management purposes. When there is critical need to prevent false negatives, such as during an incipient invasion elsewhere, targeted searches of high‐use resources could augment other detection tools to improve detection probabilities of this and other cryptic species.ble for detection or they were available but not detected because the surveyors missed them. These situations lead to availability and perception bias, respectively, and can result in misleading estimates of abundance and habitat use. In this study, we examined potential biases of visual surveys used for the brown treesnake (Boiga irregularis), a cryptic invasive snake responsible for the extirpation of at least 15 vertebrates on Guam. We simultaneously executed visual surveys and radiotelemetry in a low-density population of brown treesnakes with two goals in mind: to assess the efficacy of visual surveys in detecting subjects at low densities and to identify sources of perception and availability bias in such surveys. Results indicated that with considerable effort, visual surveys can predict the presence of this cryptic reptile even at low densities (0.4 animals/ha) but perform poorly at predicting areas of high use resulting in inaccurate estimates of relative habitat importance. Telemetered snakes used densely foliated plants including Pandanus tectorius and ferns (epiphytic and terrestrial species) for nearly half of their time yet less than 9% of visual survey observations occurred in these microhabitats. Visibility of snakes decreased as they perched higher in the canopy mirroring the disparity between visual survey and telemetry detections but was also surprisingly low near the forest floor (0-1 meter). Microhabitats identified in this study are likely to disproportionately affect visual surveys and would be appropriate resources to target for management purposes. When there is critical need to prevent false negatives, such as during an incipient invasion elsewhere, targeted searches of high-use resources could augment other detection tools to improve detection probabilities of this and other cryptic species.
","language":"English","doi":"10.1002/ecs2.3000","usgsCitation":"Boback, S., Nafus, M.G., Yackel Adams, A.A., and Reed, R., 2020, Use of visual surveys and radiotelemetry reveals sources of detection bias for a cryptic snake at low densities: Ecosphere, v. 11, no. 1, e03000, 19 p., https://doi.org/10.1002/ecs2.3000.","productDescription":"e03000, 19 p.","onlineOnly":"Y","ipdsId":"IP-112922","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":458103,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.3000","text":"Publisher Index Page"},{"id":437158,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P939BM0W","text":"USGS data release","linkHelpText":"Brown Treesnake visual survey and radiotelemetry data, Guam 2015"},{"id":377685,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Boback, SM","contributorId":238881,"corporation":false,"usgs":false,"family":"Boback","given":"SM","email":"","affiliations":[{"id":39028,"text":"Dickinson College","active":true,"usgs":false}],"preferred":false,"id":796828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nafus, Melia G. 0000-0002-7325-3055 mnafus@usgs.gov","orcid":"https://orcid.org/0000-0002-7325-3055","contributorId":197462,"corporation":false,"usgs":true,"family":"Nafus","given":"Melia","email":"mnafus@usgs.gov","middleInitial":"G.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":796829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":796830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reed, Robert 0000-0001-8349-6168 reedr@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-6168","contributorId":152301,"corporation":false,"usgs":true,"family":"Reed","given":"Robert","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":796831,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70219598,"text":"70219598 - 2020 - The lead (Pb) lining of agriculture‐related subsidies: enhanced Golden Eagle growth rates tempered by Pb exposure","interactions":[],"lastModifiedDate":"2021-04-15T12:36:37.360403","indexId":"70219598","displayToPublicDate":"2020-01-17T07:33:10","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The lead (Pb) lining of agriculture‐related subsidies: enhanced Golden Eagle growth rates tempered by Pb exposure","docAbstract":"Supplementary food resources (e.g., subsidies) associated with agriculture can benefit wildlife species, increasing predictability and availability of food. Avian scavengers including raptors often utilize subsidies associated with both recreational hunting and pest shooting on agricultural lands. However, these subsidies can contain lead (Pb) fragments if they are culled with Pb‐based ammunition, potentially leading to Pb poisoning and physiological impairment in wildlife. Nesting Golden Eagles (Aquila chrysaetos) commonly forage in agricultural lands during the breeding season, and therefore, both adults and their nestlings are susceptible to Pb exposure from scavenging shot wildlife. We assessed drivers of Pb exposure in 258 nestling Golden Eagles (401 total blood samples), along with physiological and growth responses, in agricultural lands across four western states in the United States. We also evaluated the birds’ Pb stable isotope signatures to inform exposure sources. Twenty‐six percent of Golden Eagle nestlings contained Pb concentrations associated with subclinical poisoning for sensitive species (0.03–0.2 μg/g ww), 4% had Pb concentrations that exceeded subclinical poisoning benchmarks (0.2–0.5 μg/g ww), and <1% exceeded either concentrations associated with clinical poisoning (0.5–1.0 μg/g ww) and or those deemed to cause severe clinical poisoning (>1.0 μg/g ww). Lead concentrations were highest in nestlings with close proximity to fields that potentially provided subsidies and declined exponentially as distance to subsidies increased. However, close proximity to agriculture, and presumably subsidies, positively influenced nestling growth rates. Across the range of Pb exposure, nestlings experienced a 67% reduction in delta‐aminolevulinic acid dehydratase (δ‐ALAD) activity, suggesting nestlings may have been anemic or experiencing cellular damage. Isotopic ratios of 206Pb/207Pb increased non‐linearly with increasing blood Pb in Golden Eagle nestlings, and 45% of the birds were consistent with those of ammunition. However, above 0.10 μg/g ww, the proportion associated with ammunition increased to 89% of the nestlings. An improved understanding of how these positive (growth) and negative (physiology) effects associated with proximity to subsidies interact would be beneficial to managers when considering management scenarios and potentially evaluating any measures taken to reduce Pb exposure across the landscape.
Population monitoring of nesting waterbirds often involves frequent entries into the colony, but alternative methods such as local remotely sensed thermal imaging may help reduce disturbance while providing a cost-effective way to survey breeding populations. Such an approach can have high initial costs, however, which may have reduced the number of studies investigating functionality of paired thermal infrared camera and small unmanned aerial systems. Here, we take the first step of exploring the ability of two thermal infrared cameras to detect an avian chick under varying vegetative cover and distances, preceding field-mounting applications on a small unmanned aerial system. We created seven “bioboxes” to simulate a range of natural vegetation types and densities for a globally important colonial ground-nesting waterbird species, the common tern Sterna hirundo. We placed a juvenile chicken Gallus gallus (surrogate for the locally endangered common tern) in each box, and we tested two market-accessible infrared cameras (produced by FLIR Systems and Infrared Cameras, Inc.) at five elevations using a stationary boom (maximum height = 12 m). We applied computer-based digital thresholding to collected images, identifying pixels meeting one of seven threshold values. The chick was visible from at least one threshold value in 19 and 31 of 35 processed by the FLIR Systems and Infrared Cameras, respectively. Percentage of the chick identified across thresholds was generally highest at lower threshold values and elevations and decreased as elevation and threshold increased; however, the relative importance of each variable changed dramatically across bioboxes and camera types. Ability to detect a chick from processed images generally decreased with increasing elevation, and although we made no quantitative comparisons among boxes, detectability appeared greatest in images from both cameras when little or no vegetation was present. Interestingly, no single threshold value was best for all bioboxes. We observed notable differences between cameras including visual resolution of detected temperature differentials and image processing speed. Results of this controlled study show promise for the use of thermal infrared systems for detecting cryptic species in vegetation. Future research should work to combine thermal infrared and visual sensors with small unmanned aerial systems to test applicability in a mobile field application.
