Wetland environments provide numerous ecosystem services but also facilitate methylmercury (MeHg) production and bioaccumulation. We developed a wetland‐management technique to reduce MeHg concentrations in wetland fish and water. We physically modified seasonal wetlands by constructing open‐ and deep‐water treatment cells at the downstream end of seasonal wetlands to promote naturally occurring MeHg‐removal processes. We assessed the effectiveness of reducing mercury (Hg) concentrations in surface water and western mosquitofish that were caged at specific locations within 4 control and 4 treatment wetlands. Methylmercury concentrations in wetland water were successfully decreased within treatment cells during only the third year of study; however, treatment cells were not effective for reducing total Hg concentrations. Furthermore, treatment cells were not effective for reducing total Hg concentrations in wetland fish. Mercury concentrations in fish were not correlated with total Hg concentrations in filtered, particulate, or whole water; and the slope of the correlation with water MeHg concentrations differed between months. Fish total Hg concentrations were weakly correlated with water MeHg concentrations in April when fish were introduced into cages but were not correlated in May when fish were retrieved from cages. Fish total Hg concentrations were greater in treatment wetlands than in control wetlands the year after the treatment wetlands’ construction but declined by the second year. During the third year, fish total Hg concentrations increased in both control and treatment wetlands after an unexpected regional flooding event. Overall, we found limited support for the use of open‐ and deep‐water treatment cells at the downstream end of wetlands to reduce MeHg concentrations in water but not fish. We suggest that additional evaluation over a longer period of time is necessary.
","language":"English","publisher":"Wiley","doi":"10.1002/etc.4535","usgsCitation":"Ackerman, J., Fleck, J., Eagles-Smith, C.A., Marvin-DiPasquale, M.C., Windham-Myers, L., Herzog, M.P., and McQuillen, H.L., 2019, Wetland management strategy to reduce mercury export in water and bioaccumulation in fish: Environmental Toxicology and Chemistry, v. 38, no. 10, p. 2178-2196, https://doi.org/10.1002/etc.4535.","productDescription":"19 p.","startPage":"2178","endPage":"2196","ipdsId":"IP-104169","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":437381,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NUANQU","text":"USGS data release","linkHelpText":"Wetland Management Strategy to Reduce Mercury Export in Water and Bioaccumulation in Fish"},{"id":367232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":770315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":770317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":770318,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Windham-Myers, Lisamarie lwindham-myers@usgs.gov","contributorId":218804,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","email":"lwindham-myers@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":770319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":770320,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McQuillen, Harry L.","contributorId":218805,"corporation":false,"usgs":false,"family":"McQuillen","given":"Harry","email":"","middleInitial":"L.","affiliations":[{"id":6696,"text":"BLM","active":true,"usgs":false}],"preferred":false,"id":770321,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204480,"text":"ofr20191079 - 2019 - Effects of microcystin-LR on juvenile Lost River suckers (Deltistes luxatus) during feeding trials, Upper Klamath Lake, Oregon, 2014−16","interactions":[],"lastModifiedDate":"2019-07-26T09:26:00","indexId":"ofr20191079","displayToPublicDate":"2019-07-25T14:52:04","publicationYear":"2019","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":"2019-1079","displayTitle":"Effects of Microcystin-LR on Juvenile Lost River Suckers (Deltistes luxatus) during Feeding Trials, Upper Klamath Lake, Oregon, 2014−16","title":"Effects of microcystin-LR on juvenile Lost River suckers (Deltistes luxatus) during feeding trials, Upper Klamath Lake, Oregon, 2014−16","docAbstract":"Historically, populations of Lost River suckers (Deltistes luxatus) of the Upper Klamath Basin were so numerous that they were commercially harvested; however, declining numbers throughout the 20th century led to the listing of the species under the United States Endangered Species Act in 1988. Habitat destruction, poor water quality, competition with (and predation by) nonnative species, especially fathead minnows (Pimephales promelas) and yellow perch (Perca flavescens), are hypothesized as primary causes of population decline (U.S. Fish and Wildlife Service, 2013). Age data indicate that almost all adult suckers presently in Upper Klamath Lake spawning populations were hatched in the early 1990s. While entrainment of young fish (especially larvae) may contribute, catch-at-length and age data suggest consistently high mortality during the first year of life may be preventing the recruitment of young adults. The specific causes of juvenile sucker mortality are unknown; however, the absence of juvenile suckers in trap net catches coincides with degraded water quality associated with the decay of cyanobacteria blooms and exposure to toxic microcystin produced by Microcystis cyanobacteria.