","language":"English","publisher":"Fish and Wildlife Management","doi":"10.3996/072019-JFWM-062","usgsCitation":"Prosser, D., Collier, T., Sullivan, J.D., Dale, K.E., Callahan, C.R., McGowan, P.C., Gaylord, E., Geschke, J.M., Howell, L., Marban, P., and Raman, S., 2020, Using thermal infrared cameras to detect avian chicks at various distances and vegetative coverages: Journal of Fish and Wildlife Management, v. 11, no. 1, p. 245-257, https://doi.org/10.3996/072019-JFWM-062.","productDescription":"13 p.","startPage":"245","endPage":"257","ipdsId":"IP-077752","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":458106,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/072019-jfwm-062","text":"Publisher Index Page"},{"id":437159,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97UT9B7","text":"USGS data release","linkHelpText":"Using Thermal Infrared Cameras to Detect Avian Chicks at Various Distances and Vegetative Coverages"},{"id":377208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collier, Tom","contributorId":208436,"corporation":false,"usgs":false,"family":"Collier","given":"Tom","email":"","affiliations":[{"id":37801,"text":"UASbio","active":true,"usgs":false}],"preferred":false,"id":795296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":795297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dale, Katherine Emily 0000-0002-8544-1571","orcid":"https://orcid.org/0000-0002-8544-1571","contributorId":237786,"corporation":false,"usgs":true,"family":"Dale","given":"Katherine","email":"","middleInitial":"Emily","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":795298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":795299,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":795300,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gaylord, Edward","contributorId":237787,"corporation":false,"usgs":false,"family":"Gaylord","given":"Edward","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795301,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Geschke, Julia M.","contributorId":237788,"corporation":false,"usgs":false,"family":"Geschke","given":"Julia","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795302,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Howell, Lucas","contributorId":237789,"corporation":false,"usgs":false,"family":"Howell","given":"Lucas","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795303,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Marban, Paul R.","contributorId":221168,"corporation":false,"usgs":false,"family":"Marban","given":"Paul R.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795304,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Raman, Saba","contributorId":237790,"corporation":false,"usgs":false,"family":"Raman","given":"Saba","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":795305,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70249835,"text":"70249835 - 2020 - Alpine plant community diversity in species-area relations at fine scale","interactions":[],"lastModifiedDate":"2023-11-01T20:51:01.204397","indexId":"70249835","displayToPublicDate":"2020-01-16T15:49:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":899,"text":"Arctic, Antarctic, and Alpine Research","active":true,"publicationSubtype":{"id":10}},"title":"Alpine plant community diversity in species-area relations at fine scale","docAbstract":"Observations of diversity in alpine vegetation appear to be scale dependent. The relations of plant species richness with surface processes and geomorphology have been studied, but patterns of beta diversity are less known. In Glacier National Park, Montana, diversity has been examined within 1 m2 plots and for 16 m2 plots across two ranges, with within-plot and across-range explanatory factors, respectively. The slopes of species–area equations for nested 4, 8, 12, and 16 m2 plots were used as an indicator of beta diversity in Glacier National Park, where smaller and larger scales have been examined. The slopes were negatively related to a field assessment of surface stability and positively to the presence of talus—two sides of the same coin. A positive relationship with bedrock outcrops may be due to a misrepresentation of area for plants. The relationship of species–area slopes to plot-level gamma diversity was negative, weak, and marginally significant, and this variable did not enter the general linear model (GLM). Beyond simple differences in diversity with differences in environment, examination of beta diversity at a scale between that of earlier studies revealed surface processes and geomorphology as drivers that were also at a scale between those previously reported.
The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE), analyzed streamflow trends and streamflow-related variables through 2017 in seven important water-supply basins to provide information that can help water managers with the USACE and river authorities make future water management decisions. The primary purpose of this report is to document trends in long-term streamflow data at 114 selected USGS streamflow-gaging stations and 36 simulated reservoir-inflow stations in 7 river basins primarily in Texas: Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity. In this report, trends were considered statistically significant if their p-values were less than or equal to 0.05 (p-value ≤0.05). Streamflow data selected for temporal trend analyses included annual minimum streamflow, annual peak streamflow, and streamflow volume. Precipitation, air temperature, and groundwater-level-elevation data were analyzed for trends that may help to explain changes observed in the streamflow statistics. Basins were divided into sections along county lines for precipitation analyses. Streamflow volumes were analyzed for associations with potential flood storage. The potential flood storage, defined as the difference between maximum storage and normal storage, was computed for each dam from the National Inventory of Dams database and accumulated over time based on the completion date of the dam.
Precipitation and air temperature trends were analyzed for each of the eight climate divisions (High Plains, Trans-Pecos, Low Rolling Hills, Edwards Plateau, North Central Texas, South Central Texas, East Texas, and Upper Coast). Results of precipitation trend analyses indicated moderate upward trends in the Upper Coast and East Texas Climate Divisions analyzed on an annual time step from 1900 through 2017. These two climate divisions are in the eastern and southeastern parts of the State, and they receive more mean annual precipitation (45.88 and 46.09 inches, respectively) than the other climate divisions. The results of air temperature analyses indicated upward trends in annual mean air temperature within all climate divisions, with a mean slope of 0.02 degree Fahrenheit per year, or 1 degree every 50 years.
Within the Brazos River Basin, results of precipitation trend analyses on an annual time step indicated that precipitation amounts are most likely increasing in the lower and middle sections of the basin. Downward trends in annual streamflow and in the ratio of streamflow volume to precipitation volume were indicated at 7 of the 15 stations in the upper sections of the basin. The lower sections of the basin had mostly downward trends in annual minimum streamflow, whereas upward trends in annual minimum streamflow were indicated in the upper sections of the basin. Downward trends in annual peak streamflow were indicated at many of the stations in the upper sections of the basin. At the same seven stations in the upper sections of the basin where there were downward trends in annual streamflow, there were also downward trends in the ratio of streamflow volume to precipitation volume. The data from the same seven stations indicated negative associations between potential flood storage volume and annual streamflow volume and downward trends in the ratio of annual streamflow volume to potential flood storage volume. With the known addition of 13,006,394 acre-feet of potential flood storage between 1900 and 2010 in the subbasins analyzed, streamflow volumes have decreased in the upper sections of the Brazos River Basin.
Within the Colorado River Basin, results of precipitation trend analyses on an annual time step indicated no trends in the basin. Downward trends in annual streamflow were indicated at 16 stations in the upper sections of the basin, whereas no trends in annual streamflow were indicated in the lower section of the basin. In the lower section of the basin, one station that was operated as a continuous streamflow-gaging station through 2017 had a downward trend in annual minimum streamflow, and another station (operated through 2007) had an upward trend in annual minimum streamflow. In the upper sections of the basin, data from seven stations indicated upward trends in annual minimum streamflow, and data from six stations indicated downward trends. Data from 18 stations in the upper sections of the basin indicated downward trends in annual peak streamflow. Thirteen of the 16 stations in the upper sections of the basin with data that indicated downward trends in annual streamflow also have data that indicated downward trends in the ratio of streamflow volume to precipitation volume. Data from the same 13 stations indicated negative associations between potential flood storage volume and annual streamflow volume and downward trends in the ratio of annual streamflow volume to potential flood storage volume. With the known addition of 7,193,147 acre-feet of potential flood storage between 1891 and 2014 in the subbasins analyzed, streamflow volumes have decreased in the upper sections of the Colorado River Basin.
Within the Big Cypress Basin, results of precipitation trend analyses on annual, seasonal, and monthly time steps indicated almost no trends in the basin as defined in this report. However, the annual precipitation p-value only slightly exceeded the p-value threshold for a statistically significant trend. Given the upward trend in precipitation in the East Texas Climate Division, which includes the Big Cypress Basin, and the low p-value for annual precipitation within the basin, precipitation in the basin may be increasing over time. Two annual streamflow trends, one upward and one downward, were in the upper parts of the basin. Data from USGS streamflow-gaging station 07346000 Big Cypress Bayou near Jefferson, Texas, indicated an upward trend in annual minimum streamflow and a downward trend in annual peak streamflow. The station is immediately downstream from Lake O’ the Pines; presumably, minimums have increased because of regulated releases, and annual peaks have decreased because of storage from the lake for flood control. Despite the known addition of 2,737,154 acre-feet of potential flood storage between 1898 and 2011 in the subbasins analyzed, there have not been widespread reductions in streamflow volumes in the Big Cypress Basin, except for within the drainage area for the farthest upstream station on the main stem downstream from Mount Pleasant, Texas.
Within the Guadalupe River Basin, results of precipitation trend analyses on an annual time step indicated an upward trend in the lower section of the basin, but no trends in annual streamflow were indicated in the lower section of the basin. In the upper section of the basin, data from 1 of the 13 stations indicated an upward trend in annual streamflow. Data from 6 of the 13 stations in the upper section of the basin indicated a trend in annual minimum streamflow with 4 upward and 2 downward trends. Data from 2 of the 13 stations in the upper section of the basin indicated downward trends in annual peak streamflow. Despite the known addition of 2,016,534 acre-feet of potential flood storage between 1849 and 2013 in the subbasins analyzed, streamflow volumes have not decreased in the Guadalupe River Basin.
Within the Neches River Basin, results of precipitation trend analyses on an annual time step indicated upward trends in the basin. None of the data from stations analyzed in the Neches River Basin indicated annual trends in streamflow despite upward trends in annual precipitation within the basin. Data from 9 of the 19 stations analyzed in the basin indicated upward trends in annual minimum streamflow. Data from one of the simulated-inflow stations indicated a downward trend in annual minimum streamflow into Sam Rayburn Reservoir. Data from two stations indicated downward trends in annual peak streamflow, and data from one small subbasin indicated an upward trend in annual peak streamflow. Despite the known addition of 4,839,609 acre-feet of potential flood storage between 1888 and 2008 in the subbasins analyzed, there have not been widespread reductions in streamflow volumes in the Neches River Basin.
Within the Sulphur River Basin, results of precipitation trend analyses on an annual time step indicated a moderate upward trend within the basin. Data from only one of the stations, the simulated inflow to Jim Chapman Lake, indicated an annual upward trend in streamflow despite an upward trend in annual precipitation throughout the basin. Data from three of the six stations in the Sulphur River Basin indicated upward trends in annual minimum streamflow, and data from one of the six stations indicated a downward trend in annual peak streamflow. Despite the known addition of 6,933,361 acre-feet of potential flood storage between 1904 and 2006 in the subbasins analyzed, streamflow volumes have not decreased in the Sulphur River Basin.
Within the Trinity River Basin, results of precipitation trend analyses on an annual time step indicated upward trends in most sections of the basin. Data from 8 of the 36 stations analyzed for trends in annual streamflow indicated upward trends, and all 8 stations are in the upper sections of the basin. None of the data from stations in the lower sections of the basin indicated trends in annual streamflow. Data from 16 of the 36 stations indicated upward trends in annual minimum streamflow. Upward trends in annual minimum streamflow could be the result of managed reservoir releases in combination with wastewater treatment plant releases in the large Dallas-Fort Worth metroplex in the upper sections of the basin. All the trends in annual peak streamflow were in the sections of the basin that include the Dallas-Fort Worth metroplex. Data from two stations, one USGS streamflow-gaging station and one simulated-inflow station, indicated upward trends in annual peak streamflow, and data from one streamflow-gaging station indicated a downward trend in annual peak streamflow. Of the basins included in this study, the Trinity River Basin has the second largest amount of potential flood storage of 8,947,349 acre-feet from dams added between 1890 and 2013. Eleven stations in the Trinity River Basin had positive associations between potential flood storage volume and annual streamflow volume, indicating that annual streamflow increases as potential flood storage increases. Data from 7 of the 11 stations also indicated upward trends in annual streamflow. The positive associations may be the result of increases in minimum streamflow, which could be the result of any combination of managed reservoir releases, wastewater treatment plant releases, or increased runoff from urbanized areas, particularly in the urbanized area of the Dallas-Fort Worth metroplex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195137","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District","usgsCitation":"Harwell, G.R., McDowell, J.S., Gunn, C.L., and Garrett, B.S., 2020, Precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins in Texas through 2017 (ver. 1.1, April 2020): U.S. Geological Survey Scientific Investigations Report 2019–5137, 94 p., https://doi.org/10.3133/sir20195137.","productDescription":"Report: x, 94 p.; 5 Tables; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102896","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":399613,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109606.htm"},{"id":374071,"rank":9,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5137/coverthb2.jpg"},{"id":373986,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5137/versionHist.txt","text":"Version History","size":"1.35 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2019–5137 Version History"},{"id":371261,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table9.xlsx","text":"Table 9—","size":"120 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 9","linkHelpText":"Summary of annual, seasonal, and monthly trends in the ratio of streamflow volume to precipitation volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371258,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table7.xlsx","text":"Table 7—","size":"64 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 7","linkHelpText":"Summary of precipitation temporal trends around the time of annual peak streamflow in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371255,"rank":2,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table5.xlsx","text":"Table 5—","size":"80 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 5","linkHelpText":"Summary of annual, seasonal, and monthly associations between precipitation volume and streamflow volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371252,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L1F7PT","text":"USGS data release","description":"USGS data release","linkHelpText":"Data used to assess precipitation, temperature, groundwater-level elevation, streamflow, and potential flood storage trends within the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins in Texas through 2017"},{"id":373985,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_v1.1.pdf","text":"Report","size":"20.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5137"},{"id":371259,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table8.xlsx","text":"Table 8—","size":"144 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 8","linkHelpText":"Summary of annual, seasonal, and monthly streamflow volume trends in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"},{"id":371262,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2019/5137/sir20195137_table10.xlsx","text":"Table 10—","size":"48 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Table 10","linkHelpText":"Summary of trends in annual minimum streamflow and annual peak streamflow and relations between streamflow volume and potential flood storage volume in the Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River Basins"}],"country":"United States","state":"Texas","otherGeospatial":"Brazos, Colorado, Big Cypress, Guadalupe, Neches, Sulphur, and Trinity River basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.4667,\n 28.4167\n ],\n [\n -93.0619,\n 28.4167\n ],\n [\n -93.0619,\n 33.6667\n ],\n [\n -101.4667,\n 33.6667\n ],\n [\n -101.4667,\n 28.4167\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: January 2020; Version 1.1: April 2020","contact":"Director, Oklahoma-Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Seepage investigations were conducted periodically by the U.S. Geological Survey (USGS) from 1988 to 1998 and from 2006 to 2015 along a 64-mile reach of the Rio Grande as part of the Mesilla Basin monitoring program. Past studies were conducted during no-flow or low-flow periods. In 2018, a seepage investigation was conducted during April 3–4 along a 62.4-mile study reach, from below Leasburg Dam, Leasburg, New Mexico, to above El Paso, Texas, during a period of high flows due to dam releases of water for irrigation purposes. During this investigation, there was measurable streamflow at 31 of the 41 measurement locations: 22 river sites, 8 inflow sites, and 1 outflow site. Results of the 2018 high-flow seepage investigation are presented in this report.