Water-quality data collected in Upper Klamath Lake from 2011 to 2016 suggest that microcystin concentrations in Upper Klamath Lake reached potentially lethal levels based on literature findings from studies on a variety of fish species. We conducted a laboratory feeding trial to determine if microcystin toxicity could potentially be a direct cause of juvenile Lost River sucker mortality. We examined the effects of environmentally relevant doses of microcystin on the survival and health of hatchery-reared juvenile Lost River suckers. Results from this laboratory study suggest that Lost River suckers are very tolerant of the microcystin-LR toxin. Histopathological analysis revealed no evidence of tissue changes associated with microcystin-LR exposure. Although no direct effects of microcystin-LR exposure were detected, suckers could potentially be negatively affected through added energy expenditures and stress associated with excretion of microcystin. Furthermore, microcystin may adversely affect other organisms in Upper Klamath Lake that could alter food availability or habitat of the suckers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191079","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and Bureau of Reclamation","usgsCitation":"Martin, B.A., Echols, K.R., Elliott, D.G., Feltz, K., Conway, C.M., and Burdick, S.M., 2019, Effects of microcystin-LR on juvenile Lost River suckers (Deltistes luxatus) during feeding trials, Upper Klamath Lake, Oregon, 2014−16: U.S. Geological Survey Open−File Report 2019–1079, 22 p., https://doi.org/10.3133/ofr20191079.","productDescription":"vi, 22 p.","onlineOnly":"Y","ipdsId":"IP-106575","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":365967,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1079/coverthb.jpg"},{"id":365968,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1079/ofr20191079.pdf","text":"Report","size":"7.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1079"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.08625793457031,\n 42.48222557002593\n ],\n [\n -122.09449768066405,\n 42.47361631282951\n ],\n [\n -122.05879211425781,\n 42.43004544849287\n ],\n [\n -122.04505920410156,\n 42.40976960320691\n ],\n [\n -122.01004028320312,\n 42.38847290951024\n ],\n [\n -121.99836730957031,\n 42.412304442420684\n ],\n [\n -121.97776794433594,\n 42.40013627993722\n ],\n [\n -121.97982788085938,\n 42.367676308265196\n ],\n [\n -121.9482421875,\n 42.39354420646467\n ],\n [\n -121.95922851562501,\n 42.42700448967684\n ],\n [\n -121.91665649414062,\n 42.36006607480819\n ],\n [\n -121.90292358398438,\n 42.357529125471395\n ],\n [\n -121.95098876953125,\n 42.341797753508665\n ],\n [\n -121.94618225097656,\n 42.30676863078423\n ],\n [\n -121.93313598632812,\n 42.2869609344916\n ],\n [\n -121.92420959472655,\n 42.284929023632834\n ],\n [\n -121.92283630371092,\n 42.30422953071753\n ],\n [\n -121.89193725585936,\n 42.31184652369511\n ],\n [\n -121.87889099121092,\n 42.293056273848215\n ],\n [\n -121.85897827148438,\n 42.267655135366624\n ],\n [\n -121.84593200683592,\n 42.254442496693386\n ],\n [\n -121.8438720703125,\n 42.242243757492766\n ],\n [\n -121.83425903320314,\n 42.23461834757937\n ],\n [\n -121.81022644042969,\n 42.23004265933714\n ],\n [\n -121.80335998535158,\n 42.24122708941077\n ],\n [\n -121.8109130859375,\n 42.25850821886463\n ],\n [\n -121.82807922363281,\n 42.28289704723818\n ],\n [\n -121.81846618652345,\n 42.29661161608281\n ],\n [\n -121.80816650390625,\n 42.3143853165376\n ],\n [\n -121.81571960449217,\n 42.33773740551283\n ],\n [\n -121.82533264160156,\n 42.34535034292539\n ],\n [\n -121.80885314941406,\n 42.38137240541685\n ],\n [\n -121.81777954101561,\n 42.40064333382955\n ],\n [\n -121.85966491699217,\n 42.437647200108685\n ],\n [\n -121.86927795410156,\n 42.44980808481614\n ],\n [\n -121.89056396484375,\n 42.44727476182866\n ],\n [\n -121.91253662109376,\n 42.47969355851231\n ],\n [\n -121.92008972167969,\n 42.48019996901214\n ],\n [\n -121.92420959472655,\n 42.49285889946235\n ],\n [\n -121.94000244140624,\n 42.49235259142821\n ],\n [\n -121.94000244140624,\n 42.500959270579585\n ],\n [\n -121.94892883300781,\n 42.49792175437361\n ],\n [\n -122.0086669921875,\n 42.49792175437361\n ],\n [\n -122.03407287597655,\n 42.500959270579585\n ],\n [\n -122.04849243164061,\n 42.49589666159403\n ],\n [\n -122.05879211425781,\n 42.48425110546248\n ],\n [\n -122.06359863281249,\n 42.461460050936715\n ],\n [\n -122.07527160644531,\n 42.46399280017058\n ],\n [\n -122.08625793457031,\n 42.48222557002593\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Contemporary policymakers rarely stress ecological knowledge, and yet this knowledge remains crucial—just as it was in prehistory—to protecting overall human well-being. Measuring carefully selected ecological health indicators—that is, signs or symptoms, especially those focused on biotic assemblages—can provide insights into the ecological condition of a place and the variety of ecological consequences of proposed or present human actions there. In turn, measured ecological conditions may be judged as acceptable (healthy) or unacceptable (unhealthy), depending on prevailing value systems and societal goals. Ecological health indicators characterize the ecological conditions of where we live; improve scientific understanding of ecosystems and the benefits they provide; diagnose causes of ecological degradation; communicate scientific knowledge to nontechnical audiences; guide environmental policy; and measure progress toward societal goals. By helping to identify who benefits and who suffers from societal choices, ecological health indicators inform our choices about how to use or protect ecosystems and their living components, including human society itself.
The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 resulted in an increased demand for water in areas within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project.