Net seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the streamflow measured at the upstream location from the streamflow measured at the closest downstream location and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful if it exceeded the cumulative measurement uncertainty associated with the net seepage computation. During this investigation, streamflow on the main stem of the Rio Grande ranged from 577 to 1,000 cubic feet per second (ft3/s). Nine subreaches were found to have meaningful net seepage gain or loss, four gaining subreaches and five losing subreaches. Because of high cumulative uncertainty (plus or minus 111.3 ft3/s) relative to the calculated cumulative loss (−57.7 ft3/s) over the entire study reach, no meaningful gain or loss was determined in this study. Like all of the previous USGS seepage studies on this reach of the Rio Grande, this study reported a net seepage loss, and the magnitude of that loss was within the range of historical values.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195140","collaboration":"Prepared in cooperation with the Bureau of Reclamation, New Mexico Office of the State Engineer, City of Las Cruces Utilities, New Mexico Interstate Stream Commission, New Mexico State University, and the Elephant Butte Irrigation District","usgsCitation":"Ball, G.P., Robertson, A.J., and Medina Morales, K., 2020, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above El Paso, Texas, 2018: U.S. Geological Survey Scientific Investigations Report 2019–5140, 16 p., https://doi.org/10.3133/sir20195140.","productDescription":"iv, 16 p.","onlineOnly":"Y","ipdsId":"IP-109490","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":371305,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5140/sir20195140.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5140"},{"id":371304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5140/coverthb.jpg"}],"country":"United States","state":"Texas, New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.787109375,\n 31.475524020001806\n ],\n [\n -105.71044921875,\n 31.175209828310845\n ],\n [\n -105.875244140625,\n 31.512995857454676\n ],\n [\n -106.69921875,\n 32.82421110161336\n ],\n [\n -106.44653320312499,\n 34.07996230865873\n ],\n [\n -107.127685546875,\n 34.1890858311724\n ],\n [\n -107.567138671875,\n 33.58716733904656\n ],\n [\n -107.611083984375,\n 33.091541548655215\n ],\n [\n -106.787109375,\n 31.475524020001806\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd.
Albuquerque, NM 87113
Advances in underwater camera technology provide an affordable means to quantify the environmental conditions under which fish spawn. This information is important for investigating spawning ecology, managing habitat, or providing information for captive breeding programs. We deployed 12 modified security cameras underwater to identify environmental conditions related to the spawning behavior of the critically endangered Moapa Dace Moapa coriacea, a Mojave Desert stream-dwelling cyprinid that had never been observed spawning and that had fallen to a low of 459 individual fish 4 years prior to this study. Camera sites were selected systematically along the stream to represent the variety of conditions available. We divided the field of view in front of each camera into a grid, and we estimated both the available environment and the habitat over which Moapa Dace showed spawning behavior. From over 4,000 10-min video clips that were randomly selected for analysis, 13 spawning events were identified. Using nonparametric contingency table analyses, we found that Moapa Dace selected depths between 30 and 34 cm, water velocities between 0.11 and 0.17 m/s, cobble substrate, and overhead instream cover. Although the recorded sample size of spawning events was small (13), our sample represents a large proportion of events given that the world's entire population of Moapa Dace at the time was approximately 650 fish distributed over multiple kilometers of stream length. Environmental conditions identified by this study were replicated in laboratory facilities to successfully propagate Moapa Dace for the first time in captivity. These propagation methods are now used in a management setting by the Nevada Department of Wildlife to maintain a captive population of this rare fish. Camera methods can be effective in helping to identify spawning conditions where water clarity is sufficient.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10356","usgsCitation":"Ruggirello, J.E., Bonar, S.A., Feuerbacher, O.G., and Simons, L.H., 2020, Use of underwater videography to quantify conditions utilized by endangered Moapa Dace While spawning: North American Journal of Fisheries Management, v. 40, no. 1, p. 17-28, https://doi.org/10.1002/nafm.10356.","productDescription":"12 p.","startPage":"17","endPage":"28","ipdsId":"IP-110930","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395702,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Plumer Stream, Warm Springs area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.74601745605469,\n 36.696502641380036\n ],\n [\n -114.66361999511719,\n 36.696502641380036\n ],\n [\n -114.66361999511719,\n 36.74108512094412\n ],\n [\n -114.74601745605469,\n 36.74108512094412\n ],\n [\n -114.74601745605469,\n 36.696502641380036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Ruggirello, Jack E.","contributorId":30526,"corporation":false,"usgs":true,"family":"Ruggirello","given":"Jack","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":833924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonar, Scott A. 0000-0003-3532-4067 sbonar@usgs.gov","orcid":"https://orcid.org/0000-0003-3532-4067","contributorId":3712,"corporation":false,"usgs":true,"family":"Bonar","given":"Scott","email":"sbonar@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":833923,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feuerbacher, Olin G.","contributorId":275282,"corporation":false,"usgs":false,"family":"Feuerbacher","given":"Olin","email":"","middleInitial":"G.","affiliations":[{"id":40855,"text":"UA","active":true,"usgs":false}],"preferred":false,"id":833925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simons, Lee H.","contributorId":264621,"corporation":false,"usgs":false,"family":"Simons","given":"Lee","email":"","middleInitial":"H.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":833926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207451,"text":"ofr20191147 - 2020 - Kelp forest monitoring at Naval Base Ventura County, San Nicolas Island, California: Fall 2017 and Spring 2018, Fourth Annual Report","interactions":[],"lastModifiedDate":"2022-04-21T20:21:41.150501","indexId":"ofr20191147","displayToPublicDate":"2020-01-16T09:37:32","publicationYear":"2020","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":"2019-1147","displayTitle":"Kelp Forest Monitoring at Naval Base Ventura County, San Nicolas Island, California: Fall 2017 and Spring 2018, Fourth Annual Report","title":"Kelp forest monitoring at Naval Base Ventura County, San Nicolas Island, California: Fall 2017 and Spring 2018, Fourth Annual Report","docAbstract":"To assess and track changes to the rocky subtidal communities surrounding San Nicolas Island, the U.S. Navy entered into an agreement with the U.S. Geological Survey (USGS) in 2014 to conduct an ecological monitoring program at several sites around the island. Four permanent sites—Nav Fac 100, West End, Dutch Harbor, and Daytona 100—were established. The sites were based on ones that had been monitored since 1980 by USGS and were combined or expanded for better comparability with monitoring programs conducted at the other California Channel Islands. At the sites, scientists from USGS and our cooperator, the University of California, Santa Cruz, measured bottom cover of algae and sessile invertebrate species in quadrats, counted and sized fish on swimming transects, and counted a suite of kelps and invertebrates on benthic band transects. Holdfast diameter and number of stipes of giant kelp (Macrocystis pyrifera) were recorded on these transects, and size data were collected for urchins, sea stars, and shelled mollusks. Bottom temperatures were recorded at hourly intervals by archival data loggers that were deployed at the sites. This report focuses primarily on data collected in fall 2017 and spring 2018 and makes comparisons with data collected in previous years, beginning in fall 2014.
Nav Fac 100 is a site with a relatively low benthic profile, situated on the north side of San Nicolas Island. It was previously urchin dominated but underwent a dramatic decline in purple sea urchins in 2015 and 2016. Since then, macroalgae has become more prevalent as both annual brown algae, such as Dictyota, and perennials (for example, Cystoseira) have become established. The invasive brown alga Sargassum horneri has also become established. West End, on the southwest side of the island, also lacks much bottom relief but has more crevice habitat associated with boulders. It remains dominated by kelps and red algae, but red algae have decreased recently. Dutch Harbor, on the south side, has many high relief rocky reefs and had the greatest fish and non-motile invertebrate densities. It remains the most stable of the sites. Daytona 100, on the southeast side, has moderate relief and has remained a patchwork of kelp and urchin dominated areas with moderate fish density.
The main change at the sites during the last 4 years was the decline in urchin numbers at Nav Fac 100. There was storm-related mortality and subsequent recruitment in the M. pyrifera population at several of the sites in both 2016 and 2017. The winter of 2018, however, was relatively mild, with less destructive storm-related disturbance. The invasive brown alga S. horneri, first seen at San Nicolas Island at Nav Fac 100 in fall 2015, has become firmly established there during the last 2 sampling years. Finally, moderate increases were observed in purple urchin densities at all sites this spring. Long-term data are presented to illustrate trends and changes over the past three decades. Results indicate continued monitoring to evaluate ecosystem effects from perturbations owing to natural processes and anthropomorphic factors, including recovery of the sea otter population, changes in fisheries, invasive species and changing environmental conditions, could be valuable to inform managers’ decision-making.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191147","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Kenner, M.C., and Tomoleoni, J., 2020, Kelp forest monitoring at Naval Base Ventura County, San Nicolas Island, California: Fall 2017 and Spring 2018, Fourth Annual Report: U.S. Geological Survey Open-File Report 2019–1147, 76 p., https://doi.org/10.3133/ofr20191147.","productDescription":"vi, 76 p.","numberOfPages":"76","onlineOnly":"Y","ipdsId":"IP-111796","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":399434,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109596.htm"},{"id":371253,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1147/coverthb.jpg"},{"id":371254,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1147/ofr20191147.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1147"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.64111328125,\n 33.18353672893615\n ],\n [\n -119.37744140625,\n 33.18353672893615\n ],\n [\n -119.37744140625,\n 33.32134852669881\n ],\n [\n -119.64111328125,\n 33.32134852669881\n ],\n [\n -119.64111328125,\n 33.18353672893615\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) along the San Luis Rey River, between College Boulevard in Oceanside and Interstate 15 in Fallbrook, California (middle San Luis Rey River), in 2019, and we surveyed and conducted nest monitoring for Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) in a survey area where breeding had historically been documented on the middle San Luis Rey River, in 2019. Surveys were conducted from April 11 to June 24 (vireo) and from May 16 to July 15 (flycatcher). We found 179 vireo territories, at least 124 of which were occupied by pairs. Vireo territories increased by 100 percent within the portion of the middle San Luis Rey River that burned as a result of a wildfire in 2017. In contrast, vireo territories increased by 5 percent within the unburned portion of the middle San Luis Rey River.
Vireos used five different habitat types in the survey area: mixed willow riparian, willow-cottonwood, riparian scrub, willow-sycamore, and upland scrub. Fifty-two percent of the vireos were detected in habitat characterized as mixed willow, and 92 percent of the vireos were detected in habitat with greater than 50 percent native plant cover. Of the 12 banded vireos detected in the survey area, 5 were resighted with a full color-band combination. One adult female with a unique color-band combination immigrated to the middle San Luis Rey River from Marine Corps Base Camp Pendleton (MCBCP). Five other vireos with single (natal) federal bands were recaptured, identified, and color banded in 2019. Two vireos with a single dark blue federal band, indicating that they were banded as nestlings on the lower San Luis Rey River (LSLR), could not be recaptured for identification. The five natal vireos that were recaptured on the middle San Luis Rey River dispersed from 1.4 to 8.3 kilometers (km) from their natal territories. Banded vireos with a known age ranged from 1 to 11 years old.
One resident flycatcher was observed in the survey area in 2019. The resident flycatcher (male) was detected in a territory of mixed willow habitat with greater than 50 percent native plant cover. He was detected as a single male from May 16 to July 17, 2019, and no evidence of pairing or nesting was observed. The male flycatcher with a unique color-band combination occupied the same territory in 2018 and 2019.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1122","usgsCitation":"Allen, L.D. and Kus, B.E., 2020, Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) on the Middle San Luis Rey River, San Diego County, southern California—2019 data summary: U.S. Geological Survey Data Series 1122, 11 p., https://doi.org/10.3133/ds1122.","productDescription":"iv, 11 p.","numberOfPages":"11","onlineOnly":"Y","ipdsId":"IP-114314","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":371284,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1122/coverthb.jpg"},{"id":371285,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1122/ds1122.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Data Series 1122"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.55920410156249,\n 33.1398510418607\n ],\n [\n -116.5264892578125,\n 33.1398510418607\n ],\n [\n -116.5264892578125,\n 33.61919376817004\n ],\n [\n -117.55920410156249,\n 33.61919376817004\n ],\n [\n -117.55920410156249,\n 33.1398510418607\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
One of the North American bat species most impacted by white-nose syndrome (WNS) is the northern long-eared bat Myotis septentrionalis, which as a result has been listed under the Endangered Species Act. WNS was first detected in Wisconsin in 2014. Unfortunately, little is known regarding the ecology of M. septentrionalis in this state pre-WNS to guide management supporting post-WNS recovery efforts. The objectives of our research were to (1) assess characteristics of trees that are associated with roost tree selection and (2) investigate how characteristics of maternity colony networks compare to colonies in the eastern USA. We mist-netted at 3 sites in Wisconsin in 2015 and 2016, and affixed radio transmitters to 39 female M. septentrionalis. We tracked bats to 53 confirmed day roosts. We found that roost trees were larger, more decayed, and more likely to be in dominant canopy closure areas than random trees. Oaks Quercus spp. were used most frequently and in proportion to their availability in the landscape at 2 field sites, whereas invasive black locust Robinia pseudoacacia was used more than expected based on availability at another site. Overall, minimum convex polygon sizes for maternity roosts were variable (5.2 to 8.9 ha) but similar to values reported for other regions. However, network centrality was low, indicating equitable use of day roosts and more frequent roost switching compared to other regions. Our findings provide information that increasing availability of potential day roosts in the landscape during the reproductive period may improve recruitment, which may in turn mitigate some of the detrimental population effects from WNS.