An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. As of 2018, the network consisted of 120 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the ABCWUA, the New Mexico Office of the State Engineer, and Bernalillo County, measures water levels from the 120 wells and piezometers in the network; this report, prepared in cooperation with the ABCWUA, presents water-level data collected by USGS personnel at those 120 sites through water year 2018 (October 1, 2017, through September 30, 2018). Water levels that were collected from wells in previous water years were published in previous USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1116","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Ritchie, A.B., and Galanter, A.E., 2019, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2018 (ver. 1.1, August 2021): U.S. Geological Survey Data Series 1116, 40 p., https://doi.org/10.3133/ds1116.","productDescription":"iii, 40 p.","numberOfPages":"49","onlineOnly":"Y","ipdsId":"IP-108049","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":365903,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1116/coverthb2.jpg"},{"id":388360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1116/ds1116.pdf","text":"Report","size":"5.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1116"},{"id":388361,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/1116/versionHist.txt","text":"Version History","size":"554 B","linkFileType":{"id":2,"text":"txt"},"description":"DS 1116 Verson History"}],"country":"United States","state":"New Mexico","otherGeospatial":"Albuquerque Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107,\n 34.85\n ],\n [\n -106.375,\n 34.85\n ],\n [\n -106.375,\n 35.4\n ],\n [\n -107,\n 35.4\n ],\n [\n -107,\n 34.85\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: August 2021","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Exotic predators create novel ecological contexts for native species, particularly when prey exhibit predator naïve behaviors. Population recovery of island endemic species following predator eradication has been documented broadly, but studies examining mammalian prey behavioral responses to exotic predator removal are less common. The Key Largo woodrat (Neotoma floridana smalli) is an endangered Florida endemic species that exhibited drastic declines, signified by the loss of natural stick-nests, over the past three decades due to habitat loss and effects from exotic predators. We conducted camera trap surveys of woodrats at supplemental nests and used dynamic multistate occupancy models to evaluate changes in woodrat distribution and stick-nest building behavior over a two-year period of exotic predator (domestic cats [Felis catus] and Burmese pythons [Python bivittatus]) removal. The distribution of woodrats using supplemental nests increased from 27% to 39% in the two-year period, while the proportion of occupied supplemental nests with stick-nests increased from 37% in 2013 to 54% in 2015. The probabilities of supplemental nest use and stick-nest building behavior increased over time following a gradient away from the northern extent of Key Largo, an area associated with high cat activity and the only sites of python captures during the surveys. Woodrats that built stick-nests were more detectable than those that did not, which suggests that stick-nest building could make woodrats more susceptible to predation from novel predators when performing the behavior. We documented increasing woodrat occurrence, along with increasing stick-nest building behavior, which supports recovery and management objectives focused on exotic predator removal.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2019.07.032","usgsCitation":"Cove, M., Simons, T., Gardner, B., and O’Connell, A.F., 2019, Towards recovery of an endangered island endemic: Distributional and behavioral responses of Key Largo woodrats associated with exotic predator removal: Biological Conservation, v. 237, p. 423-429, https://doi.org/10.1016/j.biocon.2019.07.032.","productDescription":"7 p.","startPage":"423","endPage":"429","ipdsId":"IP-106113","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467424,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2019.07.032","text":"Publisher Index Page"},{"id":365984,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Crocodile Lake National Wildlife Refuge, North Key Largo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.33512115478516,\n 25.242522196751892\n ],\n [\n -80.32379150390625,\n 25.229168280105522\n ],\n [\n -80.27847290039062,\n 25.301510302409604\n ],\n [\n -80.27503967285155,\n 25.311752681576287\n ],\n [\n -80.2606201171875,\n 25.326028492609215\n ],\n [\n -80.25581359863281,\n 25.333786379654885\n ],\n [\n -80.27778625488281,\n 25.335027595439435\n ],\n [\n -80.28980255126953,\n 25.324787184543645\n ],\n [\n -80.29151916503906,\n 25.315787320493133\n ],\n [\n -80.30593872070311,\n 25.30678678767568\n ],\n [\n -80.33306121826172,\n 25.286610751172574\n ],\n [\n -80.34095764160156,\n 25.290956642751954\n ],\n [\n -80.36567687988281,\n 25.28536903925994\n ],\n [\n -80.36602020263672,\n 25.280402064492023\n ],\n [\n -80.34164428710938,\n 25.264568475331583\n ],\n [\n -80.3323745727539,\n 25.263947508176397\n ],\n [\n -80.33512115478516,\n 25.242522196751892\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"237","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cove, Michael V.","contributorId":176507,"corporation":false,"usgs":false,"family":"Cove","given":"Michael V.","affiliations":[],"preferred":false,"id":767193,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simons, Theodore","contributorId":217660,"corporation":false,"usgs":false,"family":"Simons","given":"Theodore","affiliations":[{"id":39678,"text":"NC State","active":true,"usgs":false}],"preferred":false,"id":767194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":767195,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Connell, Allan F. 0000-0001-7032-7023 aoconnell@usgs.gov","orcid":"https://orcid.org/0000-0001-7032-7023","contributorId":471,"corporation":false,"usgs":true,"family":"O’Connell","given":"Allan","email":"aoconnell@usgs.gov","middleInitial":"F.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":767192,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70223427,"text":"70223427 - 2019 - Population dynamics and evaluation of management scenarios for white sturgeon in the Sacramento-San Joaquin River basin","interactions":[],"lastModifiedDate":"2021-08-26T16:58:08.151328","indexId":"70223427","displayToPublicDate":"2019-07-25T11:26:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics and evaluation of management scenarios for white sturgeon in the Sacramento-San Joaquin River basin","docAbstract":"Recent surveys suggest a declining population of White Sturgeon Acipenser transmontanus in the Sacramento–San Joaquin River basin (SSJ), California. Probable reasons for the decline include overharvest and habitat degradation compounded by poor recruitment during recent droughts. Despite the importance and status of White Sturgeon, knowledge of their population dynamics in the SSJ remains incomplete and additional information is needed to further inform management decisions. The purpose of this study was to evaluate the population dynamics of White Sturgeon in the SSJ and use the information to estimate the population-level response under plausible management scenarios. White Sturgeon in the SSJ exhibited fast growth and high rates of mortality and experienced relatively high levels of exploitation. Under current conditions, the population will likely continue to decrease (population growth rate λ = 0.97); however, there was considerable uncertainty in estimates of future population growth. Population growth of White Sturgeon in the SSJ was most influenced by the survival of sexually mature adults. The models also suggested that White Sturgeon in the SSJ could reach the replacement rate (i.e., λ ≥ 1.00) if total annual mortality for age-3 and older fish does not exceed 6%. Low levels of exploitation (i.e., <3%) would likely be required to maintain a stable population.