","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01004","usgsCitation":"Hyzy, B.A., Russell, R.E., Silvis, A., Ford, W., Riddle, J., and Russell, K., 2020, Investigating maternity roost selection by northern long-eared bats at three sites in Wisconsin: Endangered Species Research, v. 41, p. 55-65, https://doi.org/10.3354/esr01004.","productDescription":"11 p., Data release","startPage":"55","endPage":"65","ipdsId":"IP-106190","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":458110,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01004","text":"Publisher Index Page"},{"id":418323,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YH1668","text":"USGS data release","description":"USGS data release","linkHelpText":"Roost selection for Northern Long-eared Bats (Myotis septentrionalis) in Wisconsin"},{"id":391798,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Black River State Forest, Governor Dodge State Park, Sandhill Wildlife Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.1479721069336,\n 42.996110107947956\n ],\n [\n -90.07038116455078,\n 42.996110107947956\n ],\n [\n -90.07038116455078,\n 43.05785119934999\n ],\n [\n -90.1479721069336,\n 43.05785119934999\n ],\n [\n -90.1479721069336,\n 42.996110107947956\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.89813232421875,\n 44.049102784014536\n ],\n [\n -90.52871704101562,\n 44.049102784014536\n ],\n [\n -90.52871704101562,\n 44.50825885600572\n ],\n [\n -90.89813232421875,\n 44.50825885600572\n ],\n [\n -90.89813232421875,\n 44.049102784014536\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.20736694335936,\n 44.295349956045804\n ],\n [\n -90.11398315429686,\n 44.295349956045804\n ],\n [\n -90.11398315429686,\n 44.39257961837961\n ],\n [\n -90.20736694335936,\n 44.39257961837961\n ],\n [\n -90.20736694335936,\n 44.295349956045804\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hyzy, Brenna A.","contributorId":171457,"corporation":false,"usgs":false,"family":"Hyzy","given":"Brenna","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":826915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":826916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvis, Alex","contributorId":269007,"corporation":false,"usgs":false,"family":"Silvis","given":"Alex","affiliations":[],"preferred":false,"id":826917,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":826918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riddle, Jason","contributorId":269008,"corporation":false,"usgs":false,"family":"Riddle","given":"Jason","affiliations":[],"preferred":false,"id":826919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Russell, Kevin","contributorId":269009,"corporation":false,"usgs":false,"family":"Russell","given":"Kevin","affiliations":[],"preferred":false,"id":826920,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70208459,"text":"70208459 - 2020 - Amphibian chytrid prevalence on boreal toads in SE Alaska and NW British Columbia: Tests of habitat, life stages, and temporal trends","interactions":[],"lastModifiedDate":"2020-02-12T06:13:53","indexId":"70208459","displayToPublicDate":"2020-01-16T07:52:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1396,"text":"Diseases of Aquatic Organisms","active":true,"publicationSubtype":{"id":10}},"title":"Amphibian chytrid prevalence on boreal toads in SE Alaska and NW British Columbia: Tests of habitat, life stages, and temporal trends","docAbstract":"Tracking and understanding variation in pathogens such as Batrachochytrium dendrobatidis ([Bd]), which causes amphibian chytridiomycosis and has caused population declines globally, is a priority for many land managers. However, there has been relatively little sampling of amphibian communities at high latitudes. We used skin swabs collected during 2005–2017 from boreal toads (Anaxyrus boreas; N = 248), in southeast Alaska (USA; primarily in Klondike Gold Rush National Historical Park [KLGO]) and northwest British Columbia (Canada) to determine how Bd prevalence varied across life stages, habitat characteristics, local species richness, and time. Across all years, Bd prevalence peaked in June and was >3 times greater for adult toads (37.5%) vs. juveniles and metamorphs (11.2%). Bd prevalence for toads in the KLGO area, where other amphibian species are rare or absent, was highest from river habitats (55.0%), followed by human-modified upland wetlands (32.3%) and natural upland wetlands (12.7%) — the same rank-order these habitats are used for toad breeding. No Columbia spotted frogs (N = 12) or wood frogs (N = 2) from the study area tested Bd-positive, although all were from an area of low host density where Bd has not been detected. Prevalence of Bd on toads in the KLGO area decreased during 2005–2015. This trend from a largely single-species system may be encouraging or concerning, depending on how Bd is affecting vital rates, and emphasizes the need to understand effects of pathogens before translating disease prevalence into management actions.","language":"English","publisher":"Inter-Research","doi":"10.3354/dao03430","usgsCitation":"Hossack, B.R., Adams, M.J., Honeycutt, R., Belt, J.J., and Pyare, S., 2020, Amphibian chytrid prevalence on boreal toads in SE Alaska and NW British Columbia: Tests of habitat, life stages, and temporal trends: Diseases of Aquatic Organisms, v. 137, p. 159-165, https://doi.org/10.3354/dao03430.","productDescription":"7 p.","startPage":"159","endPage":"165","ipdsId":"IP-109582","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":372209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States, Canada","otherGeospatial":"Southeastern Alaska, Northwestern British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.416015625,\n 60.02095215374802\n ],\n [\n -139.04296875,\n 58.03137242177637\n ],\n [\n -133.9453125,\n 52.26815737376817\n ],\n [\n -130.166015625,\n 50.62507306341435\n ],\n [\n -124.1015625,\n 51.6180165487737\n ],\n [\n -127.79296875,\n 53.330872983017066\n ],\n [\n -129.814453125,\n 57.89149735271034\n ],\n [\n -137.4609375,\n 61.18562468142281\n ],\n [\n -141.416015625,\n 60.02095215374802\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"137","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":781975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Michael J. 0000-0001-8844-042X","orcid":"https://orcid.org/0000-0001-8844-042X","contributorId":211916,"corporation":false,"usgs":true,"family":"Adams","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":781976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Honeycutt, R Ken","contributorId":222362,"corporation":false,"usgs":false,"family":"Honeycutt","given":"R Ken","affiliations":[],"preferred":false,"id":781977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belt, Jami J","contributorId":222363,"corporation":false,"usgs":false,"family":"Belt","given":"Jami","email":"","middleInitial":"J","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":781978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pyare, S","contributorId":222364,"corporation":false,"usgs":false,"family":"Pyare","given":"S","affiliations":[{"id":40534,"text":"University of Alaska Southeast, Juneau","active":true,"usgs":false}],"preferred":false,"id":781979,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70208965,"text":"70208965 - 2020 - A new stratigraphic framework and constraints for the position of the