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10316","usgsCitation":"Blackburn, S.E., Gingras, M.L., DuBois, J., Jackson, Z.J., and Quist, M.C., 2019, Population dynamics and evaluation of management scenarios for white sturgeon in the Sacramento-San Joaquin River basin: North American Journal of Fisheries Management, v. 39, no. 5, p. 896-912, https://doi.org/10.1002/nafm.10316.","productDescription":"7 p.","startPage":"896","endPage":"912","ipdsId":"IP-103139","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":388552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.728271484375,\n 37.337408137077986\n ],\n [\n -121.54998779296874,\n 37.337408137077986\n ],\n [\n -121.54998779296874,\n 38.26621945628273\n ],\n [\n -122.728271484375,\n 38.26621945628273\n ],\n [\n -122.728271484375,\n 37.337408137077986\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"5","noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Blackburn, Shannon E.","contributorId":264816,"corporation":false,"usgs":false,"family":"Blackburn","given":"Shannon","email":"","middleInitial":"E.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":822019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gingras, Marty L.","contributorId":264817,"corporation":false,"usgs":false,"family":"Gingras","given":"Marty","email":"","middleInitial":"L.","affiliations":[{"id":54562,"text":"cdfw","active":true,"usgs":false}],"preferred":false,"id":822020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DuBois, Jason","contributorId":264818,"corporation":false,"usgs":false,"family":"DuBois","given":"Jason","email":"","affiliations":[{"id":54562,"text":"cdfw","active":true,"usgs":false}],"preferred":false,"id":822021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, Zachary J.","contributorId":264819,"corporation":false,"usgs":false,"family":"Jackson","given":"Zachary","email":"","middleInitial":"J.","affiliations":[{"id":37461,"text":"fws","active":true,"usgs":false}],"preferred":false,"id":822022,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Quist, Michael C. 0000-0001-8268-1839 mquist@usgs.gov","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":171392,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":822018,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204755,"text":"70204755 - 2019 - Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat","interactions":[],"lastModifiedDate":"2019-08-15T11:11:11","indexId":"70204755","displayToPublicDate":"2019-07-25T10:50:49","publicationYear":"2019","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":"Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat","docAbstract":"Coastal storms have consequences for human lives and infrastructure but also create important early successional habitats for myriad species. For example, storm-induced overwash creates nesting habitat for shorebirds like piping plovers (Charadrius melodus). We examined how piping plover habitat extent and location changed on barrier islands in New York, New Jersey, and Virginia after Hurricane Sandy made landfall following the 2012 breeding season. We modeled nesting habitat using a nest presence/absence dataset that included characterizations of coastal morphology and vegetation. Using a Bayesian network, we predicted nesting habitat for each study site for the years 2010/2011, 2012, and 2014/2015 based on remotely sensed spatial datasets (e.g., lidar, orthophotos). We found that Hurricane Sandy increased piping plover habitat by 9 to 300% at 4 of 5 study sites but that one site saw a decrease in habitat by 27%. The amount, location, and longevity of new habitat appeared to be influenced by the level of human development at each site. At three of the five sites, the amount of habitat created and the time new habitat persisted were inversely related to the amount of development. Furthermore, the proportion of new habitat created in high-quality overwash was inversely related to the level of development on study areas, from 17% of all new habitat in overwash at one of the most densely developed sites to 80% of all new habitat at an undeveloped site. We also show that piping plovers exploited new habitat after the storm, with 14–57% of all nests located in newly created habitat in the 2013 breeding season. Our results quantify the importance of storms in creating and maintaining coastal habitats for beach-nesting species like piping plovers, and these results suggest a negative correlation between human development and beneficial ecological impacts of these natural disturbances.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0209986","usgsCitation":"Zeigler, S.L., Gutierrez, B.T., Sturdivant, E.J., Catlin, D.H., Fraser, J., Hecht, A., Karpanty, S.M., Plant, N.G., and Thieler, E.R., 2019, Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat: PLoS ONE, v. 14, no. 7, e0209986, 30 p., https://doi.org/10.1371/journal.pone.0209986.","productDescription":"e0209986, 30 p.","ipdsId":"IP-092113","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467425,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0209986","text":"Publisher Index 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Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768445,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70204625,"text":"70204625 - 2019 - Decision analysis for the reintroduction of Bull Trout into the lower Pend Oreille River, Washington","interactions":[],"lastModifiedDate":"2019-10-28T10:07:48","indexId":"70204625","displayToPublicDate":"2019-07-25T09:43:23","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Decision analysis for the reintroduction of Bull Trout into the lower Pend Oreille River, Washington","docAbstract":"The decision to reintroduce a species can be difficult owing to conflicting opinions and objectives, as well as uncertainty of the outcome. Structured decision making addresses these considerations by identifying realistic fundamental objectives and building achievable management alternatives, within a quantitative modeling framework. The process is driven by participation of stakeholders that represent diverse objectives, policy mandates, and opinions regarding decision alternatives. We applied structured decision making to evaluate reintroduction of Bull Trout Salvelinus confluentus in the lower Pend Oreille River in northeastern Washington State. We engaged stakeholders from Tribal, municipal, county, state and federal agencies to specify fundamental objectives, formulate feasible reintroduction decisions, and conceptualize a modeling framework that includes biological information and stakeholder assumptions. Stakeholders requested iterative decision sets to determine the optimal recipient streams and release strategies. The optimal decision, based on the fundamental objective of maximizing adult abundance at year 10, was artificial propagation of 4500 juvenile Bull Trout coupled with translocation of 25 adult migrants to be reintroduced into a tributary and lake system that produced at least 18% more adult fish relative to alternatives. Sensitivity analyses were robust to the identity of the recipient stream (i.e., Sullivan Lake/Harvey Creek was always the optimal recipient stream) but suggested that maximizing the number of artificially produced juveniles released could produce a similar number of adult Bull Trout as the coupled release strategy. Results also suggested that ensuring fish passage at the Albeni Falls Dam in the mainstem Pend Oreille River could increase the abundance of adult fish. The process followed for this case study can be adapted to similar decisions regarding reintroduction or other translocations of fish in other systems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10334","usgsCitation":"Benjamin, J.R., Brignon, W.R., and Dunham, J.B., 2019, Decision analysis for the reintroduction of Bull Trout into the lower Pend Oreille River, Washington: North American Journal of Fisheries Management, v. 39, no. 5, p. 1026-1045, https://doi.org/10.1002/nafm.10334.","productDescription":"20 p.","startPage":"1026","endPage":"1045","additionalOnlineFiles":"N","ipdsId":"IP-104456","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":366328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Pend Oreille River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.48779296875,\n 48.07257353224749\n ],\n [\n -116.74072265625,\n 48.07257353224749\n ],\n [\n -116.74072265625,\n 48.99103162515999\n ],\n [\n -117.48779296875,\n 48.99103162515999\n ],\n [\n -117.48779296875,\n 48.07257353224749\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":767827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brignon, William R.","contributorId":193087,"corporation":false,"usgs":false,"family":"Brignon","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":767828,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":767829,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223294,"text":"70223294 - 2019 - Spatial and temporal variation of ecosystem properties at macroscales","interactions":[],"lastModifiedDate":"2021-08-20T14:04:32.279269","indexId":"70223294","displayToPublicDate":"2019-07-25T08:59:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal variation of ecosystem properties at macroscales","docAbstract":"Although spatial and temporal variation in ecological properties has been well-studied, crucial knowledge gaps remain for studies conducted at macroscales and for ecosystem properties related to material and energy. We test four propositions of spatial and temporal variation in ecosystem properties within a macroscale (1000 km's) extent. We fit Bayesian hierarchical models to thousands of observations from over two decades to quantify four components of variation – spatial (local and regional) and temporal (local and coherent); and to model their drivers. We found strong support for three propositions: (1) spatial variation at local and regional scales are large and roughly equal, (2) annual temporal variation is mostly local rather than coherent, and, (3) spatial variation exceeds temporal variation. Our findings imply that predicting ecosystem responses to environmental changes at macroscales requires consideration of the dominant spatial signals at both local and regional scales that may overwhelm temporal signals.
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Center","active":true,"usgs":true}],"preferred":true,"id":821632,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206209,"text":"70206209 - 2019 - Fluvial sedimentary history of Arlington Canyon, Channel Islands National Park, California","interactions":[],"lastModifiedDate":"2019-10-25T06:59:32","indexId":"70206209","displayToPublicDate":"2019-07-25T06:58:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2437,"text":"Journal of Quaternary Science","active":true,"publicationSubtype":{"id":10}},"title":"Fluvial sedimentary history of Arlington Canyon, Channel Islands National Park, California","docAbstract":"Arlington Canyon, in the northwest part of Santa Rosa Island, Channel Islands National Park, California, has been the setting for important scientific discoveries over the past half century, including the oldest human remains in North America, several 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The canyon is filled with alluvial sediments that date to between 16.4 and 1.1 ka (thousands of calibrated years before present), representing accumulation that occurred primarily in response to rising sea levels during the late Pleistocene and Holocene. The deposits are laterally discontinuous, exhibit a high degree of sedimentary complexity, and contain evidence of past climates and environments, including fossil bones, burned plant macrofossils, and invertebrate microfossils. Here, we show that it is critical to view the observations, data, and conclusions of scientific studies conducted in the canyon within this larger context so that localized facets of the spatially and temporally extensive alluvial deposits are not misinterpreted or misrepresented. By improving the baseline understanding of processes and drivers of sediment accumulation in Arlington Canyon, we hope to offer a solid foundation and better underpinning for future archeological, paleontological, and geochemical studies here and throughout the northern Channel Islands.","language":"English","publisher":"Wiley","doi":"10.1002/jqs.3123","usgsCitation":"Schumann, R.R., and Pigati, J.S., 2019, Fluvial sedimentary history of Arlington Canyon, Channel Islands National Park, California: Journal of Quaternary Science, v. 34, no. 7, p. 499-508, https://doi.org/10.1002/jqs.3123.","productDescription":"10 p.","startPage":"499","endPage":"508","ipdsId":"IP-102249","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":368588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Channel Islands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.62988281249999,\n 33.80197351806589\n ],\n [\n -119.24560546875001,\n 33.80197351806589\n ],\n [\n -119.24560546875001,\n 34.18454183141725\n ],\n [\n -120.62988281249999,\n 34.18454183141725\n ],\n [\n -120.62988281249999,\n 33.80197351806589\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"34","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Schumann, R. 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Mottled ducks are a priority species in the Texas/Louisiana Gulf Coast area and have been affected by critical habitat reduction. In recent years, mottled duck habitats have been threatened by natural and anthropogenic changes including urbanization, flooding, saltwater intrusion, and hydrologic alterations. These impacts are affecting the quality of habitat that is essential for the mottled duck nesting, feeding, and livelihood. Cumulative and synergistic effects of contamination and invasive species encroachment have also caused mottled duck habitat to be considered as some of the most critically endangered habitats in the United States. To help understand the environmental conditions that characterize the coastal landscape, U.S. Geological Survey researchers used an unmanned aerial system (UAS) to acquire high-resolution imagery to document current land and water spatial configuration and wetland health at McFaddin National Wildlife Refuge, Texas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191045","usgsCitation":"Jones, W.R., Hartley, S.B., Stagg, C.L., and Osland, M.J., 2019, Using UAS capabilities to help identify hummock-hollow formation and fragmentation in critical marsh habitat (Spartina patens) for mottled ducks in southeast Texas: U.S. Geological Survey Open-File Report 2019–1045, 6 p., https://doi.org/10.3133/ofr20191045.","productDescription":"6 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-105924","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365530,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1045/coverthb.jpg"},{"id":365531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1045/ofr20191045.pdf","text":"Report","size":"4.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1045"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.66796875,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 25.760319754713887\n ],\n [\n -93.6474609375,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 32.24997445586331\n ],\n [\n -99.66796875,\n 25.760319754713887\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