Paleocene-Eocene boundary in the rapidly subsiding Hanna Basin, Wyoming","interactions":[],"lastModifiedDate":"2020-04-06T23:19:14.853954","indexId":"70208965","displayToPublicDate":"2020-01-16T07:22:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"A new stratigraphic framework and constraints for the position of the Paleocene-Eocene boundary in the rapidly subsiding Hanna Basin, Wyoming","docAbstract":"The Paleocene–Eocene strata of the rapidly subsiding Hanna Basin give insights in sedimentation patterns and regional paleogeography during the Laramide orogeny and across the climatic event at the Paleocene–Eocene Thermal Maximum (PETM). Abundant coalbeds and carbonaceous shales of the fluvial, paludal, and lacustrine strata of the Hanna Formation offer a different depositional setting than PETM sections described in the nearby Piceance and Bighorn Basins, and the uniquely high sediment accumulation rates give an expanded and near-complete record across this interval. Stratigraphic sections were measured for an ~1250 m interval spanning the Paleocene–Eocene boundary across the northeastern syncline of the basin, documenting depositional changes between axial fluvial sandstones, basin margin, paludal, floodplain, and lacustrine deposits. Leaf macrofossils, palynology, mollusks, δ13C isotopes of bulk organic matter, and zircon sample locations were integrated within the stratigraphic framework and refined the position of the PETM. As observed in other basins of the same age, an interval of coarse, amalgamated sandstones occurs as a response to the PETM. Although this pulse of relatively coarser sediment appears related to climate change at the PETM, it must be noted that several very similar sandstone bodies occur with the Hanna Formation. These sandstones occur in regular intervals and have an apparent cyclic pattern; however, age control is not sufficient yet to address the origin of the cyclicity. Signs of increased ponding and lake expansion upward in the section appear to be a response to basin isolation by emerging Laramide uplifts.","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02118.1","usgsCitation":"Dechesne, M., Currano, E.D., Dunn, R.E., Higgins, P., Hartman, J., Chamberlain, K.R., and Holm-Denoma, C.S., 2020, A new stratigraphic framework and constraints for the position of the Paleocene-Eocene boundary in the rapidly subsiding Hanna Basin, Wyoming: Geosphere, v. 16, no. 2, p. 594-618, https://doi.org/10.1130/GES02118.1.","productDescription":"15 p.","startPage":"594","endPage":"618","ipdsId":"IP-104460","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":458113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02118.1","text":"Publisher Index Page"},{"id":373034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Hanna Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.7266845703125,\n 41.352072144512924\n ],\n [\n -106.0565185546875,\n 41.352072144512924\n ],\n [\n -106.0565185546875,\n 42.049292638686836\n ],\n [\n -106.7266845703125,\n 42.049292638686836\n ],\n [\n -106.7266845703125,\n 41.352072144512924\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2020-01-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Dechesne, Marieke 0000-0002-4468-7495","orcid":"https://orcid.org/0000-0002-4468-7495","contributorId":213936,"corporation":false,"usgs":true,"family":"Dechesne","given":"Marieke","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":784211,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Currano, Ellen D","contributorId":219803,"corporation":false,"usgs":false,"family":"Currano","given":"Ellen","email":"","middleInitial":"D","affiliations":[{"id":34987,"text":"University of Wyoming, Laramie, WY","active":true,"usgs":false}],"preferred":false,"id":784212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Regan E","contributorId":219801,"corporation":false,"usgs":false,"family":"Dunn","given":"Regan","email":"","middleInitial":"E","affiliations":[{"id":40073,"text":"The Field Museum, Chicago","active":true,"usgs":false}],"preferred":false,"id":784213,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higgins, Pennilyn","contributorId":223122,"corporation":false,"usgs":false,"family":"Higgins","given":"Pennilyn","email":"","affiliations":[{"id":40676,"text":"University of Rochester, NY","active":true,"usgs":false}],"preferred":false,"id":784214,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartman, Joseph","contributorId":223123,"corporation":false,"usgs":false,"family":"Hartman","given":"Joseph","email":"","affiliations":[{"id":17628,"text":"University of North Dakota","active":true,"usgs":false}],"preferred":false,"id":784215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chamberlain, Kevin R","contributorId":223124,"corporation":false,"usgs":false,"family":"Chamberlain","given":"Kevin","email":"","middleInitial":"R","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":784216,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440 cholm-denoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":2442,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher","email":"cholm-denoma@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":784217,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70217320,"text":"70217320 - 2020 - Effects of elevated sea levels and waves on southern California estuaries during the 2015–2016 El Niño","interactions":[],"lastModifiedDate":"2021-01-18T13:14:55.631177","indexId":"70217320","displayToPublicDate":"2020-01-16T07:11:44","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Effects of elevated sea levels and waves on southern California estuaries during the 2015–2016 El Niño","docAbstract":"The 2015–2016 El Niño provided insight into how low-inflow estuaries might respond to future climate regimes, including high sea levels and more intense waves. High waves and water levels coupled with low rainfall along the Southern California coastline provided the opportunity to examine how extreme ocean forcing impacts estuaries independently from fluvial events. From November 2015 to April 2016, water levels were measured in 13 Southern California estuaries, including both intermittently closed and perennially open estuaries with varying watershed size, urban development, and management practices. Elevated ocean water levels caused raised water levels and prolonged inundation in all of the estuaries studied. Water levels inside perennially open estuaries mirrored ocean water levels, while those inside intermittently closed estuaries (ICEs) exhibited enhanced higher-high water levels during large waves, and tides were truncated at low tides due to a wave-built sand sill at the mouth, resulting in elevated detided water levels. ICEs closed when sufficient wave-driven sand accretion formed a barrier berm across the mouth separating the estuary from the ocean, the height of which can be estimated using estuarine lower-low water levels. During the 2015–2016 El Niño, a greater number of Southern California ICEs closed than during a typical year and ICEs that close annually experienced longer than normal closures. Overall, sill accretion and wave exposure were important contributing factors to individual estuarine response to ocean conditions. Understanding how estuaries respond to increased sea levels and waves and the factors that influence closures will help managers develop appropriate adaptation strategies.