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We surveyed the bee fauna at Napatree Point, a coastal barrier beach in southwestern Rhode Island, using bee-bowl and netting samples, and compared results to bee-bowl samples at 2 inland sites. We collected a total of 53 species and morphospecies at Napatree Point, including 5 likely Rhode Island state records and several coastal dune and sand-nesting species that were not found inland. The comparative bee-bowl samples (colored bowls with soapy water placed at the sites to collect visiting bees) captured 35 species at Napatree Point and 66 at the inland sites (which included 6 likely state records, 2 shared with Napatree). The Napatree fauna shared numerous species with the inland sites, but overall species composition differed substantially. Both Napatree and inland sites showed greatest bee activity and species richness in spring. During spring, the most common bees at Napatree were twig- and cavity-nesting species such as Ceratina dupla and Osmia simillima, and the wood-nesting Lasioglossum oblongum, while the most abundant bees inland were the soil-nesting Andrena nasonii and Augochlorella aurata. Netting samples differed from bee-bowl samples in that they captured larger species and species foraging at flowers distant from the bee-bowl transects, but they missed several diminutive species that were captured by bee bowls. Use of 2 sampling methods, therefore, provided a broader view of the bee fauna than would have been possible with a single collection method.
","language":"English","publisher":"BioOne","doi":"10.1656/045.026.0301","usgsCitation":"Rothwell, A., and Ginsberg, H., 2019, The bee fauna of coastal Napatree Point and two inland sites in southern Rhode Island: Northeastern Naturalist, v. 26, no. 3, p. 446-464, https://doi.org/10.1656/045.026.0301.","productDescription":"19 p.","startPage":"446","endPage":"464","ipdsId":"IP-100044","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488834,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/138","text":"External Repository"},{"id":368032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Napatree Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.90277099609375,\n 41.30257109430557\n ],\n [\n -71.46469116210936,\n 41.352072144512924\n ],\n [\n -71.51309967041016,\n 41.50832019744722\n ],\n [\n -71.63223266601562,\n 41.48311944560493\n ],\n [\n -71.90277099609375,\n 41.30257109430557\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rothwell, Aya","contributorId":219515,"corporation":false,"usgs":false,"family":"Rothwell","given":"Aya","email":"","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":772438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":147665,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard S.","email":"hginsberg@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772437,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70204133,"text":"tm7C23 - 2019 - Resource Assessment Economic Filter (RAEF)—A graphical user interface supporting implementation of simple engineering mine cost analyses of quantitative mineral resource assessment simulations","interactions":[],"lastModifiedDate":"2019-07-25T10:29:02","indexId":"tm7C23","displayToPublicDate":"2019-07-24T09:15:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"7-C23","displayTitle":"Resource Assessment Economic Filter (RAEF)—A Graphical User Interface Supporting Implementation of Simple Engineering Mine Cost Analyses of Quantitative Mineral Resource Assessment Simulations","title":"Resource Assessment Economic Filter (RAEF)—A graphical user interface supporting implementation of simple engineering mine cost analyses of quantitative mineral resource assessment simulations","docAbstract":"Economic evaluations of undiscovered mineral resources provide important context in which to consider the results of quantitative mineral resource assessments. The U.S. Geological Survey economic analysis method uses a simple engineering cost model approach developed by the U.S. Bureau of Mines that applies mine and mill engineering cost equations to simulated undiscovered deposits. The important characteristics of these deposits are derived from Monte Carlo simulations that combine probabilistic estimates of undiscovered deposits that might occur in a study area and a grade-tonnage model defined for a specific deposit type. This report describes the Resource Assessment Economic Filter (RAEF), a graphical user interface (GUI) tool that applies a set of mine cost equations to the deposits under consideration. RAEF, which is written in the open-source statistical programming language R, is an easy-to-use tool to apply user-defined mine, mill, and study area parameters to simulated deposits. For a given deposit type, it estimates the undiscovered resources that might be economic to extract. In addition, RAEF provides a series of graphical, tabular, and statistical summaries that document the results of the economic filter analysis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm7C23","usgsCitation":"Shapiro, J.L., and Robinson, G.R., Jr., 2019, Resource Assessment Economic Filter (RAEF)—A graphical user interface supporting implementation of simple engineering mine cost analyses of quantitative mineral resource assessment simulations: U.S. Geological Survey Techniques and Methods, book 7, chap. C23, 18 p., https://doi.org/10.3133/tm7C23.","productDescription":"18 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104850","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":365868,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/07/c23/tm7c23.pdf","text":"Report","size":"1.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 7-C23"},{"id":365867,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/07/c23/coverthb.jpg"},{"id":365869,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/07/c23/tm7c23_package.zip","text":"Resource Assessment Economic Filter Package","size":"125.87 MB","linkFileType":{"id":6,"text":"zip"}}],"contact":"Eastern Mineral and Environmental Resources Science Center
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Satellite-derived spectral indices such as the relativized burn ratio (RBR) allow fire severity maps to be produced in a relatively straightforward manner across multiple fires and broad spatial extents. These indices often have strong relationships with field-based measurements of fire severity, thereby justifying their widespread use in management and science. However, satellite-derived spectral indices have been criticized because their non-standardized units render them difficult to interpret relative to on-the-ground fire effects. In this study, we built a Random Forest model describing a field-based measure of fire severity, the composite burn index (CBI), as a function of multiple spectral indices, a variable representing spatial variability in climate, and latitude. CBI data primarily representing forested vegetation from 263 fires (8075 plots) across the United States and Canada were used to build the model. Overall, the model performed well, with a cross-validated R2 of 0.72, though there was spatial variability in model performance. The model we produced allows for the direct mapping of CBI, which is more interpretable compared to spectral indices. Moreover, because the model and all spectral explanatory variables were produced in Google Earth Engine, predicting and mapping of CBI can realistically be undertaken on hundreds to thousands of fires. We provide all necessary code to execute the model and produce maps of CBI in Earth Engine. This study and its products will be extremely useful to managers and scientists in North America who wish to map fire effects over large landscapes or regions.
","language":"English","publisher":"MDPI","doi":"10.3390/rs11141735","usgsCitation":"Parks, S., Holsinger, L.M., Koontz, M.J., Collins, L.S., Whitman, E., Parisien, M., Loehman, R.A., Barnes, J.L., Bourdon, J., Boucher, J., Boucher, Y., Caprio, A.C., Collingwood, A., Hall, R., Park, J., Saperstein, L., Smetanka, C., Smith, R.J., and Soverel, N., 2019, Giving ecological meaning to satellite-derived fire severity metrics across North American forests: Remote Sensing, v. 11, 1735, 19 p., https://doi.org/10.3390/rs11141735.","productDescription":"1735, 19 p.","ipdsId":"IP-109412","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":460326,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11141735","text":"Publisher Index Page"},{"id":367416,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United 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National Park, PO Box 168, 22 Stable Street, Yellowstone National Park, WY, 82190, USA","active":true,"usgs":false}],"preferred":false,"id":770808,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Soverel, Nick","contributorId":218977,"corporation":false,"usgs":false,"family":"Soverel","given":"Nick","email":"","affiliations":[{"id":39948,"text":"Self-employed","active":true,"usgs":false}],"preferred":false,"id":770809,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70203800,"text":"ofr20191062 - 2019 - Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17","interactions":[],"lastModifiedDate":"2019-07-25T10:24:32","indexId":"ofr20191062","displayToPublicDate":"2019-07-23T14:26:27","publicationYear":"2019","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":"2019-1062","displayTitle":"Monitoring Breeding and Survival of Ring-Necked Pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, Northern California—Five-Year Summary, 2013–17","title":"Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17","docAbstract":"The U.S. Geological Survey Western Ecological Research Center, Pheasants Forever, Mandeville Island Duck Club, and the California Department of Fish and Wildlife collaborated in a reconnaissance study to monitor populations of ring-necked pheasant (Phasianus colchicus) using radio-telemetry in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin of northern California. The purpose of this study was to provide agencies and private landowners with a framework of decision-support tools to help manage pheasant populations in California. During winter, spring, and autumn of 2013–17, we radio- or Global Positioning System-marked 227 female pheasant across six study sites. Data collection was focused on investigating nest-site and brood-rearing habitat selection, examining avian predator composition, and estimating population vital rates to improve our understanding of pheasant population dynamics and to identify factors that may contribute to decreases in pheasant populations in California. The cumulative annual adult survival probability across all sites during 2013–17 was 27.6 percent (95-percent confidence interval [CI], 21.9–33.6), and the cumulative nest and brood survival probabilities were 34.5 percent (95-percent CI, 27.0–42.2) and 54.2 percent (95-percent CI, 43.7–63.5), respectively. Evidence from microhabitat surveys completed at nest-sites, brood locations, and random locations suggested that marked female pheasant tended to select increasing vertical cover and residual vegetation cover and tended to avoid areas of increasing bare ground cover regardless of life-history stage. However, females at nest-sites selected increasing grass cover and height, whereas brood-rearing females tended to select increasing forb cover and height. Only perennial grass cover and perennial grass height were shown to have a positive influence on nest survival, which suggests that increasing perennial grass cover in areas occupied by pheasant may increase nest survival. Analysis of environmental factors linked to vital rate information are ongoing and will continue with investigations at increased spatial scales (that is, macro-habitat) to develop integrated population models that can incorporate abundance estimates from crow count data with vital rates from telemetry data. This report includes results from 5 years of data collection and should be interpreted with caution, as these findings are preliminary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191062","collaboration":"Prepared in cooperation with the California Department of Fish and Wildlife and Pheasants Forever","usgsCitation":"=Dwight, I.A., Coates, P.S., Vogt, J.H., Atkinson, J.L., Fleskes, J.P., Connelly, D.P., Meshriy, M.C., Gardner, S.C., Stoute, S.T., and Pitesky M.E., 2019, Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17: U.S. Geological Survey Open-File Report 2019–1062, 90 p., https://doi.org/10.3133/ofr20191062.","productDescription":"90 p.","onlineOnly":"Y","ipdsId":"IP-099248","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":365826,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1062/ofr20191062.pdf","text":"Report","size":"44.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1062"},{"id":365825,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1062/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.9644775390625,\n 37.55328764595765\n ],\n [\n -119.5147705078125,\n 37.55328764595765\n ],\n [\n -119.5147705078125,\n 39.89709437260048\n ],\n [\n -122.9644775390625,\n 39.89709437260048\n ],\n [\n -122.9644775390625,\n 37.55328764595765\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive
Modoc Hall, Room 4004
Sacramento, California 95819
This scientific investigations report describes an effort by the U.S. Geological Survey (USGS) that used research, monitoring data, and modeling to develop a methodology to assess both the current and future population-level consequences of wind energy development on species of birds and bats that are present in the United States during any part of their life cycle. The methodology is currently applicable to birds and bats, focuses primarily on the effects of collisions with turbines, and can be applied to any species that breeds in, migrates through, or otherwise uses any part of the United States. The methodology assesses species at the national and regional scales and identifies those species potentially in need of more detailed study, as well as those species that are likely at low risk from wind energy development. This approach is fundamentally different from existing methods focusing on impacts at individual facilities.