The Agricultural Water Use (AG) Package was developed for simulating demand-driven and supply-constrained agricultural water use in MODFLOW and GSFLOW models. The AG Package uses pre-existing hydrologic simulation provided by MODFLOW and GSFLOW. Three options are available for simulating water use for agriculture: (1) user-specified demands, (2) demands determined by a user-specified irrigation trigger value that is compared to the ratio of the simulated actual to potential evapotranspiration (ET), and (3) demands determined by minimizing the difference between potential and actual ET. The latter two approaches use energy and soil-water balance to determine crop-water demands. Irrigation withdrawals are diverted into canals and routed to fields using the MODFLOW SFR Package, or irrigation water is provided/supplemented by groundwater. Combined with MODFLOW or GSFLOW, the AG Package can simulate dynamic water use by agriculture in developed basins while providing flexibility to represent a range of irrigation practices.
Rapid seismic deployments following large earthquakes capture ephemeral near‐field recordings of aftershocks and ambient noise that can provide valuable data for seismological studies. The U.S. Geological Survey installed 19 temporary seismic stations following the 4 July 2019 Mw 6.4 and 6 July 2019 (UTC) Mw 7.1 earthquakes near the city of Ridgecrest, California. The stations record the aftershock sequence beginning two days after the mainshock and are expected to remain in the field through approximately January 2020. The deployment augments the permanent seismic network in the area to improve azimuthal coverage and provide additional near‐field observations. This article summarizes the motivation and goals of the deployment; details of station installation, instrumentation, and configurations; and initial data quality and observations from the network. We expect these data to be useful for a range of studies including detailing near‐field variability in strong ground motions, determining stress drops and rupture directivity of small events, imaging the fault zone, documenting the evolution of crustal properties within and outside of the fault zone, and others.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190296","usgsCitation":"Cochran, E.S., Wolin, E., McNamara, D.E., Yong, A., Wilson, D.C., Alvarez, M., van der Elst, N., McClain, A.R., and Steidl, J.H., 2020, The U.S. Geological Survey’s Rapid Seismic Array Deployment for the 2019 Ridgecrest Earthquake Sequence: Seismological Research Letters, v. 91, p. 1952-1960, https://doi.org/10.1785/0220190296.","productDescription":"9 p.","startPage":"1952","endPage":"1960","ipdsId":"IP-113314","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":378081,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n 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0000-0003-1610-1191","orcid":"https://orcid.org/0000-0003-1610-1191","contributorId":221834,"corporation":false,"usgs":true,"family":"Wolin","given":"Emily","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McNamara, Daniel E. 0000-0001-6860-0350 mcnamara@usgs.gov","orcid":"https://orcid.org/0000-0001-6860-0350","contributorId":402,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","email":"mcnamara@usgs.gov","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797745,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, David C. 0000-0001-9667-9449 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-9667-9449","contributorId":239707,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":797746,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alvarez, Mark 0000-0002-1361-5616","orcid":"https://orcid.org/0000-0002-1361-5616","contributorId":222021,"corporation":false,"usgs":true,"family":"Alvarez","given":"Mark","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797747,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"van der Elst, Nicholas 0000-0002-3812-1153 nvanderelst@usgs.gov","orcid":"https://orcid.org/0000-0002-3812-1153","contributorId":147858,"corporation":false,"usgs":true,"family":"van der Elst","given":"Nicholas","email":"nvanderelst@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":797748,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McClain, Adria Ruth 0000-0001-9371-9994","orcid":"https://orcid.org/0000-0001-9371-9994","contributorId":239708,"corporation":false,"usgs":true,"family":"McClain","given":"Adria","email":"","middleInitial":"Ruth","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797749,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steidl, Jamison Haase 0000-0003-0612-7654","orcid":"https://orcid.org/0000-0003-0612-7654","contributorId":239709,"corporation":false,"usgs":true,"family":"Steidl","given":"Jamison","email":"","middleInitial":"Haase","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":797750,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70207962,"text":"70207962 - 2020 - Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014-2016","interactions":[],"lastModifiedDate":"2023-06-23T14:25:48.582192","indexId":"70207962","displayToPublicDate":"2020-01-15T13:49:36","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014-2016","docAbstract":"About 62,000 dead or dying common murres (Uria aalge), the trophically dominant fish-eating seabird of the North Pacific, washed ashore between summer 2015 and spring 2016 on beaches from California to Alaska. Most birds were severely emaciated and, so far, no evidence for anything other than starvation was found to explain this mass mortality. Three-quarters of murres were found in the Gulf of Alaska and the remainder along the West Coast. Studies show that only a fraction of birds that die at sea typically wash ashore, and we estimate that total mortality approached 1 million birds. About two-thirds of murres killed were adults, a substantial blow to breeding populations. Additionally, 22 complete reproductive failures were observed at multiple colonies region-wide during (2015) and after (2016–2017) the mass mortality event. Die-offs and breeding failures occur sporadically in murres, but the magnitude, duration and spatial extent of this die-off, associated with multi-colony and multi-year reproductive failures, is unprecedented and astonishing. These events co-occurred with the most powerful marine heatwave on record that persisted through 2014–2016 and created an enormous volume of ocean water (the “Blob”) from California to Alaska with temperatures that exceeded average by 2–3 standard deviations. Other studies indicate that this prolonged heatwave reduced phytoplankton biomass and restructured zooplankton communities in favor of lower-calorie species, while it simultaneously increased metabolically driven food demands of ectothermic forage fish. In response, forage fish quality and quantity diminished. Similarly, large ectothermic groundfish were thought to have increased their demand for forage fish, resulting in greater top-predator demands for diminished forage fish resources. We hypothesize that these bottom-up and top-down forces created an “ectothermic vise” on forage species leading to their system-wide scarcity and resulting in mass mortality of murres and many other fish, bird and mammal species in the region during 2014–2017.
Genomic tools are lacking for invasive and native populations of sea lamprey (Petromyzon marinus). Our objective was to discover single nucleotide polymorphism (SNP) loci to conduct pedigree analyses to quantify reproductive contributions of adult sea lampreys and dispersion of sibling larval sea lampreys of different ages in Great Lakes tributaries. Additional applications of data were explored using additional geographically expansive samples. We used restriction site‐associated DNA sequencing (RAD‐Seq) to discover genetic variation in Duffins Creek (DC), Ontario, Canada, and the St. Clair River (SCR), Michigan, USA. We subsequently developed RAD capture baits to genotype 3,446 RAD loci that contained 11,970 SNPs. Based on RAD capture assays, estimates of variance in SNP allele frequency among five Great Lakes tributary populations (mean FST 0.008; range 0.00–0.018) were concordant with previous microsatellite‐based studies; however, outlier loci were identified that contributed substantially to spatial population genetic structure. At finer scales within streams, simulations indicated that accuracy in genetic pedigree reconstruction was high when 200 or 500 independent loci were used, even in situations of high spawner abundance (e.g., 1,000 adults). Based on empirical collections of larval sea lamprey genotypes, we found that age‐1 and age‐2 families of full and half‐siblings were widely but nonrandomly distributed within stream reaches sampled. Using the genomic scale set of SNP loci developed in this study, biologists can rapidly genotype sea lamprey in non‐native and native ranges to investigate questions pertaining to population structuring and reproductive ecology at previously unattainable scales.
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