This report supersedes USGS Scientific Investigations Report 2015–5066 by the same authors, which described a preliminary version of the methodology. Following reviews of the preliminary methodology by a panel of external experts, public comments, and additional internal review, the methodology was revised and finalized.
The three components of the refined methodology described in this new report rely on publicly available fatality information, population estimates, species range maps, turbine location data, biological characteristics of species, and population models. First, three metrics are combined to determine direct and indirect relative effects from wind energy facilities to generate a list of species scores. Second, a generic population model estimates the expected change in population trend caused by the additive mortality from collisions with wind turbines. Third, the methodology combines an estimate of observed fatalities and an estimate of potential biological removal to assess the possibility of a decrease in population size. The latter two components are quantitative. In a test case, the methodology was used to analyze data for six bird species and three bat species.
Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable or may require further study. These assumptions should be carefully considered when using outputs from the methodology. Increases in the quality of data for fatalities from collisions with wind turbines, species distributions, abundance, and demography will likely improve results for uses of the methodology.
The methodology’s design identifies and prioritizes a subset of the bird and bat species that may experience population-level impacts from collisions with wind turbines, both currently and from future wind energy development in the United States. Results of an assessment using this methodology could focus future research to improve our understanding of those impacts and to guide avoidance and minimization strategies. In addition, this methodology can be used to identify species for more intensive demographic modeling or to highlight those species that may not require any additional research because effects of wind energy development on their populations are projected to be small. The effects of wind energy facilities on nine unidentified species used in the test case described in this report have not been assessed. Their data were simply used to show the application of the methodology to real-world data and the types of outputs it would produce.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185157","usgsCitation":"Diffendorfer, J.E., Beston, J.A., Merrill, M.D., Stanton, J.C., Corum, M.D., Loss, S.R., Thogmartin, W.E., Johnson, D.H., Erickson, R.A., and Heist, K.W., 2019, A methodology to assess the national and regional impacts of U.S. wind energy development on birds and bats: U.S. Geological Survey Scientific Investigations Report 2018–5157, 45 p., https://doi.org/10.3133/sir20185157. [Supersedes USGS Scientific Investigations Report 2015–5066.]","productDescription":"ix, 45 p.","onlineOnly":"Y","ipdsId":"IP-079749","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365690,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5157/coverthb.jpg"},{"id":365691,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5157/sir20185157.pdf","text":"Report","size":"1.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5157"}],"publicComments":"Scientific Investigations Report 2018-5157 supersedes Scientific Investigations Report 2015-5066.","contact":"Director, Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956
12201 Sunrise Valley Drive
Reston, VA 20192
Energy Resources Program
Wind Energy
In support of nutrient reduction efforts, nitrate (as nitrate plus nitrite) and phosphorus loads and yields were computed for selected streams in Iowa based on continuously monitored sensor data for 2008–17 and 2014–17, respectively. Sample data were used to assess nitrate sensor bias and to create phosphorus-turbidity surrogate models. Where needed, nitrate loads were corrected for site-specific sensor bias, which was determined to be as high as 9.25 percent. Nitrate loads presented in this report using continuous (generally 15-minute interval) data were on average 4 percent less, but as much as 38 percent less, than annual loads computed from daily mean nitrate concentrations not corrected for sensor bias. Streamflow-based phosphorus models had poorer fit (adjusted coefficient of determination values less than 0.75) than turbidity-based models (adjusted coefficient of determination approximately 0.9). However, alternate models based on streamflow were used to obtain a more complete annual phosphorus load despite seasonal and fragmentary sensor data.
Mean annual nitrate yields for 18 selected sites (96 site-years) ranged from 1.68 to 164 pounds per square mile per day (lb/mi2/d), compared to 19.4 lb/mi2/d average statewide yield needed to achieve the nitrate-reduction goal. Mean annual phosphorus yields for selected sites on the Maquoketa River, South Raccoon River, and West Nishnabotna River range from 1.57 to 7.19 lb/mi2/d, compared to 1.06 lb/mi2/d average statewide yield needed to achieve the phosphorus-reduction goal.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195054","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Garrett, J.D., 2019, The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17: U.S. Geological Survey Scientific Investigations Report 2019–5054, 31 p., https://doi.org/10.3133/sir20195054.","productDescription":"Report: viii, 31 p.; Appendixes: 2","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098143","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":365814,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5054/sir20195054.pdf","text":"Report","size":"1.97 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U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240